Literature DB >> 33258096

Assessing the Scope and Predictors of Intentional Dose Non-adherence in Clinical Trials.

Kenneth Getz1, Zachary Smith2, Laura Shafner3, Adam Hanina3.   

Abstract

BACKGROUND: Although there is broad agreement that the accurate estimation of non-adherence rates in clinical trials is essential to determining the dose-response relationship, treatment safety and efficacy effects, no accurate estimates have ever been produced.
METHODS: This study used a novel platform combining artificial intelligence and virtual patient monitoring to identify and quantify the scope of unreported intentional non-adherence in clinical trials of new medical therapies. Nearly 260,000 observations were drawn from a convenience sample of 2976 study volunteers participating in 23 clinical trials of psychiatric, neurological and neuromuscular diseases.
RESULTS: The results indicate that 4% of all confirmed doses were intentionally non-adherent, 48% of all study volunteers had at least one intentionally non-adherent dose and 5% of study volunteers were intentionally non-adherent for more than one-third of all doses required.
CONCLUSIONS: Several factors were associated with, and predictive of, unreported intentional non-adherence including clinical trial phase; clinical trial duration; geographic location where the study was conducted; and investigative site enrollment volume. The findings also show that although the overall rate of intentional non-adherence does not change over the course of a clinical trial, study volunteers who deliberately chose not to take their first dose had a mean intentional non-adherence rate five times higher than that observed among those who were first dose adherent. Implications of the study results are discussed.

Entities:  

Keywords:  Data quality; Dose adherence; Dose response; Investigational drug safety; Modeling behavior; Non-adherence; Treatment effect size

Mesh:

Year:  2020        PMID: 33258096     DOI: 10.1007/s43441-020-00155-x

Source DB:  PubMed          Journal:  Ther Innov Regul Sci        ISSN: 2168-4790            Impact factor:   1.778


  1 in total

Review 1.  Technology for Measuring and Monitoring Treatment Compliance Remotely.

Authors:  Richard H Christie; Anzar Abbas; Vidya Koesmahargyo
Journal:  J Parkinsons Dis       Date:  2021       Impact factor: 5.568

  1 in total

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