Predicting Medication Adherence in Stroke Clinical Trials May Boost Patient Retention

Enrollment recently completed in 20 clinical trials of stroke prevention and recovery therapeutics, according to data and analytics provider GlobalData. As challenging as it is to find participants for these studies, equally important is ensuring that every participant successfully completes the trial as designed. New improvements in using AI-assisted dosing to understand medication adherence could make the task of patient retention easier.

A review of large stroke trials found the rate of premature and permanent discontinuation ranged from 10% to 34% (mean 18%) and was higher for participants in the active treatment groups in most studies.1

When study participants don’t take medication as directed it can be an early warning sign of discontinuation; knowing the factors that negatively impact patient retention is a powerful motivator for exploring methods that use medication adherence behavior to forecast who will drop out of a trial and who will stay in.

At AiCure, predictive adherence models built into our clinical development software enable sponsors to understand which participants will continue to follow the dosing protocol over the course of the study. Download this infographic to learn more.

AiCure and New York Hospital examine adherence to direct oral anticoagulants

To assess and optimize drug adherence in a stroke population, AiCure partnered with New York’s Montefiore Medical Center to run a study in 28 elderly participants over the course of 12 weeks and compare the use of the AiCure platform to standard of care for medication adherence, which was pill counts.

In clinical trials of stroke prevention and recovery therapeutics, medication adherence is a critical component of anticoagulation therapy.2 When anticoagulation is indicated for stroke prevention, strict adherence to warfarin has been shown to be highly effective. The introduction of direct oral anticoagulants (DOACs), while reducing the need for regular monitoring in an elderly and sick patient population, also places pressure on patients to self-manage and be fully adherent.

Elderly patients who are discharged home after a stroke are at high risk of medication non-adherence and discontinuation of therapy. Regular monitoring of INR levels in patients prescribed warfarin allows for suboptimal adherence rates to be detected in a timely manner. Often, however, suboptimal rates of adherence to DOACs go undetected, placing high-risk patients at increased risk of stroke.

In the AiCure-Montefiore study, participants on warfarin as well as an oral anticoagulant, as well as those only on an oral anticoagulant, demonstrated adherence using the AiCure app was significantly higher than in the control group. The AiCure platform drove 100% medication adherence in this population whereas in the control group medication adherence was at 50% and even lower.

View this video to learn more about the work by AiCure and Montefiore Medical Center.

Please contact us today to see how you can improve your medication adherence and participant retention.

1 Kiran A, et al. Adherence to study drug in a stroke prevention trial. J Stroke Cerebrovasc Dis. 2020.

2 Labovitz D, Shafner L, Virmani D, Hanina A. Using Artificial Intelligence to Measure and Optimize Adherence in Patients on Anticoagulation Therapy. iproc 2016;2(1):e33 URL:https://www.iproc.org/2016/1/e33 DOI: 10.2196/iproc.6201