Acanthocytosis and Other Hematological and Serum Biochemical
ACANTHOCYTOSIS AND OTHER HEMATOLOGICAL AND SERUM BIOCHEMICAL
PAMMETERS M THE DIAGNOSIS OF CmHEMANGIOSARCOMA
A Thesis
Presented to
The Faculty of Graduate Studies
of
The University of Guelph
by
MARGO SUSAN TANT
(n partial fuifilment of requirernents
for the degree of
Doctor of Veterinary Science February, 1998
Q Margo Susan Tant, 1998 National Library Bibliotheque nationale du Canada Acquisitions and Acquisitions et Bibliographie Services seMces bibliographiques 395 Wellington Street 395, rue Weilingtori ûüawaON KIAM ûaawaON K1AON4 Canada canada
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ACANTHOCYTOSIS AND OTHER HEMATOLOGICAL AND SERUM BIOCHEMICAL PARAMETERS iN THE DIAGNOSIS OF CANINE HEMANGIOSARCOMA
Margo Susan Tant Advisor: University of Guelph, 1998 Dr. J. H. Lumsden
A retrospective case-control study was conducted using the records of 80 dogs with visceral hemangiosarcoma (HSA) and 200 dogs with various diseases that had features simila. to HSA. Al1 dogs were older than one year of age, had histologically confirxned disease, and had a complete blood count performed prior to the ha1 diagnosis. A
standard protocol was used to count acanthocytes in the blood film of each dog.
Acanthocyte count had a diagnostic sensitivity of 53.8% (and specificity of 61.5%) at a cutpoint of 21 acanthocyte/2000 red blood cells. A diagnostic specificity of 100% (and sensitivity of 7.5%) was achieved at a cutpoint of Hl acanthocytes/2000 red blood ceiis, which represented a marked acanthocytosis. The precision of acanthocyte count was poor to fair due to the subjective nature of identifjing acanthocytes. Although dogs with
acanthocytes were more likely to have HSA (P = 0.02), and dogs with HSA had higher
acanthocyte counts than controls (P = 0.003), acanthocyte count had Mted utility as a
diagnostic test There was no level of acanthocytosis at which HSA could be ruled out
and, although HSA could be ruled in at counts >71 acanthocyted2OOO red blood celis,
ody a smdpercentage of dogs with HSA would be detected at this level. A multivariable logistic regsession analysis was performed using demographic, hematology, and serum biochernistry data for the study population. The resulthg predictive model for HSA included age greater than 8 years, Golden retriever breed, anemia, and thrombocytopenia. The mode1 had a sensitivity of 83.9% and a specificity of
80.9% in predicting the presence of HSA. In a related rnodel, acanthocyte count was retained as a significant variable, demonstrating that although acanthocyte count may not be useW. as a separate diagnostic test for HSA, it cm contribute to diagnostic certainty in the context of other findings. Hypoalbuminemia and elevated senun akaline phosphatase were associated with the absence of HSA, but inclusion of these variables did not improve the diagnostic performance of the logistic model. Therefore, although select serum biochemistry variables may help to deout HSA, a biochemistry profile is unlikely to contribute to the certainty of the diagnosis. 1 would like to thank the members of my advisory cornmittee for their advice and assistance in the preparation of this thesis, and in particdar, Dr. Tim Lumsden for his endless patience, Dr. Robert Jacobs for the generous use of his cornputer software, Dr.
Brian Wilcock for his refieshing perspective fiom the other side, and Dr. Breoda Bo~ett for her detailed appraisd of my work, and for her interest and encouragement. I am deeply indebted to those who bravely agreed to count acanthocytes for me as pari of the multi-rater studies, including Dr. Th Lumsden, Dr. Robert Jacobs, Dr. Krk Ruotsalo, and Mn. Phyilîs Few - I truiy couldn't have done it without you. Dr. Frank Pollari fiom the Department of Population Medicine worked tirelessly with me on the logistic regression, and aiso helped with the statisticai analysis in the acanthocyte study. Thank you Frank, for being a good sport, and for your patience and humour throughout. The
OVC Computer Support Group, including Mrs. Wendy Woodhouse and Ms. Elizabeth
Reemeyer, and the Staff of the Medical Records Depariment, were instrumental in helping me find my study population, and without their help the project would have remained just an interesting idea The Pet Trust Fund is also gratefûlly acknowledged for its hanciai support of my research.
To my fellow graduate students - especidy Krys Grodecki and Kris Ruotsaio, who were mentors and colieagues, but more importantiy, invaluable fnends and supporters; and Emma Michel (nee Hamilton) who shed with me that trial-by-fie known as
Statistics, and stayed on to become a good fiiend - my special thanks for making the experîence more enjoyable. 1 thank my family for their love and support durhg the last three years; in particular, my parents for instilling the value of education, and the importance of nnishing what you start, and my sisten Uea and Judy for their encouragement when things were bleakest, and for cheerfully hunting down obscure journal articles for me. My most heartfelt appreciation is reserved for my husband, Alan Sippel, who has been my anchor throughout, and without whom this project would have been neither started nor completed. His direct contribution as the infamous "disinterested third party" (if the studies were properly blinded it's al1 his fault) was crucial. But of greater importance was his confidence in me, his moral support, and his patience. TABLE OF CONTENTS
...... LIST OF TABLES ...... v
LIST OF FIGURES ...... vi
CHAPTER I
Prevalence ...... *...... $...... *....*1 Biology of Hemangiosarcoma ...... 2 Age. Sex. and Breed ...... 3 Etiology ...... 5 Chcal Course and Prognosis ...... 6 Visceral Hemangiosarcorna...... 6 Cutaneous Hemangiosarcoma ...... 8 Diagnostic Findings ...... 8 Hematological Changes in Dogs with Hemangiosarcoma ...... 10 Erythron ...... 10 Leukon ...... 12 PIatelets ...... 13 Acanthocytes ...... 14 Acanthocytes in Humans ...... 14 Acanthocytes in Animals ...... 17 Acanthocytes in Canine Hemangiosarcoma ...... 18 CHAPTER II:
CHAPTER III EVALUATIONOF ACANTHOCYTE COUNTAS A DIAGNOSTICTEST FOR CANIhE HEMANGIOSARCOMA...... 33 Introduction ...... 33* ...... Materials and Methods ...... 34 Def~tionand Criteria for Inclusion and Exclusion ...... 34 Acanthocyte Smdy ...... 35 Analysis ...... 37 Resuits ...... 39 Blood Film Smdy ...... 42 Photographic Study ...... 46 Superficial Hemangiosarcoma ...... 49 Discussion ...... -50 Blood Film Study ...... 55 Photographie Study ...... 58 Superficial Hemangiosarcoma ...... 62 Conclusion...... -62 CHAPTER IV
ASSOCIA'TIONSOF HEMATOLOGICAL AND SERUM BIOCHEMICAL PMETERS WITH HEMANGIOSARCOMAINDOGS ...... 66 Introduction ...... 66 Material and Methods ...... 68 Results ...... 72 Descriptive Statistics and Bivariable Analysis ...... 72 Demographics...... 72 Hrmatology ...... 74 Serum Biochemisîry ...... 76 Missing Values ...... 77 Logistic Regession Analysis ...... 77 Discussion ...... 83 Bivariable Analysis ...... 85 Multivariable Regression Analysis ...... 89 Conclusion...... 97 CHAPTER V SUMMARY AND GENERALCONCLUSIONS ...... 101
ACANTHOCYTESTUDY Appendix 1A ...... 107 Appendix 1B ...... 1 Il Appendix 1C ...... 113
Appendix 2A ...... 115 Appendix 2B ...... 127 LIST OF TABLES
Table 3.1 Intra-observer agreement for acanthocyte counts on penpheral blood smears......
Table 3.2 uitersbserver agreement for acanthocyte counts on penpheral blood smears - Fifit Reading......
Table 33 Inter-observer agreement for acanthocyte counts on penpherai blood smears - Second Reading......
Table 3.4 Inter-observer agreement for acanthocyte counts on peripheral blood smears - Intraclass Correlation Coefficients......
Table 3.5 intrasbserver agreement for acanthocyte counts on photogniphs......
Table 3.6 Inter-observer agreement for acanthocyte counts on photographs First Reading......
Table 3.7 Intersbserver agreement for acanthocyte counts on photographs Second Reading......
Table 4.1 Frequency distribution of the nineteen canine breeds common to both cases and control groups......
Table 4.2 Model 1. Results of muitivariable logistic regression analysis of associations between HSA and demographic variables......
Table 4.3 Model 2. Results of multivariable logistic regression analysis of associations between demographic and hematology variables and HSA.
Table 4.4 Model 3. Results of multivariable logistic regression analysis of associations between demographic, hematology, and red cell morphology variables and HSA ......
Table 4.5 Model 4. Redts of multivariable logistic regression analysis of associations between demographic, hematology red cell morphology, and semm biochemistry variables and HSA......
Table 4.6 Summary of fit and predictive performance for logistic regression models for associations between HSA and demographic, hernatology, red blood ceU morphology, and senmi biochemistry variables...... LIST OF FIGURES
Figure 3.1 Frequency Distribution of Acanthocytes for Dogs with Hemangiosarcoma @SA) and Controls ...... 40
Figure 3.2 Receiver Operator Characteristics Plot for Acanthocyte Count ...... 41
Figure 4.1 Frequency Distribution of Hematocrit for Dogs with Hemangiosarcoma (HSA) and Controls ...... 75 CHAPTER 1
LITERATURE REWEW OF CANINE HEMANGIOSARCOMA
PREVALENCE
Hemangiosarcoma (HSA) is a maligaant neoplasm of vascular endothelium
(Waller and Rubarth 1967, Frey and Betts 1977, von Beust et al 1988, Pulley and
Staanard 1990). It is an uncornmon cancer in most species including the cat (Miller et al
1992), cow (Queen et al 1992), home (Jean et al 1994), and human being (Ludwig and
Hoffrizan 1975), but is fiequently encountered in the dog. Early studies report a prevaience of 0.39% to 0.92% of canine necropsies (Wder and Rubarth 1967, Kleine et al 1970) but more recent studies report a prevalence of 1.08% to 1.98% (Pearson and
Head 1976, Oksanen 1978, Ng and Mills 1985). This apparent increase in the number of dogs diagnosed with HSA on postmortem may represent a true nse in the frequency of the disease, or may be a fiuiction of the studies themselves. The earlier studies were large
(e.g. 1î,63 5 cases over 25 years) and therefore possibly more representative than later studies which were smaller (e.g. 3,000 cases over 4-6 years). The studies also came fiom referral institutions in Werent parts of the world, and differences in local referral populations and referral patterns, may have contributed to the variability in prevalence figures. The increase over the past twenty years could also be explained by improved training and awareness of pathologists, as well as changes in the demographics (breed and age distriauton etc.) of the canine population, and owners' attitudes about seeking veterinary attention and permitting autopsies. A larger canine population and an increase
in the number of dogs presented for diagnosis and subsequent post mortem examination
could increase the observed prevaience of HSA without an attendant increase in the û-ue
prevalence. Al1 of the studies cited have the limitation that they are based on referral
populations and cannot be considered to be representative of the canine population at
large. Furthemiore, these studies actually provide only an expression of proportional
morbidity (or mortality) rather than prevalence in the referrai population. Therefore,
while these data give a general estimate of prevalence, it is important to reaiize that the true prevalence of hemangiosarcoma in the canine population is unknown (Bomett and
Reid-Smith 1996).
BIOLOGY OF HEMANGIOSARCOMA
As a tumour arising fiom blood vessels, HSA can develop in any organ (Hammer and Couto 1992, Pearson and Head 1976). The most common primary sites are the right auricle/atrium and the spleen, followed by the liver and subcutis (Kleine et al 1970, Hirsch et al 1981, Brown et al 1985, Hammer and Couto 1992). Other primary sites reported include the kidney (Waller and Rubarth 1967, Kleine et al 1970), prostate ( Brown et ai
1985, Hayden et ai 1992), bladder (Kleine et al 1970, Brown et al 1985, Martinez and
Schulman 1988), bone (Waller and Rubarth 1967, Parchman and Crameri 1989, Jenning et ai 1990), ski.( Oksanen 1978, Arp and Gner 1984, Ward et al 1994), tongue (Cuibertson
1982) and muscle (Auen 1982). Metastars is very common and likely occurs hematogenously (Oksanen 1978). Metastasis can be widespread and fkquently precedes diagnosis. Cardia HSA most commonly ~preadsto the lungs (Kleine et al 1970, Pearson and Head 1976, Ng and Mills 1985, Waters et al 1988) but may spread more widely
(Kleine et al 1970). Splenic HSA usually spreads to the liver, omenturn and other abdominal viscera (Brodey 1964, Hirsch et al 198 1, Ng and Mills 1985, Waters et al 1988,
Vail et al 1995) but may metastasue to extraperitoneal sites (Waters et al 1988) including the lungs (Ng and Milis 1985, Vail et al 1995). Other metastatic sites include bone
(Parchman and Cameri 1989), skin (Walier and Rubarth 1967, Vail et al 1995), eye
(Symanski 1972, Ng and Milis 1985, Marciani et al 1995), brain (Kleine et al 1970,
Oksanen 1978, Waters et al 1989, Vail et al 1995), kidney (Kleine et al 1970, Crow et al
1980) and bladder (Vail et al 1995). When there is multiple organ involvement, the primary site may be ditficuit to determine (Pearson and Head 1976, Oksanen 1978, Waters et al
1988) and some authors have speculated that in some dogs HSA can occur as a multicentric disease (Oksanen 1978).
AGE, SEX ,AND BREED
Most authors concur that HSA occurs in older dogs. The average age is 9-1 1 years with a range of one to sixteen years (Waller and Rubarth 1967, Kleine et al 1970, Frey and
Betts 1977, Oksanen 1978, Hirsch et al 1981, Brown et al 1985, Ng and Mills 1985,
Johnson et al 1989). Young dogs can be afZected (Jenning et al 1990, Arp and Grier 1984) but the diagnosis in dogs less than seven years of age is uncornmon mrodey 1964, Frey and
Betts 1977, Prymak et al 1988).
There is no clear consensus on the breed and sex predilection of HSA. Two papers do not find any breed predilection (Brodey 1964, Oksanen 1978), but several case series studies report that the German shepherd is over represented (Frey and Betts 1977, Fees and
Withw 1981, Hirsch et al 1981, Brown et ai 1985, Wrigley et al 1988, Johnson et al
1989). While this suggests a breed prediiection, descriptive studies provide only weak evidence for a tnie association. Three other papers report a statistically significant predilection for the German shepherd (Waller and Rubarth 1967, Ng and Mills 1985,
Pearson and Head 1976) but the comparison groups are either inadequate or poorly defined, and the conclusions regarding a breed association are therefore questionable. The most convinchg statistical evidence for a breed predilection is presented by Kleine et al, and
Prymak et al. The fomer analyzed the incidence of HSA in German shepherds using a Chi- square comparison with the hospital population (Kleine et al 1970), and the latter used a
Chi-square and odds ratio comparison with a control population (Prymak et al 1988). Both studies indicated that the increased incidence of HSA in the German shepherd was statisticdy sipnincant.
Although there is some evidence that the German shepherd is more at risk for HSA, it is clear that many breeds can be Sected. In one study of 104 dogs there were 22 breeds represented (Brown et al 1985), and in derstudy of 28 dogs there were 16 different breeds (Frey and Betts 1977). In both studies the mixed breed constituted 25% of all cases.
Evidence for a sex predilection is weaker than for age and breed. The majority of studies do not provide statistical analysis of the sex distribution of HSA. Seved authors observe that more males are affécted than females (Pearson and Head 1976, Frey and Betts
1977, Fees and Withrow 1981, Hirsch et al 1981, Brown et al 1985, Ng and Mills 1985) but most conclude that the numbers do not support a sex predisposition for the male 4 and Head 1976, Oksanen 1978, Fees and Withrow 198 1 , Hirsch et al 1981, Ng and Mills
1985). When statistical analyses are reported, the results are contradictory. Kleine et al used a Chi-square test to compare the study group and the hospital population and found that there was no statistical evidence for a sex predilection (Kleine et al 1970). Prymak et al, using odds ratio and Chi-square cornparisons with a control population found that the spayed fernale had a statistically increased risk for HSA (odds ratio 1.2-4.1 95% CI)
(hymak et al 1988). Two other studies used a Chi-square cornparison with the autopsy population; one identified a predisposition for the male ( Waller and Rubarth 1967) and the other found no evidence for a sex predisposition (Ng and Mills 1985). Some iiterature presents HSA as having a sex predilection for the male, but the authors have relied heavily on observational data (Couto 1989, Pulley and Stannard 1990, Hammer and Couta 1991) which when assessed critically does not support the conclusion.
ETIOLOGY
The etiology of hemangiosarcoma in the dog is uot known. Visceral turnours have been produced experimentally in beagles following exposure to radiation (Rebar et ai 1980) and by inhalation of radionucleotides (Benjamin et al 1975). Solar radiation has been proposed as a causative agent in cutaneous HSA (Hargis et al 1992). However no correlation has been confirmed between a specinc etiological agent and spontaneous disease (Oksanen 1978). This is in con- to humans where the development of HSA has ken documented to follow exposure to thorium, vinyl chloride, and arsenical insecticides
(Ludwig and HotSnan 1975). CLINICAL COURSE AND PROGNOSIS
Visceral Hemangiosarcoma
Dogs with HSA involving intemal organs may present with a variety of clinical signs depending on the primary site and the extent of metastatic involvement (Oksanen 1978,
Harmner and Couto 1992). Presenting cornplaints are fiequentiy non-specific and include
Iethargy, anorexia, weight loss, weakness, and dyspnea (Ng and Mills 1985, Wykes et al
1986, Wngley et al 1988). Signs may be intermittent (Fees and Withrow 198 1, Ng and
MiUs 1985) and are generally of short duration, usually less than three months prior to presentation (Waller and Rubarth 1967, Kleine et al 1970, Oksanen 1978, Prymak et al
1988). Some animals may die acutely without previous signs of illness (Waller and Rubarth
1967, Kleine et al 1970, Oksanen 1978) or present in acute collapse and shock. This is attributed to major hemonhage into abdominal, thoracic or pericardial spaces following rupture of large blood-fXed tumour masses (Kleine and Zook 1970). Other signs can be athibuted to specific organ involvement. Arrhythmias and syncope rnay reflect neoplastic interference with the cardia conduction system (Kleine et al 1970, Aronsohn 1985, deMadron et al 1990). Sirnilarly neurologicai signs (Kleine et al 1970, Waters et al 1Mg), hemahnia (Crow et al 1980), bone pain (Fees and Withrow 1981), or abdominal distension
(Waters et al 1988, Johnson et al 1989) may indicate tumour invasion of the respective organs or tissues.
The prognosis for dogs with these fomis of HSA is poor. Many animals are beyond medical help when nrst examined because of widespread metastasis (Brown et al 1985,
Bigbie et al 1986, Hosgood 1991). Treatment, if undertaken, involves surgical removal of 6 tumour masses, foiiowed by combination chemotherapy Uicluding Wicristine, cyclophosphamide and doxombicin (Johnson et al 1989, deMaciron et al 1990, Hammer et al 1991, Sorenmo et al 1993, Ogilvie et al 1996 ), methotrexate (Brown et ai 1985), and
Liposome-encapsuiated muramyl tripeptide phosphatidylethanolamine (Vail et al 1995).
Complete surgical resection of tumours has been associated with sudval times of up to
theyears (Brodey 1964, Hahn et al 1992), but typically fewer than 10% of dogs sunrive
beyond one year (E9yna.k et al 1988). Mean swival the after surgery without adjuvant therapy was 4 months (range 2 days to 8 months) in one study of 38 dogs with cardiac HSA
(Aronsohn 1985). ui mother study of 47 dogs with splenic hemangiosarcoma, the average
survivd time was four months (range 14 to 533 days) regardless of the extent of disease at the tirne of diagnosis and treatment protocol used (Brown et al 1985). Chemotherapy was effective in reducing the size of a cardiac hunour and resolving the pericardial effision in one dog, but did not improve &val tirne beyond 20 weeks (deMaciron et al 1990). Better
&val statistics were reported for dogs with spienic HSA that received therapy with
Liposome-encapsulated muramyl tripeptide phosphatidylethanolamine following splenectomy (Vail et al 1995). Median Survival times of 14 months (425 days) were reported for dogs receivhg treatment before splenic rupture, and 5.4 months (162 days) for
dogs receiving trament &er splenic rupture. However, all dogs were fiee of gross
metastases at the time of enrolment in the study. This may have resulted in more favomble
Suntival data, especiaily for dogs without splenic rupture since such dogs wouid have had a
better initial prognosis. Similar &val rates may not be reproducible in the typical dog
with HSA that already has metastatic disease at the time of diagnosis. Some authors are optimistic about the efficacy of chemotherapy (Hammer et al 199 1,
Vail et al 1995) but others are not convhced that such treatment significantly aiters the prognosis (Johnson et al 1989, Brown et al 1985). One reason for the poor response to adjuvant therapy may be that secondary metastases are resistant to treatment despite sensitivity of the primary hmiour (deMadron et al 1990).
