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

To review literature on relationship between quality of life data and thelength of survival in cancer patients.methods: a literature search was carried out using medline to assess existingknowledge on relationship between quality of life data as a prognostic factor andsurvival in cancer patients. the intention was to review all full publications in englishlanguage biomedical journals. the search strategy included the combination ofkeywords ‘cancer’, ‘prognostic’, ‘predictor’, ‘predictive’, ‘quality of life’ and‘survival’ in titles of publications. the literature was also examined to ensure that thestudy used multivariate analyses. pure psychological studies were excluded. theinitial search was carried out twice in december 2008 and twice for a final check inearly and late january 2009. a manual search also was performed for includingpossible additional papers.results: in all 146 citations were identified and reviewed. of these, 88 citations onrelationship between quality of life and survival were found relevant and examinedin this rapid and systematic review of the literature. the findings are summarizedunder different headings including studies on heterogeneous sample of cancerpatients, lung cancer, breast cancer, gastro-oesophageal cancers, colorectal cancerand other cancers. except a few exceptions most studies found that quality of lifedata or some aspects of quality of life measures were significant independentpredictors of survival duration. global quality of life, functioning domains andsymptom scores such as appetite loss, fatigue and pain individually or in combinedwere the most important factors that predicted the length of survival in cancerpatients after adjusting for one or more demographic and known clinical prognosticfactors.conclusion: studies reported in this review provide evidence for a positiverelationship between quality of life data or some aspects of quality of lifemeasures and the length of survival in cancer patients. pre-treatment quality of lifedata are appeared to be most reliable information that could help clinicians toestablish prognostic criteria for treatment of their cancer patients. indeed,conducting studies using valid instruments, applying sound methodologicalapproaches and adequate but not sophisticated multivariate statistical analysesadjusted for demographic characteristics and known clinical prognostic factors arerecommended in order to yield more specific quality of life related prognosticvariables for specific cancers.