The Quality of Life Questionnaire Core 30 (QLQ-C30) and Functional Assessment of Cancer-General (FACT-G) differ in responsiveness, relative efficiency, and therefore required sample size

Madeleine T. King, Melanie L. Bell, Daniel Costa, Phyllis Butow, Byeongsang Oh

Research output: Contribution to journalArticle

25 Scopus citations

Abstract

Objectives 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. Results 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. Conclusion 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).

Original languageEnglish (US)
Pages (from-to)100-107
Number of pages8
JournalJournal of Clinical Epidemiology
Volume67
Issue number1
DOIs
StatePublished - Jan 1 2014
Externally publishedYes

Keywords

  • Health status
  • Quality of life
  • Reliability
  • Sample size
  • Statistical data analysis
  • Validity

ASJC Scopus subject areas

  • Epidemiology

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