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An Original Study

Operative Versus Nonoperative Treatment of Jones Fractures: A Decision Analysis Model

Julius A. Bishop, MD, Hillary J. Braun, BA, and Kenneth J. Hunt, MD

Abstract Optimal management of metadiaphyseal decision tree was constructed, and fold-back fifth metatarsal fractures (Jones fractures) and sensitivity analyses were performed to remains controversial. Decision analysis can determine optimal treatment. optimize clinical decision-making based on Nonoperative treatment was associated available evidence and patient preferences. with a value of 7.74, and operative treatment We conducted a study to establish the with an intramedullary screw was associat- determinants of decision-making and to ed with a value of 7.88 given the outcome determine the optimal treatment strategy probabilities and utilities studied, making for Jones fractures using a decision analysis operative treatment the optimal strategy. model. Probabilities for potential outcomes When parameters were varied, nonoperative of operative and nonoperative treatment treatment was favored when the likelihood of Jones fractures were determined from a of healing with nonoperative treatment rose review of the literature. Patient preferences above 82% and when the probability of heal- for outcomes were obtained by question- ing after surgery fell below 92%. naire completed by 32 healthy adults with no In this decision analysis model, operative history of fracture. Derived values were fixation is the preferred management strate- used in the model as a measure of utility. A gy for Jones fractures.

he optimal management strategy for Expected-value decision analysis, a research tool acute fractures of the metadiaphyseal fifth that helps guide decision-making in situations of metatarsal (Jones fractures) is controversial. uncertainty, has been effectively applied to other T 11-14 Patients can be successfully treated nonoperative- areas of uncertainty in the orthopedic literature. ly with non-weight-bearing and immobilization in Borrowed from gaming theory, the technique a short leg cast1-7 or operatively with placement of involves creating a decision tree to define the an intramedullary screw.8-10 The primary advantage clinical problem, determining outcome probabilities of nonoperative treatment is avoiding the risks and and utilities, performing a fold-back analysis to discomfort of surgery; disadvantages include the determine the optimal decision-making strategy, need for prolonged immobilization and protect- and performing a sensitivity analysis to model the ed weight-bearing as well as a decreased union effect of varying outcome probabilities and utilities rate.8,9 Advantages of operative treatment include on decision-making. Decision analysis may there- accelerated functional recovery and an improved fore allow the clinician and the patient to optimize union rate; disadvantages include exposure to the decision-making based on best available evidence risks, inconvenience, and discomfort of surgery. and patient preferences. It also helps determine Clear, definitive evidence for guiding treatment the most important factors affecting management is not available in the orthopedic literature, and strategies and the decision-making process, which treatment strategies vary substantially according may not always be intuitive. to surgeon and patient preference. In the present study, we used expected-

Authors’ Disclosure Statement: The authors report no actual or potential conflict of interest in relation to this article. www.amjorthopedics.com March/April 2016 The American Journal of Orthopedics ® E69 Operative Versus Nonoperative Treatment of Jones Fractures: A Decision Analysis Model

value decision analysis to determine the optimal comprehensive review by Dean and colleagues15, management strategy, operative or nonoperative, who extracted data from 19 studies: 1 randomized for acute Jones fracture. We also explored factors controlled trial, 1 prospective case series, and 17 with the most influence on the model and identi- retrospective case series.15 We used data from fied important questions for future research. these studies to determine outcome probabilities (Table). Materials and Methods Institutional review board approval was obtained Outcome Utilities for this study. Analysis was performed with Tree- Utilities represent patient preferences for vari- age Pro statistical software (Treeage Software). ous disease states. Outcome utility values were obtained from 32 adults (25 women, 7 men) with Outcome Probabilities no history of foot injury. Mean age was 32.4 years Outcome probabilities were determined by re- (range, 20-69 years). The questionnaire presented viewing the literature for articles on Jones frac- scenarios for the different outcomes and asked tures. This body of literature was summarized in a patients to rate these outcomes on a scale ranging

Table. Outcome Probabilities in Decision Analysis Derived From 19 Studies Summarized in Review by Dean and Colleagues15

Nonoperative Operative

Nonunion, Nonunion, Nonunion, Surgery, Nonunion, Surgery, Total Surgery, Minor Minor Surgery, Minor Fractures Study Year Healed Healed Complication Healed Complication Healed Complication Treated

