Use of Decision Analysis and Economic Evaluation in Breast Reconstruction: A Systematic Review

Abstract

Background: Decision analysis allows clinicians to compare different strategies in the context of uncertainty, through explicit and quantitative measures such as quality of life outcomes and costing data. This is especially important in breast reconstruction, where multiple strategies can be offered to patients. This systematic review aims to appraise and review the different decision analytic models used in breast reconstruction.

Methods: A search of English articles in PubMed, Ovid, and Embase databases was performed. All articles regardless of date of publishing were considered. Two reviewers independently assessed each article, based on strict inclusion criteria.

Results: Out of 442 articles identified, 27 fit within the inclusion criteria. These were then grouped according to aspects of breast reconstruction, with implant-based reconstruction (n = 13) being the most commonly reported. Decision analysis (n = 19) and/or economic analyses (n = 27) were employed to discuss reconstructive options. The most common outcome was cost (n = 27). The decision analysis models compared and contrasted surgical strategies, management options, and novel adjuncts.

Conclusions: Decision analysis in breast reconstruction is growing exponentially.The most common model used was a simple decision tree. Models published were of high quality but could be improved with a more in-depth sensitivity analysis. It is essential for surgeons to familiarize themselves with the concept of decision analysis to better tackle complicated decisions, due to its intrinsic advantage of being able to weigh risks and benefits of multiple strategies while using probabilistic models.

Fig. 1.

Example of a decision tree. We read the tree from left to right, with the clinical question being the furthest left. A square represents a decision node, with the strategies being compared branching out from it. A circle represents a chance node, with possible events branching out from it. From there on, a line represents a strategy pathway, accompanied by a probability of experiencing this event. The sum of all probabilities at a chance node must equal to 1. A triangle represents an outcome node, accompanied by the cost and/or utility of that pathway. To quantifiably compare strategies, each chance node is then assigned a probability-weighted average of the outcomes stemming from it, yielding the expected value.

Fig. 2.

PRISMA search strategy. PRISMA indicates Preferred Reporting Items for Systematic Reviews and Meta-Analyses.