Dynamic Change in Patient Reported Quality of Life is a Predictor for Survival in Localized Prostate Cancer: Exploratory Analysis from a Phase III Randomized Controlled Trial

Abstract

<h3>Purpose/Objective(s)</h3> Patient reported quality of life (QOL) outcomes are pivotal endpoints to determine treatment efficacy and safety. However, it remains unknown if treatment induced change in patient reported QOL outcomes correlate with survival in localized prostate cancer (LPCa). We performed an exploratory analysis of a phase III randomized controlled study to determine the association of treatment induced dynamic change in patient reported global QOL with long-term overall survival (OS) and disease-free survival (DFS) in LPCa treated with radiotherapy (RT) and androgen deprivation therapy (ADT). <h3>Materials/Methods</h3> LPCa patients with Gleason score ≤7, clinical stage T1b-T3a, and PSA <30 ng/mL were randomized to neoadjuvant and concurrent ADT for 6 mos starting 4 mos before prostate RT or concomitant and adjuvant ADT for 6 mos starting concurrently with RT. Patient reported QOL outcomes were collected using EORTC QOL questionnaires. We used the global QOL (G-QOL) score from C30 questionnaire. Increase in G-QOL score indicated improvement in global QOL. To capture the association between the dynamic change in the G-QOL of each patient and the hazard of outcome, we utilized the framework of multivariate joint modeling for longitudinal and survival outcomes. For the time-to-event submodel, a Cox proportional hazard regression model was built with covariables including treatment arm, baseline PSA, tumor stage, Gleason score, and age. For the longitudinal submodel, a linear mixed effect model was built with an interaction term for treatment arm and time of evaluation in addition to fixed covariables - treatment arm, time of evaluation, baseline G-QOL score and age. Time of assessment was included as a random slope while patients were included as random intercepts in the mixed models. The two submodels were linked through a random effect. Baseline hazard was modeled using penalized splines. A two-sided p-value <0.025 was chosen to be the threshold for statistical significance. <h3>Results</h3> A total of 388 patients were eligible for this study – 191 belonged to the neoadjuvant arm while 197 to the adjuvant arm. At a median follow-up of 148 mos, a total of 133 deaths were recorded. On joint modelling, an increase in G-QOL score by 10 units (the threshold for clinically meaningful change) was associated with a 11.2% decrease in the hazard of death (hazard ratio [HR] per 1 unit increase G-QOL: 0.988, 95% CI: 0.980-0.996; p=0.007). An increase in G-QOL score by 10 units was associated with 10% decrease in the hazard of progression or death (HR per 1 unit increase in G-QOL: 0.990; 95% CI: 0.984-0.999; p=0.023). <h3>Conclusion</h3> Treatment induced improvement in global QOL is a predictor for improved DFS and OS in LPCa. This suggests a significant interplay of patient-reported quality of life and quantity of life in LPCa which could mainly be driven by the non-cancer specific mortality in this patient population. Judicious use of these QOL metrics could guide risk stratification and potentially inform treatment decision in these patients