Nagao et al27 2012 0 0 0 56 3 1 0 60

Thomas and 2011 0 6 1 0 0 0 0 7 Davis28

Habbu et al29 2011 0 10 4 0 0 0 0 14

Hunt and 2011 0 5 0 0 0 16 0 21 Anderson30

Torg et al7 1984 26 17 2 0 0 1 0 46

Mologne et al21 2005 14 4 0 12 7 0 0 37

Chuckpaiwong 2008 14 3 0 11 4 0 0 32 et al31

Devries et al32 2011 0 0 0 50 1 2 0 53

Porter et al10 2005 0 7 0 17 0 0 0 24

Porter et al20 2009 0 0 0 17 3 0 0 20

Reese et al33 2004 0 1 0 14 0 0 0 15

Lombardi et al34 2004 0 0 0 7 3 0 0 10

Portland et al35 2003 0 0 0 15 0 0 0 15

Clapper et al36 1995 18 7 0 0 0 0 0 25

Josefsson et al37 1994 24 0 0 0 0 0 0 24

Mindrebo et al38 1993 0 0 0 9 0 0 0 9

Zogby and 1987 10 0 0 0 0 0 0 10 Baker39

Dameron40 1975 15 5 0 0 0 0 0 20

Fernandez41 1999 4 4 0 0 0 0 0 8

Totals — 125.00 69.00 7.00 208.00 21.00 20.00 0.00 450.00

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from 0 (worst possible outcome) to 10 (best pos- The management strategy associated with the sible outcome). The Sports subscale of the Foot highest expected value is optimal for the given and Ankle Ability Measure (FAAM) 16 was used to outcome utilities and probabilities. quantify patient activity level. Sensitivity Analysis Decision Tree and Fold-Back Analysis One-way sensitivity analysis was performed A decision tree was constructed with 1 decision to model the effect on decision-making of node, 4 chance nodes, and 7 terminal nodes changing the values for utility for uncomplicat- (Figure 1). The decision tree demonstrates 2 ed surgery, utility for healing with nonoperative different strategies for managing a Jones fracture. treatment, utility for uncomplicated treatment of The decision node divides the tree into 2 branches: nonunion, likelihood of healing with nonoperative initial operative or nonoperative treatment. Both treatment, likelihood of healing with surgery, and branches are followed by various chance nodes, likelihood of minor complication with surgery. each terminating in a discrete clinical outcome. Per These were the variables found to affect the convention, utility data were placed to the right decision-making strategy within their clinically of the terminal nodes, and probability data were plausible ranges. placed under the terminal nodes. Fold-back analysis was performed to identify Results the optimal strategy. Fold-back analysis involves Outcome Probabilities and Utilities multiplying each outcome utility by its associated Outcome probabilities and utilities are illustrated probability, thereby providing an “expected value” in Figure 1. By convention, probabilities appear for each clinical endpoint. Then, the expected val- below the corresponding branches of the decision ues for each endpoint can be summed for a given tree, and utilities appear at the end of each branch. management strategy, and the ultimate expected Mean (SD) FAAM Sports subscale score was 84.6 values of the different strategies can be compared. (27.4). This subscale is scored as a percentage

Healed 8.30; P = .760 0.760

No Complication Nonoperative 6.20; = .214 Treatment P 0.920 7.74 Healed 6.07 Nonunion Treated 0.970 Complication With Surgery 4.60; P = .019 0.080 5.96 0.240 No Complication Persistent Nonunion 2.50; P = .007 Treated With 0.920 Surgery 2.44 Jones Fracture 0.030 Operative Treatment: 7.88 Complication 1.80; P = .001 0.080

No Complication 8.20; P = .883 Healed 0.920 8.04 0.960 Complication Operative 6.20; P = .077 Treatment 0.080 7.88 Nonunion Treated No Complication With Surgery 4.20; P = .037 0.920 4.09 0.040 Complication 2.80; P = .003 0.080

Figure 1. Completed decision tree includes outcome utilities, probabilities, and expected values of each treatment strategy. www.amjorthopedics.com March/April 2016 The American Journal of Orthopedics ® E71 Operative Versus Nonoperative Treatment of Jones Fractures: A Decision Analysis Model

from 0% to 100%, with higher scores indicating a below 92% (Figure 5). Nonoperative treatment is higher level of physical function. also favored when the probability of minor compli- cation with surgery is above 17% (Figure 6) and Decision Analysis when utility for a successfully treated nonunion is The expected value for nonoperative treatment higher than 6.9 (Figure 7). was 7.74, and the expected value for intramedul- lary screw fixation was 7.88 (Figure 1). Therefore, Discussion operative treatment was identified as the optimal Optimal management of a metadiaphyseal fracture treatment strategy. of the fifth metatarsal (Jones fracture) remains Sensitivity analyses revealed that the optimal controversial. The decision between initial op- decision making strategy was very sensitive to erative or nonoperative treatment lends itself small changes in several variables. Nonoperative to expected-value decision analysis because of treatment becomes the preferred strategy when well-defined treatment options and relatively dis- the utility value for uncomplicated surgery falls crete outcomes. The principal advantages of non- below 8.04 (Figure 2), when the utility for healing operative treatment are that it allows the patient with nonoperative treatment rises above 8.49 to avoid the risks and discomfort of surgery, and (Figure 3), when the likelihood of healing with non- the principal advantages of operative treatment are operative treatment rises above 82% (Figure 4), or that it maximizes the chance of fracture union and when the probability of healing after surgery falls may accelerate functional recovery.