Cutaneous Hemangîosarcoma
Cutaneous HSA has been reported to have a statistically significant breed predilection for the Whippet (Hargis et ai 1992) but is also fkquently found in Pitbds,
Boxer, and mixed breeds (Ward et al 1994). Cutaneous HSA is a tumour of the aged dog similar to the visceral form of the disease. It can be either primary or metastatic and commonly aects the ventral body dace where the skin is lightly pigmented and the haircoat is sparse. Mected dogs present with d,discrete, red-black masses in the deds or subcutis that are readily detected and resected. Although some resected tumours will recur locdy, and about 30% of dogs wiii develop metastatic disease, the majority of dogs have Survival times in excess of 1 year (Hargis et al 1992, Ward et al 1994).
DIAGNOSTIC FNDINGS
Many different diagnostic modaiities are descnbed in the literature, including hematology, radiology, cytology, and ultrasonography. Definitive diagnosis dyrequires
surgical biopsy and histopathology. Radiographie changes that would support a diagnosis of HSA include general Ioss of detail suggestive of hemorrhage into body cavities (Kleine et al 1970, Jenning et al 1990), globose cardiac shadow consistent with pericardial effusion (Kieine et al 1970, Hosgood
1991), a nodula. or diffuse interstitial pattern in the lungs indicating pulmonary metastases
(Kleine et al 1970, Hammer and Couto 1992, Hammer et al 1993), and a soft tissue mass displacing abdominal viscera consistent with a splenic tumour (Kleine et al 1970, Wrigley
1988, Hahn 1992). Rend and bladder HSA require excretory urograrns and positive contra* cystograms, respectively, for detection (Martinez and Schulman, 1988). Osseous
HSA appears as a poorly defined and highly osteolytic lesion with minimai periosteal reaction on radiographs (Parchman and Crameri 1989, Jenning et al 1990).
Echocardiography is used to conhn pencardial effusion, and to identa the presence and location of cardiac masses ( deMacIron et al 1987). On ultrasound, HSA nimour masses appear as a cornplex, mked pattern of echoic, hyperechoic and hypoechoic areas (Wngiey et al 1986) that refiect the mixhne of cystic areas, with areas of fibrosis, mineralization and recent hematorna formation (33).
Aspiration of fke fluid fiom serous cavities usually produces variable amounts of bloody fluid that does not dot (Legendre and Krehbiel 1977). Cytological examination reveals a nomdammatory hemorrhagic effusion resembliag peripheral blood with few if any neoplastic ceus (Kieine et al 1970, Brody 1964, Legendre and Krebhiei). In one study only 25% of effusions yielded a diagnosis of HSA (Hammer and Couto 1992). This is iikely due to the tendency of sarcornas to exfoliate poorly, and the heterogeneous nature of the tumour (Johnson et al 1989). HEMATOLOGICAL CHANGES IN DOGS WITH HEMANGIOSARCOMA
Several hematological abnomalities are encountered in dogs with hemangiosarcoma.
The moa commonly reported are a regenerative anemia with poikilocytes and mbncytes, neutrophilia with lefi shift, and thrombocytopenia (Kleine et al 1970, Crow et al 1980, Ng and Mills1985, knning et ai 1990).
The anemia is usually mild to moderate but can be severe (Kleine et ai 1970) and rnay fluctuate rapidly in the same animal (Ng and Mills 1985). Kleine et al found anemia in
18 of 29 dogs with HSA. The packed cell volume (PCV) was 0.06-0.32UL with a mean of
0.24 yL (Kleine et al 1970). Ng and Mills nmilarly found that 8 of 10 dogs had mild to moderate anemia with packed ce11 volumes of 0.1 8-0.3 3 L/L (reference limits, 0.37-0.55
LA,). Hemoglobin values were 60-1 13 g/L with a mean of 78 g/L (reference Iimits, 120-180 g/L) (Ng and Mills 1985). Wailer and Rubarth reported that all 15 cases in one study had low hemoglobin valws ranging fiom 32-125 gL (no reference values given) (Wailer and
Rubarth 1967). The anemia is described as very responsive with prominent polychromasia, reticuiocytosis and anisocytosis (Hifich et al 198 1, Ng and Mills 1985, Johnson et ai 1989).
However, the anemia may also be non-responsive @lg and Mills 1985) as is reported with primary cardiac (Rebar et al 1980) and prostatic HSA Wayden et al 1992).
The etiology of the anemia is attri'buted to interna1 hemorrhage subsequent to rupture of amiour masses (Kleine et al 1970, Oksanen 1978). In addition there is likely a concurrent mîcroangiopathic hemolytic destruction of red celis (Rebar et ai 1980). Microangiopathic hemolytic anemia refers to the mechanical hgmentation of red cells that occurs when blood is forced through abnomai vascular channels, or when red blood cells with diminished membrane deformability pass through normal capillaries (Rebar et al
198 1). In HSA the fhgmentation likely occurs as blood flows through aberrant and tortuous vascular channels in tumour masses (Rebar et al 1980) or subsequent to disseminated intravascdar coagulopathy. The rnisshapened and darnaged erythrocytes (poikilocytes) are rapidiy removed fiom circulation by the spleen (Jain 1993), contributhg to anemia by shortening erythrocyte lXe span. The fluctuating nature of the anernia is likely due to the rapid compensation that occurs afler a hemorrhagic episode, characteristic of anemias due to internai hemonhage ( Hirsch et al 198 1) and hemolytic destruction (Jain 1993).
Rubncytes are commonly found in the blood of dogs with HSA. Some authoa consider an inappropriate nibncytosis to be diagnosticaliy signifîcant (Kleine et al 1970,
Johnson et al 1989). Ng and Mills found an average of 6-7 rubncytes/100 white blood ceils
(WC) in 7 of 10 cases (Ng and Mills 1985), and KIeine et al found an average of 5-10 mbricytes/100 WBC (range 1-187 ntbricytes/lOO WBC) in 17 of 29 cases (Kieine et al
1970). Rubricytosis in the presence of polychromasia may be expected as part of a strong response to anemia (appropriate rubricytosis) (KIeine et ai 1970). However, an inappropriate rubricytosis may develop in HSA due to infiltration of the bone marrow by neoplastic ceUs (Poo1 1990), extrarneduilary hematopoiesis (O'Keefe and Couto 1987), splenic hypofiinction ( Couto 1989) or hypoxemia (Kleine et ai 1970). The hypoxemia may develop due to hypovolemia caused by hemorrhsge, or may be due to poor cardiac function and impaired oxygenatîon subsequent to tumour invasion of the heart or lungs (Kleine et al
1970). The term poikilocytes is a general term used to describe red blood cells with abnormal morphology (Jain 1993, Dun= & Rasse 1994). Many of the individual aberrations have been assigned names and are linked with specific pathology or physiological conditions. In HSA the poikilocytes variously reported in the literaîtue include acanthocytes, keratocytes, schistocytes, microcytes, spherocytes, target cells, and ecchinocytes (Ng and MUS 1985, Rebar et al 1980, Weiss et al 1989).
Leukon
Another hematological hding described in HSA is neutrophilic leukocytosis with left shiR In a study of ten dogs (Ng and Mills 1985), four had white celi counts of 21.1-
5 1.9 x 109/L (reference limits, 66-17 x 109/L) with an absolute neutrophilia of 13.6-36.8 x lo9n (reference kits, 3-1 1.5 x 109/L). Two of the four cases also had a left shift. Three other cases had ddabsolute neutrophilia, but without a left shift. Heine et al (1970) reported an average white cell count of 27.8 x 109/L (range 19.0-47.9 x 10'/~) with absolute neutrophilia and left shift in 10 of 15 dogs with primary cardiac hemangiosarcorna
(Ueine et al 1970). Similarly, Waller and Rubarth found a leukocytosis of 16.0-58.5 x
109/L in 1O of 15 hemograms examhed (Waller and Rubarth 1967).
The leukocytosis may be the product of increased marrow activity found with responsive anemia prodey 1964, Jain 1993). It may also represent an infiammatory response to tumour necrosis (Hosgood 1991) or the presence of hemorrhagic effusions in body cavities (Brodey 1964). Ng and Mills interpreted the neutrophilia in 8 of 10 dogs as a normal stress response (Ng and Mills 1985) as did Wrigley et al in 7 of 11 dogs (1986). Platelets
Thrombocytopenia is cornmonly reported in dogs with hemangiosarcoma (Legendre and Krehbiel1977, Zenoble and Gabbert 1977, Men 1982, Ng and Mills 1985, Hammer et al 1991). It may appear as an isolated hematological abnormality. Hammer et ai found 6 of
24 dogs with HSA had thrombocytopenia without evidence of disseminated intravascular coagulation (DIC) or rnicroangiopathic hemolytic anemia The platelet counts ranged fiom
45.5-148 x 1O'/L (Hammer et ai 1991). Several authors report thrombocytopenia as part of the pattern of abnormalities associated with DIC including increased fibrin degradation products, decreased fibrinogen levels, and prolonged prothrombin and activated partial thromboplastin times. In a study of 24 dogs, 11 had thrombocytopenia and laboratory evidence of DIC (Hammer et al 1991). Ng and MUS (1985) reported 9 of 10 dogs were thrombocytopenic as assessed subjectively fxom the blood smear or by actuai count The platelet counts ranged fiom 55-140 x 109/L (reference limits 200-900 x 109/L). Two thrombocytopenic dogs also had elevated fibrin split products in association with clinical
DIC, and one had a prolonged prothrombin time and activated partial thromboplasth thne
(Ng and Mills 1985). Simila. hdings are documented in several other studies (Legendre and Krehbiel 1977, Zenoble and Gabbert 1977, Rebar et al 1980, Hammer et al 1991,
Hosgood 1991).
In HSA platelets may be lost through hemorrhage or consumed in hemostasis foiiowing tumour rupture (Zenoble and Gabbert 1977). Platelets may also be sequestered in cavitated tunom (Ng and Mills 1985, Men 1982), or coasumed in DIC. Disseminated intravascular coagulation is fkquently triggered in malignant neoplasia following the exposure of blood to foreign (tumour) cells, or inflamed vascular endothelium, or by the
presence of sequestered blood in tumour masses or serous cavities Gegendre and Krehbiel
1977). The co~lsumptionof platelets, clotting factors and fibruiogen produce the observed
laboratory abnormalities. The deposition of fibrin in DIC has been cited as a cause of
microangiopathic hemolytic anernia (Zenoble and Gabbert 1977, Rebar et al 1981, Jain
2 993).
ACANTHOCYTES
The acanthocyte is a poikilocyte that is fkquently identified in dogs with HSA. The
acanthocyte is described as an irregularly spiculated red blood ce11 of normal volume. It is
spheroidal with 3-12 (up to 20) hger-like projections unevenly distributed on its surface.
Projections Vary in length and width and typically have blunt or clubbed tips (Bessis 1977).
Acanthocytes in Humans
The acanthocyte was fïrst described in humans in 1950 by Bassen and Komzweig
who described the abnormal erythrocytes as unusually crenated cells with bizarre shapes
resembling "small beetles, crabs and tudes. They resembled spherocytes fiom which buds
or pseudopods were protmding" (Bassen and Komzweig 1950). The abnormal ceils were
found consistently in &sh and dned preparations of blood fkom a young woman whose
parents were first cousins. She was diagnosed with an atypical retinitis pigmentosa
associated with musual neurologicd sîgns. The etiology was not clear, but when the bIood was re-examined a year later, the abnormal red blood celis were still present in the same numbers (Bassen and Komzweig 1950).
In 1952 Singer et al describe a similar case, of a young boy fiom a consanguineous mamiage that presented with progressive neurological signs and the same irregdarly spiculated red blood cells in repeated blood samples (Singer et al 1952). The name
"acanthrocyte" (Greek akantha = thom) was proposed for this abnormal ce11 which was considered the characteristic feature of the new hereditary syndrome. (The name was later modifïed to acanthocyte in subsequent papers (Salt et al 1960)). Experimentation demonstrated that the acanthocytes had an increased osmotic resistance in hypotonic solution but an increased mechanical hpiiity when rotated with glass beads (Singer et al
1952). In addition, Singer et al reported that the defect lay with the ce11 and not with the plasma. He exposed acanthocytes to nomal plasma, and normal red cells to plasma fiom the affiected patient. They found that no changes in cell morphology occurred in either situation.
Salt et al in 1960 determined that the condition arose fkom an inbom emr of lipoprotein metabolism resulting in very low levels of p-üpoprotein in affected patients
(Sait et ai 1960). The condition was cded abetaiipoproteinemia The membranes of the defective red blood cells were shown to have a mildly increased cholesterolghosphotipid ratio and a lS-2O% increase in the cholesterol content (McBride and Jacob 1970).
A second condition called 'spur-cell anemia' was descriid in 1964 by Smith et al who found abnormal red blood ceils, indistinguishabte nom hereditary acanthocytes, in a patient with advanced cirrhosis of the Liver (Smith and Lonergan 1964). In contrast to abetalipoproteinemia, which is not associated with signifïcant anemia, this condition was noted for its severe hemoiytic anemia ûthet ciifferences were that the P-lipoprotein level was nomal, sem cholesterol was elevated, the cholestero1:phospholipid ratio was markedly increased (McBride and Jacob 1970, Cooper 1969), and red cell life span was shortened to 20 days (Smith and Lonergan 1964). In contrast to congenital acanthocytosis,
Smith demoiistrated that in acquired acanthocytosis, washed acanthocytic celis placed in normal senun resurned a normal discoid conformation. When normal homologous red blood cells were placed in patient plasma, they acquired the spiculated shape typical of the patient's altered red blood celis. This suggested that a factor in the plasma was responsible for the change (Smith and Lonergan 1964).
It was later proposed that the elevated serum cholesterol in acquired acanthocytosis is due to a deficiency of lecithyl cholesterol acyl tramferase (LCAT), an enzyme responsible for the esterification of kecholesterol (Smith and Lonergan 1964). The deficiency of
LCAT, due to impaired hepatic fimction, results in an increase in plasma &e cholesterol and the phospholipid lecithin. Since the cholesterol and phospholipid in the red ce11 membrane are in dynamic equilibrium with the plasma (Cooper et al 1975), the ce11 membrane takes on extni lecithin and cholesterol. This effectively increases the dacearea of the membrane and causes it to become folded and de4and to take on the appeariuce of the acanthocyte (Cooper et al 1975).
The lipid loading of the membrane results in increased osmotic resistance and increased membrane rigidity as indicated by reduced fîiterability (Cooper 1969). The increased ngidity contriiutes to mechanical nragility and redts in fragmentation and extravascular hemolysis as the spleen removes damaged red blood ceh (Cooper 1969). The hemolysis can be reduced by splenectomy but the acanthocytes remain (Silber et al 1966). merreports of acquired acanthocytosis have appeared in the human literature. In one case, acanthocytosis was associated with massive hepatic metastasis of a rectal carcinoid Even though there was a hemolytic anemia present, the red ceil membranes had normai quantities of cholesterol, and the plasma did not ûansform normal erythrocytes
(Keller et al 1971). Acanthocytes have also been descnbed in people following splenectomy (Brecher et al 1973) but have not been reported in the context of hemangiosarcoma or other splenic disease in human beings. It wouid appear that there are multiple factors responsible for the formation of acanthocytes (Keller et al 1971).
Acanthocytes in Animais
Acanthocytosis can be experimentally produced in rabbits and guinea pigs by feeding high cholesterol diets (Sardet et al 1972). Rats fed orotic acid (which blocks the synthesis of P-lipoprotein) develop acanthocytosis (McBride and Jacob 1WO), as do rhesus monkeys fed lithocholic acid (a bile acid that is elevated in human liver disease) (Cooper et al 1972).
Spurîell anemia has been reported in a dog with severe hepatoceliular disease but without the membrane lipid abnonnalities seen in man (Shull et al 1978). Acanthocytes are reported in cats with hepatic disease (Christopher and Lee 1994), and in dogs with chronic passive congestion, hepatic fibrosis, nodula. hyperplasia and hepatic neoplasîa (Rebar et al 1981).
Very Little is known about the pathogenesis of acanthocytosis in animals (Ng and Mills
1985). Membrane lipid abnormaiities have not been reported in canine acanthocytes so it is not known if they exhibit the same properties as reported for humans ( Hinch et al 198 1). Acanthocytes and Canine Hemangiosarcoma
Gelberg and Stackhouse (1977) were the nrst to suggest an association between acanthocytes and hemangiosarcoma They identified "numerous" acanthocytes in the peripheral blood smears of three mked breed dogs with splenic hemangiosarcoma
Hematology resuits were not included so it is not possible to interpret what "numerous" means regarding the number of acanthocytes found. A second paper by Rebar et al described acanthocytosis and anexnia in 20 of 53 dogs with experirnentd radiation-induced hemangiosarcomas (Rebar et al 1980). in the report, acanthocytes were associated with hepatic hemangiosarcoma rather than splenic HSA, as in the earlier report, but were also found in dogs with HSA of the heart, lungs and bone. Acanthocytes were not identified in control dogs. The nwnber of acanthocytes was assessed semi-quantitatively on a scale of O to 4, but the correlation between score and ceil count was not described (Rebar et al 1980).
The association between HSA and acanthocytes was specifically addressed by Hirsch et ai (1981). They examined 12 blood films fiom dogs with HSA and identified acanthocytosis in six dogs. The presence of acanthocytes did not correlate with any specific organ involvement. The acanthocytes were described as "numerous and readiIy recognized", but no details were given as to how numbers were assessed. Controls were not included. In spite of the small sample size and lack of statistical analysis, the authors claimed that there was a "dennite association of acanthocytosis with hemangiosarcoma in the dog".
In a more detailed study of 10 dogs with HSA, acanthocytes were identified in nine
(Ng and MiIls 1985). Acanthocytes were assessed semi-quacltitatively using a one-plus, two-plus system. They were found to be present in ail (515) cases of liver involvement and in eight of nine cases of splenic involvement. The study provides good observational detail, but controls are not included and the sample size is too smd to permit conclusions regardhg the association between acanthocytes and HSA.
The diagnostic significance of acanthocytes in HSA is unclear. The existing evidence is largely descriptive and it is hampered by small sample sizes, subjective assessrnent techniques, and the absence of controls. However, the concept of acanthocytosis as an indicator of HSA has entered the general veterinary literature (Couto 1989). The attractiveness of this association is understandable since it appears to offer clinicians a potentially useful tool in the diagnosis of a difficult disease. Unforhmtely, the studies in the literature have focused on acanthocytosis in dogs with confirmed HSA rather than the clinicd situation in which the practitioner must use diagnostic data to distinguish behveen difXerent diseases with shilar presenting sip. The utility of acanthocytosis as a diagnostic
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Couto CG. Diseases of the lymph nodes and the spleen. Ln. Eainger SJ ed. Textbook of Veterinary Intemal Medicine. 3rd ed. Philadephia: WB Saunders, 1989: 2225-226.
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Culbertson MR. Hemangiosarcoma of the caoine skin and tongue. Vet Pathol 1982; 19: 556-558. deMaciron E, Helfand SC, Stebbins KE. Use of chemotherapy for trament of cardiac hemangiosarcoma in a dog. J Am Vet Med Assoc 1987; 190: 887.89 1.
Duncan JR, Prasse KW, MahafEey EA. Veterinary Laboratory Medicine. Iowa: Iowa State University Press, 1994: 15.
Fees DL, Withrow SJ. Canine Hemangiosarcoma Comp Contin Educ Pract Vet 198 1; 3 : 1047-1051.
Frey AJ, Betts CW. A retrospective survey of splenectomy in the dog. J Am Anim Hosp Assoc 1977; 13: 730-734.
Gelberg H, Stackhouse LL. Three cases of canine acanthocytosis associated with splenic neoplasia. Vet Med SmdAnim Clin 1977; 72: 1183- 1184.
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Hammer AS, Couto CG, Swardson C, Getzy D. Hemostatic abnormalities in dogs with hemangiosarcoma. J Vet htMed 1991; 5: 1 1-14.
