Is Quality of Life Data Predictive of the Survival in Cancer Patients? A Rapid and Systematic Review of the Literature

Objective: To review literature on relationship between quality of life data and the length of survival in cancer patients. Methods: A literature search was carried out using MEDLINE to assess existing knowledge on relationship between quality of life data as a prognostic factor and survival in cancer patients. The intention was to review all full publications in English language biomedical journals. The search strategy included the combination of keywords ‘cancer’, ‘prognostic’, ‘predictor’, ‘predictive’, ‘quality of life’ and ‘survival’ in titles of publications. The literature was also examined to ensure that the study used multivariate analyses. Pure psychological studies were excluded. The initial search was carried out twice in December 2008 and twice for a final check in early and late January 2009. A manual search also was performed for including possible additional papers. Results: In all 146 citations were identified and reviewed. Of these, 88 citations on relationship between quality of life and survival were found relevant and examined in this rapid and systematic review of the literature. The findings are summarized under different headings including studies on heterogeneous sample of cancer patients, lung cancer, breast cancer, gastro-oesophageal cancers, colorectal cancer and other cancers. Except a few exceptions most studies found that quality of life data or some aspects of quality of life measures were significant independent predictors of survival duration. Global quality of life, functioning domains and symptom scores such as appetite loss, fatigue and pain individually or in combined were the most important factors that predicted the length of survival in cancer patients after adjusting for one or more demographic and known clinical prognostic factors. Conclusion: Studies reported in this review provide evidence for a positive relationship between quality of life data or some aspects of quality of life measures and the length of survival in cancer patients. Pre-treatment quality of life data are appeared to be most reliable information that could help clinicians to establish prognostic criteria for treatment of their cancer patients. Indeed, conducting studies using valid instruments, applying sound methodological approaches and adequate but not sophisticated multivariate statistical analyses adjusted for demographic characteristics and known clinical prognostic factors are recommended in order to yield more specific quality of life related prognostic variables for specific cancers.