Skip to main content

Advertisement

SpringerLink
Log in

Accounting for Noncompliance in the Design of Clinical Trials

  • Published:
Drug information journal : DIJ / Drug Information Association Aims and scope Submit manuscript

Abstract

Patient noncompliance with study regimens may greatly impact the interpretation of results from randomized clinical trials. Although much has been written about issues related to noncompliance, there has been little done to provide an overall framework for designing efficacy trials in a way that accommodates possible noncompliance. This paper is intended to help fill this gap. First, decisions directly related to the randomized treatment comparison, such as sample size and the number of study arms, are discussed. Next, the secondary or observational component of the design involving compliance monitoring is examined. Alternative methods for monitoring compliance, with their relative advantages and disadvantages, are reviewed. Subsampling of patients to be monitored, and the construction of a compliance score, are also addressed. Much work remains in developing and understanding methods of analysis that incorporate compliance data; nevertheless, compliance information may be crucial for optimizing the use of drugs in clinical practice and in developing more effective therapeutic regimens.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Schwartz D, Lellouch J. Explanatory and pragmatic attitudes in therapeutic trials. J Chronic Dis. 1967;20:637–648.

    Article  CAS  Google Scholar 

  2. Haynes RB, Dantes R. Patient compliance and the conduct and interpretation of therapeutic trials. Control Clin Trials. 1987;8:12–19.

    Article  CAS  Google Scholar 

  3. Friedman LM, Furberg CD, DeMets DL. Fundamentals of Clinical Trials. St. Louis, MO: Mosby-Year Book, Inc; 1985.

    Google Scholar 

  4. Foulkes MA, Ellenberg SS. Large, simple trials of HIV therapies. In: Finkelstein DM, Schoenfeld DA, Eds. AIDS Clinical Trials. New York, NY. Wiley-Liss, Inc; 1995.

    Google Scholar 

  5. Pullar T. Compliance with drug therapy. Br J Clin Pharmacol. 1991;32:535–539.

    Article  CAS  Google Scholar 

  6. Ellenberg SS, Finkelstein DM, Schoenfeld DA. Statistical issues arising in AIDS clinical trials (with comments and rejoinder). J Am Stat Assoc. 1992;87:562–583.

    Article  Google Scholar 

  7. Freedman LS. The effect of partial noncompliance on the power of a clinical trial. Control Clin Trials. 1990;11:157–168.

    Article  CAS  Google Scholar 

  8. Lachin JM. Introduction to sample size determination and power analysis for clinical trials. Control Clin Trials. 1981;2:93–114.

    Article  CAS  Google Scholar 

  9. Lachin JM, Foulkes MA. Evaluation of sample size and power for analysis of survival with allowance for nonuniform patient entry, losses to follow-up, noncompliance, and stratification. Biometrics. 1986;42:507–519.

    Article  CAS  Google Scholar 

  10. Pledger GW. Compliance in clinical trials: impact on design, analysis, and interpretation. In: Schmidt D, Leppik IE, Eds. Compliance in Epilepsy. Amsterdam: Elsevier Science Publishers BV; 1988.

    Google Scholar 

  11. Eisen SA, Miller DK, Woodward RS, Spitznagel E, Pryzbeck TR. The effect of prescribed daily dose frequency on patient medication compliance. Arch Intern Med. 1990;150:1881–1884.

    Article  CAS  Google Scholar 

  12. Taggart AJ, Johnson GD, McDevitt DG. Does the frequency of daily dosage influence compliance with digoxin therapy? Br J Clin Pharmacol. 1991;1:31–34.

    Google Scholar 

  13. Lang J. The use of a run-in to enhance compliance. Stat Med. 1990;9:87–95.

    Article  CAS  Google Scholar 

  14. Brittain E, Wittes J. The run-in period in clinical trials: the effect of misclassification on efficiency. Control Clin Trials. 1990;11:327–338.

    Article  CAS  Google Scholar 

  15. Fletcher SW, Pappius EM, Harper SJ. Measurement of medication compliance in a clinical setting. Arch Intern Med. 1979;139:635–638.

    Article  CAS  Google Scholar 

  16. Cramer JA. Overview of methods to measure and enhance patient compliance. In: Cramer JA, Spilker B, Eds. Patient Compliance in Medical Practice and Clinical Trials. New York, Raven Press; 1991.

    Google Scholar 

  17. Kruse W, Nikolaus T, Rampmaier J, Weber E, Schlierf G. Actual versus prescribed timing of lovastatin doses assessed by electronic compliance monitoring. Eur J Clin Pharmacol. 1993;45:211–215.

