Cancer · 2014 · 107 citations · 15 references
PharmacyOncologyCancer RehabilitationFunctional AssessmentHealth AssessmentHealth Outcomes MeasurementHealth Status MeasurementHealth-related Quality Of LifeHealth-related Quality Of Life MeasurementQuality Of LifeQuality Of Life AssessmentBurden Of Illness MeasurementCancer-related Quality Of LifeDisease-specific Health StatusQuality Of Life EndpointsSymptom Assessment Tools
BACKGROUND: Health-related quality of life (HRQOL) measures are commonly used in oncology research. Interest in their use for monitoring or screening is increasing. The Functional Assessment of Cancer Therapy (FACT) is one of the most widely used HRQOL instruments. Consequently, oncology researchers and practitioners have an increasing need for reference values for the Functional Assessment of Cancer Therapy-General (FACT-G) and its 7-item rapid version, the Functional Assessment of Cancer Therapy-General 7 (FACT-G7), to compare FACT scores across specific subgroups of patients in research trials and practice. The objectives of this study are to provide 1) reference values from a sample of the general US adult population and a sample of adults diagnosed with cancer and 2) cutoff scores for quality of life. METHODS: A sample of the general US population (N = 1075) and a sample of patients with cancer from 12 studies (N = 5065) were analyzed. Cutoff scores were established using distribution- and anchor-based methods. Mean values for the cancer sample were analyzed by performance status, cancer type, and disease status. Also, t tests and established criteria for meaningful differences were used to compare values. RESULTS: FACT-G and FACT-G7 scores in the general US population sample and cancer sample were generally comparable. Among the sample of patients with cancer, FACT-G and FACT-G7 scores worsened with declining performance status and increasing disease status. CONCLUSIONS: These data will aid interpretation of the magnitude and meaning of FACT scores, and allow for comparisons of scores across studies.
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Statistical Power Analysis for the Behavioral Sciences
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