DOCSLIB.ORG

Seer Research Data Record Description 2019

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Seer Research Data Record Description 2019 SEER RESEARCH DATA RECORD DESCRIPTION CASES DIAGNOSED IN 1975-2016* Submission: November 2018 Follow-up Cutoff Date: December 31, 2016 Documentation Version: April 2019 Diagnosis Years: 1975-2016 * This documentation describes the data files in the incidence/yr1975_2016.seer9, yr1992_2016.sj_lx_rg_ak, yr2000_2016.gc_ky_la_nj_gg , and yr2005.la_2nd_half directories. Refer to individual variable definitions to determine the differences between the directory files. Starting with November 2017 submission, all cervix in situ cases have been removed. In prior submissions, cervix in situ cases were included for 1975-1995 diagnoses Starting with November 2018 submission, all 1973-1974 diagnosed cases have been removed. 2 SEER Research Data Record Description April 2019 TABLE OF CONTENTS PATIENT ID NUMBER ........................................................................................................... 10 REGISTRY ID .......................................................................................................................... 10 MARITAL STATUS AT DX..................................................................................................... 11 RACE / ETHNICITY ................................................................................................................ 12 SEX .......................................................................................................................................... 13 AGE AT DIAGNOSIS .............................................................................................................. 13 BIRTHDATE—YEAR ............................................................................................................. 13 SEQUENCE NUMBER--CENTRAL ........................................................................................ 14 MONTH OF DIAGNOSIS ........................................................................................................ 15 YEAR OF DIAGNOSIS ............................................................................................................ 15 PRIMARY SITE ....................................................................................................................... 15 LATERALITY.......................................................................................................................... 16 HISTOLOGY (92-00) ICD-O-2 ................................................................................................. 16 BEHAVIOR (92-00) ICD-O-2 ................................................................................................... 18 HISTOLOGIC TYPE ICD-O-3 ................................................................................................. 19 BEHAVIOR CODE ICD-O-3 .................................................................................................... 19 GRADE .................................................................................................................................... 20 DIAGNOSTIC CONFIRMATION ............................................................................................ 20 TYPE OF REPORTING SOURCE ............................................................................................ 21 EOD—TUMOR SIZE ............................................................................................................... 22 EOD—EXTENSION ................................................................................................................ 22 EOD—EXTENSION PROST PATH ......................................................................................... 22 EOD—LYMPH NODE INVOLV ............................................................................................. 23 REGIONAL NODES POSITIVE............................................................................................... 23 REGIONAL NODES EXAMINED ........................................................................................... 24 EOD—OLD 13 DIGIT .............................................................................................................. 24 EOD—OLD 2 DIGIT ................................................................................................................ 25 EOD—OLD 4 DIGIT ................................................................................................................ 25 CODING SYSTEM FOR EOD .................................................................................................. 25 TUMOR MARKER 1 ................................................................................................................ 26 TUMOR MARKER 2 ................................................................................................................ 27 TUMOR MARKER 3 ................................................................................................................ 28 CS TUMOR SIZE ..................................................................................................................... 29 CS EXTENSION ...................................................................................................................... 29 CS LYMPH NODES ................................................................................................................. 30 CS METS AT DX ..................................................................................................................... 30 CS SITE-SPECIFIC FACTOR 1 ................................................................................................ 