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, log in to check access.
Buy single article
Instant unlimited access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Efron B. Foreword: Limburg Compliance Symposium. Stat Med. 1998;17:249–250.
Tsiatis A. Methodological issues in AIDS clinical trials. Intent-to-treat analysis. J Acquir Immune Defic Syndr. 1990;3 Suppl 2:S120–S123.
Rubin DB. More powerful randomization-based P-values in double-blind trials with noncompliance. Stat Med. 1998;17:371–385.
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.
Robins JM. Correction for noncompliance in equivalence trials. Stat Med. 1998;17:269–302.
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.
Miller FG. Placebo-controlled trials in psychiatric research: An ethical perspective. Biological Psychiatry. 2000;47:707–716.
Lavori PW. Placebo controls in randomized treatment trials: A statistician’s perspective. Biological Psychiatry. 2000;47:717–723.
Lavori PW. Clinical trials in psychiatry: should protocol deviation censor patient data? Neuropsycho-pharmacol. 1992;6(1):39–47.
Little R, Rubin D. Statistical Analysis with Missing Data. New York, NY: Wiley; 1987.
Lavori PW, Dawson R, Shera D. A multiple imputation strategy for clinical trials with truncation of patient data. Stat Med. 1995;14:1913–1925.
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.
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.
Lavori PW, Dawson R, Rush AJ. Flexible treatment strategies in chronic disease: clinical and research implications. Biological Psychiatry. 2000;48:604–614.
Rothman KJ, Michels KB. The continued unethical use of placebo controls. New Eng J Med. 1994;31(6): 394–398.
Leber PD. Hazards of inference: The active control investigation. Epilepsia. 1989;30(Suppl 1):S57–S63.
Supported by a grant from the National Institute of Mental Health (R01-MH51481) to Stanford University.
About this article
Cite this article
Lavori, P.W., Dawson, R. Designing for Intent-to-Treat. Ther Innov Regul Sci 35, 1079–1086 (2001). https://doi.org/10.1177/009286150103500405
- Adaptive treatments