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Zenoble RD, Gabbert NH. A possible case of disserninated intravascular coagulation and sptenic hemangiosarcoma. ChePract 1977; 4: 52-55. GENERAL INTRODUCTION: DIAGNOSIS OF CANINE: ~MANGIOSARCOMA
Antemortem diagnosis of canine hemangiosarcoma (HSA) is fiequently a clinical challenge due to the variable and often non-specific presenting signs in affected dogs
(Smith et al 1992). The involvement of different organs, with either primary or metastatic tumour, can produce an array of localizing signs that may confound a dennitve diagnosis.
Some dogs show only vague clinical sigm mch as lethargy, exercise intolerance, or weight loss without any localizing signs. ûther dogs show no prodromal signs at aii and present as cases of acute collapse or sudden death.
The spectnim of clinical signs has led to the use of many diagnostic modalities, including hematology, coagulation panels, radiography, ultrasound, echocardiography, angiography, fine needle aspiration and cytology, and ubately laparotomy, surgical biopsy and histology. The multipiicity of procedures is testament to the illusive nature of the diagnosis.
The need for an effective diagnostic test for HSA lies in the fact that early detection of the disease, before metastasis occurs, appears to offer the best prognosis. Extirpation of localized tumours results in less metastatic disease, longer disease-ftee tirnes (Vail et al
1995) and longer ovdsumival times (Prymak et al 1988, Vail et al 1995). However, the high metastatic potential of HSA makes early detection of the disease problematic (Fees and Withrow 1981, Waters et al 1988), and only reinforces the exigency of a tdy definitive diagnostic test The key value of a diagnostic test Lies in its abiiity to differentiate between subjects with similar clinical signs but with different diseases (Sackett et al 1991). Although the literature contains a large number of reports describing diagnostic findings in dogs with confïrmed HSA (KIeine et al 1970, Hirsch et al 1981, Thomas et al 1984, Oksanen 1978,
Ng and Mills 1985, Wrigley et al 1988, Prymak et al 1988, Hammer et al 199 1, Hammer and Couto 1992, Holt et al 1992, Smith et ai 1992, Hammer et al 1993), few studies address the issue of the diagnostic usefulness of specinc hdings in distinguishing between disease states. Most of these studies are retrospective case series which by definition are purely descriptive (Dohoo and Waltner-Toews 1985) and, because they typicdy describe only selected cases and do not include control groups for cornparison, the findiigs cmot be extrapolated to aay larger population (Bonnett and Reid-Smith 1996). Descriptive studies are valuable in suggesting trends and associations, but their clinical usefulness is limited
(Bonnett and Reid-Smith 1996).
There are three retrospective shidies that attempt to quanta the clinical significance of diagnostic findings with respect to the detection of HSA. The first study
(Holt et al 1992) calculated the accuracy of thoracic radiography as a diagnostic test for pulmonary and cardiac HSA. A small number of control radiographs were included and consisted of chest nIms fiom dogs that were either normal (negative control) or had radiographie evidence of nodular interstitial pulmonary disease (positive control).
Control radiographs for cardiac lesions were not included. The diagnostic sensitivity and specincity of thoracic radiographs was 78% and 90% respectively for pulmonary HSA, and 47% and 85% for cardiac HSA respectively. The size of the control group was smd relative to the numbet of dogs with con£irrned HSA, and since cardiac controls were also not included, the control group was inadequate in both size and representation. As a redt the vaiidity of the findings of the study may be questionable. in addition, the conclusions of this study pertain only to the diagnosis of dogs with pulmonary and cardiac HSA and therefore have limited applicability in the diagnosis of HSA in its various clinical presentations.
The second study (Hammer et al 1993) investigated the ability of radiography to detect puimonary metastasis in dogs with HSA. The diagnostic sensitivity was calculated to be 79% based on the number of dogs with metastatic lung patterns on radiograph that had HSA on postmortem. The study group was small and no controls were included.
Therefore, although evaluators were blinded, confidence in the calculated sensitivity of the test is tempered by the lack of idionnation about the test's ability to distinguish between HSA and other diseases with similar radiographie patterns. This study suffers the same limitation as the earlier study in that pulmonary radiographs are a diagnostic test for only a restricted subset of dogs with HSA.
Ody one report (Johnson et al 1989) has used logistic regression to assess multiple diagnostic indicators of HSA. Hematology, radiology, surgery and histology data were dyzedto determine the likelihood of splenic neoplasia in dogs with splenomegaiy. The study showed that anemia and splenic rupture were the most important indicators of splenic neoplasia However, in the antemortem situation, splenic rupture is largely a surgical diagnosis. As Bomett and Reid-Smith (1996) pointed out, biopsy for histology would undoubtediy be collected at the tirne of surgery, obviating the need for other diagnostic tests or indicators including splenic rupture. Interestingly, the authon also demonstmted that anemia, nucleated red celis, and abnomml red cell morphology were statisticaily associated with the presence of splenic HSA. However, only the three hematology parameters were considered, abnormalities were only reported as being present or absent, there was no distinction made between the various abnormalities in red ce11 morphology, and the results couid only be extrapolated to dogs with splenic disease.
One of the commonly reported red ce11 shape changes in dogs with HSA is the acanthocyte (Gelberg and Stackhouse 1977, Hirsch et al 198 1, Ng and Mills 1985). With its chatacteristic appearance, the acanthocyte is an excellent candidate as a diagnostic marker for the HSA if an association between the poikilocyte and the disease exists.
However, there are no midies that examine this association, or quantify the clhical usefulness of the acanthocyte either alone or in the context of other hematological changes.
The statistical association between hematological abnormalities and HSA established by Johnson et al (1989) together with the plethora of descriptive studies of hematological changes, would suggest that the diagnosis of HSA may be facilitated through the use of routine hematology. The attractiveness of a diagnosis based on a blood sample is that the diagnostic procedure is within the gnisp of all practitioners, it is non- invasive, inexpensive and readily available. As such, it has important advantages over the more sophisticated diagnostic protocols many of which are available only at referral institutions. Furthemore, routine hematology is one of the first tests performed in a diagnostic work up, and reliable detection of HSA during preliminary evaluation, or evidence to deout competing differential diagnoses could forestall unnecessary work up and hasten the institution of therapy, thereby possibly affecting the prognosis, depending on the stage of the disease. Comprehensive statistical studies of clinical pathological data in canine HSA have not been published. Hematological changes have been described but their clinical relevancy has not been quantified. Serum biochemistry data are rarely reported (Smith et al 1992) and the role of biochemical changes in the diagnosis of HSA has not yet been examined. This thesis explores the association between abnormalities in hematological and semm biochemical parameters and canine HSA, and assesses how useful specific changes are in the diagnosis of the disease.
The thesis is presented as two self-contained papers; the first paper (Chapter III) examines the association between acanthocytosis and hemangiosarcoma, and the value of acanthocyte count as a diagnostic test; the second paper (Chapter IV) employs logistic regression to create a predictive or diagnostic mode1 for canine HSA based on a wide range of demogtaphic, hematological, and senun biochemical parameters. As self- contained papers, each chapter consists of an introduction, materials and methods, redts, discussion, conclusions, and references. A final chapter (Chapter V) includes a surnmary of the results, and final conclusions as to the significance and applicability of the findings to the diagnosis of canine hemangiosarcoma. REFERENCES
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Oksanen A. Haemangiosarcoma in dogs. J Comp Pathol1978; 88: 585-595. Prymak C, KcKee LJ, Goldschmidt MH, Glickman LT. Epidemiologic, clinical, pathologic, and propostic characteristics of splenic hemangiosarcoma and splenic hernatorna in dogs: 2 17 cases (1 985). J Am Vet Med Assoc 1988; 193: 706-712.
Sackett DL, Haynes RB, Guyatt GH, Tugwell P. 2nd ed Clinicai Epidemiology. Boston: Little, Brown and Company. 199 1: 30-85.
Smith KA, Miller LM, Biller DS. Detection of nght atrial hemangiosarcoma using nonselective mgiocardiography in a dog. Can Vet J 1992; 33: 673-675.
Thomas WP, Sisson D, Bauer T, Reed JR. Detection of cardiac masses in dogs by two- dimensional echocardiography. Vet Radio1 1984; 24:65-72.
Vaii DM, MacEwen EG, Kman ID, Dubielzig RR, Helfand SC, Kisseberth WC, London CA, Obradovich JE, Madeweli BR, Rodrigwz Cû, Fidel J, Suaneck S, Rosenberg M. Liposome-encapsulated muramyl tripeptide phosphatidylethaoolamine adjuvant immunotherapy for splenic hemangiosarcoma in the dog: a randomized multi-institutional clinical trial. Clin CmRes 1995; 1: 1 165- 1170.
Waters DJ, Caywood DD, Hayden DW, Klaumer JS. Metastatic pattern in dogs with splenic haemangiosarcoma: dinical implications. J. Small Anh Pract 1988; 29: 805-814.
Wngley RH, Park RD, Konde LJ, Lebel Ji,. Ultrasonographic features of splenic hemangiosarcoma in dogs: 18 cases (19804986). J Am Vet Med Assoc 1988; 192: 1 113- EVALUATION OF ACANTEiOCYTE COUNT AS A DIAGNOSTIC TEST FOR CANINE HEMANGIOSARCOMA
INTRODUCTION
The acanthocyte is an irregularly spiculated red blood ce11 (rbc) fiequently found in the peripherai blood of dogs with hemangiosarcoma (HSA). The misshapen erythrocyte is characterized by numerous fuiger-like projections which Vary in length and width, and are irregularly distributed over the surface of the cell (Bessis 1977).
The link between acanthocytosis and hemangiosarcoma was first suggested in a report by Oelberg and Stackhouse (1977) who described "numerous" acanîhocytes in the periphed blood of three dogs with splenic HSA. In subsequent papas, several other authors also observed acanthocytes in dogs with HSA (Rebar et al 1980, Hirsch et al 198 1,
Ng and Milis 1985) and a "definite association of acanthocytosis with hemangiosarcoma in the dog" was reported by one author (Hirsch et ai 1981). These studies were purely descriptive, and involved small numbers of dogs, lssuaiiy without control groups for appropriate cornparîsons. These studies also did not address the issue of whether acanthocytosis satisfied any of the criteria for a valid or useful diagnostic test for hernangiosarcoma.
In spite of these limitations, a correlation between acanthocytosis and hemangiosarcoma has been accepted as a diagnostic tenet by some clinicians, and is described in general veterinary textbooks (Couto 1989, Jain 1993). The purpose of this paper is to investigate the putative association betxeen HSA and acanthocytes, and to mess the utility of the acanthocyte count as a diagnostic test for HSA in the dog by such standard measures as accuracy, precision, and predictive value.
MATERIALS AND METHODS
A retrospective case-control design was chosen for the study using the medical records of the Veterinary Teaching Hospital (VTH) of the Ontario Veterinary College for the period January 1983 to Febniary 1994.
Definitions and Criteria for Inclusion and Exclusion
Cases were defined as dogs with a histologicai diagnosis of hemangiosarcoma @SA) based on surgical biopsy or post-mortem examination. Further criteria for inclusion were age greater than one year, and a complete blood count (CBC) collected on admission to the
VTH within eight days prior to the histological diagnosis. Dogs were excluded fiom the case group ifthey had a second concurrent cancer or other primary disease such as diabetes or hypothyroidisn.
Controls were defined as dogs with clinical signs or physical bdings resembling
HSA, but with a final diagnosis of disease other than HSA. Eligible fïndings included abdominal mas; abdominal, thoracic or cardiac neoplasia; abdominal, thoracic or pericardiai effusion; and intemal hemorrhage. Control dogs were required to have a histological diagnosis of their disease, to be older than one year of age, and to have a CBC
collected at the VTH within eight days prior O the histological diagnosis. Dogs were
34 excluded fiom the control group if they had concurrent HSA, or were dering tiom recent trauma, pst surgical complicatioas, or acute surgical conditions such as gastric dilatation and torsion.
Dogs were excluded fkom both case and control groups if they had received intravenous fluid therapy, a blood transfiision, or chemotherapy prior to collection of the
CBC. Dogs were also excluded if either the patient's record or peripheral blood smear was unavailable for examination.
Potential cases and controls were initially identified using the computerized medical records data base (Veterinary Medical Information Management System) of the VTH. The case group was derived fiom dogs with "hemangiosarcomayyappearing in any computerized data entry field including admissions, clinical examination, radiology, ultrasound, biopsy and post-mortem. The control group represented diseased dogs whose conditions would support a differential diagnosis of HSA. The data entry fields searched were the same as for the case group, but a variety of diseases and conditions (See Appendix lA), with features resembling HSA, were considered. The paper files of all candidate dogs were examined in detail to determine eligibility for the study.
Acanthocyte Study
One eligible blood smear was retneved for each dog in the study, and prior to microscopie examination the slides were randomized and masked so that each slide was identined only by an assigned sequence number. Using a Miller's ocular (product #176,
Leica Inc., Toronto, Cd),which is the reticule used for routine reticdocyte counts (Brecher and Schneiderman 1950), 1500-2000 red blood cens were evaluated in the monolayer of the blood fi by the primary author (Rater A), a senior doctoral graduate student in veterinary clinical pathology. Among the 1500-2000 red blood ceus, the nurnber of acanthocytes were counted. Keratocytes, schistocytes, Howell-loily bodies, and rubricytes were also counted for use in a later study.
The repeatability of acanthocyte counts was detennined by measuring intrasbserver and inter-observer agreement for repeated acanthocyte counts on subsets of the blood films.
For the initial inûa-observer agreement study, 195 of the 295 blinded blood films were randomiy selected, and the acanthocyte count was repeated by Rater A using the original protocol. The inter-observer Wement study was performed on the first 95 of the 195 slides used in the inûa-observer study. The two independent observers, identified as Rater
B and Rater C, iacluded a Registered Medical Technologist with 20 years experience in hematology, and a doctoral graduate in veterinary clinical pathology employed as a diagnostician in a private laboratory. The slides were blinded, and acanthocytes were counted ushg the original protocol. A second smailer intra-observer study was performed by having Raters B and C repeat acanthocyte counts on 62 of the 95 blinded blood srnears.
Due to variation in acanthocyte counts in the inter-observer study, a separate study was designed to characterize causes of the variation, and to establish if a consensus gold standard existed for the acanthocyte. For this study 5"xT'colou. photomicrographs were taken (Provis Tme Research System Microscope Mode1 AX70, Olympus Optical Co. Ltd.
Japan) of blood smears fiom dogs with histologically confirmed HSA and fiom control dogs. AU fields were selected at 400x and photographed with 2.5~rnagnincation for an overall mapification of 1000~.A total of 37 photographs were taken including fields with many acanthocytes, fields with no acanthocytes, and fields with dflerent artefacts that might confound identification of acanthocytes. Sample photographs are included in
Appendk 1C. The photopphs were randomized and masked, and given to five observen
(Raters 1-5) who independently examined the photographs and recorded the number of acanthocytes seen per photograph. The observers included two Diplomates of the Arnerican
Coiiege of Veterinary Clinical Pathology, each with at least 20 years of faculty experience in a university veterinary school, and the three raters mentioned earlier (with different designations). When the photographs had been examined once, they were re-randomized and blinded, and the process was repeated by al1 five observers.
Analy sis
The andysis of acanthocyte counts fiom dogs with superficial HSA was limited to descriptive statistics, a two sarnple Student's t-test, and Chi-square comparison with dogs with visceral HSA. Further dysis was not performed due to the small number of dogs affecteci, and also because dogs with cutaneous diseases were not included in the control group as needed for appropriate comparison. In this paper, all reference to hemangiosarcoma, case, or aeddogs, implies visceral disease uniess cutaneous disease is specined.
For acanthocyte counts on blood srnears, descriptive statistics, two-sample Student's t-test, and Chi-square tests were performed for dogs with visceral HSA and control dogs.
Acanthocyte count was evaluated as a diagnostic test for HSA by calcuiating its sensitivity, specificity and predictive value using histopathology as the gold standard. Possible diagnostic cutpoints were examined using a receiver operator characteristic (ROC)plot.
In the tests of precision, the intra-observer agreement was quantified in three ways:
Kappa values (IC)with 95% confidence intervals (CI) (Shoukri and Edge 1996) for the binary cutpoints O vs. 21,515 vs. s15, and GO vs. >50 acanthocytes/2000 rbc; weighted
(quadratic) Kappa values (and 95% CI) for acauthocyte counts categorized as 0, 1-1 5, 16-
50, and >50 acanthocyted2000 rtic; and intra-class correlation coefficient (ICC) for acanthocyte count as a continuous variable. Two ICC's for intra-observer agreement were calcuiated for Rater A; one for the initiai 195 observations, and a second one for the 62 observations that were used to calculate the individual intra-observer ICC for Raters B and
C (Table 3.1). The inter-observer agreement between Raters A, B and C was assessed with unweighted and weighted (quadratic) Kappa values for categorical data, and by ICC's for the 62 observations in common.
In the photographie study, intra-observer and intersbserver agreement was quantified by unweighted aod weighted (quadratic) Kappas on categorized data, and by intra-class correlation coefficients. For the intra-observer agreement, acanthocyte counts were grouped into 17 scaled categones: 0, 1-2, 3-5, 6-10..... 1 1 1-130, 13 1-150 acanthocytes/photograph. The data for inter-observer agreement were grouped as 0, 1- 1 5,
16-50 and >50 acanthocytes/photograph to parallel the groupings used in the blood film study. Agreement within and between raters was measured for nrst and second readings of the photographs.
The STATISTIX sobare program (version 1.O for Windows, Anaiytic Software,
Tallahassee FL, 1996) was used for the descriptive statistics and for tests of association. The intra-class correlation coefficients were generated with the Statistical Analysis System uistitute software program (version 1 for Windows, SAS Institute hc., Cary, NC, 1996).
The details of the selection process for the midy population are presented in
Appendix 1A. The final study group consisted of 95 dogs with HSA and 200 control dogs.
The dogs with HSA were subdivided into 80 dogs with tumour masses in the thoracic and abdominal viscera and 15 dogs with ~ourmasses in the demis, subcutis, or superficial muscle. Dogs with tumours in both visceral and superficial locations were included in the visceral group because of the wider organ involvement.
The fkquency distribution of acanthocytes for cases and controls is presented in
Figure 3.1. For dogs with viscemi HSA, the mean (& standard deviation) acanthocyte count was 18.4/2000 rbc (2 42.3) which was significantly higher than the value of 3.Y2OOO rbc (k
9.9) for the control group Q = 0.003). There was also a significant association between the presence of acanthocytes and visceral HSA (P = 0.02). There were 46.3% of dogs with
HSA that did not have acanthocytes present, and 38.5% of control dogs that did, including
13 dogs (6.5%) with moderate to marked acanthocytosis (>15 acanthocytes/2000 rbc). The range of acanthocyte counts was 0-241 acanthocytes/2OOO rbc for dogs with HSA, and 0-71 acanthocytes/2000 rbc for controls. The sensitivity and speciîïcity of acanthocyte count at various cutpoints are Listed in Appendk 1B and presented graphicdy as a receiver operator characteristic (ROC) curve in Figure 3.2. The positive and negative predictive values for acanthocyte count at various cutpoints are also listed in Appendk 18. Figure 3.1 Frequency Distribution of Acanthocyte Couots For Dogs With Hemangiosamma (HSA) and Contro ls.
HSA CONTROLS
O 1-15 18-50 51-71 >71 Acanthocyte Count / 2000 red blood cek Figure 3.2 Receiver Operator Characteristics Plot for Acanthocyte Count
0 .O 0.2 0.4 0.6 0.8 1.O 1-Speciîicity (false positives) Blood Film Study
In the blood film study, the intra-observer agreement across binary cutpoints varied hmpoor to good for d three raters (Table 3.1). The highest point estimate for intra- observer agreement (K = 0.77) was achieved by Rater A at the cutpoint of <15 vs. >15 acanthocyted2OOO rbc. For categoncal data, the unweighted r values were consistently poor for intra-observer agreement, but the weighted K were adequate for al1 three observers.
This denotes acceptable relative agreement between readings by the sarne observer, although absolute agreement was poor. The ICC for Rater A was excellent (0.92), but ICC was relatively poor for Rater B and C suggesting there was bias in the disagreement between first and second readings for these raters.
The K values for inter-observer agreement across binary cutpoints were poor to fair for ail rater-pairs. The range of K for both readings was 0.07-0.66 with the majority of vaiues falling below 0.50 indicating poor agreement beh~eenraters (Tables 3.2 and 3.3).
