Assessing heterogeneity of treatment effect analyses in health-related cluster randomized trials: A systematic review

Monique Anderson Starks, Gillian D Sanders, Remy Rene Coeytaux, Isaretta L Riley, Larry R Jackson, Amanda McBroom Brooks, Kevin L Thomas, Kingshuk Roy Choudhury, Robert M Califf and Adrian F Hernandez

PLOS ONE, 2019, vol. 14, issue 8, 1-13

Abstract: Background: Cluster-randomized trials (CRTs) are being increasingly used to test a range of interventions, including medical interventions commonly used in clinical practice. Policies created by the NIH and the Food and Drug Administration (FDA) require the reporting of demographics and the examination of demographic heterogeneity of treatment effect (HTE) for individually randomized trials. Little is known about how frequent demographics are reported and HTE analyses are conducted in CRTs. Objectives: We sought to understand the prevalence of HTE analyses and the statistical methods used to conduct them in CRTs focused on treating cardiovascular disease, cancer, and chronic lower respiratory diseases. Additionally, we also report on the proportion of CRTs that reported on baseline demographics of its populations and conducted demographic HTE analyses. Data sources: We searched PubMed and Embase for CRTs published between 1/1/2010 and 3/29/2016 that focused on treating the top 3 Center for Disease Control causes of death (cardiovascular disease, chronic lower respiratory disease, and cancer). Results: Age and sex were reported in greater than 95.3% of CRTs, while race and ethnicity were reported in only 20.3% of CRTs. HTE analyses were conducted in 28.1% (n = 18) of included CRTs and 77.8% (n = 12) were prespecified analyses. Four CRTs conducted a demographic subgroup analysis. Only 6/18 CRTs used interaction testing to determine whether HTE existed. Conclusions: Baseline demographic reporting was high for age and sex in CRTs, but was uncommon for race and ethnicity. HTE analyses were uncommon and was rare for demographic subgroups, which limits the ability to examine the extent of benefits or risks for treatments tested with CRT designs.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0219894

DOI: 10.1371/journal.pone.0219894

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