31 CS SITE-SPECIFIC FACTOR 2 ................................................................................................ 31 CS SITE-SPECIFIC FACTOR 3 ................................................................................................ 31 CS SITE-SPECIFIC FACTOR 4 ................................................................................................ 32 CS SITE-SPECIFIC FACTOR 5 ................................................................................................ 32 CS SITE-SPECIFIC FACTOR 6 ................................................................................................ 33 CS SITE-SPECIFIC FACTOR 25 .............................................................................................. 33 DERIVED AJCC-6 T ................................................................................................................ 34 DERIVED AJCC-6 N ................................................................................................................ 35 DERIVED AJCC-6 M ............................................................................................................... 36 DERIVED AJCC-6 STAGE GRP .............................................................................................. 36 DERIVED SS1977 .................................................................................................................... 38 SEER COMBINED SUMMARY STAGE 2000 (2004+) ............................................................ 38 CS VERSION INPUT ORIGINAL ............................................................................................ 39 CS VERSION DERIVED .......................................................................................................... 39 CS VERSION INPUT CURRENT ............................................................................................. 39 April 2019 SEER Research Data Record Description 3 TABLE OF CONTENTS RX SUMM—SURG PRIM SITE............................................................................................... 40 RX SUMM—SCOPE REG LN SUR ......................................................................................... 41 RX SUMM-SURG OTH REG/DIS ............................................................................................ 41 RX SUMM-REG LN EXAMINED ............................................................................................ 42 REASON FOR NO SURGERY ................................................................................................. 42 RX SUMM—SURG TYPE ....................................................................................................... 43 RX SUMM—SCOPE REG 98-02 .............................................................................................. 43 RX SUMM—SURG OTH 98-02 ............................................................................................... 44 RECORD NUMBER RECODE ................................................................................................. 44 SEER TYPE OF FOLLOW-UP ................................................................................................. 44 AGE RECODE <1 YEAR OLDS ............................................................................................... 45 SITE RECODE ICD-O-3/WHO 2008 ........................................................................................ 45 RECODE ICD-O-2 TO 9 ........................................................................................................... 46 RECODE ICD-O-2 TO 10 ......................................................................................................... 46 ICCC SITE RECODE ICD-O-3/WHO 2008 .............................................................................. 46 ICCC SITE REC EXTENDED ICD-O-3/WHO 2008 ................................................................. 47 BEHAVIOR RECODE FOR ANALYSIS .................................................................................. 47 HISTOLOGY RECODE—BROAD
Load more

Recommended publications
  • Childhood Cancer Staging for Population Registries
    Childhood cancer staging for population registries according to the 1 Toronto Childhood Cancer Stage Guidelines Acknowledgements This project was funded by Cancer Australia through an initiative to strengthen national data capacity for reporting cancer stage at diagnosis. We also acknowledge and thank the Australasian Association of Cancer Registries, all Australian State and Territory Cancer Registries, the Australian Institute of Health and Welfare and the treating hospitals listed below for their support of the Australian Childhood Cancer Registry and of this project: Lady Cilento Children’s Hospital, Brisbane Sydney Children’s Hospital, Sydney The Children’s Hospital at Westmead, Sydney John Hunter Hospital, Newcastle Royal Children’s Hospital, Melbourne Monash Medical Centre, Melbourne The Women’s and Children’s Hospital, Adelaide Princess Margaret Hospital for Children, Perth Royal Hobart Hospital, Hobart Suggested citation Aitken JF, Youlden DR, Moore AS, Baade PD, Ward LJ, Thursfield VJ, Valery PC, Green AC, Gupta S, Frazier AL. Childhood cancer staging for population registries according to the Toronto Childhood Cancer Stage Guidelines. Cancer Council Queensland and Cancer Australia: Brisbane, Australia; 2017. Available at https://cancerqld.blob.core.windows.net/content/docs/childhood-cancer-staging-for- population-registries.pdf. Childhood cancer staging for population registries – November 2017 2 Table of contents Acknowledgements ........................................................................................................................................
