How the EMERGE guideline on medication adherence can improve the quality of clinical trials

Abstract

Medication adherence in drug trials is suboptimal, affecting the quality of these studies and adding significant costs. Nonadherence in this setting can lead to null findings, unduly large sample sizes and the need for dose modification after a drug has been approved. Despite these drawbacks, adherence behaviours are not consistently measured, analysed or reported appropriately in trial settings. The ESPACOMP Medication Adherence Reporting Guideline (EMERGE) offers a solution by facilitating a sound protocol design that takes this crucial factor into account. This article summarises key evidence on traditional and newer measurements of adherence, discusses implementation in clinical trial settings and makes recommendations about the analysis and interpretation of adherence data. Given the potential benefits of this approach, the authors call on regulators and the pharmaceutical industry to endorse the EMERGE guideline.

Measuring and reporting treatment adherence: What can we learn by comparing two respiratory conditions?

“…For patients, research into acceptability and effect of adherence measurement is crucial. In clinical trials, knowledge about how adherence should be measured to best understand the relationship to clinical outcomes will allow better adjustment for patient adherence and better projections about expected prevalence of adverse events 145 . Finally, researchers must learn to most efficiently use systematic and consistent data sources such as medical records and DATs.…”

Electronic Monitoring Feedback for Improving Medication Adherence and Clinical Outcomes in Early Rheumatoid Arthritis: A Randomized Clinical Trial

“…Instead, all available data were presented as descriptive statistics on the primary and secondary study outcomes after 12 months (see Table 2). No significant differences were found between the intervention arm and the usual care arm after 12-month follow-up for the following variables: proportion of adherent patients measured with the CQR (mean difference: 1.3%, 95% CI −30.0; 30.0), medication adherence measured with the MMAS-8 ® (median sum score: 7 (6-7) and 7 (6-7), respectively; p=0.27), sum scale scores for necessity beliefs (median: 18 (17-21) and 19 (16)(17)(18)(19)(20), respectively; p=0.76), sum scale scores for concern beliefs (median: 14 (9-17) and 14 (12)(13)(14)(15)(16)(17), respectively; p=0.79), and necessity concern differential score (median: 4 (2-7) and 3 (2-6), respectively; p=0.56). Patients in the intervention arm tended to discontinue methotrexate earlier than patients in the usual care arm (median time in weeks: 15.7 (9.1-33.6) and 21.9 (19-28.4), respectively; p=0.31), whereas the median time to initiate a bDMARD tended to be shorter in the usual care arm than in the intervention arm (11.9 (5.7-22) and 17 (9.9-40.9), respectively; p=0.55).…”

“…Nevertheless, there is an ongoing debate on what measurement instruments and definitions for adherence outcomes should be used to accurately capture patients' medication-taking behavior. 4,17,[36][37][38][39] The first lesson learned relates to attrition rate after randomization in this RCT together with drug survival. Although attrition rates did not significantly differ between study arms, the overall attrition rate contributed to statistical power issues for detecting an intervention effect.…”

Digitally Enabled, Patient‐Centric Clinical Trials: Shifting the Drug Development Paradigm

“…In the event of an IND failing to demonstrate efficacy in a clinical trial, this technology can help mitigate questions as to whether this was due to lack of efficacy at the selected dose(s) or a result of medication nonadherence within the trial population. Finally, adherence has a substantial impact on study power; 33,34 therefore, a truer signal of adherence may lead to reduction in clinical study size. 35 At Merck & Co., Inc. (Kenilworth, NJ), we have performed clinical pilot testing with several smart dosing technologies of interest 36,37 and are proceeding with use of some of these technologies in IND trials, including trials in neuroscience, infectious disease, and cardiovascular disease therapeutic areas.…”

“…In the event of an IND failing to demonstrate efficacy in a clinical trial, this technology can help mitigate questions as to whether this was due to lack of efficacy at the selected dose(s) or a result of medication nonadherence within the trial population. Finally, adherence has a substantial impact on study power; 33,34 therefore, a truer signal of adherence may lead to reduction in clinical study size 35 …”