Original Research

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

Am J Orthop. 2016 March;45(3):E69-E76

Optimal management of metadiaphyseal fifth metatarsal fractures (Jones fractures) remains controversial. Decision analysis can optimize clinical decision-making based on available evidence and patient preferences.

We conducted a study to establish the determinants of decision-making and to determine the optimal treatment strategy for Jones fractures using a decision analysis model. Probabilities for potential outcomes of operative and nonoperative treatment of Jones fractures were determined from a review of the literature. Patient preferences for outcomes were obtained by questionnaire completed by 32 healthy adults with no history of foot fracture. Derived values were used in the model as a measure of utility. A decision tree was constructed, and fold-back and sensitivity analyses were performed to determine optimal treatment. Nonoperative treatment was associated with a value of 7.74, and operative treatment with an intramedullary screw was associated with a value of 7.88 given the outcome probabilities and utilities studied, making operative treatment the optimal strategy. When parameters were varied, nonoperative treatment was favored when the likelihood of healing with nonoperative treatment rose above 82% and when the probability of healing after surgery fell below 92%. In this decision analysis model, operative fixation is the preferred management strategy for Jones fractures.

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The optimal management strategy for acute fractures of the metadiaphyseal fifth metatarsal (Jones fractures) is controversial. Patients can be successfully treated nonoperatively with non-weight-bearing and immobilization in a short leg cast^1-7 or operatively with placement of an intramedullary screw.^8-10The primary advantage of nonoperative treatment is avoiding the risks and discomfort of surgery; disadvantages include the need for prolonged immobilization and protected weight-bearing as well as a decreased union rate.^8,9 Advantages of operative treatment include accelerated functional recovery and an improved union rate; disadvantages include exposure to the risks, inconvenience, and discomfort of surgery. Clear, definitive evidence for guiding treatment is not available in the orthopedic literature, and treatment strategies vary substantially according to surgeon and patient preference.

Expected-value decision analysis, a research tool that helps guide decision-making in situations of uncertainty, has been effectively applied to other areas of uncertainty in the orthopedic literature.^11-14 Borrowed from gaming theory, the technique involves creating a decision tree to define the clinical problem, determining outcome probabilities and utilities, performing a fold-back analysis to determine the optimal decision-making strategy, and performing a sensitivity analysis to model the effect of varying outcome probabilities and utilities on decision-making. Decision analysis may therefore allow the clinician and the patient to optimize decision-making based on best available evidence and patient preferences. It also helps determine the most important factors affecting management strategies and the decision-making process, which may not always be intuitive.

In the present study, we used expected-value decision analysis to determine the optimal management strategy, operative or nonoperative, for acute Jones fracture. We also explored factors with the most influence on the model and identified important questions for future research.

Materials and Methods

Institutional review board approval was obtained for this study. Analysis was performed with Treeage Pro statistical software (Treeage Software).

Outcome Probabilities

Outcome probabilities were determined by reviewing the literature for articles on Jones fractures. This body of literature was summarized in a comprehensive review by Dean and colleagues¹⁵, who extracted data from 19 studies: 1 randomized controlled trial, 1 prospective case series, and 17 retrospective case series.¹⁵ We used data from these studies to determine outcome probabilities (Table).

Outcome Utilities

Utilities represent patient preferences for various disease states. Outcome utility values were obtained from 32 adults (25 women, 7 men) with no history of foot injury. Mean age was 32.4 years (range, 20-69 years). The questionnaire presented scenarios for the different outcomes and asked patients to rate these outcomes on a scale ranging from 0 (worst possible outcome) to 10 (best possible outcome). The Sports subscale of the Foot and Ankle Ability Measure (FAAM) 16 was used to quantify patient activity level.

Decision Tree and Fold-Back Analysis

A decision tree was constructed with 1 decision node, 4 chance nodes, and 7 terminal nodes (Figure 1). The decision tree demonstrates 2 different strategies for managing a Jones fracture. The decision node divides the tree into 2 branches: initial operative or nonoperative treatment. Both branches are followed by various chance nodes, each terminating in a discrete clinical outcome. Per convention, utility data were placed to the right of the terminal nodes, and probability data were placed under the terminal nodes.

Fold-back analysis was performed to identify the optimal strategy. Fold-back analysis involves multiplying each outcome utility by its associated probability, thereby providing an “expected value” for each clinical endpoint. Then, the expected values for each endpoint can be summed for a given management strategy, and the ultimate expected values of the different strategies can be compared. The management strategy associated with the highest expected value is optimal for the given outcome utilities and probabilities.

Sensitivity Analysis

One-way sensitivity analysis was performed to model the effect on decision-making of changing the values for utility for uncomplicated surgery, utility for healing with nonoperative treatment, utility for uncomplicated treatment of nonunion, likelihood of healing with nonoperative treatment, likelihood of healing with surgery, and likelihood of minor complication with surgery. These were the variables found to affect the decision-making strategy within their clinically plausible ranges.

Results

Outcome Probabilities and Utilities

Outcome probabilities and utilities are illustrated in Figure 1. By convention, probabilities appear below the corresponding branches of the decision tree, and utilities appear at the end of each branch. Mean (SD) FAAM Sports subscale score was 84.6 (27.4). This subscale is scored as a percentage from 0% to 100%, with higher scores indicating a higher level of physical function.

Decision Analysis

The expected value for nonoperative treatment was 7.74, and the expected value for intramedullary screw fixation was 7.88 (Figure 1). Therefore, operative treatment was identified as the optimal treatment strategy.