1. The EORTC QLQ‐C30 Summary Score as Prognostic Factor for Survival of Patients with Cancer in the "Real‐World": Results from the Population‐Based PROFILES Registry.
- Author
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Husson, Olga, Rooij, Belle H., Kieffer, Jacobien, Oerlemans, Simone, Mols, Floortje, Aaronson, Neil K., Graaf, Winette T.A., and Poll‐Franse, Lonneke V.
- Subjects
TUMOR treatment ,CANCER patients ,CONFIDENCE intervals ,CAUSES of death ,QUALITY of life ,QUESTIONNAIRES ,REGRESSION analysis ,SURVIVAL ,SECONDARY analysis ,SOCIOECONOMIC factors ,PROPORTIONAL hazards models ,DESCRIPTIVE statistics ,ODDS ratio - Abstract
Background: Health‐related quality of life (HRQoL) has been shown to be a prognostic factor for cancer survival in randomized clinical trials and observational "real‐world" cohort studies; however, it remains unclear which HRQoL domains are the best prognosticators. The primary aims of this population‐based, observational study were to (a) investigate the association between the novel European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire‐Core30 (QLQ‐C30) summary score and all‐cause mortality, adjusting for the more traditional sociodemographic and clinical prognostic factors; and (b) compare the prognostic value of the QLQ‐C30 summary score with the global quality of life (QoL) and physical functioning scales of the QLQ‐C30. Materials and Methods: Between 2008 and 2015, patients with cancer (12 tumor types) were invited to participate in PROFILES disease‐specific registry studies (response rate, 69%). In this secondary analysis of 6,895 patients, multivariate Cox proportional hazard regression models were used to investigate the association between the QLQ‐C30 scores and all‐cause mortality. Results: In the overall Cox regression model including sociodemographic and clinical variables, the QLQ‐C30 summary score was associated significantly with all‐cause mortality (hazard ratio [HR], 0.77; 99% confidence interval [CI], 0.71–0.82). In stratified analyses, significant associations between the summary score and all‐cause mortality were observed for colon, rectal, and prostate cancer, non‐Hodgkin lymphoma, chronic lymphocytic leukemia, and multiple myeloma. The QLQ‐C30 summary score had a stronger association with all‐cause mortality than the global QoL scale (HR, 0.82; 99% CI, 0.77–0.86) or the physical functioning scale (HR, 0.81; 95% CI, 0.77–0.85). Conclusion: In a real‐world setting, the QLQ‐C30 summary score has a strong prognostic value for overall survival for a number of populations of patients with cancer above and beyond that provided by clinical and sociodemographic variables. The QLQ‐C30 summary score appears to have more prognostic value than the global QoL, physical functioning, or any other scale within the QLQ‐C30. Implications for Practice: The finding that health‐related quality of life provides distinct prognostic information beyond known sociodemographic and clinical measures, not only around cancer diagnosis (baseline) but also at follow‐up, has implications for clinical practice. Implementation of cancer survivorship monitoring systems for ongoing surveillance may improve post‐treatment rehabilitation that leads to better outcomes. This article reports on the association of the novel QLQ‐C30 summary score with all‐cause mortality for several cancer diagnoses and discusses the prognostic value of the summary score above and beyond that of more traditional sociodemographic and clinical prognostic factors. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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