    [Show full text]
  • Paediatric Cancer Stage in Population-Based Cancer Registries: the Toronto Consensus Principles and Guidelines
    Review Paediatric cancer stage in population-based cancer registries: the Toronto consensus principles and guidelines Sumit Gupta, Joanne F Aitken, Ute Bartels, James Brierley, Mae Dolendo, Paola Friedrich, Soad Fuentes-Alabi, Claudia P Garrido, Gemma Gatta, Mary Gospodarowicz, Thomas Gross, Scott C Howard, Elizabeth Molyneux, Florencia Moreno, Jason D Pole, Kathy Pritchard-Jones, Oscar Ramirez, Lynn A G Ries, Carlos Rodriguez-Galindo, Hee Young Shin, Eva Steliarova-Foucher, Lillian Sung, Eddy Supriyadi, Rajaraman Swaminathan, Julie Torode, Tushar Vora, Tezer Kutluk, A Lindsay Frazier Population-based cancer registries generate estimates of incidence and survival that are essential for cancer Lancet Oncol 2016; 17: e163–72 surveillance, research, and control strategies. Although data on cancer stage allow meaningful assessments of Division of Haematology/ changes in cancer incidence and outcomes, stage is not recorded by most population-based cancer registries. Oncology, Hospital for Sick The main method of staging adult cancers is the TNM classifi cation. The criteria for staging paediatric cancers, Children, Toronto, ON, Canada (S Gupta PhD, U Bartels MD, however, vary by diagnosis, have evolved over time, and sometimes vary by cooperative trial group. Consistency in the L Sung PhD); Department of collection of staging data has therefore been challenging for population-based cancer registries. We assembled key Paediatrics, Faculty of experts and stakeholders (oncologists, cancer registrars, epidemiologists) and used a modifi ed Delphi approach to Medicine, University of establish principles for paediatric cancer stage collection. In this Review, we make recommendations on which Toronto, Toronto, ON, Canada (S Gupta, U Bartels, L Sung); staging systems should be adopted by population-based cancer registries for the major childhood cancers, including Cancer Council Queensland, adaptations for low-income countries.
    [Show full text]
  • Lugano Recommendations
    VOLUME 32 ⅐ NUMBER 27 ⅐ SEPTEMBER 20 2014 JOURNAL OF CLINICAL ONCOLOGY SPECIAL ARTICLE Recommendations for Initial Evaluation, Staging, and Response Assessment of Hodgkin and Non-Hodgkin Lymphoma: The Lugano Classification Bruce D. Cheson, Richard I. Fisher, Sally F. Barrington, Franco Cavalli, Lawrence H. Schwartz, Emanuele Zucca, and T. Andrew Lister Bruce D. Cheson, Georgetown Univer- See accompanying article on page 3048 sity Hospital, Lombardi Comprehensive Cancer Center, Washington, DC; Rich- ard I. Fisher, Fox Chase Cancer Center, ABSTRACT Philadelphia, PA; Sally F. Barrington, St Thomas’ Hospital; T. Andrew Lister, St Abstract Bartholomew’s Hospital, London, The purpose of this work was to modernize recommendations for evaluation, staging, and response United Kingdom; Franco Cavalli and assessment of patients with Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL). A workshop Emanuele Zucca, Oncology Institute of was held at the 11th International Conference on Malignant Lymphoma in Lugano, Switzerland, in Southern Switzerland, Bellinzona, Swit- June 2011, that included leading hematologists, oncologists, radiation oncologists, pathologists, zerland; and Lawrence H. Schwartz, radiologists, and nuclear medicine physicians, representing major international lymphoma clinical trials Columbia University, New York, NY. groups and cancer centers. Clinical and imaging subcommittees presented their conclusions at a Published online ahead of print at subsequent workshop at the 12th International Conference on Malignant Lymphoma, leading to www.jco.org on August 11, 2014. revised criteria for staging and of the International Working Group Guidelines of 2007 for response. Processed as a Rapid Communication As a result, fluorodeoxyglucose (FDG) positron emission tomography (PET)–computed tomogra- manuscript. phy (CT) was formally incorporated into standard staging for FDG-avid lymphomas.
