Statistical power considerations in genotype-based recall randomized controlled trials

Abstract

Randomized controlled trials (RCT) are often underpowered for validating gene-treatment interactions. Using published data from the Diabetes Prevention Program (DPP), we examined power in conventional and genotype-based recall (GBR) trials. We calculated sample size and statistical power for gene-metformin interactions (vs. placebo) using incidence rates, gene-drug interaction effect estimates and allele frequencies reported in the DPP for the rs8065082 SLC47A1 variant, a metformin transported encoding locus. We then calculated statistical power for interactions between genetic risk scores (GRS), metformin treatment and intensive lifestyle intervention (ILI) given a range of sampling frames, clinical trial sample sizes, interaction effect estimates, and allele frequencies; outcomes were type 2 diabetes incidence (time-to-event) and change in small LDL particles (continuous outcome). Thereafter, we compared two recruitment frameworks: GBR (participants recruited from the extremes of a GRS distribution) and conventional sampling (participants recruited without explicit emphasis on genetic characteristics). We further examined the influence of outcome measurement error on statistical power. Under most simulated scenarios, GBR trials have substantially higher power to observe gene-drug and gene-lifestyle interactions than same-sized conventional RCTs. GBR trials are becoming popular for validation of gene-treatment interactions; our analyses illustrate the strengths and weaknesses of this design.

Quality of dietary fat and genetic risk of type 2 diabetes: individual participant data meta-analysis

“…Moreover, the design and implementation of new studies, such as genotype-based recall clinical trials intended for the investigation of genetic and lifestyle interactions, with more accurate objective measurement of diet are required to better understand the interplay between genetic and lifestyle factors on the risk of type 2 diabetes. 54 …”

Gene-lifestyle interplay in type 2 diabetes

“…Furthermore, the careful integration of these more detailed exposure measures with multi-omics data (epigenomics, transcriptomics, proteomics metabolomics or metagenomics) [52 •• ], is likely to be necessary if we are to understand the complexities of gene × lifestyle interactions, and translate this knowledge into clinical action. Moreover, the application of cutting-edge technologies to biomaterials from historical cohorts, whilst powerful in many ways, requires the design and implementation of new studies, intended specifically for the investigation of gene × lifestyle interactions; such studies are likely to include genotype-based recall clinical trials [53].…”

Genotype-Based Recall Studies in Complex Cardiometabolic Traits

“…The vast majority of published GBR studies have focused on elucidating how genetic variants manifest phenotypically. Other forms of GBR have looked to assess the causal impact of specific risk factors and also to enhance trial design through informed participant selection 2, 3 . More than a dozen GBR studies focusing on cardiometabolic traits have been reported in the past two decades 4–20 with contrasting genetic characteristics, with the PPARG Pro12Ala variant (rs1801282) being the single most extensively studied locus.…”