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Madeleine T King1, David Cella2, David Osoba3, Martin Stockler4, David Eton5, Joanna Thompson6, Amy Eisenstein71Psycho-oncology Co-operative Research Group School of Psychology, University of Sydney, New South Wales, Australia; 2Department of Medical Social Sciences, Northwestern University, Illinois, USA; 3QOL Consulting, Vancouver, British Columbia, Canada; 4NHMRC Clinical Trials Centre, University of Sydney, New South Wales, Australia; 5Mayo Clinic, Rochester, Minnesota, USA; 6Centre for Health Economics Research and Evaluation, University of Technology, Sydney, New South Wales, Australia; 7Center on Outcomes Research and Education (CORE), Evanston Northwestern Healthcare (ENH), Evanston, Illinois, USAAbstract: Our aim was to develop evidence-based interpretation guidelines for the Functional Assessment of Cancer Therapy-General (FACT-G), a cancer-specific health-related quality of life (HRQOL) instrument, from a range of clinically relevant anchors, incorporating expert judgment about clinical significance. Three clinicians with many years’ experience managing cancer patients and using HRQOL outcomes in clinical research reviewed 71 papers. Blinded to the FACT-G results, they considered the clinical anchors associated with each FACT-G mean difference, predicted which dimensions of HRQOL would be affected, and whether the effects would be trivial, small, moderate, or large. These size classes were defined in terms of clinical relevance. The experts’ judgments were then linked with FACT-G mean differences, and inverse-variance weighted mean differences were calculated for each size class. Small, medium, and large differences (95% confidence interval) from 1,118 cross-sectional comparisons were as follows: physical well-being 1.9 (0.6–3.2), 4.1 (2.7–5.5), 8.7 (5.2–12); functional well-being 2.0 (0.5–3.5), 3.8 (2.0–5.5), 8.8 (4.3–13); emotional well-being 1.0 (0.1–2.6), 1.9 (0.

Background Although individual studies show that baseline health-related quality of life (HRQOL) is a prognostic factor for survival, contradictory results have been published and very few meta-analyses have confirmed the finding. We examined whether HRQOL scores are associated with survival when pooled across a large sample of patients with different disease sites. Methods We selected 30 randomised controlled trials from the European Organisation for Research and Treatment of Cancer (EORTC) started between 1986 and 2004, which included survival data for 10108 patients with 11 different cancer sites. Patients were eligible for inclusion if they had completed a baseline HRQOL assessment with the EORTC core quality of life questionnaire (QLQ-C30; n=7417). Sociodemographic variables were age (<= 60 vs >60 years) and sex (men vs women), and clinical variables were WHO performance status (0-1 vs 2-3), distant metastases (no vs yes), and cancer site. We assessed prognostic significance of sociodemographic and clinical variables and the 15 QLQ-C30 scales with Cox proportional hazard models. Findings In the stratified multivariate model including sociodemographic, clinical, and HRQOL data, the HRQOL parameters of physical functioning (hazard ratio 0.94, 95% CI 0.92-0-96; p<0.0001), pain (1.04, 1.02-1.06; p<0.0001), and appetite loss (1.05, 1.03-1.06; p<0.0001) provided significant prognostic information in addition to the parameters age (1.17, 1.06-1.28; p=0.0001), sex (0.74, 0.67-0.82; p<0.0001), and distant metastases (1.70, 1.49-1.93; p<0.0001), but not for WHO performance status (1.07, 0.97-1.19; p=0.11). Consideration of the three HRQOL parameters and sociodemographic and clinical data increased the predictive accuracy of prognosis of overall survival by 6% relative to sociodemographic and clinical characteristics alone (C statistic for concordance between predicted and observed overall survival 0.68 for sociodemographic and clinical variables, and 0.72 for sociodemogr

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 R-2- 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 R-2- 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.

Purpose : The aim of this study was to evaluate whether the inclusion of health-related quality of life (HRQOL), as a part of the trial design in a randomized controlled trial (RCT) setting, has supported clinical decision making for the planning of future medical treatments in prostate cancer. Materials and Methods: A minimum standard checklist for evaluating HRQOL outcomes in cancer clinical trials was devised to assess the quality of the HRQOL reporting and to classify the studies on the grounds of their robustness. It comprises 11 key HRQOL issues grouped into four broader sections: conceptual, measurement, methodology, and interpretation. Relevant studies were identified in a number of databases, including MEDLINE and the Cochrane Controlled Trials Register. Both their HRQOL and traditional clinical reported outcomes were systematically analyzed to evaluate their consistency and their relevance for supporting clinical decision making. Results: Although 54% of the identified studies did not show any differences in traditional clinical end points between treatment arms and 17% showed a difference in overall survival, 74% of the studies showed some difference in terms of HRQOL outcomes. One third of the RCTs provided a comprehensive picture of the whole treatment including HRQOL outcomes to support their conclusions. Conclusion: A minimum set of criteria for assessing the reported outcomes in cancer clinical trials is necessary to make informed decisions in clinical practice. Using a checklist developed for this study, it was found that HRQOL is a valuable source of information in RCTs of treatment in metastatic prostate cancer. (C) 2003 by American Society of Clinical Oncology.

Clinical trials involving quality of life measurement published in the literature suffer from important weaknesses due to the lack of information on numerous topics. The psychometric properties of the instruments are often lacking as well as data on the number of patients treated and analyzed. The handling of missing data is rarely documented. In order to facilitate the reporting of trials and the evaluation of published results, this article proposes a set of general guidelines for the reporting of clinical trials which include a quality of life assessment. A checklist designed to assist authors is appended., SCOPUS: ar.j, info:eu-repo/semantics/published