Plastic Surgeon Expertise in Predicting Breast Reconstruction Outcomes for Patient Decision Analysis

Abstract

Background: Decision analysis offers a framework that may help breast cancer patients make good breast reconstruction decisions. A requirement for this type of analysis is information about the possibility of outcomes occurring in the form of probabilities. The purpose of this study was to determine if plastic surgeons are good sources of probability information, both individually and as a group, when data are limited. Methods: Seven plastic surgeons were provided with pertinent medical information and preoperative photographs of patients and were asked to assign probabilities to predict number of revisions, complications, and final aesthetic outcome using a questionnaire designed for the study. Logarithmic strictly proper scoring was used to evaluate the surgeons’ abilities to predict breast reconstruction outcomes. Surgeons’ responses were analyzed for calibration and confidence in their answers. Results: As individuals, there was variation in surgeons’ ability to predict outcomes. For each prediction category, a different surgeon was more accurate. As a group, surgeons possessed knowledge of future events despite not being well calibrated in their probability assessments. Prediction accuracy for the group was up to 6-fold greater than that of the best individual. Conclusions: The use of individual plastic surgeon–elicited probability information is not encouraged unless the individual’s prediction skill has been evaluated. In the absence of this information, a group consensus on the probability of outcomes is preferred. Without a large evidence base for calculating probabilities, estimates assessed from a group of plastic surgeons may be acceptable for purposes of breast reconstruction decision analysis.