Designing for Intent-to-Treat


The principle of analysis by intent-to- treat (ITT) serves as the standard basis for design decisions as well as choice of analysis in clinical trials. ITT correctly contrasts the pragmatic consequences of the treatments offered in a study, as long as the study protocol accurately reflects the realities of clinical practice. We identify the study of ongoing treatment for chronic disease as the clinical context that most strains the ITT principle. In a placebo-controlled trial of a new drug in patients with a condition for which there are standard treatments, the ethical requirement to “rescue” patients who do poorly, and who might be taking placebo, causes “drop-in” from placebo to a standard treatment. We propose that this problem reflects a lack of fit between the standard fixed design and clinical reality, rather than a weakness of ITT. We propose that the adaptive nature of clinical decision making should be captured in the design of trials, and we show how the ITT principle can be used in such designs.

This is a preview of subscription content, access via your institution.


  1. 1.

    Efron B. Foreword: Limburg Compliance Symposium. Stat Med. 1998;17:249–250.

    Article  Google Scholar 

  2. 2.

    Tsiatis A. Methodological issues in AIDS clinical trials. Intent-to-treat analysis. J Acquir Immune Defic Syndr. 1990;3 Suppl 2:S120–S123.

    PubMed  Google Scholar 

  3. 3.

    Rubin DB. More powerful randomization-based P-values in double-blind trials with noncompliance. Stat Med. 1998;17:371–385.

    CAS  Article  Google Scholar 

  4. 4.

    Robins JM, Tsiatis AA. Correcting for noncompliance in randomized trials using rank-preserving structural failure time models. Comm in Stat A. 1991; 20:2609–2631.

    Article  Google Scholar 

  5. 5.

    Robins JM. Correction for noncompliance in equivalence trials. Stat Med. 1998;17:269–302.

    CAS  Article  Google Scholar 

  6. 6.

    Goetghebeur E, Molenberghs G. Causal inference in a placebo-controlled clinical trial with binary outcome and ordered compliance. J Am Stat Assoc. 1996;91:444–447.

    Article  Google Scholar 

  7. 7.

    Miller FG. Placebo-controlled trials in psychiatric research: An ethical perspective. Biological Psychiatry. 2000;47:707–716.

    CAS  Article  Google Scholar 

  8. 8.

    Lavori PW. Placebo controls in randomized treatment trials: A statistician’s perspective. Biological Psychiatry. 2000;47:717–723.

    CAS  Article  Google Scholar 

  9. 9.

    Lavori PW. Clinical trials in psychiatry: should protocol deviation censor patient data? Neuropsycho-pharmacol. 1992;6(1):39–47.

    CAS  Google Scholar 

  10. 10.

    Little R, Rubin D. Statistical Analysis with Missing Data. New York, NY: Wiley; 1987.

    Google Scholar 

  11. 11.

    Lavori PW, Dawson R, Shera D. A multiple imputation strategy for clinical trials with truncation of patient data. Stat Med. 1995;14:1913–1925.

    CAS  Article  Google Scholar 

  12. 12.

    Lavori PW, Wagner TH, Feussner JR. Ethics and economics in placebo-controlled trials of new drugs for mood disorders. Economics Neuroscience. 2000; 2(9):44–48.

    Google Scholar 

  13. 13.

    Lavori PW, Dawson R. A design for testing clinical strategies: Biased-coin adaptive within-subject randomization. J Roy Stat Society Series A. 2000; 163(1):29–38.

    Article  Google Scholar 

  14. 14.

    Lavori PW, Dawson R, Rush AJ. Flexible treatment strategies in chronic disease: clinical and research implications. Biological Psychiatry. 2000;48:604–614.

    Article  Google Scholar 

  15. 15.

    Rothman KJ, Michels KB. The continued unethical use of placebo controls. New Eng J Med. 1994;31(6): 394–398.

    Article  Google Scholar 

  16. 16.

    Leber PD. Hazards of inference: The active control investigation. Epilepsia. 1989;30(Suppl 1):S57–S63.

    Article  Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Philip William Lavori PhD.

Additional information

Supported by a grant from the National Institute of Mental Health (R01-MH51481) to Stanford University.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Lavori, P.W., Dawson, R. Designing for Intent-to-Treat. Ther Innov Regul Sci 35, 1079–1086 (2001).

Download citation

Key Words

  • Intent-to-treat
  • Design
  • Adaptive treatments