Research · Oct 23, 2026
Participant adherence: measurement, run-in and effect on the estimate
Concept
Adherence is the degree to which a participant follows the prescribed regimen. In drug trials it is often defined as intake of a predetermined fraction of the dose, for example 80%. Persistence is a different measure: the time a participant remains on treatment, regardless of the proportion of doses taken.
Definitions
- Crossover: a participant who follows the other group’s regimen.
- Drop-in: a control participant who starts following the intervention.
- Drop-out: an intervention participant who stops following it.
- Withdrawal: a participant who leaves the study and has no further follow-up.
A participant who stops study medication but keeps attending visits is not a withdrawal. That participant still contributes outcomes.
Effect on the estimate and on power
In an intention-to-treat analysis, low adherence dilutes the difference between groups. It underestimates both benefit and adverse effects. According to Friedman, to maintain power, a 20% reduction in adherence may require more than a 50% increase in sample size, and a 30% reduction may require doubling it. In noninferiority trials, dilution favors a conclusion of no difference (see noninferiority margin).
In COURAGE, 2,287 patients with stable coronary disease were randomized to PCI plus optimal medical therapy or medical therapy alone. According to Friedman, 46 of the 1,149 PCI patients never underwent the procedure, and 32.6% of the medical group were revascularized over a median of 4.6 years. The primary outcome did not differ (19.0% vs 18.5%; HR 1.05; 95% CI 0.87 to 1.27). The comparison becomes one between initial strategies.
Adherence is also associated with prognosis for reasons unrelated to treatment. Participants adherent to placebo have lower mortality (see CHARM and the healthy adherer effect). For this reason, analysis by level of adherence compares non-randomized groups.
Design factors
Short, supervised trials with simple regimens have better adherence. A review of studies using electronic monitoring showed an inverse relation between the number of daily doses and adherence. With four doses a day, on-schedule adherence was about 50%.
Run-in period
During a run-in, candidates receive placebo or active drug for weeks before randomization. Those who do not adhere or do not tolerate it are excluded.
In the Physicians’ Health Study, 33,223 eligible physicians entered an 18-week run-in. The 22,071 who had taken at least two thirds of their pills were randomized. Lang and colleagues estimated a 20 to 41% increase in adherence and a 34% reduction in sample size, with power equal to or higher than randomizing everyone.
An active run-in also excludes those with adverse effects. PARADIGM-HF had two consecutive run-ins, with enalapril and then sacubitril-valsartan. According to Friedman, about 20% of eligible patients were excluded, mostly for adverse events. The result answers the question for patients who tolerated both drugs.
Berger and colleagues showed that selection by run-in response changes the representation of subpopulations and affects external validity. Lee and colleagues compared 43 SSRI datasets in depression and found no difference in effect size between trials with and without a placebo run-in.
Measuring adherence
No single measure is complete.
- Pill count: simple, but assumes that pills not returned were taken. It tends to overestimate adherence.
- Electronic monitoring of package opening: records timing. In 4,783 hypertensive patients, Vrijens and colleagues showed that about half had stopped treatment within 1 year.
- Drug or metabolite assay: reflects only the last few days and does not apply to placebo.
- Physiological variables (LDL, blood pressure): useful for group data.
- Self-report: a participant who says the medication was not taken can be trusted.
Common errors when reading a paper
- Interpreting a neutral result without checking observed adherence against the adherence assumed in the sample size.
- Accepting an analysis by adherence as an estimate of the treatment effect.
- Confusing stopping medication with loss to follow-up.
- Applying to unselected patients the result of a trial whose run-in excluded intolerant patients.
- Reading noninferiority with low adherence as evidence of equivalence.
What to check when reading a trial
- Definition and method of measuring adherence.
- Adherence by group and over time, compared with that assumed in the design.
- Crossover rates in each direction.
- Presence of a run-in, its duration and the proportion excluded.
- Distinction between those who stopped medication and those who left follow-up.
- Use of concomitant therapies by group.
References
- Friedman LM, Furberg CD, DeMets DL, Reboussin DM, Granger CB. Fundamentals of Clinical Trials. 5th ed. Springer; 2015. Chapter 14, Participant Adherence.
- Boden WE, O’Rourke RA, Teo KK, et al. Optimal medical therapy with or without PCI for stable coronary disease. N Engl J Med. 2007;356:1503-16. doi: 10.1056/NEJMoa070829
- Claxton AJ, Cramer J, Pierce C. A systematic review of the associations between dose regimens and medication compliance. Clin Ther. 2001;23:1296-310. doi: 10.1016/s0149-2918(01)80109-0
- Lang JM, Buring JE, Rosner B, Cook N, et al. Estimating the effect of the run-in on the power of the Physicians’ Health Study. Stat Med. 1991;10:1585-93. doi: 10.1002/sim.4780101010
- McMurray JJ, Packer M, Desai AS, Gong J, et al. Angiotensin-neprilysin inhibition versus enalapril in heart failure. N Engl J Med. 2014;371:993-1004. doi: 10.1056/NEJMoa1409077
- Berger VW, Rezvani A, Makarewicz VA. Direct effect on validity of response run-in selection in clinical trials. Control Clin Trials. 2003;24:156-66. doi: 10.1016/s0197-2456(02)00316-1
- Lee S, Walker JR, Jakul L, Sexton K. Does elimination of placebo responders in a placebo run-in increase the treatment effect in randomized clinical trials? A meta-analytic evaluation. Depress Anxiety. 2004;19:10-9. doi: 10.1002/da.10134
- Vrijens B, Vincze G, Kristanto P, Urquhart J, et al. Adherence to prescribed antihypertensive drug treatments: longitudinal study of electronically compiled dosing histories. BMJ. 2008;336:1114-7. doi: 10.1136/bmj.39553.670231.25