Evidence map›Paper›PMID 42867630›Full record

ReviewTherapeutic innovation & regulatory science2026

Protecting Trial Integrity Through Monitoring and Analysis of Medication Adherence.

Bernard Vrijens, Bruce Binkowitz, Els Goetghebeur, Richard C Zink, Rakhi Kilaru, Garrick Wallstrom

Abstract readReview
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In one paragraph

Review in Therapeutic innovation & regulatory science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Bernard VrijensAARDEX Group, Seraing, Belgium.ORCID http://orcid.org/0000-0002-9090-1253
Bruce BinkowitzArcutis Biotherapeutics Inc., Westlake Village, California, United States.
Els GoetghebeurGhent University, Ghent, Belgium.
Richard C ZinkJMP Statistical Discovery LLC, Cary, North Carolina, United States.
Rakhi KilaruThermo Fisher Scientific, Waltham, Massachusetts, United States.
Garrick WallstromThermo Fisher Scientific, Waltham, Massachusetts, United States. Garrick.Wallstrom@thermofisher.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To better inform patient and physician decisions, it is vital to clearly describe a medication's efficacy and safety, acknowledging that drug exposure may vary due to suboptimal patient adherence to medication schedules. ICH E9(R1) sets out the expectation that randomized controlled trials prespecify an estimand aligned with such research objectives. This involves specifying a well-defined population and anticipation of intercurrent events.Lack of medication adherence, including treatment interruptions and treatment discontinuation, are intercurrent events that complicate the interpretation of all efficacy, safety, and pharmacokinetic data, as well as the interpretation of corresponding estimands and estimated treatment effects. Under a treatment policy strategy, the treatment effect averages over the consequences of adherence-related events occurring under each randomized treatment condition; non-adherence is therefore part of the effect being estimated rather than explicitly acknowledged. However, transportability of resulting effectiveness will still depend on adherence patterns. Equally, our derived understanding of underlying treatment efficacy and its potential under alternative assignment mechanisms depends on adherence.Therefore, adopting a standardized framework for identifying, reporting, interpreting, and limiting lack of medication adherence is essential in explanatory clinical trials. This may need precise measurement methods to avoid biases inherent in traditional methods like pill counts and self-reports, and reliably recognize cases of excessive non-adherence affecting the drug's biological effects. Unanticipated medication non-adherence must be treated as a key risk area within any risk-based quality management (RBQM) framework. Integrating adherence-related risk assessments into quality-by-design processes, monitoring plans, and data review strategies enables early identification and mitigation of adherence issues that could compromise the validity of trial findings.Electronically compiling real-time dosing data surpasses traditional methods in reliability and comprehensiveness and improves the credibility of trial designs. Especially with adaptive components requiring critical decisions from small samples, addressing adherence in interim analyses can prevent premature trial termination. It facilitates pre-specified post-trial analyses of adherence to better understand failures and guides future development. Adherent patients require smaller sample sizes through reduced variance and increased effect size, assuming they represent the target population.

Indexed as

Clinical TrialsDose- Exposure- ResponseDose FindingDrug ExposureMedication AdherencePatient Compliance

Identifiers

PMID42867630

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.