What is lost in an average? Identifying distinct post-radical prostatectomy functional recovery profiles.

Abstract

To describe, via latent variable mixture modelling, distinct post-radical prostatectomy (RP) patient-reported outcome (PRO) recovery profiles, which are positioned to complement currently disseminated statistical averages for shared decision-making. Patients undergoing RP and completing the 26-item Expanded Prostate Cancer Index Composite 12 months after surgery were identified from the Michigan Urological Surgery Improvement Collaborative data registry. Hierarchical cluster analysis and latent variable mixture modelling was applied to urinary incontinence (UI) and sexual function (SF) recovery scores, and final models chosen based on optimal performance. A total of 3956 patients comprised the study cohort. Three distinct UI profiles were identified with prevalence of 49%, 37% and 14% from best to worst recovery, respectively. Four distinct SF profiles were identified with prevalence of 14%, 24%, 42%, and 20%, from best to worst recovery, respectively. The last two SF profiles had similar function scores but differed based on perception of function being bothersome. Limitations include incomplete PRO capture, which may introduce bias. We identify distinct UI and SF recovery profiles and their prevalence from a large, prospectively maintained registry, potentially improving interpretability of PRO data for decision making.