8.80 8.6 8.60 8.4

8.40 8.488

8.038 8.2 8.20 8.0 8.00 7. 8 7.80 7. 6 7.60 7. 4 7.40 7. 2 7.20 7. 0 7. 0 0 6.8 6.80 6.6 6.60 6.4 6.40 6.2 6.20 6.0 6.00 5.8 5.80 5.6 5.60 5.4 5.40 5.2 5.20 2.0 5.00 4.8

4.80 Value Expected 4.6 4.60 4.4 4.40 4.2 4.20 4.0 4.00 3.8 Expected Value Expected 3.80 3.6 3.60 3.4 3.40 3.2 3.20 3.0 3.00 2.8 Non-Operative Treatment 2.80 2.6 2.60 2.4 Operative Treatment 2.40 Non-Operative Treatment 2.2 2.20 2.0 2.00 Operative Treatment 1. 8 1.80 1. 6 1.60 1. 4 1.40 1.20 0 2.25 4.50 6.75 9.00 1. 0 0 0.80 U_Nonop_Healed 0.60 0.40 Figure 3. One-way sensitivity analysis for utility for uncomplicated healing 0 2.25 4.50 6.75 9.00 with nonoperative treatment. Above threshold value (utility for uncompli- U_Op_Healed cated healing after nonoperative treatment, 8.49), nonoperative treatment is favored.

Figure 2. One-way sensitivity analysis for utility for uncomplicated healing with operative treatment. Utility of uncomplicated healing is varied on x-axis. Lines represent values for decision to manage operatively and non- operatively. Below threshold value (utility for uncomplicated healing after operative treatment, 8.04), nonoperative treatment is favored.

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Our decision analysis determined that operative emphasize the importance of patient preferences fixation is the optimal decision path, given the and shared decision-making. Higher rates of heal- outcome probabilities derived from the literature ing with nonoperative treatment, lower rates of and the utilities obtained from surveys. This finding healing with surgery, and higher complication rates is in accordance with several expert opinions in with surgery also favor nonoperative management. foot and surgery.1 7, 1 8 However, the It would therefore be valuable to identify risk expected values of the operative and nonopera- factors for nonunion with nonoperative treatment tive treatment strategies differed by only 0.3 on a and to identify the technical details of surgery that 10-point scale. Such similar expected values in our maximize rates of healing and minimize the risk of model are not surprising given the controversy sur- complications. rounding clinical decision making in the treatment The limitations of decision analysis involve the of these fractures.19 methods by which probabilities and utilities are ob- In addition, our analysis identified the important tained. In general, the most accurate, stable, and variables in the decision-making process. Patients robust estimates of outcome probabilities are de- averse to surgery, patients not averse to success- rived from a meta-analytic synthesis of randomized ful nonoperative treatment, and patients who view clinical trials, the highest level of clinical evidence. successful nonunion surgery after initial nonoper- In our model, data were extracted primarily from ative treatment as a relatively positive outcome level IV studies; only 1 level III study20 and 1 level may be best treated nonoperatively. These findings II study21 were available for analysis. Thus, as is

8.40 8.00 8.30 7.90 7.80 8.20 0.821 7.70 8.10 7.60 8.00 7.50 7.40 7.90

7.30 0.924 7.80 7.20 7.70 7. 1 0 7.60 7. 0 0 6.90 7.50 6.80 7.40 Non-Operative Treatment 6.70 7.60 6.60 Operative Treatment 6.50 7.20 6.40 7. 1 0 6.30 7. 0 0 6.20 6.90 6.10 Expected Value Expected 6.00 6.80 5.90 6.70 5.80 6.60 5.70 Expected Value Expected 5.60 6.50 5.50 6.40 5.40 6.30 5.30 6.20 5.20 5.10 Non-Operative Treatment 6.10 5.00 6.00 4.90 Operative Treatment 5.90 4.80 4.70 0 0.25 0.50 0.75 1. 0 0 4.60 P_Nonop_Healed 4.50 4.40 4.30 4.20 Figure 4. One-way sensitivity analysis for probability of healing with non- 4.20 operative treatment. Above threshold value (probability of healing after 4.00 nonoperative treatment, 82%), nonoperative treatment is favored. 0 0.24 0.48 0.72 0.96 P_Op_Healed

Figure 5. One-way sensitivity analysis for probability of healing with operative treatment. Below threshold value (probability of healing after operative treatment, 92%), nonoperative treatment is favored.

