Quality of life data as prognostic indicators of survival in cancer patients: an overview of the literature from 1982 to 2008

<p>Abstract</p> <p>Background</p> <p>Health-related quality of life and survival are two important outcome measures in cancer research and practice. The aim of this paper is to examine the relationship between quality of life data and survival time in cancer patients.</p> <p>Methods</p> <p>A review was undertaken of all the full publications in the English language biomedical journals between 1982 and 2008. The search was limited to cancer, and included the combination of keywords 'quality of life', 'patient reported-outcomes' 'prognostic', 'predictor', 'predictive' and 'survival' that appeared in the titles of the publications. In addition, each study was examined to ensure that it used multivariate analysis. Purely psychological studies were excluded. A manual search was also performed to include additional papers of potential interest.</p> <p>Results</p> <p>A total of 451 citations were identified in this rapid and systematic review of the literature. Of these, 104 citations on the relationship between quality of life and survival were found to be relevant and were further examined. The findings are summarized under different headings: heterogeneous samples of cancer patients, lung cancer, breast cancer, gastro-oesophageal cancers, colorectal cancer, head and neck cancer, melanoma and other cancers. With few exceptions, the findings showed 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 - were the most important indicators, individually or in combination, for predicting survival times in cancer patients after adjusting for one or more demographic and known clinical prognostic factors.</p> <p>Conclusion</p> <p>This review provides evidence for a positive relationship between quality of life data or some quality of life measures and the survival duration of cancer patients. Pre-treatment (baseline) quality of life data appeared to provide the most reliable information for helping clinicians to establish prognostic criteria for treating their cancer patients. It is recommended that future studies should use valid instruments, apply sound methodological approaches and adequate multivariate statistical analyses adjusted for socio-demographic characteristics and known clinical prognostic factors with a satisfactory validation strategy. This strategy is likely to yield more accurate and specific quality of life-related prognostic variables for specific cancers.</p

The prognostic value of health-related quality-of-life data in predicting survival in glioblastoma cancer patients: results from an international randomised phase III EORTC Brain Tumour and Radiation Oncology Groups, and NCIC Clinical Trials Group study

This is one of the few studies that have explored the value of baseline symptoms and health-related quality of life (HRQOL) in predicting survival in brain cancer patients. Baseline HRQOL scores (from the EORTC QLQ-C30 and the Brain Cancer Module (BN 20)) were examined in 490 newly diagnosed glioblastoma cancer patients for the relationship with overall survival by using Cox proportional hazards regression models. Refined techniques as the bootstrap re-sampling procedure and the computation of C-indexes and R2-coefficients were used to try and validate the model. Classical analysis controlled for major clinical prognostic factors selected cognitive functioning (P=0.0001), global health status (P=0.0055) and social functioning (P<0.0001) as statistically significant prognostic factors of survival. However, several issues question the validity of these findings. C-indexes and R2-coefficients, which are measures of the predictive ability of the models, did not exhibit major improvements when adding selected or all HRQOL scores to clinical factors. While classical techniques lead to positive results, more refined analyses suggest that baseline HRQOL scores add relatively little to clinical factors to predict survival. These results may have implications for future use of HRQOL as a prognostic factor in cancer patients

Thin slices of behavior as cues of personality and intelligence

Borkenau P, Mauer N, Riemann R, Spinath FM, Angleitner A. Thin slices of behavior as cues of personality and intelligence. JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY. 2004;86(4):599-614.Self-reports, peer reports, intelligence tests, and ratings of personality and intelligence from 15 video-taped episodes were collected for 600 participants. The average cross-situational consistency of trait impressions across the 15 episodes was .43. Shared stereotypes related to gender and age were mostly accurate and contributed little to agreement among judges. Agreement was limited mainly by nonshared meaning systems and by nonoverlapping information. Personality inferences from thin slices of behavior were significantly associated with reports by knowledgeable informants. This association became stronger when more episodes were included, but gains in prediction were low beyond 6 episodes. Inferences of intelligence from thin slices of behavior strongly predicted intelligence test scores. A particularly strong single predictor was how persons read short sentences