    [Show full text]
  • Current Issues in Cancer
    Current Issues in Cancer Non-Hodgkin's lymphoma-. I: characterisation and treatment BMJ: first published as 10.1136/bmj.304.6843.1682 on 27 June 1992. Downloaded from Susan E O'Reilly, Joseph M Connors This is the eighth in a series of The non-Hodgkin's lymphomas are a heterogeneous providing increasing insight into the molecular artic es examining recent collection of lymphoproliferative malignancies whose biological origin of lymphomas and have shown that developments in cancer clinical behaviour, prognosis, and management vary the follicular (nodular) lymphomas are almost exclu- widely according to histological subtype, stage, and sively ofB cell origin and that lymphoblastic lymphoma bulk of disease. They are the seventh most commonly and mycosis fungoides typically arise from T cells. diagnosed malignancy. Typically patients present with Diffuse lymphomas may arise from B or T cells or may localised or generalised lymphadenopathy. Common be of indeterminate origin. We have used the working presenting findings are haematological cytopenias, formulation terminology throughout this review (table drenching night sweats, unexplained fevers, or weight I). loss greater than 10% of baseline (B symptoms); Developmentsinimmunology, monoclonal antibody hepatosplenomegaly, abdominal masses, or compres- probes, cytogenetics, and characterisation ofoncogenes sion of internal organs such as the gastrointestinal and growth factors will continue to expand our under- tract, blood vessels, airways, spinal cord, ureters, or standing of lymphomas. And these added insights into bile ducts; or localised tumours of parenchymal or lymphoma classification may eventually translate into visceral organs. Nevertheless, lymphoma may mimic improved treatments. Nevertheless, despite the virtually any other neoplasm. increasing sophistication of the molecular biologists Until about 25 years ago, most patients with non- and pathologists most clinical decisions are based on Hodgkin's lymphomas died of their disease.
    [Show full text]
  • Prognostic Significance of P53, Bcl-2, and Fas Expression in Patients With
    102 Erciyes Med J 2015; 37(3): 102-5 • DOI: 10.5152/etd.2015.150001 Prognostic Significance of P53, Bcl-2, and Fas Expression in Patients with Primary Gastrointestinal Diffuse Large B-Cell Lymphoma ORIGINAL INVESTIGATION Erol Çakmak1, İsmail Sarı2, Özlem Canoz3, Bülent Eser4, Fevzi Altuntaş5, Mustafa Çetin4, Ali Ünal4 ABSTRACT Objective: P53, Bcl-2, and Fas proteins play significant roles in lymphoid cell apoptosis. These proteins affect the prognosis and treatment response of lymphoma and various malignancies. The aim of the present study was to investigate the effects of P53, Bcl-2, and Fas protein expression on treatment and prognosis in patients with primary gastrointestinal diffuse large B-cell lymphoma. Materials and Methods: Thirty-nine patients with primary gastrointestinal diffuse large B-cell lymphoma were included in the study. Immunohistochemical staining was performed to analyze P53, Bcl-2, and Fas protein expression levels in paraffin sections. Results: We examined 39 patients with primary gastrointestinal diffuse large B-cell lymphoma, 21 males and 18 females, with a median age of 54 years. P53 protein expression was detected in 24 patients (61.5%), Bcl-2 protein expression was detected in 26 (67%), and Fas protein expression was detected in 28 (72%). The five-year overall survival rate was significantly lower in patients with P53 and Bcl-2 expression; on the other hand, we did not find a significant difference in the five-year overall survival with respect to Fas protein expression. Conclusion: We found that P53 and Bcl-2 protein expression had a negative effect on prognosis and survival in patients with primary gastrointestinal diffuse large B-cell lymphoma.
