The value of adherence information during clinical pharmaceutical trials. (June 2022)

• Record Type: Journal Article
• Authors: Grayek, Emily N; Fischhoff, Baruch; Davis, Alexander L; Krishnamurti, Tamar
• Is Part Of: Clinical trials. Volume 19:Number 3(2022)
• Page Start: 326
• Page End: 336
• Publication Date: 2022-06
• Subjects: Adherence monitoring -- simulation -- trial enrichment -- clinical trial design -- cost-effectiveness -- digital medicine -- FDA; 615.5072405
• DOI: 10.1177/17407745221084127
• Languages: English
• ISSNs: 1740-7745

Abstract

Background/Aims: The quality of the evidence used to evaluate a drug's safety and efficacy depends, in part, on how well participants adhere to the prescribed drug-taking regime. There are multiple approaches to measure adherence in clinical trials, varying in their cost and accuracy. We demonstrate a method for evaluating the cost-effectiveness of common adherence monitoring methods, considering the costs and data quality for drugs that differ in how forgiving they are of nonadherence. Methods: We propose a simulation approach to estimate the value of evidence about adherence, considering both costs of collection and potential errors in interpreting clinical trial results. We demonstrate the approach with a simulated clinical trial of nitrendipine, a common calcium channel blocker. We consider two trial designs, one using pretrial adherence to "enrich" the trial sample and one without an enrichment strategy. We use scenarios combining high and low values of two key properties of a clinical trial: participant adherence and drug forgiveness. Results: Under the conditions of these simulations, the most cost-effective adherence monitoring approach depends on both trial participant adherence and drug forgiveness. For example, the enrichment strategy is not cost-effective for the base scenario (high forgiveness and high adherence), but is for other scenarios. We also estimate the effects of evaluable patient analysis, a controversial procedure that excludes nonadherent participants from the analyses, after a trial is completed. Conclusions: Our proposed approach can guide drug regulators and developers in designing efficient clinical trials and assessing the impact of nonadherence on trial results. It can identify cost-effective adherence-monitoring methods, given available knowledge about the methods, drug, and patients' expected adherence.