Likewise for categoncal data, the unweighted r values were consistentiy poor for ail pair- wise inter-observer comparisons (0.16-0.39),except for Rater C who had fair agreement with Rater B on the first reading (K = 0.66), and good agreement with Rater A on second reading (K = 0.71). The poorest agreement was between Raters A and B, with weighted r values of 0.25 and 0.47 for first and second readings respectively.
The ICC for the inter-observer comparisons (Table 3.4) were mostly faV to poor, with considerable variation between raters both within, and between readings. The data indicate that inter-observer agreement was generally better on the nrst reading than on the Table 3.1 Inûa-observer agreement for acanthocyte counts on peripheral blood smears. Show are kappa values (K) (95% Confidence Interval) for agreement on binary cutpints; unweighted and weighted K for categorical data; and intraclass correlation coefficients for Raters A-C. n = number of slides read in eacli reading.
K Intra-class Categorical Data Correlation
Unweighted Weighted
Rater A 0.32 0.64 0.92 (0.19-0.44) (0.52-0.75)
Rater A 0.46 0.72 0.92 (0.27-0.66) (0.55-0.88)
Rater B 0.33 0.66 0.46 (O. 17-0.49) (0.42-0.91)
Rater C 0.30 0.62 0.5 1 (O. 14-0.47) (0,s-0.76)
" 62/195 ;O read hvice by Raten B and^ Table 3.2 Inter-observer agreement for acanthocyte counts on peripheral blood smears. Shown are Kappa vdues (95% Conildence Interval) for agreement on binary cutpoints; and unweighted and weighted Kappa values for categoricai data Results are for Raters A-C on nrst reading of 95 blood smears.
First Reading
K Categorical Data
O VS. 21 SIS VS. >is GOVS. >50 Unweighted Weighted
0.26 0.53 (O. 1200.4) (0.38-0.67)
Table 3.3 Inter-observer agreement for acanthocyte counts on peripheral blood smears. Shown are Kappa values (95% Confidence interval) for agreement on binary cutpoints; and unweighted and weighted Kappa values for categoricd data. Results are for Raters A-C on second reading of 62 blood smears.
Second Reading
cutpoints K Acanthocytes/2000 rbc Categorical Data
Ovs.21 SlSvs.>15 GOvs. >50 Unweighted Weighted
0.23 0.24 0.07 (0.0-0.46) (0.05-0.44) (0.0-027)
0.48 0.66 0.55 (0.27-0.70) (039-0.93) (O.1 1-0.99)
0.56 0.4 1 0.22 0.27 0.54 (037-0.75) (0.2-0.62) (0.0-0.5) (O. 12-0.42) (O3 8-0.70) Table 3.4 Inter-observer agreement for acanthocyte counts on peripheral blood smears. uitra-Class Correlation Coefficients for subset of 62 blood smears comrnon to all raters. n = number of observation included in cornparison.
Rater n Reading Intra-class Correlation
second 0.34 second 1 0.87 B, C 124 second 0.27 A, B, C 186 first 0.54 second combined combined combined
Table 3.5 Intra-observer agreement for acanthocyte counts on photographs. Shown are unweighted and weighted Kappa values (95% Confidence Interval), and intra-class correlation coefficients for Raters 1-5 for two readings of 37 photographs of peripheral blood containing vaqhg numbers of acanthocytes.
Rater Unweighted K Weighted K Intra-class Correlation Coefficient
0.48 (0.3 1-0.64 )
0.3 1 (O. 13-0.49)
0.2 1 (0.06-0.35)
0.51 (0.34-0.67)
O -65 (0.47-0.83 ) second, and that the best inter-observer agreement for al1 observations was achieved by
Raters A and C (ICC = 0.75), and the poorest by Raters A and B (ICC = 0.57).
In the photographie study, the unweighted K values for htra-obsewer agreement across 17 categones of acanthocyte counts were fair to poor for most raters, while the values for weighted K and ICC for al1 raters were excellent (Table 3.5 ). Rater 3 had the weakest unweighted K, and even though the weighted K was scored as excellent, it was noticeably lower than those of the other four ratea. The ICC for Rater 3 was roughly half that of the other raters, denoting a disagreement bias that was not present for the other raters. Rater 5 had the best unweighted K (0.65), and also had the best ICC for inûa-rater agreement (0.9 8).
nie variability in acanthocyte counts for Rater 3 contnbuted to poor inter-observer agreement with ail 0thobservers on the first reading of the photographs. The unweighted
K for individuai cornparisons with Rater 3 mnged fiom 0.07-0.32,with only moderate improvements with weighted K. In contrast, the inter-observer agreement between the other four raters varied fiom good to excellent with only 1 of 6 weighted r values falling below
0.6 (Table 3.6). The effect of this polarization of agreement was evident when data f?om
Rater 3 was excluded fiom the cdculation of the inter-rater ICC. The ICC for all 5 observers was 0.42, but excluding Rater 3, the ICC improved to 0.71 confïrming good inter-observer agreement between Raters 1,2,4, and 5, and poor agreement between Rater
3 and the others. On second reading of the photographs, all inter-observer c values for
Rater 3 improved, denoting better agreement with the other observers (Table 3.7). ln con- ail intersbserver K for Raters 1,2,4 and 5 deteriorated slightly. However, the net effect of these shifts was an improvement in overall agreement between ail five raters resulting in a respectable ICC of 0.71 that dropped only mmpinaiiy to 0.70 when data for
Rater 3 was excluded.
Although there was good inter-rater agreement for Raters 1,2,4 and 5 as a group for both readings of the photographs, there was considerable variability between observers within the group (Tables 3.6 and 3.7). The best score was achieved by Raters 1 and 4 (0.91) on first reading, and the lowest was between Rater 1 and 2 (0.46) on second reading. There was consistently better agreement between Raten 1 and 4 and between Raters 2 and 5, and within the four observers, Rater 5 had inter-observer agreement vdues consistentiy greater than 0.75, while Rater 2 had more values below 0.75 than above.
Superficial HSA
The mean (+ standard deviation) acanthocyte count for the 15 dogs with cutaneous and superficial HSA was 7.9 (it 24.1 1) which was not signincantly Werent f?om the mean of 18.4 1 2000 rbc (k42.3) for dogs with visceral HSA (P = 0.19). The counts for dogs with superficiai disease ranged fiom 0-94 acanthocytes/2000 rbc. Among the 95 dogs with ail fomis of HSA, the Chi-square test did not show a.association between acanthocyte count and the presence of superficial disease (P = 0.98). DISCUSSION
In contrast to earüer descriptive reports of acaathocytosis and HSA, this study included an appropnate control group. As a result it was possible to test for a statistical association between acanthocytosis and HSA, and to calculate the appropriate meamres of utility to assess acanthocyte count as a diagnostic test.
The case-control study may be considered one of the weaker experimental designs due to the potentiai for bias in the selection of the study population (Hayden et al 1982).
This bias is fiequently a result of hcomplete or inaccurate records and flawed selection criteria. In this study, computerized medical records were used, and the effect of record quality was minimized by directly examining the paper files and original documents to ensure the accuracy of the data, and coanmi the eligibility of al1 dogs in the study. In addition, the selection criteria for inclusion and exclusion were specinc and unequivocal, and although possibly flawed, they were applied with equal ngour to both cases and controls to avoid unintentional bias.
Histopathology was used in this study as the best "gold standard" available to ensure that aH dogs in the case group did in fact have HSA, and that dogs in the control group did not. Primary selection of dogs for the case group was relatively straightforward and hinged on a recorded histological diagnosis of HSA. However, selection of the control poup was problematic because, beyond the prerequisite histological diagnosis of disease other than
HSA, the selection process required a reconstruction of the clinical diagnostic process to determine XHSA might reasonably have been a de-out for the dog. It could be argued that clinical fïndings such as abdominal mass, pericardiai effusion etc. were arbitrary critena applied to controls even though similar hdlligs were not required of dogs in the case group. However, the ciinical features matched in the controls were those most commonly reported in dogs with HSA and therefore represented at least the "classic" presentations of
HSA. Every effort was made to select control dogs with conditions that resembled some aspect of HSA, but whether HSA was a differential diagnosis at the the of clinical presentation is dSicult to know fiom the existing records. Regardless of possible flaws, the control group in this study is an improvement over that in any previous study, and is a credible backdrop against which to study the association between acanthocytosis and HSA.
Diagnostic tests are perfomed for a variety of reasons (Sackett et al 1991 PSI), but for the clhician, a primary objective is to classify subjects into clinically meaningful mbgroups so that appropnate patient care can be implemented (Martin and Bonnett 1987,
Sackett et ai 1991 p. 4). The value or usefulness of a diagnostic test is detennined by its ability to differentiate between different diseases with similar clhical signs (Sackett et al
1991). Usefulness is rneasured by objective criteria such as accuracy (sensitivity and specifïcity), precision (repeatability), and predictive value, as well as by subjective cnteria mch as the advantages one test has over another (e.g. allows for earlier detection of disease, alters medical management, or is less expensive, invasive, or tirne-coosuming) (Sackett et ai 1991 p. 57).
Briefly, sensitivity is "positivity in disease" or the proportion of inavidds with disease who have a positive test result. Specincity is "negativity in health" or the proportion of individuals without disease who have negative test results (Sackett et al 1991 pp. 8 1-82).
Precision is the ability of the test to field the same meron repeated testing of the same sampie (Sackett et al 1991 p.58). Positive predictive value îs the proportion of individuals with a positive test result that have the disease of interest, and conversely, negative predictive value is the proportion of individuals with a negative test result that do not have the disease of interest (Sackett et al 1991 p. 85). Although diagnostic sensitivity and specificity are genedy stable characteristics of a test, predictive values are dependent on the prevalence of the disease.
A connection has been made in the literature between acanthocytosis and hemangiosarcoma in dogs (Gelberg and Stackhouse 1977, Hirsch et al 198 1, Ng and Mills
1985). The redts of this study confimi that a statistical association exists between acanthocytosis and HSA, but demonstrate that acanthocyte count has very limited utility as a diagnostic test for the disease. Dogs with HSA were more likely to have acanthocytes, and to have higher acanthocyte counts than controls, but the high percentage of case dogs that did not have acanthocytes in their blood films resulted in a very poor sensitivity for acanthocyte .count. A maximal sensitivity of 53.8% at a level of 21 acanthocytes/2000 rbc means that the presence of acanthocytes has approxhately the same probability for success as a coin toss in detecting the presence of disease. The low sensitiviy also means that there is no level of acanthocytosis at which HSA can be ruied out.
nie presence of moderate to marked acanthocytosis in 6.5 % of control dogs proves that acanthocytes are not unique to HSA. Acanthocytes were found in the blood of dogs dering fiom a variety of diseases af5ecting diverse organs. A List of these diseases is included in Appendix 1A.
Although sensitivity was poor, specincity was excellent for ail degrees of acanthocytosis except very low counts. The high specincity ûanslated into a strong positive predictive value for rnarked acanthocytosis, and produced the ody useful cutpoint in the study which was 272 acanthocytes/2000 rbc. At this cutpoint, positive predictive value was
100%, and acanthocyte count would confidentiy dein HSA. However, the associated sensitivity at this level was 7.5%. So although marked acanthocytosis would dein HSA, it wodd detect only a smail proportion of diseased dogs.
Positive predictive value was high due to the small proportion of control dogs that had acanthocytes. By cornparison, negative predictive values were equivocal, approximately 75%, at ali levels of acanthocytosis due to the high proportion of dogs with
HSA that did not have acanthocytes.
The receiver operator characteristic (ROC) curve is a plot of aii possible sensitivity 1 specifïcity pairs for a given test. It is a simple, graphitai way to visualize a test's ability to distinguish between two alternate states of health over aii decision cutpoints (Zweig and
Campbell 1993). The ROC curve for the perfect test would pas through the upper left comer of the graph which iodicates 100% sensitivity and 100Y0 specificity (0% faise positives). The test without any ability to distinguish between chical states would generate a ROC curve dong the 45O diagonal line hmlower lefi comer to the upper right comer
(Zweig and Campbell 1993). The ROC curve for acanthocyte count fdsslightly away fiom the diagonal, indicating some ability to distinguish between disease states. However, the curve remains closer to the diagonal than to the upper Ieft comer at all points iilustrating the generaily weak performance of the test There is also no single point that could be interpreted as a cutpoint with any pater diagnostic signincance than any other cutpoint, a
Merdemonstration of the Limited utility of the test
The repeatability of acanthocyte counts was assessed by both intra-observer and inter-observer agreement ushg the kappa statktic and the intraclass correlation coefficient
53 Kappa is a measure of clinical agreement for categorical data, and represents the proportion of the total possible agreement beyond chance that is actually achieved by two observers
(Fleiss 198 1, Sackett et ai 1991 p. 30). When the data are in three or more categories, K can be weighted to quanti@ the disagreement between observers such that higher scores are achieved when observations are mildly disparate and lower scores result when there is serious disagreement between observers. The weighting scheme applied in this study was quadratic weighting, which assigris a heavy penalty for e-e disagreement. The interpretation of K varies somewhat between authors (Fleiss 1981, Martin and Bonnett
1987, Sackett et al 1991) but the scoring used in this study, following Fleiss, was K < 4.0 represents poor agreement beyond chance, K > 7.5 represents excellent agreement beyond chance, and values between 4.0 and 7.5 represent fair (4.0< K 69)to good (6.0< K g.5) agreement beyond chance.
The advantage of the K statistic is that it can measure agreement behnreen categones that have been stnictured to represent the diagnostic cutpoints used in the &y-to-day application of the test. For example, in this shidy the categones were established based on patterns in the data to reflect absent, mild, moderate, and marked acmthocytosis. Inspection of constnicted r tables also permits visualization of patterns or trends in the data that can explain disagreement when the r score is low. The disadvantage of the K statistic, is that artefactual disagreement can be created when values are similar but on opposite sides of a
£ked cutpoint. This drawback is counterbaianced by use of the ICC.
The ICC measures variation within a goup of observations relative to variation between groups. If the observations in a group are sirnilar, they are said to be correlated and will yield a positive correlation coefficient (Snedecor and Cochran 1967, Keuhl 1994). The 54 ICC is derived fiom the analysis of variance for continuous data, and is a summary estimate of the overall agreement between individual observations. It is essentially identical to the weighted Kappa (FIeiss 1981) and is interpreted similady (Sackett et ai 1991). Its advantages are that agreement is not lost across cutpoints, and it is able to detect systematic variation between observations by producing a lower ICC when bias exists. (Bias is defined as "any effect at any stage of an investigation or inference tending to produce results that depart systematidy fiom the true values" (Last 1983)).
Blood Film Study
The intra-observer K values for dichotomous cutpoints were variable for the three raters suggesting that precision was a problem regardless of the degree of acanthocytosis present. There was no single threshold for which al1 raters had good precision. However, the most promising cutpoint appeared to be S15 vs. >15 acanthocyted2000 rbc based on the resdts for Rater A. At this cutpoint, Rater A had K and ICC values consistent with good intra-rater agreement without bias. The evidence niggests that acanthocyte counts 45 acanthocytes/2OOO rbc can be repeated with adequate precision by an experienced observer.
The higher K and ICC achieved by Rater A may be attributable to the additional experience acquired through the assessrnent of the complete set of 280 blood smears in the £îrst phase of the study. The extra experience may have offered greater cornfort with the protocol, and more practised in the detection of acanthocytes.
The systematic intra-observer disagreement for Ebters B and C is evident in the constructed K tables for each rater (Appendix 1B). Rater B was consistently higher on the second reading compared to the fusf and Rater C consistently lower. This disagreement bias undoubtedly contributed to the poor inter-observer K and ICC on the second reading, and resulted in the generally mediocre ICC for al1 2-way and 3-way comparisons. It is noteworthy that for the two comparisons with the strongest inter-observer agreement
(weighted K = 0.66,0.71) the cutpoint of S15b15 acanthocytes/2000 rbc was the thrrshold where agreement was strongest This is Merevidence that CO- >15 acanthocyted2000 rbc are repeatable in some situations.
Poor inter-observer agreement can usually be attnbuted to three sources: the examiner, the examined and the examination (Sackett et al 1991 p. 35). The examiners in this study may have introduced disagreement through clifferences in a) visual acuity, either due to individual biologicd variation or due to eye strain and fatigue, b) tolerance of tedious repetitious work, which may have afEected the amount of time an individual was willing to spend in classifying a red celi shape abnormality, c) interpretation of the test protocol, and application of the cnteria for acanthocyte identification, and d) expenence, not only in counting acanthocytes where Rater A had an advantage, but also Merences due to technicd versus professional background.
The blood nIms, as the "examined", may have ken r~sponsiblefor a large portion of both the intra- and inter-observer disagreement. The distrïïution of acanthocytes may not have been domwithin the monolayer, acanthocytes in some blood smears appeared to be more numerous in the deeper portions of the monolayer as compared to the feather edge.
On occasion there was considerable variability between blood films in ternis of spreading and staining of erythrocytes, and also in the presence of crenation and drying artefacts.
These factors may have skewed the number of acanthocytes present in a selected field or
56 afFiited the ease with which they could be disthguished.
The examination process is also a likely source for considerable disagreement.
Efforts were made to minimi7t? variation by the use of standardized equipment, written protocols, and preliminary joint training sessions. However, other factors that may have contributed to disagreement are the inherent error associated with counting, and the variability in the appearance of acanthocytes. The expected mor for ~canthocytecount would be the sarne as for the routine reticulocyte count as described elsewhere (Brecher and
Schneiderman 1950, Furlong 1973), and would be inversely related to the number of cells counted and the percent of acanthocytes present. Therefore, acanthocyte counts of 1% (20 acanthocytedîOOO rbc) would be expected to have a coefficient of variation (CV) of approximately 22%, and counts of 0.05% (1 acanthocyte/2000rbc) would have a CV of alrnost 100%. Although CV's were not caiculated in this study, at very iow counts, which were fiequent in this study, error alone couid account for disagreement between raters.
The acanthocyte itseIf may have been a source of variability in the examination.
Some authors report that acanthocytes ca.be "readily recognized" (Hirsch et al 1981). Yet others wam about the need to differentiate acanthocytes fiom ecchhocytes and staining artefacts (Gelberg and Stackhouse 1972) suggesting that a degree of discernment rnay be necessary in some situations. The '%lassic" acanthocyte is unlikeIy to be mistaken for anything else, but there is no irrefiitable way to determine if a poikilocyte is, or is not, an acanthocyte. Each rater must decide if a celi meets the published criteria for an acanthocyte.
This element of decision-making adds considerably to the potential for disagreement between raters. The subsample used to mess inter-observer and intra-observer agreement rnay dso have contnbuted to poor precision. The 95 and 62 slides read by raters B and C were not randomly selected and it is possible that there was uneven representation of mil4 moderate, and marked acanthocytosis. if one level of acanthocytosis was more difficult to read than another level, and the dersubsets contained a higher proportion of these slides, then a lower rate of agreement would be expected.
Photographie Study
The photographic study was an effort to assess how much of the observer disagreement in the blood film study might be due to imperfect and/or inconsistent recognition of acanthocytes. Photopphs were used to eliminate the variability associated with field selection, focus, biological variation etc. It was expected that by using this standardized presentation, five trained and experienced individuals would achieve hi& intra- and inter-obse~eragreement on acanthocyte counts. Since substantial agreement may serve in lieu of a true gold standard (Martin and Bonnett 1W), the demonstration of a c4conse~''gold standard for the acanthocyte would then imply that the poor agreement in the blood film study was Mydue to factors other thaa the lack of a unined concept of what constituted an acanthocyte. Perhaps not surprisingly, the data fiom the photographic study indicated that a consensus gold standard does not exist for the acanthocyte.
The data from the photographic study demonstrated that acanthocyte counts were repeatable with relative, though not perfect, precision by trained observers. The ciifference between unweighted and weighted r for intra-rater agreement afnmied that while moa raters did very poorly at repeating acanthocyte counts exactly, even in the ngidly controiied presentation, they were consistentiy close in their quantification. It could be argued that 17 categories for acanthocytes counts was unduly restrictive, and contributed to lower rates of exact agreement. However, with a fixed presentation, a higher degree of intra-rater precision might reasonably be expected. It was important to determine if that level of agreement couid be achieved, and scoring with nmwer categories gave a more cogent measure of the intra-observer agreement.
ui con- inter-observer agreement was scored more generously because under
'%orking conditions" the exact number of acanthocytes is likely not relevant, but rather the general categones of absent, mild, moderate or marked acanthocytosis. Therefore the categories of O, 1-1 5, 16-50, and >50 acanthocytes/2000 rbc were deemed more appropnate as they had been for the blood film study. Llsing broad categories, and weighted K to give credit for relative agreement, most observers were able to achieve good to excellent scoring for alî inter-observer comparisons with the exceptions of Raters 2 and 3.