    [Show full text]
  • Paraneoplastic Cerebellar Degeneration Preceding the Diagnosis of Hodgkin’S Lymphoma
    CA s E r E p o r T paraneoplastic cerebellar degeneration preceding the diagnosis of hodgkin’s lymphoma P.F. Ypma1*, P.W. Wijermans1, H. Koppen2, P.A.E. Sillevis Smitt3 Departments of 1Haematology and Neurology, HagaZiekenhuis, location Leyenburg, Leyweg 75, 545 CH The Hague, the Netherlands, 3Department of Neurology, Erasmus Medical Centre, Dr Molewaterplein 40, 3015 GD Rotterdam, the Netherlands, *corresponding author: tel.: +31 (0)70-359 5 56, fax: +31 (0)70-359 22 09, e-mail: [email protected] A B s T r act i N T r o d u ct i o N paraneoplastic cerebellar degeneration (pCd) can present Paraneoplastic cerebellar degeneration (PCD) typically as a severe and (sub)acute cerebellar syndrome. pCd presents with (sub)acute, severe cerebellar ataxia.1 PCD can accompany different kinds of neoplasms including is most commonly associated with small cell lung cancer small cell lung cancer, adenocarcinoma of the breast and (SCLC), adenocarcinoma of the breast and ovary, followed ovary, and hodgkin’s lymphoma. A 34-year-old patient is by Hodgkin’s lymphoma.2 Sometimes the diagnosis described with acute dysarthria, gait ataxia and diplopia. of a malignant disease is made before the syndrome despite extensive laboratory and radiological evaluations in occurs. Usually, however, PCD precedes the underlying this patient with rapidly deteriorating cerebellar syndrome, neoplastic disease, posing a diagnostic challenge. The the diagnosis of a paraneoplastic syndrome was only detection of antineuronal autoantibodies directed against made after several months, when an anti-Tr antibody was onconeural antigens helps diagnose the neurological detected in his serum.
    [Show full text]
  • Plasma Circulating Tumor DNA Assessment Reveals KMT2D As A
    Li et al. Biomarker Research (2020) 8:27 https://doi.org/10.1186/s40364-020-00205-4 RESEARCH Open Access Plasma circulating tumor DNA assessment reveals KMT2D as a potential poor prognostic factor in extranodal NK/T-cell lymphoma Qiong Li1,2†, Wei Zhang1,2†, Jiali Li1,2, Jingkang Xiong1,2, Jia Liu1,2, Ting Chen1,2, Qin Wen1,2, Yunjing Zeng1,2, Li Gao1,2, Lei Gao1,2, Cheng Zhang1,2, Peiyan Kong1,2, Xiangui Peng1,2, Yao Liu1,2*, Xi Zhang1,2* and Jun Rao1,2* Abstract Background: The early detection of tumors upon initial diagnosis or during routine surveillance is important for improving survival outcomes. Here, we investigated the feasibility and clinical significance of circulating tumor DNA (ctDNA) detection for Extranodal NK/T-cell lymphoma, nasal type (ENTKL). Methods: The plasma ctDNA assessment was based on blood specimens collected from 65 newly diagnosed patients with ENKTL in the hematology medical center of Xinqiao Hospital. Longitudinal samples collected under chemotherapy were also included. The gene mutation spectrum of ENKTL was analyzed via next generation sequencing. Results: We found that the most frequently mutated genes were KMT2D (23.1%), APC (12.3%), ATM (10.8%), ASXL3 (9.2%), JAK3 (9.2%), SETD2 (9.2%), TP53 (9.2%) and NOTCH1 (7.7%). The mutation allele frequencies of ATM and JAK3 were significantly correlated with the disease stage, and mutated KMT2D, ASXL3 and JAK3 were positively correlated with the metabolic tumor burden of the patients. Compared with the tumor tissue, ctDNA profiling showed good concordance (93.75%). Serial ctDNA analysis showed that treatment with chemotherapy could decrease the number and mutation allele frequencies of the genes.
