Life Expectancy Predictions for Older Diabetic Patients as Estimated by Physicians and a Prognostic Model

Background: Multiple medical organizations recommend using life expectancy (LE) to individualize diabetes care goals. We compare the performance of patient LE predictions made by physicians to LE predictions from a simulation model (the Chicago model) in a cohort of older diabetic patients. Design: Retrospective cohort study of a convenience sample (n = 447) of diabetes patients over 65 years and their physicians. Measurements: Physicians provided LE estimates for individual patients during a baseline survey (2000–2003). The prognostic model included a comprehensive geriatric type 2 diabetes simulation model (the Chicago model) and combinations of the physician estimate and the Chicago model (“And,” “Or,” and “Average” models). Observed survival was determined based on the National Death Index through 31 December 2010. The predictive accuracy of LE predictions was assessed using c-statistic for 5-year mortality; Harrell’s c-statistic, and Integrated Brier score for overall survival. Results: The patient cohort had a mean (SD) age of 73.4 (5.9) years. The majority were female (62.6%) and black (79.4%). At 5 years, 108 (24.2%) patients had died. The c-statistic for 5-year mortality was similar for physicians (0.69) and the Chicago model (0.68), while the average of estimates by physicians and Chicago model yielded the highest c-statistic of any method tested (0.73). The estimates of overall survival yielded a similar pattern of results. Limitations: Generalizability of patient cohort and lack of updated model parameters. Conclusions: Compared with individual methods, the average of LE estimates by physicians and the Chicago model had the best predictive performance. Prognostic models, such as the Chicago model, may complement and support physicians’ intuitions as they consider treatment decisions and goals for older patients with chronic conditions like diabetes.