There was a repeatable sub-grouping of agreement among Raters 1, 2, 4, and 5 that did not correlate with years of experience or Diplomate status. The constnicted r tables for these observers revealed that Raters 1 and 4 were consistently more generous in their quantification of acanthocytes than Raters 2 and 5, with an average 3-5 fold difference in achial acanthocyte counts. For any given photograph, Rater 1 tended to have the highest count foiiowed in decreasing order by Rater 4, and Rater 5, and Rater 2. The significance of this finding is that even among trained expenenced veterlliary clinical pathologists, there was a strong subjective element in the identification of acanthocytes that resulted in a liberal versus a consmative hterpretation of what constituted an acanthocyte. It is
59 important to note, that aithough the two sub-groups of raters Mered in actual acanthocyte counts, there was good general agreement among the four raters about which photopphs had mil& moderate, or marked acanthocytosis. Furthennore, the ICC for first and second readings of the photographs were the same for these observers. This demonstrated that inter-rater agreement was repeatable, and that some measure of precision had been achieved in counting acanthocytes in spite of the inter-rater variability.
Rater 3 also had a tendency towards high acanthocyte counts but did not have the general agreement shared by the other four ratea. The trend was sutticiently pronounced on the first reading of the photographs that it arnounted to bias, and contributed to the Iow
ICC, not only for the inca- agreement for Rater 3, but also for the inter-observer agreement for aii five raters on the first reading.
Once the Merent approaches to counting acanthocytes was factored in, the pattern of inter-rater agreement was much more easily interpreted. Rater 2, by being the most cornervative of aii raters, was destined to have consistently poor agreement with Raters 1 and 4 who were more liberal, and extremely poor agreement with Rater 3 who not only had the most generous counts (especidy on the fint reading of the photographs), but whose data also suffered fiom bias and poor precision.
The photographs that generated the most confusion were ones wîth numerous crenated red cells, and red cells with miscellaneous spicdation. These changes are Wcely a cornmon source of confusion to many raters when counting acanthocytes.
There was disagreement between the two faculty observers, between the two doctoral observers, and especiaily between the professional and technical observers. The partition of disagreement dong technicd versus professional lines likely had more to do with Merence in experience derthan type of tdhg. The most consistent performance was achieved by the obsexver who, over the course of these studies, had counted more acanthocytes than the others. Experience may not have produced better accuracy but it appeared to enhance precision. This merreinforces the supposition that acanthocyte count, as a diagnostic test, likely would not perfonn well outside of the research environment.
By comparing the results of the photographic study and the blood film study, it was evident that the level of agreement for Raters A, B, and C was the same whether the individuals were counting acanthocytes on blood smears or photographs. It was possible to conclude that Rater A was consistentiy more conservative in counting acanthocytes than either Rater B or C, and that Rater B was not only more liberal but aiso less precise than
Rater A and C. These two pieces of evidence explain the pattern of agreement, disagreement, and bias found in the blood film study of acanthocytes. It is likely that the variability seen among these raters reflects how acanthocyte count would fiinction as a diagnostic test in the "real world"; for any given degree of acanthocytosis, it is likely that some raters would over-estimate the numbers present, others would under-estimate them, and there wodd be limited confidence in the estimate due to poor precision.
The cutpoints of O, 1-15, 16-50, and >SO acanthocytes/2000 rbc were arbitrarily established based on the data generated by Rater A on first readhg of 295 blood films. If the evidence of the photographic saidy is correct, and Rater A is conservative in the identification of acanthocytes, then these cutpoints should be considered conservative as weU. However, the breadth of categones that wouid be necessary to accommodate the wide variability between raters would make acanthocyte count unwieldy as a diagnostic test. Superfmial Hemangiosarcoma
There were relatively few dogs with superficial HSA in this study, and the small sample size may have contributed to the lack of statistical association between acanthocyte count and HSA. The paucity of dogs in the hospital population with superficial disease is likely a reflection of the fact that superficial masses are readily detected and more arnenable to surgical resection by practitioners in the field. As a result, dogs are less likely to be referred for treztment. However, it is more plausible that the lack of association between acanthocytes and superficial disease is an indication of the poor diagnostic ability of acanthocytes to detect HSA, regardless of the clinical manifestation.
CONCLUSION
This chapter provides statistical evidence of an association between acanthocytosis and the presence of HSA in the dog. Dogs with acanthocytes in their penpherd blood smears were more iikely to have HSA, and dogs with HSA had higher acanthocyte counts than dogs with clinicdy similar diseases. These fkding corroborate the anecdotal evidence in the literature that dogs with HSA fkquently have acanthocytosis.
However, despite a proven statistical association berneen acanthocytosis and HSA, acanthocyte count is a poor diagnostic test for the disease. Technically, the test ders fiom having neither a formal gold standard nor even a consensus gold standard for the acanthocyte itse1.f The subjective nature of identifjing acanthocytes, together with the many other sources of variability extant in most teclmical tests, results in generaily poor precision for acanthocyte counts. The lack of precision makes it difficult to be confident in the accuracy of the test. The sensitivity and specificity reported in this study are based on one conservative observer's interpretation of acanthocytes, and are likely an overestimation of how the test would perform in the "real world". In other laboratories or diagnostic situations, with other observers, the precision of acanthocyte counts would iikely be even worse, and sensitivity and specificity, as poor as they are to begin with, wouid deteriorate accordingly. However, the study did demonstrate that in select situations, counts were repeatable with at least moderate precision, which provides a modicum of validity for the test.
From a clinical perspective, the presence or absence of acanthocytes does not help in the diagnosis of HSA. There is no level of acanthocytes that will enable a clinician to rule out HSA. The ody diagnostic value of acanthocyte count lies in its excellent positive predictive value at acanthocyte counts of >71 acanthocytes/2000 rbc (3.55%). By conservative standards this represents a marked acanthocytosis. At this level, acanthocyte count would confidentiy rule in HSA, although it would detect only a small proportion of the diseased dogs.
In conclusion, the study connmis that acanthocytosis is associated with HSA, but that for ail practical purposes, acanthocyte count is an unreliable and insensitive test with limited clinical usefulness. Without agreement between rat ers, neither the rater' s opinion, nor the test result is of much value (Martin and Bomett 1987). REFERENCES
Bessis M. Blood smears reinterpreted. New York: Springer International, 1977: 64.
Brecher G, Schneiderman M. A tirne-saving device for the counting of reticulocytes. Am J. Clin Path 1950; 20: 1079-1083.
Couto CG. Diseases of the lymph nodes and the spleen. in: Ettinger SI ed. Textbook of Veterinary Internai Medicine. 3rd ed. Philadephia: WB Saunders, 1989: 2225-2245.
Fleiss JL. Statistical Methods of Rates and Proportions. 2nd ed. New York: Wiley, 198 1: 2 17-234.
Furlong MB. Interpreting the reticulocyte count. Postgrad Med 1973; 54: 207-21 1.
Gelberg H, Stackhouse LL. Three cases of canine acanthocytosis associated with splenic neoplasia. Vet Med Small Anim Clin 1977; 72: 1 183-1 184.
Hayden GF, herMS, Horwitz RI. The case-control study. J Am Med assoc 1982; 247: 326-33 1.
Hirsch VM, Jacobson J, Mills JHL. A retrospective study of canine hemangiosarcoma and its association with acanthocytosis. Can Vet J 198 1; 22: 152- 155.
Hayden GF, Kramer MS, Horwitz RI. The case-control study. J Am Med assoc 1982; 247: 326-33 1.
Jain NC. Essentials of Veterinary Hematology. Philadelphia: Lea & Febiger, 1993.
Kuehl RO. Statistical Principles of Research Design and Analysis.California: Duxbury, 1994: 137-138.
Last JM. A Dictionary of Epidemiology. Toronto: Oxford University Press, 1983: 10.
Martin SW, Bonnett B. Clinical Epidemiology. Can Vet J 1987; 28: 3 18-325.
Ng CY,Milis JN. Clinical and haematological feanires of haemangiosarcoma in dogs. Aust Vet J 1985; 62: 1-4.
Rebar AH, Hahn FF, HaUwelI WH, DeNicola DB, Benjamin SA. Microangiopathic hemolytic anemia associated with radiation-induced hemangiosarcomas. Vet Pathol 1980; 17: 443-454. Sackett DL, Haynes RB, Guyatt GH, Tugweil P. 2nd ed Clinical Epidemiology. Boston: Little, Brown and Company. 199 1: 30-85.
Snedecor GW, Cochran WG. Statistical Methods. 6th ed. Iowa: Iowa State University Press. 1967: 294-296.
Shoukri MM, Edge VL. Statisticai Methods for Health Sciences. Boca Raton: CRC press. 1996: 89-96.
Zweig MH, Campbell G. Receiver-operating characteristic (ROC) plots: a fùndamental evaluation tool in clinical medicine. Clin Chem 1993; 39: 56 1-577. CHAPTERIV
ASSOCIATIONS OF HEMATOLOGICAL AND SERUM BIOCHEMlCAL CHANGES WITH HEMANGIOSARCOMA IN DOGS
INTRODUCTION
Most of the published studies that purport to identify diagnostic indicators of hemangiosarcoma (HSA)are descriptive case reports or case series that catalogue the clinical or labonitory abnormalities in dogs diagnosed with HSA (Bonnett and Reid-
Smith 1996). Because controls are not included in these studies, it is not possible to establish that a txue association exists between the disease and the described abnormalities. Furthemore, these papers fail to demonstrate that the observed abnormalities have any power to distinguish between different diseases with similar clinical signs. The sensitivity, specificity and predictive value, the standard measures of value for a diagnostic test, are rarely reported (Holt et al 1992, Harnrner et al 1993).
One statistical method for describing the relationship between a binary outcome and a large number of potentially explanatory variables is logistic regression, a type of multivariable analysis. A brief discussion of the technique is provided in Appendix 2A.
Multivariable logistic regression has been used widely in medicine and related disciplines
(e.g. psychiatry (Fleiss et al 1986)) as weU as veterinary medicine for predictive, diagnostic and prognostic purposes. In vetetinary medicine logistic regression has been use& for example, to identify factors affecthg postpartum reproduction in dairy cattle
(Bonnett et al 1993), to predict mortality in septic neonatal foals (Hofian et al 1 to determine prognosis for cows with abornasal displacement (Cfiohn et al 1990), and to distinguish between systemic lupus erythematosus and clinically similar conditions in dogs (Kass et al 1985). An example using clinicopathologicai data was published by
Jensen and Hoier (1993) in which logistic regression analysis was used to predict the presence of primary or secondary hepatobiliary disease in dogs based on routine sem biochemistry data.
Only one report (Johnson et al 1989) has used multivariable analysis to assess diagnostic indicators of HSA. The method was used to determine the likelihood of splenic neoplasia in dogs with splenomegaly. The study showed that anemia and splenic rupture were the most important indicators of splenic neoplasia Since splenic rupture is a surgical diagnosis in the antemortem situation, a biopsy for histology would undoubtedly be collected at the time of surgery, obviating the need for other diagnostic tests or indicators including splenic rupture (Bomett and Reid 1996). Furthemore, the results of the study can be extrapolated only to a population of dogs that present with splenomegaly thnt subsequently undergo surgery. Although this may be of value in some cases of splenic HSA, it cannot be considered to be Myrepresentative of HSA in al1 its clinical manifestations.
In view of the limited discussion on the association and diagnostic usefulness of clinical laboratory hdings in HSA, the first objective of this study was to examine a variety of demographics, hematology, and serurn biochemistry data and determine which parameters were statisticdy associated with HSA. The second goal was to use multivariable logistic regression andysis to identify the combination of parameters that best predicted the presence of HSA, and to quantify the predictive and diagnostic usefulness of the resulting mode1 with respect to it sensitivity and specificity and total correctly classifïed.
MATERIAL AND METHODS
The shidy population was selected firom the medical records of the Veterinary
Teaching Hospital (VTH) of the Ontario Veterinary Coliege for the penod Ianuary 1983 to
Febniary 1994. The experimental design was a retrospective case-control study with cases dehed as dogs with histologically confhned HSA, and controls defined as dogs with chical or diagnostic hdings that resembled HSA but with histological diagnoses of disease other than HSA. The final study population consisted of 80 dogs with visceral HSA and 200 controls. A complete description of the cnteria for inclusion and exclusion in the study is outlined in the matend and methods section of Chapter III and Appendix LA.
Hematology, senun chemistry? and demographic data for each of the 280 dogs in the study were retrieved fiom the computerized medical records (Veterinary Medicai
Idormation Management System (VMIMS)) of the VTH. The data collected included age, breed and sex, a standard complete blood count (CBC), and a standard biochemical profile of 19 analytes plus 9 misceilaneous semm chemistry analytes. In addition to the computerized data, one representative peripheral blood smear for each dog was microscopically examined in a blinded and randomized fashion, and the number of acanthocytes, keratocytes, schistocytes, and Howell-Jolly bodies were counted and recorded as celld2OOO red blood ceils (rbc) and absolute count (cells x 109/L). The £inal regression data set contained 57 parameters: 3 demographic, 21 hematology, 5 red ceil morphological abnormalities, and 28 semm chemistry. A complete îist of the parameters in the data set is included in Appendix 2A.
The paper files for individual dogs were examined to search for unreported data, and also to verify unusual values found in the cornputer records. For 11 dogs without a recorded platelet count, the eligible smears were rnicroscopically examined in a blinded and randomized fashion, and a platelet estimate was generated for 8 of them following a standard protocol (Weiss 1984, Tvedten et al 1988). A count was not possible on the remaining three films due to platelet clumping.
A preliminary anaiysis including basic descriptive statistics and bivariable analysis of the data were performed using STATISTIX software (version 1.0 for Windows,
Analytic Software, Tallahassee FL, 1996). Descriptive statistics for continuous variables included N (number of values), mean, median, number of rnissing values, and minimum and maximum values. Frequency tables were computed for age, breed, and sex. Two sample t-tests were performed for continuous variables using HSA statu as the categoncal variable. Chi square tests were cornputed for HSA vernis breed and sex.
Pearson correlation coefficients were computed for hematology and biochemistry parameters.
The multivariable logistic regression analysis was performed using statistical software fiom Statistical Analysis Systems Insftute (version 1 for Windows, SAS
Institute Inc., Cary, NC, 1996). In the preliminary multivariable analyses, variables with a high proportion of missing values were excluded fiom further consideration. Those variables which had an unconditional association with HSA with P I 0.25 in the bivariable analysis were offered to the model. In addition, all hematology variables were offered for inclusion regardless of the P-value because of the emphasis placed on hematological abnomalities in the literature. Senun alanine transferase (ALT)was also included due to the high rate of liver involvement in HSA, even though the P-value for the variable was not sipaincant in the bivariable anaiysis.
The variable for age was entered as quintiles rounded off to the nearest whole year.
Nucleated red blood ceil count (nRBC) was entered as rubricytes/100 white blood cells
(WBC)as part of the routine CBC, and also as nRBC/2000 rbc and as nRBC x 109/L
(calculated fiom total red ce11 count). Acanthocyte count and platelet count were entered as both continuous and categoncal variables. Acanthocyte count was categorized to reflect absent, mild, moderate, or marked acanthocytosis, and platelet count was categorized to reflect mild moderate or marked thrombocytopenia. In addition, bands and immatures were combined to create a single variable to represent left shift, and HCT and absolute reticulocyte count were combined to represent responsive anemia.
Dumrny variables were created for al1 categorical and cornbined variables as described by Walter (Walter 1987). Examples of Walter dummy variables are presented in Appendix 2A. AU Walter dummy variables were offered for inclusion in the multivariable models. If the probability of having HSA changed across a cutpoint, then the durnmy variable that defined that cutpoint was signifîcant in the model. For example, if the probability of having HSA was greater in dogs older than 6 years than in dogs younger than 6 years, then the Wdter variable that identifies cutpoint of "greater than 6 years" (i.e. AGEl) would be retained by the model as being signincant.
Models were built in a stepwise fashion with backwards elimination, and variables were retained only if P L 0.05 as described by Hosemer and Lemeshow (1989). Separate analyses were performed regressing HSA against each of the four classes of data
(demographic, hematology, red celi abnormalities, and serum chernistry). Variables significant in these individuai models were then offered for inclusion in four final models as follows: 1) demographics only, 2) demographics and hematology, 3) demographics, hematology, and red ceil morphology, and 4) demographics, hematology, red ce11 morphology, and biochemistry. Each of the preliminary multivariable analyses used a slightly different subset of dogs, since the nurnber of dogs with complete data varied depending on the parameters considered by the model. However, the fmal four models were built using a single subset of 62 cases and 162 controls common to al1 four preliminary models that had complete data for the eligible variables.
Each model was assessed for goodness-of-fit using global rneasurernents such as covariate Chi square, and total correctiy classified, as well as diagnostic procedures including change in Chi square (AX2), change in deviance (AD), and change in Chi square confidence interval (leverage). These diagnostic procedures identified subjects whose data did not fit the models (Le. weakened the goodness-of-fit). The paper files of influentid subjects were reviewed to cobtheir HSA or control status, and to vem that the data included for these dogs were correct. If no reason was found to exclude the case, then it was readmitted to the model as a legitimate non-conforming component.
Finaily, the odds ratio (OR) (the inverse natural log of the regression coefficient) and 95% confidence interval (CI) were computed for each variable to put the models into a clinical context. The ciinical usefiilness of each model was described in terms of its semitivity, specificity, and total percentage correctly classified, which assess a model's accuracy in predicting the presence or absence of disease in the study population. Descriptive Statistics and Bivrriable Analys*
Demographics
There were 65 breeds in the study with the bulk of the dogs represented by 19 breeds (Table 4.1). In both case and controls groups, the mixed breed was most comrnon, followed by the Labrador retriever, German shepherd, and Golden retriever as the most fiequent purebreds.
The study population as a whole was 53% male (149 dogs includuig 60 castrated) and 47% femaie (1 3 1 bitches including 102 spayed) with a comparable sex distribution in both the case group (57% male, 43% fernale) and control group (5 1% males and 49% fernales).
nie age quintiles of the study population were 5.8, 8.1, 9.4, and 11.5 years. Case dogs had a mean age of 9.6 years (SD = 2.5 years) with a median age of 9.5 pus and a range of 3.4- 16 years. Control dogs had a mean age of 8.1 years (SD = 3.4 years) with a median age of 8.4 and a range of 1.2-16.2 years.
In the bivariable analysis of demographics, dogs with HSA were older than control dogs (P = 0.000), and were more iikely to be a Golden retriever than any other purebred
(P = 0.012), although the mixed breed was slightly more at risk overall (P = 0.01 1).
Neither gender nor neutered status was signincantly associated with HSA Table 4.1 Frequency distribution of the nineteen canine breeds common to both cases and control groups. Shown are the number of individuals for each breed, and the percent of group in parentheses.
ElREED Cases Control (% of group) (% of group) - - ---
Mixed breed 27 (33.8) 39 (19.5) Labrador retriever 5 (6.3) 19 (9.5) Golden retriever 11 (13.8) 10 (5.0) German shepherd 6 (7.5) 12 (6.0) Siberian husky 2 (2.5) 7 (3.5) Cocker spaniel 1 (1.3) 8 (4.0) Standard poodle 2 (2.5) 6 (3 .O) Rottweiler 1 (1.3) 7 (3.5) Doberman pincher 2 (2.5) 5 (2.5) Bouvier 1 (1.3) 6 (3.0) Miniature schnauzer 1 (1.3) 5 (2.5) Collie 1 (1.3) 4 (2.0) Afghan 3 (3.8) 2 (1.0) Boxer 3 (3.8) 1 (0.5) Chow 1 (1.3) 3 (1.5) Old English sheep dog 1 (1.3) 2 (1.0) Shetland sheep dog 1 (1.3) 2 (1.0) West highland white temer 1 (1.3) 1 (0.5) Beagie 1 (1.3) 1 (0.5) other 9 (1 1.3) 60 (30.0)
TOTALS 80 (100 ) 200 (100 ) Hematology
Descriptive statistics for hernatology variables are summarized in Appendix 2B.
Hernoglobin (HGB) and red celi count (MC) were very highly correlated with hematocrit (HCT) (Pearson correlation coefficients 0.95-0.99). Consequently, the fkequency distributions for HGB and RBC were essentially identical to that for HCT.The fkequency distribution of HCT is presented in Figure 4.1. The range of HCT was comparable for cases and controls but anemia (HCT < 0.38) was more frequent in the case group (82.5%) than control group (41%) and was moderate to severe (HCT < 0.30) in 60% of dogs with HSA as cornpared to 18.5% of controls. Of the 48 cases that had moderate or marked anemia, 47.2% had a strong response (reticulocyte count > 200 x109/L) as compared to 34.5% of the 37 control dogs with a simila.degree of anemia.
