OBJECTIVES: To construct and validate a prediction model of preference-adjusted health status (EQ-5D) for metastatic hormone-refractory prostate cancer (HRPCA) patients using cancer-specific health-related quality of life (HRQoL) measures. METHODS: Data were obtained from a multicenter, multinational observational study of metastatic HRPCA patients conducted during 2002 to 2004. In addition to clinical and resource utilization, preference-adjusted health status (EQ-5D) and HRQoL (Functional Assessment of Cancer Therapy-Prostate [FACT-P] and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire [EORTC QLQ-C30]) data were collected. Predictive validity of ordinary least square (OLS) and median regressions of various model specifications were tested using cross-validation samples. The selected specification was then further refined and tested for alternative model specifications and restrictions. RESULTS: OLS regression with both HRQoL measures as individual components and patient demographics was the best-performing model. It explained 58.2% of the observed EQ-5D variation in the validation sample. A model including only the prostate cancer-specific HRQoL measure, FACT-P, explained 53.5% of the observed EQ-5D variation. CONCLUSIONS: The models developed have good predictive validity. These algorithms enable researchers to translate cancer-specific HRQoL measures to preference-adjusted health status in metastatic HRPCA patients. The findings will help perform health status adjustments in cost-utility analyses.
OBJECTIVES: To construct and validate a prediction model of preference-adjusted health status (EQ-5D) for metastatic hormone-refractory prostate cancer (HRPCA) patients using cancer-specific health-related quality of life (HRQoL) measures. METHODS: Data were obtained from a multicenter, multinational observational study of metastatic HRPCA patients conducted during 2002 to 2004. In addition to clinical and resource utilization, preference-adjusted health status (EQ-5D) and HRQoL (Functional Assessment of Cancer Therapy-Prostate [FACT-P] and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire [EORTC QLQ-C30]) data were collected. Predictive validity of ordinary least square (OLS) and median regressions of various model specifications were tested using cross-validation samples. The selected specification was then further refined and tested for alternative model specifications and restrictions. RESULTS: OLS regression with both HRQoL measures as individual components and patient demographics was the best-performing model. It explained 58.2% of the observed EQ-5D variation in the validation sample. A model including only the prostate cancer-specific HRQoL measure, FACT-P, explained 53.5% of the observed EQ-5D variation. CONCLUSIONS: The models developed have good predictive validity. These algorithms enable researchers to translate cancer-specific HRQoL measures to preference-adjusted health status in metastatic HRPCA patients. The findings will help perform health status adjustments in cost-utility analyses.
Authors: Nalin Payakachat; Kent H Summers; Andreas M Pleil; Matthew M Murawski; Joseph Thomas; Kristofer Jennings; James G Anderson Journal: Qual Life Res Date: 2009-06-19 Impact factor: 4.147