    Article  CAS  Google Scholar 

  18. Young LM, Haakenson CM, Lee KK, van Eeckhout JR Riboflavin use as a drug marker in Veterans Administration cooperative studies. Control Clin Trials. 1984;5:497–504.

    Article  CAS  Google Scholar 

  19. Hardy E, Kumar S, Peaker S, Feely M, Pullar T. A comparison of a short half-life marker (low-dose isoniazid), a long half-life pharmacological indicator (low-dose phenobarbitone) and measurements of a controlled release ‘therapeutic drug’ (metroprolol, Meteros) in reflecting compliance by volunteers. Br J Clin Pharmacol. 1990;30:437–441.

    Article  CAS  Google Scholar 

  20. Pullar T, Kumar S, Chrystyn H, Rice P, Peaker S, Feely M. The prediction of steady-state plasma phenobarbitone concentrations (following low-dose phenobarbitone) to refine its use as an indicator of compliance. Br J Clin Pharmacol. 1991;32:329–333.

    Article  CAS  Google Scholar 

  21. Richardson D, Liou S-H, Kahn JO. Uric acid and didanosine compliance in AIDS clinical trials: an analysis of AIDS Clinical Trials Group protocols 116A and 116B/117. J Acquir Immune Defic Syndr. 1993;6:1212–1223.

    CAS  Google Scholar 

  22. Pullar T, Kumar S, Tindall H, Feely M. Time to stop counting the tablets? Clin Pharmacol Ther. 1989;46:163–168.

    Article  CAS  Google Scholar 

  23. Kish L. Survey Sampling. New York, NY, John Wiley & Sons; 1965.

    Google Scholar 

  24. Coronary Drug Research Group. Influence of adherence to treatment and response of cholesterol on mortality in the Coronary Drug Project. N Engl J Med. 1980;302:1038–1041.

    Article  Google Scholar 

  25. Peduzzi P, Wittes J, Detre K, Holford T. Analysis as-randomized and the problem of nonadherence: an example from the Veterans Affairs randomized trial of coronary artery bypass surgery. Stat Med. 1993; 12:1185–1195.

    Article  CAS  Google Scholar 

  26. Lagakos SW, Lim LL-Y, Robins JM. Adjusting for early treatment termination in comparative clinical trials. Stat Med. 1990;9:1417–1424.

    Article  CAS  Google Scholar 

  27. Mark SD, Robins JM. A method for the analysis of randomized trials with compliance information: an application to the multiple risk factor intervention trial. Control Clin Trials. 1993;14:79–97.

    Article  CAS  Google Scholar 

  28. Robins JM, Tsiatis AA. Correcting for non-compliance in randomized trials using rank preserving structural failure time models. Comm Stat—Theory Methods. 1991;20:2609–2631.

    Article  Google Scholar 

  29. Efron B, Feldman D. Compliance as an explanatory variable in clinical trials. J Am Stat Assoc. 1991;86:9–26.

    Article  Google Scholar 

  30. Albert JM, DeMets DL. On a model-based approach to estimating efficacy in clinical trials. Stat Med. 1995;13:2323–2335.

    Article  Google Scholar 

  31. Newcombe RG. Explanatory and pragmatic esti-mates of the treatment effect when deviations from allocated treatment occur. Stat Med. 1988;7:1179–1186.

    Article  CAS  Google Scholar 

  32. Sommer A, Zeger SL. On estimating efficacy from clinical trials. Stat Med. 1991;10:45–52.

    Article  CAS  Google Scholar 

  33. Dixon DO, Albert JM. Issues in the design and analysis of AIDS clinical trials. In: Thall PF, Ed. Recent Advances in Clinical Trial Design and Analysis. Norwell, A: Kluwer Academic Publishers; 1995.

    Google Scholar 

  34. Lee YJ, Ellenberg JH, Hirtz DG, Nelson KB. Analysis of clinical trials by treatment actually received: is it really an option? Stat Med. 1991;10:1595–1605.

    Article  CAS  Google Scholar 

  35. May GS, DeMets DL, Friedman LM, et al. The randomized clinical trial: bias in analysis. Circulation. 1981;64:669–673.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Biostatistics Research Branch, Division of AIDS, National Institute of Allergy and Infectious Diseases, 6003 Executive Blvd., Rm 2A38, Bethesda, MD, 20892-7620, USA

    Jeffrey M. Albert PhD (Mathematical Statistician)

Authors
  1. Jeffrey M. Albert PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Albert, J.M. Accounting for Noncompliance in the Design of Clinical Trials. Ther Innov Regul Sci 31, 157–165 (1997). https://doi.org/10.1177/009286159703100123

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1177/009286159703100123

Key Words

Search

Navigation