Prognostic value for overall survival of the EORTC QLQ-C30 Summary Score: An analysis of 5 closed EORTC trials

BACKGROUND: The EORTC QLQ‑C30 Summary Score (Summary Score) aggregates 13 functioning and symptom scales to measure overall health-related quality of life (HRQoL). We assessed its baseline prognostic contribution for overall survival (OS) alongside the global health status/quality of life (Global Health/QoL) and other QLQ-C30 scales. METHODS: We pooled HRQoL data from five randomized trials including five cancer types (n = 1863). Multivariable Cox proportional hazards models were adjusted for age, sex, WHO performance status, metastatic status, and cancer type. QLQ-C30 scales were selected using stepwise backward elimination, with bootstrap validation (500 resamples) assessing stability. To avoid multicollinearity, the Summary Score and Global Health/QoL scale were evaluated in separate models, with an additional bootstrap analysis comparing their stability. Discriminative performance was assessed using Harrell's C-index. RESULTS: In separate multivariable models, the Summary Score (HR 0.904, 95% CI 0.869-0.939) and Global Health/QoL (HR 0.951, 95% CI 0.925-0.977) were retained as independent predictors, as well as Physical Functioning (HR 0.926, 95% CI 0.896-0.957) and Appetite Loss (HR 1.035, 95% CI 1.011-1.058). The Summary Score was retained in 96.6% of bootstrap samples versus 9.0% for Global Health/QoL. Compared with the clinical model (C = 0.603), C-indices increased to 0.637 with the Summary Score, 0.622 with Global Health/QoL, and 0.641 with Physical Functioning and Appetite Loss. CONCLUSION: The Summary Score, Physical Functioning, and Appetite Loss improve OS prediction beyond clinical factors. Although Global Health/QoL showed similar discrimination, the Summary Score demonstrated greater stability and may be preferable for robust risk stratification.

Authors

Institutions

Publication Details

Journal
European Journal of Cancer
Published
2026-04-30
DOI
https://doi.org/10.1016/j.ejca.2026.116774
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prognostic value for overall survival of the EORTC QLQ-C30 Summary Score: An analysis of 5 closed EORTC trials

Johan A F Koekkoek, Johannes M. Giesinger, Linda Dirven, Elke Rammant et al.
European Journal of Cancer
Inflammatory Biomarkers in Disease Prognosis
article

Prognostic value for overall survival of the EORTC QLQ-C30 Summary Score: An analysis of 5 closed EORTC trials

Johan A F Koekkoek, Johannes M. Giesinger, Linda Dirven, Elke Rammant, Corneel Coens, Winette T.A. van der Graaf, Martin Taphoorn, Nazım Serdar Turhal, M. Bolla, Neil K. Aaronson, Luigi Lim, Olga Husson, Morten Aa. Petersen, Mogens Grønvold, Jayne Galinsky, Jammbe Z. Musoro, Brigitta G. Baumert, Charalampia Kyriakou, Vesna Bjelic-Radisic, Josien C.C. Scheepens, Mary O’Brien
article en

Abstract

BACKGROUND: The EORTC QLQ‑C30 Summary Score (Summary Score) aggregates 13 functioning and symptom scales to measure overall health-related quality of life (HRQoL). We assessed its baseline prognostic contribution for overall survival (OS) alongside the global health status/quality of life (Global Health/QoL) and other QLQ-C30 scales. METHODS: We pooled HRQoL data from five randomized trials including five cancer types (n = 1863). Multivariable Cox proportional hazards models were adjusted for age, sex, WHO performance status, metastatic status, and cancer type. QLQ-C30 scales were selected using stepwise backward elimination, with bootstrap validation (500 resamples) assessing stability. To avoid multicollinearity, the Summary Score and Global Health/QoL scale were evaluated in separate models, with an additional bootstrap analysis comparing their stability. Discriminative performance was assessed using Harrell's C-index. RESULTS: In separate multivariable models, the Summary Score (HR 0.904, 95% CI 0.869-0.939) and Global Health/QoL (HR 0.951, 95% CI 0.925-0.977) were retained as independent predictors, as well as Physical Functioning (HR 0.926, 95% CI 0.896-0.957) and Appetite Loss (HR 1.035, 95% CI 1.011-1.058). The Summary Score was retained in 96.6% of bootstrap samples versus 9.0% for Global Health/QoL. Compared with the clinical model (C = 0.603), C-indices increased to 0.637 with the Summary Score, 0.622 with Global Health/QoL, and 0.641 with Physical Functioning and Appetite Loss. CONCLUSION: The Summary Score, Physical Functioning, and Appetite Loss improve OS prediction beyond clinical factors. Although Global Health/QoL showed similar discrimination, the Summary Score demonstrated greater stability and may be preferable for robust risk stratification.

European Journal of CancerVol. 241
National Health Service (GB), Anadolu University (TR), University College London Hospitals NHS Foundation Trust (GB), Vrije Universiteit Brussel (BE), Universität Innsbruck (AT), Leiden University Medical Center (NL), Centre Hospitalier Universitaire de Grenoble (FR), Frederiksberg Hospital (DK), The Netherlands Cancer Institute (NL), Ghent University (BE), Helios Universitätsklinikum Wuppertal (DE), European Organisation for Research and Treatment of Cancer (BE), European Federation of Allergy and Airways Diseases Patients Associations (BE), Erasmus MC Cancer Institute (NL), Maastro Clinic (NL), University Hospital Innsbruck (AT), University College London (GB), Istanbul University (TR)
European Organisation for Research and Treatment of Cancer
Climate action
Openalex Percentile: Top 13%
Inflammatory Biomarkers in Disease Prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.