In the bivariable analysis, dogs with HSA had lower mean values for RBC, HGB,
HCT (P = 0.0), and mean cell hemoglobin concentration (MCHC) (P = 0.001) when compared to controls. Case dogs also had higher mean values for red ce11 distribution width (RDW) (P = 0.0003), mean ceil volume (MCV) (P = 0.013), and absolute reticulocyte count (P = 0.045). In addition dogs with HSA had higher mean values for nucleated red blood cells (IIRBC) (P = 0.0), acanthocytes (P = 0.003), and Howell-Jolly bodies (P = 0.02) when compared to controls. The unis of measurement did not affect the P-value for nRBC, but P-values for acanthocytes and Howell-Jolly bodies were slightly more signincant when counts were measured as ceild2OOO rbc (or percentage) than when counts were measured in absolute numbers. Figure 4.1 Frequeacy Distriiution of Hemato crit for Dogs with Hemangiosarcoma (HSA) and Controis.
40 14 18 22 26 30 34 38 42 46 50 54 58 >58 Hematocrit (%) Platelets
The mean platelet count for dogs with HSA was below the lower reference limit and was significantly lower than for controls (P = 0.0). Thrombocytopenia (445 x
10~1~)was present in 61.5% of case dogs as compared to 15.1% of control dogs, and was severe (48 x 109k) in 17.9% of case dogs as compared to 3.5% of controls. The mean
MPV was higher for dogs with HSA than control dogs (P = 0.01) although the mean for both groups was within reference limits and the range of values was comparable.
Leukon
Dogs in both groups had mild leukocytosis with a mature neutrophilia, and a small percentage of each group had a mild left shift (band count = 1.1-2.0 x 10'~).Mean values for leukocyte parameters (WBC and differential) were not significantly dinerent between the case group and control group with the exception of lymphocyte count which was lower in afSected dogs than controls (P = 0.001). Lymphopenia was present in 42% of dogs with HSA as compared to 34.5% of control dogs (reference limits, 0.8-3.6 x
109L), and only control dogs had lymphocytosis.
The descriptive statistics for senun chemistry parameters are summarized in
Appendix 2B. On bivariable analysis, statisticd associations were identified for albumin, albuminlglobulia ratio (NG), amylase, total bilirubin (TBILI), and allraline phosphatase
(AP), steroid-induced allcaline' phosphatase (SAP), and gamma glutamyltransferase
76 (GGT). The case group had mean values for these six variables that were within or slightly above their respective reference limits. The mean values for the control group were also within reference iimits but were lower than case dogs for aibumin (P = 0.001),
NG (P = 0.01), and amylase (P = 0.001). The controls had mean values above reference range and signincantly higher than the case group for AP (P = 0.001), SAP (P = 0.005),
TBILI (P = 0.04), and GGT (P = 0.0002).
Missing Values
Approximately 54 dogs had not had a biochemical profile performed and were lacking values for the corresponding 19 analytes. A variable number of dogs also lacked data for the 9 rniscellaneous biochemistry variables. Missing values were equally distributed between cases and control with an average 32.5% of case dogs and 27.9% of control dogs lacking data for any given analyte. The hematological data was more complete. Wiîh the exception of mean platelet volume (MPV) which was available for less than half the dogs, missing data was limited to a smali number of dogs without values for platelet couat, RDW, and plasma protein. There were 10 variables for which
38%-74% of the dogs did not have data These variables (see Appendur 2B) were eliminated fiom the analysis regardless of their statistical association with HSA.
The logistic regession analysis was performed on a core nibset of 62 dogs with
HSA and 162 controls for which there was complete data. The age, breed, and sex distribution of dogs in this smaller population was evaluated statistically and found comparable to the full population that was described earlier in this section. Variables entered into the four final models were those found significant in preliminary multiple regression analyses.
The clinical significance of a rnodel is embodied in the term "6" and the odds ratio.
The "b" is an estimate of the mdtivariable logistic regression coefficient and is comparable to the slope of the regression line in Iinear regression. It is a measure of the amount of change in the response variable for a change of one unit in the independent variable. The odds ratio is the inverse natural log of "6" and expresses the strength of the effect for a given variable, contro1hg for ai1 other variables in the model.
Age and breed were the only variables offered to the demographic model (Model 1) and both were entered as categorical variables. Age was entered by quintiles as a Walter dummy variable (Appendix 2A), and breed was entered as a dichotomous variable for
Golden retriever. Sex was not entered into any of the models since it was not signincant at either the bivariable or multivariable level. Age greater than 8 years and Golden retriever breed were both strongly associated with HSA (Table 4.2). Compared to controls, dogs with HSA were 5.0 times more likely to be older than 8 years and 5.2 times more likely to be a Golden retriever than any other purebred. The diagnostic sensitivity of the model was good at 85.5% and false negatives were correspondingiy low. However, specinci@ was poor (48%), the many false positives contributed to a low total correctly classifïed (58.5%), and the covariateX2 was small(28.2).
In Model 2, anemia and degree of response was entered as a Walter dummy variable with five levels (Appendix 2A). Also included were MCHC, platelet count and band count which were added as continuous variables. In this model Golden retrievers, and dogs older than 8 yean continued to have an OR for HSA comparable to those in
Model 1. h addition, dogs with anemia, with or without response, were 4.5 times more likely than control dogs to have HSA (Table 4.3). The three other variables, MCHC, platelet count and bands, were negatively associated with HSA meaning that the OR for
HSA increased as the value for the parameters decreased (or that dogs with higher values for these parameters were more likely to be free of HSA). The most important of the three variables was platelet count with an OR of 0.991 (95% CI = 0.988-0.995). The regression coefficient shown in Table 4.3 is small, but this is based on a change in platelet count of one unit. In clinical ternis, this translates into a meaningfhlly increased likelihood of HSA in dogs with thrombocytopenia. The sensitivity of this model was
83.9%, which was comparable to model 1, but specificity (80.9%) was much itnproved as was the covariate x2(103.9), and total correctiy classined (8 1.7% ).
The variables for acanthocyte count, schistocytes, and nucleated red blood cells were offered to Model 3 as continuous variables, in addition to the demographic and hematology variables. Only acanthocyte count remained in the model and was positively associated with HSA (Table 4.4). The Golden retriever breed was retained with an OR comparable to that in model 2. The cutpoint for an age-related uicrease in the likelihood of HSA dropped to older than 6 years, as compared to older than 8 yean in the earlier models, and the OR was higher. Anemia was still associated with HSA but at a lower level of signincance and OR Platelet count and MCHC remained in the model and the associations with HSA were essentially unchanged. The performance of Model 3 was sMilar to its predecessor: the covariate x2 (103.1) and sensitivity (80.5%) were Table 4.2 Model 1. Results of multivariable logistic regression analysis of associations between HSA and demographic variables.
Variable ba SE(^)^ Pc Odds Ratio (95% CI) age > 8 years 1.60 0,3754 0,000 1 5.0 (1.1-10.3) breed: Golden retriever 1-65 0.5823 0.005 5.2 (1.7-1 6.4) CI = contïdcn~tintcrval; ~ultivariablclogistic ngnssion cocficient bStandardcmr of b T-value for Wald test statistic
Table 4.3 Model 2. Redts of multivariable logistic regression anaiysis of associations between demographic and hematology variables and HSA.
Variable ba SE(b)b Pc Odds Ratio (95% CI) age > 8 years 1.6792 0.450 1 0.0002 5.4 (2.2-1 3 .O) breed: Golden retriever 1.4759 0.7048 0.036 4.4 (1.1-1 7.4 ) HCT < 0.38 L/L 1.5033 0.4448 0.0007 4.5 (1.9-1 0.8) MCHC -0,0348 0.0 159 0.029 0.966 (0.936-0.996) platelet count -0.0089 0.00 179 0.000 1 0.99 1 (0.988-0.995) bands -0.3056 O. 1224 0.013 0.737 (0.580-0.937) CI = coafidmu intcrval; FICT = hcmatociit; MCHC = mean cd1 hemogiobin concentration; aMultivariablelogistic tegression coefficient bStandard crror ofb T-value for Wald test statistic
Table 4.4 Model 3. Results of multivariable logistic regression analysis of associations between demographic, hematology, and red cell morphology variables and HSA.
Variable ba SE(^)^ Pc Odds Ratio (95% CI)
Age > 6 years 2.2742 0.6608 0.0006 9.7 (2.3-35.5) Breed: Golden retriever 1.3579 0.6847 0.047 3.9 (1-02-14.9) HCT < 0.38 L/L 0.8937 0.4351 0.04 2.4 (1.04-5.7) MCHC -0.040 1 0.0 158 0.01 1 0.96 1 (0.93 1-0.99 1) Platelet count -0.00960 0.00 19 0.000 1 0.990 (0.987-0.994) Acanthocytes/2000 rbc 0.0303 0.0 147 0.039 1.O3 1 (1.O0 1-1-062) CI =confidence intend; HCT" hcmatocriÇ MCHC = mean œll hcmogIobin concentration; 'Multivariable logistic cegression cocfficicnt bStandardemr of 6 T-value for Wald lest statistic slightly lower, specincity (82.1%) was slightly improved, and the total correctly classified (8 1.7%) was unchanged.
When biochemistry variables were added to Model 3, the resuiting model was uostable (Le. increased numbea of non-conforming subjects). A slightly simpler model
(Model 4) including demographics, hematology, and biochemistry variables was built that offered predictive ability comparable to the full model.
Of the six eligible biochemical variables offered to the full model (Model 4), only aibumin and AP retained a significant association with HSA in the presence of the variables fiom earlier models (Table 4.5). There was a negative association between
HSA and alkaline phosphatase and a positive association with albumin. The associations for age, platelet count and anemia retained their significance, especially anemia which had the strongest OR of al1 variables in any model. The variables MCHC and breed were not retained. The covariate x2 for this mode1 was only slightly higher than the other combined models. The sensitivity (82.3%) and specifîcity (81.5%) were comparable, and the total correctly predicted (8 1%) was unchanged relative to Models 2 and 3 (Table 4.6).
The goodness-of-fit was assessed for each of the combined models (models 2-4) and iduential subjects that afTected the fit of the models were identified. There were 22 infiuential subjects, of which 14 were dogs with HSA and 8 were controls. Seven of the
14 dogs with HSA were innuential in ali three combined models, another 11 subjects were unique occurrences, and the remainhg 4 subjects af3ected two models. There was no consistent fïnding among the influential case dogs with respect to primary tumour site or extent of metastatic disease that codd explain their impact on the models. A List of the influential subjects and their final diagnoses is included in Appendix 2A. Table 4.5 Model 4. Results of multivariable logistic regression analysis of associations between demographic, hematology red ce11 morphology, and sem biochemistry variables and HSA.
Variable b SE@) P Odds Ratio (95% CI)
Age > 8 years 1.4697 0.4562 0.00 1 4.3 (1.8-1 0.6) HCT < 0.38 L/L, 1,9590 0.4892 0.0001 7.1 (2.7-1 8.5) Platelet count -0.009 15 0.00 189 0.000 1 0.991 (0.987-0.995 ) Aikaline Phosphatase -0.001 5 1 0.000547 0.006 0.998 (0.9974-0.9996) Albumin 0.1 149 0.0368 0.002 1.1 (1.04-1.21) CI = confidena interval; RETS t= hcmatocrit 030 - 0379 Ut, aMultivariablelogistic regmion cocficicnt bStandardcmt of b CP-value for Wald test statistic
Table 4.6 Summary of fit and predictive performance for logistic regession models for associations between HSA and demographic, hematology, red blood cell morphology, and senun biochemistry variables.
Model Number of Covariate x2 Sensitivity Specincity Total Conectly Variables (%) ("/D) Classified (%) 1 2 28.2 85.5 48.0 58.5 DISCUSSION
The case-control study design is a rapid and inexpensive method of obtaining infionnation from existing records, and can yield valuable information especially for diseases with low prevalence. The present study is a credible effort to simulate the clinical situation with respect to HSA because of the number of dogs involved, and the variety of conditions represented in the control group that in some way resemble HSA.
The detailed criteria for inclusion and exclusion, applied with equal rigour to cases and controls rninimized selection bias and ensured that control dogs were as similar as possible to case dogs. By doing so, the differences between cases and controls were more validly attributable to the presence or absence of HSA, and therefore more useful to mle in or deout the disease. However, as control dogs were drawn fiom a referral population, the results of this study may have application only to sirnilar populations and may not be relevant to the detection of HSA in the canine population at large.
Furthemore, as the control group consisted primarily of dogs with diseases affecting the pericardial, thoracic and peritoneal cavities apropos of typical visceral HSA, extrapolation of the fïndings to the more obscure presentations of HSA (e.g. hematuria, neurological signs etc.) may be inappropriate.
The data used in a case control study are not purposively colîected as in a prospective study, and therefore specinc data are ofien rnissing fiom the existing records.
In this study, the information most fiequently missing fÎom the records was sem biochemistry. Since dogs with incomplete data were not included in the logistic regession analysis, the resulting models were inherentiy biased in favour of dogs with complete biochemistry data It is not known why serum chemistry values were not available for al1 dogs, but it could be speculated that dogs with incomplete information were those with fiilminating illness that did not live long enough for a biochemical profile to be performed. If so, then any unique feature of their semchemistry would not have been assessed by this study, and the models could not claim to be Fully representative.
Many laboratory abnomalities have been descnbed in dogs with HSA. The purpose of bivariable analysis in this study was to distinguish between simple descriptive findings and statistically associated abnormalities. The purpose of the multivariable analysis was to detemine if those variables unconditionally associated with HSA were diagnostically important when considered together with other findings, as typically occurs in the clinicd situation.
Multivariable logistic regression is a useful tool to screen a variety of potential explanatory variables. The success of the analysis is highly uifluenced by the specinc variables offered to the model. Variables are selected by the operator on the basis of proven statistical association, established biological signincance, and arbitrary choice.
The final model is the one that in the operator's opinion best explains the outcorne, but it is not necessarily the only or the best model possible fiom the given data. Also inherent in the pedomiance of multiple cornparisons is the possibility that a sipificant association might be identified by chance alone. As the number of cornparison increases, so does the opportunity for spurious significance.
This is a retrospective study, with ail the implication for data quality that is entailed. The study is also based on a referrai population, which due to referrai patterns and regional environments, and may not be representative of the general canine population (Bonnett and Reid-Smith 1996). Therefore, because of these limitations, it is important to understand that the exact numbers generated in this study are not directly applicable to an individual clinical situation, especially outside of the referral institution fiom which the population was drawn. The models discussed are not a diagnostic blwprint for HSA, but they make an important contribution by highlighting diagnostically relevant variables and by bringing into focus relationships between variables, which may offer some insight to the clinician facing a diagnostic dilernrna.
The mean age of dogs with HSA in this study was consistent with the rnean age of
9-1 1 years published in various studies (Waller and Rubarth 1967, Kleine et al 1970, Frey and Betts 1977, Oksanen 1978, Hirsch et al 198 1, Brown et al 1985, Ng and Mills 1985,
Johnson et al 1989). Not only was there a strong statisticd association between age and
HSA in the bivariable malysis but age was consistentiy retained in the multivariable analysis which reinforces its diagnostic significance.
The association between HSA and the Golden retriever is consistent with one published study that found a similar association (Holt et al 1992), but codicts with earlier studies that showed a breed predilection for the Geman shepherd (Kleine and et al 1970, Prymak et ai 1988). The shift in breed association is most likely a reflection of the increased popularity of the Golden retriever in recent years and the increased representation of the breed in the canine population. it rnight also suggest a genetic tendency, perhaps due to over-breeding as may occur in the face of increased popularity. An association was also found between HSA and the mixed breed. This may be due to a predominance of mixed breeds in the general canine population, or at least in the referral population, or it could be that the mixed breed population includes a large proportion of cross-bred Golden retrievers as a by-product of the populanty of the purebred counterpart. The association is important because it demonstrates that HSA is not exclusively, or even primarily, a disease of the purebred dog.
The published evidence for a gender predilection in HSA is contradictory. Both the male (Waller and Rubarth 1967) and spayed female (Prymak et al 1985) have been reported at risk for HSA, and one study found no sex predilection ( Kleine et al 1970).
The curent study is in agreement with the latter study as neither gender nor neutered status were statistically associated with HSA in bivariable and multivariable analyses.
The bivariable analysis in this study demonstrated an unconditional association between HSA and decreased HCT, RBC, and HGB, as well as elevated reticulocyte count. This statisticd evidence of anemia and reticulocytosis Ui dogs with HSA is in agreement with previously published descriptions of a responsive anemia in afTected dogs (Waller and Rubarth 1967, Kleine et al 1970, Rebar et al 1980, Ng and MiIls 1985).
Case dogs also had statistically higher RDW, MCV, and higher MCHC than contmls, which in the context of anemia could be consistent with anisocytosis and polychromasia.
Both of these changes have been desmied in dogs with HSA ( Gelberg and Stackhouse
1977, Ng and Mills 1985) and are attributable to the presence of younger, larger, and less hemoglobinized erythrocytes as part of the respome to anemia (Jain 1993, Duncan et al
1994). However, the mean values for RDW,MCV, and MCHC were largely within their respective reference limits, and there was considerable overlap in values between cases and controls. So while there is statistical evidence to support anisocytosis and polychromasia in dogs with HSA consistent with published descriptions, the changes are of limited diagnostic value.
The bivariable analysis also provided statistical evidence of an association between
HSA and nrbncytosis, acanthocytosis, and increased numbers of Howell-Jolly bodies, al1 of which have been descnbed for dogs with HSA (Ng and Mills 1985). Two other poikilocytes the keratocyte (Ng and Mills 1985) and schistocyte (KLeine et al 1970, Ng and Miils 1985, Johnson et al 1989) were present in low numbers, and although they were slightly more numerous in affected dogs than in controls, the difference was not significant. These poikilocytes are indicative of red ce11 fhgmentation and are not unique to HSA (Rebar et al 1980). While this study documented that keratocytes and schistocytes may be present in dogs with HSA, it demonstrated that these poikilocytes have no statistical association with the disease, and are not diagnostically significant.
Thrombocytopenia has been kquently descnbed in dogs with HSA (Legendre and
Krehbiel 1977, Zenoble and Gabbert 1977, Allen 1982, Ng and Mills 1985, Hammer et al
1991) and this study providee clear evidence of an unconditional association between thrombocytopenia and HSA. The diagnostic signincance of the association was demonstrated by the fact that platelet count was retained by all combined models in the logistic regression analysis. The bivariable analysis also revealed an association between increased MPV and HSA which has not been reported before. Dogs with HSA had signincantly larger platelets than controls, although mean MPV for both groups was within reference limits and there was considerable overlap in the range of values. Large platelets usually indicate active thrombopoiesis, which in HSA rnight occur in response to peripheral thrombocytopenia, or as part of the general up-regulation of mmw function seen with responsive anemia. The diagnostic significance of increased MPV could not be determined in this study due to incomplete data, and therefore remains to be established.
Some of the dogs in the case group exhibited a neutrophilic leukocytosis and mild left shift consistent with previous reports (Klein et al 1970, Ng and Mills 1985), but there was no statistical association between these changes and HSA. In contrast, there was an association between lymphopenia and HSA that has not been reported before. The case group had a significantly Iower mean lymphocyte count than controls, although mean lymphocyte counts for both groups were within reference limits. From a clinical perspective, the most that cm be concluded fiom this association is that dogs with HSA are more likely to have lymphopenia than controls. The lower lymphocyte count seen in
HSA is most likely a component of the stress response.
The bivariable analysis identified a statistical association for six serum biochemistry analytes. The explanation for these associations is not readily apparent.
There was no evidence in the laboratory data to suggest an increased frequency of inflammatory disease or protein-losing conditions among control dogs that could explain the significantly lower mean albumin and NG as compared to case dogs. Similarly, there was Limited evidence to suggest cholestatic disease as the cause for the signincant elevation in mean AP, GGT, and TBILI in the control group. The elevated mean SAP could be considered evidence for exogenous corticosteroid administration, and that could explain the inmeases in AP and GGT in the control group. However, the majority of values for all these parameters for both case and control dogs were within reference limits, with the exception of SAP values which exceeded the upper reference limits for most control dogs. The ciinical significance of these changes is restricted to the observation that dogs with HSA are less kely to be hypoalbumlliernic, and less likely to have evidence of cholestatic disease or exogenous corticosteroid administration than dogs with diseases other than HSA.
