Author: King MT, Bell ML, Costa D, Butow P, Oh B.
Psycho-oncology Co-operative Research Group (PoCoG), School of Psychology, University of Sydney, New South Wales, Australia 2006. Electronic address: email@example.com.
Conference/Journal: J Clin Epidemiol.
Date published: 2013 Oct 11
Other: Pages: S0895-4356(13)00307-7 , Special Notes: doi: 10.1016/j.jclinepi.2013.02.019 , Word Count: 221
Quality of Life Questionnaire Core 30 (QLQ-C30) and Functional Assessment of Cancer Therapy-General (FACT-G) are widely used cancer-specific health-related quality of life (HRQOL) questionnaires. We aimed to compare their responsiveness with clinically important effects and statistical efficiency to detect such effects.
STUDY DESIGN AND SETTING:
Secondary analysis of QLQ-C30 and FACT-G data from a randomized controlled trial of Medical Qigong (n = 162 heterogeneous cancer patients). Difference in responsiveness (DR) and relative efficiency (RE) were calculated for five domains.
FACT-G total score was more efficient than QLQ-C30 global scale for detecting change within the intervention arm [RE = 0.31 (0.083, 0.69)] and comparing change between trial arms [RE = 0.17 (0.009, 0.58)]. In the social domain, the QLQ-C30 scale was more responsive [DR = 0.28 (0.024, 0.54)] and more efficient within arm only [RE = 5.25 (1.21, 232.26)]. In the physical, functional/role, and emotional domains, neither questionnaire was more responsive or efficient.
FACT-G would require about one-third the sample of QLQ-C30 to detect a given change in overall HRQOL, whereas in the social domain, it would require five times the sample size. FACT-G won advantage in overall HRQOL by reduced "noise" (smaller standard deviation achieved by summing across 27 items), whereas QLQ-C30 won advantage in the social domain via a larger "signal" (achieved through well-targeted item content).
Copyright © 2013 Elsevier Inc. All rights reserved.
Health status, Quality of life, Reliability, Sample size, Statistical data analysis, Validity