Abstract
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.
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.
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).
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.
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.