ASCO GU 2018: Can Health-Related Quality of Life Predict Conditional Survival in Metastatic RCC? Results from a Large Phase III Trial

San Francisco, CA ( Justin Doan presented on the effects of Health-Related Quality of Life (HRQoL) on conditional survival for patients with metastatic renal cell carcinoma (RCC). In the absence of mature overall survival (OS) endpoints, interim clinical trial data can be used to predict long-term survival in patients with advanced malignancies and inform trial continuation, treatment preference, and reimbursement decisions. HRQoL assessments may be associated with OS, offering potential utility for validated HRQoL scales. The objective of this study was to describe a predictive model used to determine the extent to which HRQoL data may predict conditional survival – ie. survival conditional on progression at either 6 or 12 months.

For this study, the authors utilized data from the large phase III trial assessing nivolumab vs everolimus in the second line setting (CheckMate 025) [1]. A simulation approach was used in which a survival random forest algorithm identified factors statistically important in predicting conditional survival from a number of covariates measured at baseline. Stepwise Cox proportional hazard survival models were fitted using covariates identified as important. Baseline scores and change over time (at a 12-month landmark) were tested to determine the influence on the predictive power of the HRQoL data (Functional Assessment of Cancer Therapy—Kidney Symptom Index (FKSI) on conditional survival.

For both nivolumab and everolimus, baseline FKSI values were significant predictors of conditional survival. In fact, the median survival times roughly doubled for patients with baseline FKSI scores ≥30 vs patients with scores < 30 (nivolumab: 31.3-16.6; everolimus: 26.6-11). Baseline FKSI scores were the most important predictor vs the other baseline covariates from the survival random forest simulation, and was a statistically significant covariate when fitting a stepwise Cox proportional hazard survival model. Change in scores over time influenced conditional survival for patients with high baseline scores, and patients who demonstrated improvement in scores vs baseline had significantly higher conditional survival vs patients with low baseline and no improvement in scores vs baseline. However, when examining change in HRQoL score over time, the statistical importance of the covariate begins to diminish due to high correlations with factors such as adverse events and weight change.

The authors concluded that HRQoL data from a large phase III RCT testing nivolumab vs everolimus, specifically the FKSI, could be useful in predicting conditional survival, especially at the onset of a trial. The importance of the FKSI score in predicting conditional survival could be a powerful complement to existing clinical prognostic factors for informing clinical decisions.

Presented by: Justin Doan, Director-Oncology, Bristol-Myers Squibb, Princeton, NJ

Co-Authors: Bill Malcolm, Eduardas Valaitis, Kristopher Hoover, Saby George; Bristol-Myers Squibb, Princeton, NJ; Bristol-Myers Squibb, Uxbridge, United Kingdom; PricewaterhouseCoopers, Washington, DC; Roswell Park Cancer Institute, Buffalo, NY

Written by: Zachary Klaassen, MD, Urologic Oncology Fellow, University of Toronto, Princess Margaret Cancer Centre, @zklaassen_md at the 2018 American Society of Clinical Oncology Genitourinary (ASCO GU) Cancers Symposium, February 8-10, 2018 - San Francisco, CA


1. Motzer RJ, Escudier B, McDermott DF, et al. Nivolumab versus Everolimus in Advanced Renal-Cell Carcinoma. N Engl J Med 2015;373(19):1803-1813.