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

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Operative Versus Nonoperative Treatment of Jones Fractures: a Decision Analysis Model 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 foot 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 E70 The American Journal of Orthopedics ® March/April 2016 www.amjorthopedics.com J. A. Bishop et al 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.
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