The mean values for senun amylase in both case and control groups were welI within reference ümits, and individual values for this analyte rarely exceeded the minimal diagnostic threshold of twice the upper reference limit. The association identified between HSA and senun amylase activity is likely a spurious statistical finding without biological signuicance.
Multivariable Regression Analysis
The objective of the multivariable logistic regression analysis was to select the combination of demographic and clinicopathologic variables that best predicted the presence or absence of hemangiosarcorna. Basic clinical data including sipalment, CBC, blood film interpretation, and semm chemistry profle were combined sequentially to replicate the sequence in which tests rnight be performed in the early stages of a hypothetico-deductive approach to canine hemangiosarcoma
With the exception of sex and breed, ail of the variables were continuous, and were entered into the models as such. Some were also entered in as categorical variables using
Walter's technique to create dummy variables. Walter variables have the advantage that they permit comparisons between successive levels of a categorized independent variable and the outcome. They cm also identm critical threshold values of the independent variable that correspond to significant change in the outcome (Walter et al 1987). This is an altemative to the traditional coding schemes for dummy variables which allow for comparisons between a response stratum and a baseline or control stratum, or comparisons between each stratum and an average of ail strata (Walter et al 1987).
Walter variables are appropriate for this study because comparison of adjacent sûata is more clinically relevant than comparison with baseline values. For example, a clinician who is aware that HSA occurs more fiequently in older dogs is more likely to be interested in the odds ratio for a 10 year old dog versus an 8 year old , rather than a 10 year old versus a baseiine 3 year old. It would also be helpful to know the age threshold for HSA i.e. the age at which the risk of HSA rises dramatically. These evaluations are possible with Walter dummy variables.
The clinical useNness of a model is determined by its sensitivity, specificity, and total percent correctly classified. Sensitivity is the ability of a model to predict disease when disease is present (ic. cases). Specincity is the ability to predict the absence of disease when none is present (i.e. controls). Total percentage correctly classified is the sum of dogs that are correctly predicted to have the disease plus those predicted to be fkee of the disease. The perfect model would have 100% sensitivity and specificity without false negatives or false positives, but because the ideal is rarely achievable, the best model is always a compromise.
The consequence of a false positive may not equal that of a fdse negative. The operator must decide which error is the more undesirable and choose the mode1 that mllillnizes the probability that the error will occur. With HSA, the cost of a false negative is that a dog will die because of an undiagnosed malignant neoplasia. The cost of a false positive is that effort may be spent treating the wrong disease, thereby delaying the correct diagnosis and resulting in additional expense to the owner and possible risk to the dog. A fdse positive might also result in the summary euthanasia of a dog due to the poor prognosis of hemangiosarcoma. in the author's opinion, a fdse negative has more serious consequences than a false positive. Therefore, the optimal model would maximize sensitivity (Le. low fdse negatives) while achieving the highest possible concurrent specificity and total percentage correctly classified.
Model 1 demonsûated that dogs with HSA were signifïcantly more likely to be
Golden retrievers and older than 8 years of age. However, it was also evident from the small covariate x2,that demographic factors explained only a small amount of the difference between cases and controls. If used to predict the presence of HSA, this rnodel would produce many false positives. The association for breed was weaker than for age in dis and al1 subsequent models, and it was not surprishg that breed dropped out of later combined models while age was retained as statistically signincant. The general interpretation of Model 1 would be that age, and to a lesser extent breed, are important predictive indicatoa for HSA, but that demographic variables alone provide an incomplete model for diagnosis.
The addition of hematology variables to the basic demographic model produced the single most dramatic improvement in specincity, predictive ability, and covariate x2that occurred in any combined model. In Model 2, the covariates with the strongest association with HSA were age greater than 8 years, anemia, and platelet count. Breed was retained in the model but with lower signiscance than in Model 1. This was consistent with the expectation that breed would become less relevant in the presence of other variables. Response io anemia might have been expected to figure into the model coasidering the strong bivariable association for reticulocyte count, but because signincantly fewer control dogs had anemia, responsive or otherwise, the tnie predictive indicator was simply the presence or absence of anemia This was consistent with the frequency distribution of HCT which defined two broad categories of data, conesponding to case dogs and control dogs, that roughly straddled the cut-off value for anemia (HCT=
0.38 U).Of the three major covariates in Model 2, platelet count was the most significant. If the model was applied in the clinical situation, accounting for age, anernia and breed, a dog with a platelet count of 45 x 109/L,would be 9.8 times more likely to have HSA than a dog with a platelet count of 300 x log&.
The other two hematological variables in Model 2 were MCFC and band count, both of which were negatively associated with HSA at a lower level of significance relative to the three strongest covariates. In the context of the other variables in the model, a dog with a MCHC of 330 g/L would be twice as likely to have HSA than a similar dog with a normal MCHC of 350 g/L. This is a small OR for a substantial shift in the variable and it is unWrely that this association would translate into a clinically useful predictor especially since there was considerable overlap in values between cases and controls. One caveat with MCHC is that, as a mathematically derived index (fiom HGB and HCT), it is susceptible to error fiom either (or both) of the constituent indices.
Therefore, it would be Unportant to ve* both HCT and HGB before postulathg the OR for the reported MCHC. The retention of band count in Model 2 was surprishg since no association was found for WC,segmented neutrophils, band neutrophils or immature granulocytes on bivariable dysis. As a group, control dogs had a mild neutrophilia with a mild left shift while the case group had a mild neutrophilia without a left shift. However, there was considerable overlap between the two groups of dogs and therefore, the association attributed to band neutrophil count is likely a spurious statistical one, since it is without biological significance. This is substantiated by the smail OR for band neutrophil count in the model.
Model 3 had little to offer over Model 2 in terms of improvernent in fit or performance. However, Model 3 was unique as the ody model where HSA was associated with age greater than 6 years and the presence of acanthocytes. The drop in age threshold did not mean that HSA was no longer associated with dogs older than 8 years of age, but rather that the presence of acanthocytes resulted in a downward extension of the age range at which a significant association with HSA could be made.
Platelet count and anemia retained their association with HSA as in Model 2 except that anemia was less signincant in Model 3 than either of the other combined models. The interpretation of this is that when acanthocytes are present, the age at which there is a signincantly increased risk for HSA is lower. Controllhg for other variables in the model, dogs with marked acanthocytosis (80 acanthocytes/2000 rbc) were 11.3 times more likely to have HSA than similar dogs without acanthocytosis. This was convincing evidence for the value of acanthocytosis as an indicator of HSA. This was an interesthg observation in view of the kdings in chapter III of this thesis in which acanthocyte count as a test for HSA was found to be a very insensitive indicator of HSA. The conclusion is that although acanthocytosis by itself is a poor indicator for HSA, it d~escontribute to
diagnostic certainty in the context of other parameters. The logistic model also confkms
the finding of the acanthocyte study that low numbers of acanthocytes are not associated with an increased probability of havhg HSA, but that marked acanthocytosis is
diagnosticaliy significant*
The addition of albumin and AP to the final model produced a rninor irnprovement
in the fit, but the overall predictive performance of Model 4 was little different fiom
Models 2 &d 3. Breed was Iost fiom Model 4, having dwindled in significance through
successive models, givhg proof to the earlier expectation that breed would be eclipsed in
importance by other variables. The retention of only hNo serum chemistry variables of
questionable clinical significance underlines the limited utility of senun biochemistry in
predicting the presence of HSA in dogs. In fact, changes in albumin and AP were more
useful in predicting the absence of HSA. In the context of the other variables in the
model, dogs were 6.3 times more likely to be free of HSA if they were moderately
hypoalbuminernic e.g. 14 g/L (reference limits, 22-3 5 g/L), and 18.2 tirnes more likely to
be fiee of HSA if they had a markedly elevated AP of 2100 U/L (reference limits, 0-200
U/L). It is important to note that there was evidence in the bivariable anaiysis that
elevation in AP in control dogs might be attributed to the to administration of exogenous
corticosteroids. Therefore an elevated value of AP may be more a function of treatment
history than pathophysiology, which makes AP even more questionable as an aid in the
detection of HSA.
In reviewing the four models, the most significant cov~ateswere age greater than
8 years, anemia, and platelet count. The persistence of these variables across three successive and increasingly complex models was convincing evidence of their le@timacy as indicators for HSA. Furthemore, the sigaincance and OR for these variables was largely unchanged across the three combined models which attests to their stability.
Variables of secondary importance were judged to be breed and acanthocyte count. While breed was not as robust as age, anemia, and thrombocytopenia, it did persist through the first three models which gives it some credibility as a predictor of HSA. The weakest of the associated variables was acanthocyte count. Although it did not persist beyond Model
3, it was the only red ce11 morphological parameter to remain in a model, and in the context of that model, acanthocyte count was able to make an important contribution to the detection of HSA.
The unique feature of model 4 was that it contained only 5 variables, whereas al1 other combined models had 6 variables. Since a parsimonious model is favoured in logistic regression (Hosemer and Lemeshow 1989) Model 4 might be considered to be a better model. Model 4 had the lest nurnber of infiuential cases which sigmfïed that, in addition to being the most parsimonious, the model was more accurate (fewer non- conforming mbjects). However, diagnostic procedures to assess goodness-oMt showed that all of the combined models were equally stable. Therefore, although Model 4 is attractive fiom a statistical perspective, it does not offer any more diagnostic certainty than Model 2 or 3, and requires the performance of a biochemical pronle as an additional test. It could be argued that biochemistry adds Little to the diagnostic process in remfor the tirne and expense involved in perfomiing the test.
There were 14 case dogs and 8 control dogs that were non-confonning individuals.
These dogs represent 22.5% of case group (14/62) and 4.9% (8/162) of the control group respectively. This suggests that the models were acWybetter at detecting control dogs than dogs with HSA. This difnculty in predicting HSA in some dogs was underscored by the fact that there were 7 dogs with HSA that did not fit any of the combined models.
The lack of consistent postmortem findings among the non-confoming cases of HSA is likely a reflection of the genuine variability of the disease, although it may be a consequence of incomplete postmortem data.
A limitation of this study is the use of variables which are restncted largely to the clinicopathological domain. Although the project focused on the value of data collected eariy in the diagnostic process, the inclusion of other preliminary information such as physical exarnination data would likely have changed the predictive performance of the models, probably for the better. For example, the detection of an abdominal fluid wave on ballottement, or auscultation of muffled heart sounds, might have greatly enhanced the predictive abilities of a strictly clinicopathologic mode1 that included age, anemia, thrombocytopenia Certainly the results of the physical examination would be available to the clinician at the tîme patient demographic data is collected, and the exclusion of the data fiom the general physical examination detracts fiom the applicability of the study.
The next stage in a study of this nature would be to combine the clinicopathological data with other non-invasive diagnostic modalities such as geneml physical exam, mdiographs, ultrasound, and perhaps even cytology. Such a study would be hught with difliculties due to the tremendous variability in quality and degree of completeness that is characteristic of retrospective studies (Bonnett and Reid-Smith
1996). On the basis of significant associations in the bivax-iable analysis, there was statistical evidence for the following conclusions: dogs with HSA had mild to moderate responsive anemia with anisocytosis. They had increased numbers of acanthocytes rubricytes, and Howell-Jolly bodies, and exhibited thrombocytopenia and increased
MPV. Dogs with HSA did not have lymphocytosis, hypoalbuminemia, or evidence of cholestatic disease.
In the multivariable analysis, the most consistently predictive indicators of HSA were age greater than 8 years, anemia, and thrombocytopenia. Other less reliable predictive indicators were Golden retriever breed and acanthocytosis. Indicators that may help deout HSA were hypoalbuminemia, left SM,and elevated alkaline phosphatase.
The logistic regession analysis demonstrated that biochemical parameters are not good predictive indicators for HSA and that the additional effort of a biochemical profile is not warranted in the diagnostic work up of a dog suspected of having HSA. The modeling process also demonsûated that in some situations, dogs with HSA may remain a diagnostic challenge.
This study iliustrates that description of an abnomality, and even proof of a statisticai association between an abnormal parameter and a disease, does not coder diagnostic usefulness on a parameter. It is necessary to use more sophisticated methods, such as logistic regression analysis, in which abnorrnalities are interpreted in the conte* of other ihdings. By simulating the clinical situation, the diagnostic utility of a test can be assessed more realisticaliy. REFERENCES
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SUMMARY AND GElYERAL CONCLUSIONS
The objectives of this thesis were: 1) to explore the putative association between acanthocytosis and canine hernangiosarcoma (HSA); specifically, to confirm or refute the association, to quantify the utility of acanthocyte count as a diagnostic test for HSA, and to examine factors that affect its utility, 2) to determine if a statistical association exists between HSA and the hematological abnomalities described for afFected dogs in the literature, and 3) to develop a diagnostic mode1 for canine HSA that would quanti@ the relative diagnostic significance of severai statistically associated clinical parameters.
The literature on canine hemangiosarcoma was reviewed with respect to the prevalence, basic biology, clinical aspects, diagnosis, and prognosis of the disease. The pathophysiology of acanthocytosis as it occurs in man and animals was reviewed, including a critical appraisal of the literature that described or supported an association between acanthocytosis and hemangiosarcoma.
The general introduction focused on the need for a diable diagnostic test for HSA and outlined the advantages of a test based on a simple and inexpensive blood sample.
The importance of quantwg the utility of a diagnostic test was stressed, and the three papers in the literanÿe that exarnined diagnostic tests for HSA were critically appraised.
Two investigative studies were presented in this thesis. A case-control design was used in the first study (Chapter III) to retrospectively examine the peripheral blood smears of 80 dogs with histologically confïrmed visceral HSA and a group of 200 control dogs that had clinicai or diagnostic findings resembhg HSA but that did not have HSA.
Ail dogs in the study met certain basic criteria for inclusion in the study as well as comparable criteria for inclusion in case and control groups. By examining blinded and randomized blood smears, and counting acanthocytes using a standard protocol, it was possible to conclude that dogs with acanthocytes in their peripheral blood smears were statistically more likely to have HSA, and that dogs with HSA had higher numbea of acanthocytes than dogs with similar clinical sigm that did not have HSA. The study also demomtrated clearly that not dl dogs with HSA had acanthocytes, and that acanthocytes were not unique to HSA, being found in control dogs with a variety of diseases.
The sensitivity of acanthocyte count as a diagnostic test was very low across al1 cutpoints but specificity was high particularly for marked acanthocytosis. Negative predictive value was equivocal over al1 cutpoints. Positive predictive value, although poor at low levels of acanthocytosis, was 100% at acanthocyte counts >71 acanthocytes/2OOO rbc which in this study represented a marked acanthocytosis. This cutpoint was usefûl for ruling in HSA, although it did so for only 6 of 80 dogs with the disease.
The diagnostic utility of acanthocyte count was deemed to be limited due to its poor precision. htrasbserver and inter-observer agreement between qualined and expenenced clinical pathologists was poor, md lead to the conclusion that counting acanthocytes was highly subjective and in general poorly repeatable. However, the study also demonstmted that reasonable precision could be achieved in certain situations by individuals expenenced in counting acanthocytes. This result lent some validity to acanthocyte count as a diagnostic test. It also suggested that the test would likely not perfiorm well outside the research environment.
In the second study (Chapter Iv), bivariable and multivariable analyses were used to identm demographic, hematologicai and senun biochemical abnormalities that had statisticd association with HSA. The analysis confimied that HSA is a disease of the aged dog (mean age = 8.6 f 3.2 years) with a strong breed predilection for the Golden retriever. There was no association between gender or neutered statu and HSA.
The results of the bivariable anaiysis proved a significant association for several of the hematological findings described in the literature for dogs with HSA. Specifically, dogs with HSA, when compared to controls, were more iikely to have a mild to moderate anemia as indicated by lower values for hematocrit, hemoglobin, and red blood ce11 number. In addition, the anemia was more likely to be responsive as charactenzed by higher absolute reticulocyte count, red ceii distribution width, and mean corpuscular volume, and lower mean corpuscular hemoglobin concentration (MCHC).In addition to being anemic, dogs with HSA were thrombocytopenic and had signifïcandy lower platelet counts than controls. Dogs with HSA also had higher nurnbers of acanthocytes, rubricytes and Howell-JoUy bodies than control dogs.
Other hematological changes such as neutrophilic leukocytosis, left shift, schistocytes, and keratocytes, that have been described for dogs with HSA, were also found in afEected dogs in this study. However, no statistical association with HSA could be proven since these changes were found with equal fiequency in control dogs as case dogs. Of 28 serum chemistry variables examined, only 7 (albumin, albuminlglobulin ratio, aikdine phosphatase, steroid-induced alkaline phosphatase, gamma- glutamyltransferase, total bilirubin and amylase) demonstrated changes that were statisticdly associated with HSA. However, most of the values outside reference lirnits for these anafytes were reported for dogs in the control group. Therefore, the clinicd significance of the sîatistical associations was limited to concluding that dogs with sem chemistry values outside the respective reference intervals for the 7 parameters were less likely to have HSA than dogs with values within reference bits.
The multivariable logistic regression analysis revealed significant associations between HSA and age greater than 8 years, Golden retriever breed, anemia, thrombocytopenia, rubricytosis, acanthocytosis, and decreased MCHC. Albumin and akaline phosphatase were the only two serum chemistry variables to remain in the logistic regression model, and the analysis revealed that HSA was not associated with hypoalburninemia or elevations in alkaline phosphatase. The arguable clinical value of these two serurn chemistry variables underscores the LMited usehilness of senim chernistry in the diagnosis of HSA.
The goodness-of-fit assessrnent of the nnal models indicated that 22.5% of the case dogs would not be detected with the constructed models. The interpretation of this fïnding was that in spite of strong associations between the individual parameters and
HSA, there was sufncient variability in the presentation of HSA to make diagnosis based on demographics, hematology, and serum biochemistry unreliable.
This study like all retrospective studies is weakened by incomplete data collection and unintentionai bias, which are characteristics of the case-control study design. 104 However, it is a credible study due to the size of the study population, the inclusion of appropnate controls, weli defined and consistentiy applied criteria for inclusion in the study, blinding and randomization of study matenal where required, and appropriate statistical analyses.