www.amjorthopedics.com March/April 2016 The American Journal of Orthopedics ® E73 Operative Versus Nonoperative Treatment of Jones Fractures: A Decision Analysis Model

the case with many foot and ankle disorders22, the cally,23 is advantageous in terms of feasibility and information on treatment of Jones fractures is very reliability,24 and has been successfully used in limited in its level of clinical evidence. other orthopedic decision analysis models.12,25,26 In Determination of outcome utility also has our estimation, generally active patients without a limitations. Utility is a subjective value that an history of foot pathology constituted a sample of individual places on a specific outcome. This can convenience but also were representative of indi- be very difficult to quantify. In general, the most viduals at risk for Jones fracture. Although specific robust estimates of patient-derived utilities are scenarios were presented, the patients who com- derived from complex qualitative methods, such as pleted the questionnaire may not have had deep the standard reference gamble or time trade-offs, insights into the subtleties and implications of the in which patients are asked to gamble or choose various disease states and treatments. Regard- between health states usually referenced to death. less of how outcome probabilities and utilities are In this study, we determined patient-derived utility determined, they are considered point estimates values from a direct scaling method using a Likert in decision analysis, and sensitivity analyses are scale because of the complexity of the standard therefore performed to assess how decision mak- reference gamble and the difficulty of referencing ing changes over a range of values. to death for metatarsal fracture. Although use of a direct scale to determine utility values is less Conclusion rigorous than the standard reference gamble, this The results of this study may help optimize the technique has been corroborated methodologi- process of deciding between operative and non-

8.10 8.40 8.05 8.34 8.00 8.30 0.831 7.95 6.867 Non-Operative Treatment 8.25 Non-Operative Treatment 7.90 8.20 7.85 Operative Treatment 8.15 Operative Treatment 7.80 8.00 7.75 7.95 7.70 7.90 7.65 7.85 7.60 7.80 7.55 7.75 7.50 7.70 7.45 7.65 7.40 7.60 7.35 7.55 7.30 7.50 7.25 7.45 7.20 7.40 7. 1 5 7.35 7. 1 0 7.30 7.05 7.25 7. 0 0 Value Expected 7.20 6.95 7. 1 5 6.90 7. 1 0 Expected Value Expected 6.85 7.05 6.80 7. 0 0 6.75 6.95 6.70 6.90 6.65 6.85 6.60 6.80 6.55 6.75 6.50 6.70 6.45 6.65 6.40 6.60 6.35 6.55 6.30 6.50 6.25 6.45 6.20 6.40 6.15 6.10 0 2.25 4.50 6.75 9.00 6.05 6.00 U_Initial_Nonunion_No_Complication 0 0.25 0.50 0.75 1. 0 0 P_No_Complication Figure 7. One-way sensitivity analysis for utility for successfully treated nonunion. Above threshold value (utility for successfully treated non- union, 6.9), nonoperative treatment is favored. Figure 6. One-way sensitivity analysis for probability of minor complica- tion with surgery. Above threshold value (probability of minor complica- tion with surgery, 17%), nonoperative treatment is favored.

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operative treatment for Jones fracture. For a given and radiographic evaluation. Am J Sports Med. 2005;33(5): patient, the optimal strategy depends not only 726-733. 11. Aleem IS, Jalal H, Sheikh AA, Bhandari M. Clinical decision on the probabilities of the various outcomes but analysis: Incorporating the evidence with patient preferenc- also on personal preference. Thus, there may not es. Patient Prefer Adherence. 2009;3:21-24. be one right answer for all patients. Patients who 12. Bishop J, Ring D. Management of radial nerve palsy associ- ated with humeral shaft fracture: a decision analysis model. value a higher chance of fracture healing with initial J Surg Am. 2009;34(6):991-996.e1. treatment or an earlier return to sports are best 13. Chen NC, Shauver MJ, Chung KC. A primer on use of deci- treated operatively, whereas patients who are risk- sion analysis methodology in hand surgery. J Hand Surg Am. 2009;34(6):983-990. averse and place a high value on fracture healing 14. Kocher MS, Henley MB. It is money that matters: decision without surgery should be managed nonoperative- analysis and cost-effectiveness analysis. Clin Orthop Relat ly. We therefore advocate a model of shared med- Res. 2003(413):106-116. 15. Dean BJ, Kothari A, Uppal H, Kankate R. The jones fracture ical decision-making in which the physician and classification, management, outcome, and complications: a the patient are jointly involved, considering both systematic review. Foot Ankle Spec. 2012;5(4):256-259. outcome probabilities and patient preferences. On- 16. Martin RL, Irrgang JJ, Burdett RG, Conti SF, Van Swearingen JM. Evidence of validity for the Foot and Ankle Ability Mea- going research efforts should focus on predictors sure (FAAM). Foot Ankle Int. 2005;26(11):968-983. of nonunion with nonoperative treatment. 17. Roche AJ, Calder JD. Treatment and return to sport following a Jones fracture of the fifth metatarsal: a systematic review. 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