    [Show full text]
  • Cell-Free DNA As a Biomarker in Diffuse Large B-Cell Lymphoma A
    Critical Reviews in Oncology / Hematology 139 (2019) 7–15 Contents lists available at ScienceDirect Critical Reviews in Oncology / Hematology journal homepage: www.elsevier.com/locate/critrevonc Cell-free DNA as a biomarker in diffuse large B-cell lymphoma: A systematic review T ⁎ Javier Arzuaga-Mendeza,b,1, Endika Prieto-Fernándeza, ,1, Elixabet Lopez-Lopeza,c, Idoia Martin-Guerreroa,c, Juan Carlos García-Ruizb,c, Africa García-Orada,c a Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Leioa, Bizkaia, 48940, Spain b Hematology and Hemotherapy Service, Cruces University Hospital, Barakaldo, Bizkaia, 48903, Spain c BioCruces Health Research Institute, Barakaldo, Bizkaia, 48903, Spain ARTICLE INFO ABSTRACT Keywords: Cell-free DNA (cfDNA), which is DNA released from cells into the circulation, is one of the most promising non- Diffuse Large B-Cell Lymphoma (DLBCL) invasive biomarkers in cancer. This approach could be of interest for the management of Diffuse Large B-Cell Non-Hodgkin lymphoma Lymphoma (DLBCL) patients, which is the most common non-Hodgkin lymphoma. Then, the aim of this sys- Liquid biopsy tematic review was to define the utility of cfDNA in this disease. Selected articles were classified in four groups, Cell-free DNA (cfDNA) depending on the aspects of cfDNA studied, i.e. concentration, methylation, IgH gene rearrangements, and so- Biomarker matic mutations. While concentration and methylation of cfDNA need to be further analyzed, IgH gene re- Treatment response arrangements and somatic mutations seem to be the most promising biomarkers to date. Their detection has been shown to allow disease monitoring and early prediction of relapse.
    [Show full text]
  • EHA-TSH Hematology Tutorial on Lymphoma
    EHA-TSH Hematology Tutorial on Lymphoma Hodgkin Lymphoma: Diagnosis and Treatment (First Line and Relapsed Disease Speaker: Pervin Topcuoglu İzmir, Turkey April 6-7, 2019 I have no actual or potential conflict of interest in relation to this presentation Learning Objectives ‒ the morphological and clinical features ‒ the staging work-up and apply the Lugano classification to patients with Hodgkin lymphoma. ‒ the risk stratification prior to the treatment ‒ the treatment in patients with newly diagnosed HL and in those with relapse/refractory HL Content ‒ History ‒ Definition ‒ Epidemiology ‒ Subtypes ‒ Etiology ‒ Presentation ‒ Diagnosis ‒ Management ‒ Follow-up ‒ Summary and Future History History Definition ‒ A type of malignant lymphoma ‒ Germinal B center or Post-GBC ‒ Dorothy Reed and Carl Sternberg first described the malignant cells of HL-called as Reed Sternberg cells -Owl Eyes appearance ‒ The first cancer could be successfully treated by radiation therapy and also combination with chemotherapy (ChT) Epidemiology Median age at 40% diagnosis 30% 39 20% New cases 2.4.-2.5/100,000 persons 10% (EU and US data) 0% male, 2.9; female, 2.2 Percent o Deathso Percent HL most frequently diagnosed in <20 >84 35-44 45-54 55-64 65-74 75-84 20-34 patients 20-34 yrs of age, older Age than 55 yrs of age Increased incidence in industrialized Median age at death countries 67 Nodular sclerosis subtype associated with high standard of living Hodgkin Lymphoma Cancer Stat Facts. 2018. https://seer.cancer.gov/statfacts/html/hodg.html. Epidemiology Estimated New Cases in 2018 8,500 % of All New Cancer Cases 0.5% Percent Surviving 5 years Estimated Death in 2018 1,050 86.6 % % of All Cancer Deaths 0.2 % 2008-2014 3,00 2,50 2,00 1,50 1,00 Persons 0,50 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 0,00 1992 Number Per 100,000 100,000 Per Number Years New Cases Death-US Hodgkin Lymphoma Cancer Stat Facts.
    [Show full text]
  • Tumour Related Prognostic Factors
    NATIONAL CANCER DATA DICTIONARY V 1.0 Part A BASIC VARIABLES for Adults, Adolescents, and Children 7.6.2019 CONTENTS CONTENTS ....................................................................................................................................... 1 ABBREVIATIONS .............................................................................................................................. 7 CASE DEFINITIONS .......................................................................................................................... 8 Person age at diagnosis ................................................................................................................... 8 Person resident status ..................................................................................................................... 8 No veto from patient ....................................................................................................................... 8 Reportable diagnosed neoplasms ................................................................................................... 8 PATIENT DATA ................................................................................................................................ 9 Family Name(s)* ............................................................................................................................ 10 First Name(s)* ................................................................................................................................ 11 Sex .................................................................................................................................................
