Research Article| Volume 56, ISSUE 9, P833-842, September 2003

Intention-to-treat approach to data from randomized controlled trials: a sensitivity analysis


      The intention-to-treat (ITT) approach to randomized controlled trials analyzes data on the basis of treatment assignment, not treatment receipt. Alternative approaches make comparisons according to the treatment received at the end of the trial (as-treated analysis) or using only subjects who did not deviate from the assigned treatment (adherers-only analysis). Using a sensitivity analysis on data for a hypothetical trial, we compare these different analytical approaches in the context of two common protocol deviations: loss to follow-up and switching across treatments. In each case, two rates of deviation are considered: 10% and 30%. The analysis shows that biased estimates of effect may occur when deviation is nonrandom, when a large percentage of participants switch treatments or are lost to follow-up, and when the method of estimating missing values accounts inadequately for the process causing loss to follow-up. In general, ITT analysis attenuates between-group effects. Trialists should use sensitivity analyses on their data and should compare the characteristics of participants who do and those who do not deviate from the trial protocol. The ITT approach is not a remedy for unsound design, and imputation of missing values is not a substitute for complete, good quality data.


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        • Lee Y.J.
        • Ellenberg J.H.
        • Hirtz D.G.
        • et al.
        Analysis of clinical trials by treatment actually received: is it really an option?.
        Stat Med. 1991; 10: 1595-1605
        • Newell D.J.
        Intention-to-treat analysis: implications for quantitative and qualitative research.
        Int J Epidemiol. 1992; 21: 837-841
        • Gibaldi M.
        • Sullivan S.
        Intention-to-treat analysis in randomized trials: who gets counted?.
        J Clin Pharmacol. 1997; 37: 667-672
        • Murray G.D.
        • Findlay J.G.
        Correcting for the bias caused by drop-outs in hypertension trials.
        Stat Med. 1988; 7: 941-946
        • Peduzzi P.
        • Detre K.
        • Wittes J.
        • et al.
        Intent-to-treat analysis and the problem of crossovers.
        J Thorac Cardiovasc Surg. 1991; 101: 481-487
        • Heitjan D.F.
        Causal inference in a clinical trial: a comparative example.
        Control Clin Trials. 1999; 20: 309-318
        • Hollis S.
        • Campbell F.
        What is meant by intention to treat analysis? Survey of published randomised controlled trials.
        BMJ. 1999; 319: 670-674
        • Ruiz-Canela M.
        • Martı́nez-González M.A.
        • de Irala-Estévz J.
        Intention to treat analysis is related to methodological quality.
        BMJ. 2000; 320: 1007
        • Roland M.
        • Torgerson D.J.
        Understanding controlled trials: what are pragmatic trials?.
        BMJ. 1998; 316: 285
        • van der Linden S.
        • Bouter L.
        • Tugwell P.
        What are the minimal methodological requirements for a good trial?.
        in: Schlapbach P. Gerber N.J. Physiotherapy: controlled trials and facts. Karger, Basel1991: 1-8
        • Schwartz D.
        • Lellouch J.
        Explanatory and pragmatic attitudes in therapeutic trials.
        J Chronic Dis. 1967; 20: 637-648
        • Fisher L.D.
        • Dixon D.O.
        • Herson J.
        • et al.
        Intention to treat in clinical trials.
        in: Pearce K.E. Statistical issues in drug research and development. Marcel Dekker, New York1990: 331-350
        • Armitage P.
        • Berry G.
        • Matthews J.N.S.
        Statistical methods in medical research.
        4th ed. Blackwell Scientific Publications, Oxford2002
        • Altman D.G.
        Practical statistics for medical research.
        Chapman & Hall, London1991
        • Sim J.
        • Wright C.
        Research in health care: concepts, designs and methods.
        Stanley Thornes, Cheltenham (UK)2000
        • Rubin D.B.
        Inference and missing data.
        Biometrika. 1976; 63: 581-592
        • Lewis J.A.
        Statistical standards for protocols and protocol deviations.
        Recent Results Cancer Res. 1988; 111: 27-33
        • Gould A.L.
        A new approach to the analysis of clinical drug trials with withdrawals.
        Biometrics. 1980; 36: 721-727
        • Everitt B.S.
        Statistical methods for medical investigations.
        2nd ed. Edward Arnold, London1994
        • Heyting A.
        • Tolboom J.T.B.M.
        • Essers J.G.A.
        Statistical handling of drop-outs in longitudinal clinical trials.
        Stat Med. 1992; 11: 2043-2061
        • Little R.J.A.
        • Rubin D.B.
        Statistical analysis of data with missing values.
        Wiley, New York1987
        • Lewis J.A.
        • Machin D.
        Intention to treat: who should use it?.
        Br J Cancer. 1993; 68: 647-650
        • Miller M.E.
        • Morgan T.M.
        • Epseland M.A.
        • et al.
        Group comparisons involving missing data in clinical trials: a comparison of estimates and power (size) for some simple approaches.
        Stat Med. 2001; 20: 2383-2397
        • Little R.
        • Yau L.
        Intent-to-treat analysis for longitudinal studies with drop-outs.
        Biometrics. 1996; 52: 1324-1333
        • van Tulder M.W.
        • Assendelft W.J.J.
        • Koes B.W.
        • et al.
        Method guidelines for systematic reviews in the Cochrane Collaboration Back Review Group for spinal disorders.
        Spine. 1997; 22: 2323-2330
        • Staquet M.J.
        • Hays R.D.
        • Fayers P.M.
        Quality of life assessment in clinical trials.
        Oxford University Press, Oxford1998
        • Tabachnick B.G.
        • Fidell L.S.
        Using multivariate statistics.
        4th ed. Allyn and Bacon, Boston2001
        • Senn S.
        Cross-over trials in clinical research.
        John Wiley, Chichester1993
        • Montgomery D.C.
        Design and analysis of experiments.
        5th ed. Wiley, New York2001
        • Sheiner L.B.
        • Rubin D.B.
        Intention-to-treat analysis and the goals of clinical trials.
        Clin Pharmacol Ther. 1994; 57: 6-15
        • Chêne G.
        • Morlat P.
        • Leport C.
        • et al.
        Intention-to-treat vs. on-treatment analyses of clinical trial data: experience from a study of pyrimethamine in the primary prophylaxis of toxoplasmosis in HIV-infected patients.
        Control Clin Trials. 1998; 19: 233-248
        • Lachin J.M.
        Statistical considerations in the intent-to-treat principle.
        Control Clin Trials. 2000; 21: 167-189
        • Gillings D.
        • Koch G.
        The application of the principle of intention-to-treat to the analysis of clinical trials.
        Drug Inf J. 1991; 25: 411-424
        • Little R.J.A.
        • Rubin D.B.
        The analysis of social science data with missing values.
        Sociol Methods Res. 1990; 18: 292-326
        • Huisman M.
        Imputation of missing item responses: some simple techniques.
        Qual Quantity. 2000; 34: 331-351
        • Allison P.D.
        Missing data.
        Sage Publications, Thousand Oaks (CA)2002
        • Begg C.B.
        Ruminations on the intent-to-treat principle.
        Control Clin Trials. 2000; 21: 241-243
        • Schulz K.F.
        • Grimes D.A.
        Sample size slippages in randomized trials: exclusions and the lost and wayward.
        Lancet. 2002; 359: 781-785