Abstract
INTRODUCTION: The impact of treatment on both the quality and the quantity of life, i.e. the ‘net clinical benefit’, should be considered to facilitate shared decision making. Two methods that combine survival and health-related quality of life (HRQoL) data: Quality Adjusted Effect Sizes (QASES) and Joint Modelling (JM) were applied to gain insight in the net clinical benefit. METHODS: The net clinical benefit in one RCT (EORTC 26951 comparing radiotherapy (RT) + PCV chemotherapy versus RT alone) was calculated as a proof of concept for other trials. With the QASES method, effect sizes for differences in survival and HRQoL between treatment arms were calculated. JM allows simultaneous modeling of a longitudinal outcome (HRQoL), and a time-to event outcome (survival). HRQoL scales/items that were selected for primary analysis in the main study were also selected for this analysis: fatigue, global health, social functioning, communication deficit, seizures, physical functioning, and nausea/vomiting. RESULTS: 288/386 patients completed baseline HRQoL forms and were included in the analysis. Overall survival (OS) was significantly longer with combined treatment (42.3 vs. 30.6 months). The percentage of patients who experienced a clinically relevant deterioration (≥10 points) in nausea/vomiting, fatigue, social functioning and global health up to one year after treatment compared to baseline was larger in the RT+PCV arm. QASES corresponded to a reduction in the median OS difference from 9.7 months up till 5.5 months, given equal weights to OS and HRQoL. JM analyses resulted in a theoretical loss of treatment effect in OS of 2–6% when adjusting for HRQoL. CONCLUSION: Both methods showed that adjusting for the impact of treatment on a relevant HRQoL parameter reduced the survival benefit in the experimental treatment arm compared to standard treatment arm. Applying these methods may facilitate communicating the impact of treatment to patients in clinical practice.