    [Show full text]
  • Peripheral T-Cell Lymphoma Facts No
    Peripheral T-Cell Lymphoma Facts No. 25 in a series providing the latest information for patients, caregivers and healthcare professionals www.LLS.org • Information Specialist: 800.955.4572 Highlights Introduction Peripheral T-cell lymphomas (PTCLs) are uncommon and l Peripheral T-cell lymphomas (PTCLs) comprise a aggressive types of non-Hodgkin lymphoma (NHL) that diverse group of uncommon and aggressive diseases develop in mature white blood cells called “T cells” and in which the patient’s T cells become cancerous. T-cell “natural killer (NK) cells.” lymphomas account for between 10 percent and 15 percent of all non-Hodgkin lymphomas (NHLs). NHL is the name for many different types of cancer that l The World Health Organization (WHO) divides start in cells called “lymphocytes,” a type of white blood PTCLs into three categories (nodal, extranodal cell that helps the body fight infection. There are three and leukemic) and classified subtypes within these types of lymphocytes: B lymphocytes (B cells), categories of PTCLs. Getting an accurate diagnosis T lymphocytes (T cells) and natural killer cells (NK cells). and knowing your PTCL subtype is important. NHL may arise in B cells or T cells. B-cell lymphomas are more common than T-cell lymphomas. NHLs may be l PTCLs are rare in the United States and are more indolent (slow growing) or aggressive (fast growing). For common in Asia, Africa and the Caribbean, possibly more information about NHL, please see the free Leukemia due to exposure to specific viruses, such as the & Lymphoma Society (LLS) booklets Non-Hodgkin Epstein-Barr virus (EBV) and the human T-cell Lymphoma and The Lymphoma Guide – Information for leukemia virus-1 (HTLV-1).
    [Show full text]
  • Myocardial Metabolic Response Predicts Chemotherapy Curative Potential on Hodgkin Lymphoma: a Proof-Of-Concept Study
    biomedicines Article Myocardial Metabolic Response Predicts Chemotherapy Curative Potential on Hodgkin Lymphoma: A Proof-of-Concept Study Cecilia Marini 1,2, Matteo Bauckneht 1,* , Anna Borra 3, Rita Lai 4, Maria Isabella Donegani 3, Alberto Miceli 3, Cristina Campi 5 , Vanessa Cossu 3, Daniela Schenone 5, Silvia Morbelli 1,3, Stephane Chauvie 6 , Michele Piana 1,5, Andrea Gallamini 7 and Gianmario Sambuceti 1,3 1 Nuclear Medicine, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; [email protected] (C.M.); [email protected] (S.M.); [email protected] (M.P.); [email protected] (G.S.) 2 CNR Institute of Molecular Bioimaging and Physiology (IBFM), 20090 Milano, Italy 3 Department of Health Sciences (DISSAL), University of Genoa, 16132 Genoa, Italy; [email protected] (A.B.); [email protected] (M.I.D.); [email protected] (A.M.); [email protected] (V.C.) 4 Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genoa, 16128 Genoa, Italy; [email protected] 5 LISCOMP Lab., Department of Mathematics (DIMA), University of Genoa, 16132 Genoa, Italy; [email protected] (C.C.); [email protected] (D.S.) 6 Department of Medical Physics, S. Croce Hospital, 12100 Cuneo, Italy; [email protected] 7 Research and Clinical Innovation Department, Antoine Lacassagne Cancer Center, 06189 Nice, France; Citation: Marini, C.; Bauckneht, M.; [email protected] Borra, A.; Lai, R.; Donegani, M.I.; * Correspondence: [email protected] Miceli, A.; Campi, C.; Cossu, V.; Schenone, D.; Morbelli, S.; et al. Abstract: Genome sharing between cancer and normal tissues might imply a similar susceptibility Myocardial Metabolic Response Predicts Chemotherapy Curative to chemotherapy toxicity.
    [Show full text]