Abstract
BackgroundEstimating a realistic effect size is an important issue in the planning of clinical studies of complementary and alternative medicine therapies. When a minimally important difference is not available, researchers may estimate effect size using the published literature. This evidence-based effect size estimation may be used to produce a range of empirically-informed effect size and consequent sample size estimates. We provide an illustration of deriving plausible effect size ranges for a study of acupuncture in the relief of post-chemotherapy fatigue in breast cancer patients.MethodsA PubMed search identified three uncontrolled studies reporting the effect of acupuncture in relieving fatigue. A separate search identified five randomized controlled trials (RCTs) with a wait-list control of breast cancer patients receiving standard care that reported data on fatigue. We use these published data to produce best, average, and worst-case effect size estimates and related sample size estimates for a trial of acupuncture in the relief of cancer-related fatigue relative to a wait-list control receiving standard care.ResultsUse of evidence-based effect size estimation to calculate sample size requirements for a study of acupuncture in relieving fatigue in breast cancer survivors relative to a wait-list control receiving standard care suggests that an adequately-powered phase III randomized controlled trial comprised of two arms would require at least 101 subjects (52 per arm) if a strong effect is assumed for acupuncture and 235 (118 per arm) if a moderate effect is assumed.ConclusionEvidence-based effect size estimation helps justify assumptions in light of empirical evidence and can lead to more realistic sample size calculations, an outcome that would be of great benefit for the field of complementary and alternative medicine.
Highlights
Estimating a realistic effect size is an important issue in the planning of clinical studies of complementary and alternative medicine therapies
In their content analysis of all scientific reviews of grant applications submitted by the Community Clinical Oncology Program for clinical trials of complementary and alternative medicine (CAM) to the National Cancer Institute, Buchanan and colleagues (p. 6685) indicated that one of the five major concerns raised by reviewers has been "justifying the anticipated effect sizes used to determine sample size."[1] With regards to published research studies, meta-analytic and systematic reviews regularly point to sample size as a troubling issue.[2]
An approach that is often preferred is to power the study to detect a minimally important difference (MID)–the magnitude of improvement for which patients would consider a course of treatment to be worthwhile.[3]
Summary
Estimating a realistic effect size is an important issue in the planning of clinical studies of complementary and alternative medicine therapies. When a minimally important difference is not available, researchers may estimate effect size using the published literature. We provide an illustration of deriving plausible effect size ranges for a study of acupuncture in the relief of post-chemotherapy fatigue in breast cancer patients. In their content analysis of all scientific reviews of grant applications submitted by the Community Clinical Oncology Program for clinical trials of complementary and alternative medicine (CAM) to the National Cancer Institute, Buchanan and colleagues BMC Complementary and Alternative Medicine 2009, 9:1 http://www.biomedcentral.com/1472-6882/9/1 results are non-significant due to insufficient sample size This recurrent finding suggests that when considering and planning studies, CAM researchers may tend to over-estimate expected treatment effect sizes. When it is neither possible to specify an MID nor feasible to collect pilot data, researchers can make use of the published literature to derive plausible effect size estimates
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