Qolp-04. Calculating the Net Clinical Benefit in Brain Tumor Trials by Combining Survival and Health-related Quality of Life Data Using Two Methods: Quality Adjusted Survival Effect Sizes and Joint Modelling
Year: 2019
Type: conference-abstract
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.
Source: Neuro-Oncology
Authors: Marijke Coomans, Linda Dirven, Andrew Bottomley, Martin van den Bent, Jeff Sloan, Roger Stupp, Michael Weller, Jaap Reijneveld, Martin Taphoorn, Neil Aaronson, Brigitta Baumert, Alba Brandes, Olivier Chinot, Corneel Coens, Thierry Gorlia, Ulrich Herrlinger, Florence Keime-Guibert, Annika Malmström, Francesca Martinelli, Andrea Talacchi, Wolfgang Wick
Institutions: Leiden University Medical Center, European Organisation for Research and Treatment of Cancer, European Organisation for Research and Treatment of Cancer, Erasmus MC, Mayo Clinic, Northwestern University, University of Zurich, University Hospital Zurich, Amsterdam University Medical Centers, The Netherlands Cancer Institute, Maastricht University Medical Centre, Istituto delle Scienze Neurologiche di Bologna, University of Bonn, University Hospital Bonn, Pitié-Salpêtrière Hospital, Linköping University, Azienda Ospedaliera San Giovanni Addolorata, Heidelberg University, University Hospital Heidelberg
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2971912833