The significance of this study is that it converts widely reported descriptive data into clinicdy interpretable and potentially us& information. The findings support the conclusions that acanthocytosis is associated with HSA, and that although acanthocyte count alone is of limited clhical utility, when interpreted in the context of other hematological and demographic data, it cm contribute to the diagnostic process. The clinical impressions of the authors that oripuially described a relationship between acanthocytes and HSA were correct. However, the association is not as stmightforward as those authoa suggested. This is a good example of a "generally accepted" concept based on descriptive findings that failed to address the complexity of the clinical diagnostic situation. It reinforces the need for healthy skepticism on the part of the reader when presented with descriptive data that purports to be diagnosticdy useful.
in addition to acanthocytosis, the study also quantifies the strength of association between several reported hematologicd changes and HSA, identifies those that have diagnostic significance, and by including them in a diagnostic mode1 confers concrete evidence of their clinical utility. Both the bivariable and multivariable analyses demonstrated that ahhough serum chernistry has Limited usefulness in the diagnosis of canine HSA, hematologicai and demographic variables cm contribute to diagnostic certainty in dogs nispected of having HSA. Pursuit of acanthocytosis as a diagnostic test for HSA is not warranted based on the results of this study. Other hematological parameters have more to offer, and fitue work may lie in the conduct of prospective studies to merdefine the role of hematology in the diagnosis of HSA. However, it is unlikely that a simple blood test is the diagnostic key to this disease, and research efforts might be better directed towards finding a ce11 marker, a genetic marker, or other molecular signal that would indicate the presence of HSA* APPENDIX IA
ACANTHOCYTE STUDY
DERIVATION OF THE STUDY POPULATION
AU data was taken fkom the records of the Veterinary Teaching Hospital of the
Ontario Veterinary College. One hundred and six codes fiom the Standard Nomenclature of Veterinary Diagnoses and Operations (SNVDO) were used to search the Veterinary
Medical Information Management System (VMIMS) database for dogs with hemangiosarcoma (HSA). AU entry fields were searched including admission, radiology, ultrasound, surgical biopsy, and post mortem. The search yielded 228 potential dogs for the case group. Five additional cases of HSA were found incidentally during the examination of other records. The paper records of these 233 dogs were examined, and
80 cases of visceral HSA and 15 cases of cutaneous HSA were confirmed and included in the shidy. There were 138 dogs that were considered ineligible for the following reasons:
16 cases (16/228 = 7.0%) - lost fiom the collection (12 paper files, 4 glas slides) 72 cases (3 1.6%) - missing CBC andlor histology ( 43 histology, 18 CBC, 11 both) 50 cases (2 1.5%) - not meet selection critena (5 ineligible CBC, 12 concurrent disease, 33 diagnosis not confirmed on histology)
The search for control dogs used 428 SNVDO codes, selected fiom approximately
4000 possible codes, to identify dogs with conditions that resembled HSA. The paper records of 609 candidate dogs were examined, and 200 dogs were judged suitable for inclusion in the study as controls. The remahhg 409 dogs were excluded for the foiiowing reasons:
12 cases (12/609=2.0%) - lost fiom the collection (4 paper files, 8 gfass slides) 241 cases (36.6%)- misshg CBC andor histology (196 histology, 37 CBC, 8 both) 156 cases (25.6%) - not meet selection critena (30 ineligible CBC, 118 diagnosis not eiigible or not confimed on histology, 8 less than 1 year of asel Distribution of Prhary Tumour Masses in 80 dogs with Visceral Hemangiosarcoma
Primary Site # of Cases
unlaiown/undetermined spleen liver heart muscle other
Number of Metastatic Sites in 80 Dogs With Visceral Hemangiosarcoma
# Metastatic SitesfDog # of Cases
O or unknown
1 2 3
4
5
6 7 Total General Criteria for Inclusion in the Control Group and the Number of Dogs with each Condition
Critenon for inclusion Number of Dogs in Control Group
abdominal neoplasm abdominal fluid thoracic fluid abdominal mass abdominal or thoracic fluid thoracic neoplasm pencardial fluid cardiac neoplasm internai hemorrhage Total
Acanthocyte Counts for Some Conditions Encountered in Control Dogs
Case # kitcrion for Inclusion 'rimary Organ ROOO rbc 180952 abdominal ncoplasia lymphoma spleen 7 1 1 1 1996 abdominal fluid organ faiturt Iiver 165486 abdominal or thonicic fluid organ faiiure hm 173413 abdominal neoplasia sarcorna spleen 158015 abdominal ntoplrisia (splcnîc enlargcmmt) lymphoma spleen 17755 1 thoracic fluid organ displacernent lui3 187347 abdominal fluid organ failure heart 172893 abdominal neoplasia adenocarcinorna intestine 172258 abdominal mass/abdominal neoplasia sarcoma undetermined 184952 abdominal neoplasia carcinoma liver 17560 1 pcricardial fluid inflammation pericardium 160630 abdominal or thoracic fluid organ failurc hm 171057 abdominai neoplasia/abdominai fluid carcinoma undetermined 166325 abdominal mass/abdominal neoplasia carcinoma Pan- 166765 thoracic fluid etTbion chylorhorax 174186 cdacneoplasia chemodecîorna heart 189154 thoracic fluid inflammation pericardiurn 162717 abdominal ncoplasia carcinoma Pan- Sensitivity, Specificity, and Predictive Values at Al1 Cutpoints of Acanthocyte Count in peripherai blood (80 Dogs with Hemangiosarcoma and 200 Controls).
cutpoint a Positive Negative (~canthocytes fredictive Predictive 12000 rbd Vaiue (%) Value (%) 100-0 73 .O 85.7 72.9 75.0 72.8 80.0 73.3 81.8 73.6 75.0 73.5 76.9 73.8 78.6 74. I 73 -3 74.0 75 .O 74.2 66.7 74.0 63.2 73.9 65 .O 74.2 61.9 74.1 59.1 74.0 60.0 74.5 57.7 74.4 53.6 74.2 55.2 74.5 58. 1 75.1 58.8 75.6 54.1 75.3 55.3 75.6 56.1 76.2 50.0 75.9 50.9 76.7 50.0 76.5 49-1 76.7 47.5 76.7 47.9 75.0 46.3 78.5 42.9 78.3 35.8 76.9 'Cutpoint is the level of acanthocytosis at which the test result is cded positive i.e. a cutpoint of 21 represents the cutpoint O vs. 21 acanthocytes/2000 rbc, and and 272 represents the cutpoint S'il vs. 272 acanthocyted2000 rbc. Constmcted K Table for Intra-Observer Agreement Categorized Data for Acanthocyte Counts on 62 Blood Films
Rater A Second Reading (Acanthocytes/2000 rbc)
16-50 MO To ta1 Rater A O 30 Fint 1-15 24 Reading 16-50>50 O O 2 2 4 04 Total 32 23 5 2 62
Constnicted K Table for Intra-Observer Agreement Categorized Data for Acanthocyte Counts on 62 Blood Films
Rater B Second Reading (Acanthocytes/2000 rbc)
Total Rater B O 18 First 1-15 21 Reading 16-50 15 >50 8 Total 62
Constnicted K Table for Intra-Obsenrer Agreement Categorized Data for Acanthocyte Counts on 62 Blood Films
Rater C Second Reading (Acanthocytes/2000 rbc)
26-50 To ta1 Rater C O 19 FUst 1-15 17 Reading 16-50 16 >50 O 4 5 10 62 APPENDIX 1C
Photomicrograph of peripheral blood srnear as presented in the photographic study of acanthocytes. The classical appeanuice of acanthocytes is shown (open arrows). The acanthocyte counts for Raters 1-5 were 50,23,52,50, and 33 respectively. Photomicrograph of peripheral blood smear as presented in the photographie study of acanthocytes. Crenated or spiculated erythrocytes (solid arrows), and acanthocytes (open arrows) are showa The acanthocyte counts for Raters 1-5 were 117,15,129,52, and 21 respectively. APPENDIX 2A
MULllVAlUABLE LOGISTTC WGRESSION ANALYSIS
LOGISTIC REGRESSION ANALYSIS
A popular statistical technique for describing the relationship between a binary event or outcome and a large number of explanatory variables is logistic regression, a type of multivariate analysis. U&e linear regression, in which the outcorne is assumed to be continwus, the outcome or response variable in logistic regression is binary or dichotomous. For this study, the outcome or response variable (also called the dependent variable) is hemangiosarcoma. It is dichotomous in that the disease is either present or absent. The explanatory or predictor variables are parameters such as age, hematocnt, and total protein etc. that may have a role in determinhg the outcome. These parameters are called independent variables because their inclusion in the mode1 is independently controlled by the investigator. The independent variables are also called covarîates.
Unlike the dichotomous dependent variable, the independent variable may be either continuous or dichotomous. For example mernia, as a continuous variable, would be indicated by any hematocrit between 0.0-0.379 YL (reference range 0.38-0.57LL). As a dichotomous variable anemia would be designated as simply present or absent.
Mode1 Building
Both linear regression and logistic regression are model-building techniques. They use comparable if slightly difTerent methods to find the best fitting and biologically meaningful model that uses the least number of variables to explain the relationship between the independent variables and the outcome. There are different strategies in model building, but a eequently used approach in logistic regression is stepwise regression with backwards elimination. Variables are considered one at a tirne in a stepwise fashion. A cornputer driven statistical algorithm assesses the contribution of each newly added variable and detemines if it is "importanty' enough to keep in the model. Mer assessing the new variable, the algorithm iooks "backwards" at the previously included variables and determines if they retain their importance in the presence of the new variable. At the end of the process, a group of variables remain that have a statistical association, as a group, with the outcome. These variables constitute the model.
Choice of Variables
The initial entry of variables into the model is controlled by the investigator. The choice of variables is Uifluenced by the statistical or biological relationship between the explanatory variables and the outcome. Before model building begins, bivarïate analyses define the statistical relationship between each individual variable and the outcome. A signifïcance threshold chosen by the investigator sets the standard that determines whether a variable is eligible to enter the model-building process. The investigator may also include variables tbat lack statistical significance but need to be included to maintain the biologîcal validity of the model. Lastly, the investigator may wish to include variables that are considered relevant by other authors even though the variables are not significant in the bivariate analysis. The objective is to offer to the model the widest range of variables that can be justified based on statistics, biology, or precedence
Interpreting the Model
The "6" is an estimate of the multivariable logistic regression coefficient and it is comparable to the slope of the regression line in linear regression. It is a measure of the amount of change in the response variable per unit change in the independent variable.
The odds ratio is the inverse log of "b" and is an expression of the proportional risk of the outcome being present in the diseased group relative to the control group, for a given independent variable.
Assesshg the Model
Once the algorithm has generated a model, the validity and usefùlness of the model can be evaluated by assessing how well the model fits the data. This is done by meamring the clifference between the observed outcome and the one predicted by the model. This is cded assessing the "goodness-of fit". In addition, the usefulness of the model can be demonstrated through general measures such as the covariate x2, semitivity, specincity, and total correctly classified. Covariate Chi-square
The significance of an independent variable (or variable vector) is determined by the likelihood ratio test. This test measures the ciifference in the log-likelihood between a model that does not include the variable and the same rnodel that does include the variable. The difference is called the likelihood ratio test statistic and it is a rneasure of the association between the independent variable and the outcome. The statistic has a x2 distribution and a calculated P-value. The software reports it as "Chi-square for the covariates" with associated P-value. A large covariate x2indicates that the variables in the model are significantly associated with the outcome and gives confidence that the model is appropriate.
Diagnostic Procedures
While large covaiate x2 and high total percentage correctly classified are general indications of a well-fitted model, a more rigourous assessrnent is achieved via diagnostic procedures for goodness-of-fit. These tests examine the size and distribution of variation within the model, and idente individual gmupings of variables (cailed covariate patterns) that contribute excessively to the variance of the model. In a weli- fitted model the distances between observed and predicted values are unsystematic in distribution, and are srnaii in cornparison to the overd variance of the model. The three tests for goodness-of-fit used in this study were change in the Chi-square statistic (&X2), change in deviance (AD),and leverage. Residuals are used in both linear and logistic regression to quanti@ the distance between observed and predicted values. In linear regression residuals are calculated for individual observations, whereas in logistic regression, residuals are calculated for individual covariate patterns. Several different residuals are used but two of the more common ones are the Pearson residual and the deviance residual. The Pearson residual is a function of the difference between the observed number of positive outcomes in subjects with a given covariate pattern, and the predicted number of positive outcomes for that covariate pattern. The surnmation of Pearson residuals over dlcovariate patterns yields the Pearson chi-square statistic (XZ) which cm be used as a mmmary measure of fit. The influence that each covariate pattern has on the fit of the model is measure by the change in the chi-square statistic (&) that occurs when al1 subjects with a given covariate pattern are deleted fiom the model. Covariate patterns that are poorly fit result in large values of fi2.
The deviance residual is based on the ciifference between the predicted and observed log-likelihood for a given covariate pattern. The summation of the deviance residuals over all covariate patterns yields the deviance statistic D or total deviance. This statistic is a summary measure of fit and is comparable to the residual sum of squares
(SSE) in linear regression. The amount of deviance that each covariate pattern contributes to the total deviance is measured by the change in D (AD) obtained when all subjects with a given covariate pattern are excluded fiom the model. Covariate patterns that are poorly fit have large deviance residuals and generate large values for AD when removed fiom the model. The range of D is smailer than x2 but both have a chi-square distribution and have a similar appeararîce when plotted graphicdy.
119 The term leverage refers to the amount of Muence that a given value has on the predicted value for that variable. In linear regression the predicted value of a variable is its mean. Individual values that are distant fiom the mean may cause the mean to sMft and are said to have leverage. The amount of shift or leverage is proportional to the distance of the value fiom the mean. In logistic regression leverage is non-linear and refers to the ability of individual covariate patterns to shift the estimated probability of a parameter away fiom 0.5. Leverage can be expressed as a change in value of the parameter estimate, or as a change in the confidence interval for the parameter estimate. in the present study, the latter approach was used. In a well-fitted model, the leverage is small and unsystematic over al1 covariate patterns.
The results of the diagnostic procedures AX2, AD, and leverage are most easily interpreted when plotted versus the estimated logistic probability. The plots for the fist two diagnostics are similar, and show two curved lines that cross to form a cup. The lhe crossing fkom upper left to lower right represents dogs with HSA and the other line control dogs. Poorly fitted covariate patterns are seen as isolated points at the upper extreme of each curve. Points that fd into the cup formed by the two crossing lines represent covariate pattems that have leverage. Points that lie away fiom the main data and are also within the cup represent covariate pattems that have both poor fit and high leverage. The plot for leverage shows a horizontal grouping of the data dong the x-axîs.
The majority of data is typicdly between 0.0 and 0.1, with low numbers of isolated points above 03.
hterpretation of diagnostic plots is partiy numeric and partly visual. For AX2 and
AD a cut off value of 4 is used as a cmde estimate of the upper 95h percentile of the x2
120 distribution and points lying above this line are considered to be poorly fit. Position within the cup is assessed visually. For the leverage plot, the cut-off value of 0.2 is suggested visually by the grouping of data, and points above this value represent iduential covariate patterns.
The effect of removing subjects with influentid and poorly fit covariate patterns can be wessed by the changes in the global measures of fit, and by changes in the re- plotted diagnostic curves. Complete Listing of Parameters Coliected for Each of 280 Dogs IncIuded in the Multivariable Logistic Regression Analysis.
Serum Chemistry Hematology Red ceIl Morphology white ceIl count acanthocyte phosphorous red blood cell count HowelCJolly body sodium hemoglobin keratocyte potassium hematocrit rubricyte Na:K mean ceIl volume schistocyte chloride mean cell hemoglobin carbon dioxide mean ce11 hemoglobin concentration anion gap red ceII distribution width total protein platelet count albumin mean platelet volume globulin plasma protein MG ratio reticulocyte % urea reticulocyte absolute count creatinine segmented neutrophils glucose band neutrophils cholesterol Iymphocytes total bilhbin monocytes conjugated biiirubin eosinophils fige bilirubin basophils alkaline phosphatase immatures steroid alkaline phosphatase rubricytes gamma-glutamyltransferase gluteraldeyde dehydrogenase alanine tramferase creatine phosphokinase amylase iipase osmolality Example of a Walter Dummy Variable for Categoncai Data - AGE
XAGE S 6 then AGEl = 1 if AGE > 6 and AGE I8 then AGEI = 2 if AGE > 8 and AGE 19then AGEl = 3 if AGE > 9 and AGE I12 thee AGEt = 4 if AGE > 12 then AGEl = 5 if AGE < 6 then AGE1= O XAGE < 6 then AGE2 = O if AGE < 6 then AGE3 = O if AGE < 6 then AGE4 = O -- AGE 1 if AGE > 6 and AGE < 8 then AGEl = 1 if AGE > 6 and AGE 5 8 then AGE2 = O if AGE > 6 and AGE I 8 then AGE3 = O if AGE>6andAGESt?thenAGE4=0
if AGE > 8 and AGE S 9 then AGEI = 1 if AGE > 8 and AGE 5 9 then AGE2 = 1 if AGE > 8 and AGE 1 9 then AGE3 = O if AGE > 8 and AGE I 9 then AGE4 = O
XAGE > 9 and AGE I12 then AGEl = 1 ifAGE > 9 and AGE 5 12 then AGE2 = 1 if AGE > 9 and AGE 5 12 then AGE3 = 1 if AGE > 9 and AGE < 12 then AGE4 = O
SAGE >12 thenAGE1 = 1 XAGE >12 thenAGE2 = 1 if AGE >12 then AGE3 = 1 ifAGE>12thenAGE4= 1 Example of a Walter Dummy Variable for A Combined Variable - Response to Anernia
Hematocrit (HCT) and Reticulocyte Count (ABS) = RETS
ZHCT 1 0.38 then RETS1 = O if HCT 2 0.38 then RETS2 = O No Anemia if HCT 2 0.38 then RETS3 = O ifHCT10.38 thenRETS4 =O if HCT 2 0.38 then RETSS = O
-HI-IIII- RETS 1 if HCT < 0.38 and HCT 1 0.30 then RETS1 = 1 if HCT < 0.38 and HCT 10.30 then RETS2 = O if HCT < 0.38 and HCT 1 0.30 then RETS3 = O Anemia if HCT < 0.38 and HCT 2 0.30 then RETS4 = O Response not Measured if HCT < 0.38 and HCT 2 0.30 then RETSS = O ------RETS2 if HCT < 0.30 and ABS = . then RETS1 = 1 if HCT < 0.30 and ABS = . then RETS2 = 1 Anemia if HCT < 0.30 and ABS = .then RETS3 = O Response Unknown XHCT < 0.30 and ABS = .then RETS4 = O if HCT < 0.30 and ABS = .then RETSS = O
__H -- RETS3 ZHCT < 0.30 and ABS 160and ABS 1 O then RETS1 = 1 if HCT < 0.30 and ABS 1 60 and ABS 1 0 then RETS2 = 1 Anemia ifHCT < 0.30 and ABS 160and ABS 2 O then RETS3 = 1 No response EHCT < 0.30 and ABS I60 and ABS 2 O then RETS4 = O if HCT < 0.30 and ABS I60 and ABS 2 O then MTSS = O
-HIIHIHHHHIII----mr-mrmrmrmr RETS4 if HCT < 0.30 and ABS 2 60 and ABS I100 then RETS 1 = 1 if HCT < 0.30 and ABS 2 60 and ABS I100 then RETS2 = 1 Anemia if HCT < 0.30 and ABS 2 60 and ABS < 100 then RETS3 = 1 Mild response ifHCT < 0.30 and ABS 160and ABS I100 then RETS4 = 1 if HCT < 0.30 and ABS 2 60 and ABS S 100 then ETSS = O
Imr--UIIIIIIII RETS5 ifHCT < 0.30 and ABS 2 100 then RETS1 = 1 ifHCT < 0.30 and ABS r 100 then RETS2 = 1 Anemia if HCT c 0.30 and ABS 2 100 then RETS3 = 1 Moderate to Good Response XHCT c 0.30 and ABS 1 100 then RETS4 = 1 if HCT < 0.30 and ABS 2 100 then RETSS = 1 Variables Ebatednom the Multivarîable Regression Analysis due to Missing Data
Variable Cases Controls Total #misshg #misshg #misshg
pp
Mean platelet volume 47 I 03 150 Albumin/GIobulin ratio 38 95 133 Anion gap 35 71 1 O6 Carbon dioxide 35 71 1 06 Free bilinibin 38 94 132 Gluteraldehyde dehydrogenase 49 113 162 Globulin 38 95 133 Lipase 39 99 138 Sodium/Dotassium ratio 39 95 134 Steroid induced alkaline phosphatase 56 151 207 Influentid Subjects Identified in the Corn bined Logistic Regression Models
File Mode Mode Mode HSA Diagnosis 1 1 1 2 3 4 11 1996 x O hepatic cirrhosis, splenic nodular hyperplasia HSA - nght atrium disserninated HSA HSA - right atrium, spleen chemodectoma cholangiocellular carcinoma HSA - bladder HSA - spleen HSA - nght atrium HSA - spleen, prostate HSA - nght atrium, spleen, liver HSA - right auricle, spleen HSA - spleen abdominal mass - gastric carcinoma HSA - spleen, liver, lung 1ymp hosarcoma multicentric leiomyosarcorna HSA - righaeft atrium, aorta lung metastatic carcinoma HSA - hepatic, mesenteric chronic micronodular cirrhosis 191985 x 1 HSA- lung Total 13 16 11 22 HSA cases 8 12 9 14 Controls 5 4 2 9
Descriptive Statistics for Bivariable Analysis of Senun Biochemistry Variables
Cases Controls 1 Variable n Mean SD calcium 61 2.46 0.23 phosphotous sodium potassium Na:K chloride carbon dioxMe anlon gap total protein abumin C h) globulin 00 AI0 ratio urea creatlnlne glucose ctiolesterol total bilirubin wnjugated bilirubin free billtubin alkaline phosphatase steroki alkaline phosphatese GGT 61 5.97 8.51 L GDH 3 1 18.45 44.42 ACT 62 204.84 936.47 CPK 6 1 607.62 1O1 3.30 amylase 6 t 1423.5 651.86 lipase 4 1 562.85 853.23 osmolatity 60 295.92 10,88 Descriptive Statistics for Bivariable Analysis of Red Cell Morphology Abnormdities
Cases Controls
Howell-Jolly bodies nucietated rbc
Absolute Y x iO'&
HowelMolly bodies nucleated rbc
%rbc acanthocyte 80 0.92 0.49 0 - 3.55 0.003 Howell-Jolly bodles 80 0.03 0.07 0 - 0.35 200 0.01 0.04 0 - 12.93 0.017 keratocyte 80 0.08 0.1 1 O - 0.45 200 0.06 0.09 0 - 0.65 0.053 nucleated rbc 80 0.07 0,lO 0 - 0.45 200 0.01 0.07 O - 0.7 0.000 schistocyte 80 0.1 1 0,18 0 - 0.95 200 0.08 0.23 0 - 1.95 0.274 IMAGE EVALUATION TEST TARGET (QA-3)
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