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Estimating Absolute Risks in the Presence of Nonadherence: An Application to a Follow-up Study With Baseline Randomization

Toh, Sengweea; Hernández-Díaz, Soniaa; Logan, Rogera; Robins, James M.a,b; Hernán, Miguel A.a,c

doi: 10.1097/EDE.0b013e3181df1b69
Methods: Original Article

The intention-to-treat (ITT) analysis provides a valid test of the null hypothesis and naturally results in both absolute and relative measures of risk. However, this analytic approach may miss the occurrence of serious adverse effects that would have been detected under full adherence to the assigned treatment. Inverse probability weighting of marginal structural models has been used to adjust for nonadherence, but most studies have provided only relative measures of risk. In this study, we used inverse probability weighting to estimate both absolute and relative measures of risk of invasive breast cancer under full adherence to the assigned treatment in the Women's Health Initiative estrogen-plus-progestin trial. In contrast to an ITT hazard ratio (HR) of 1.25 (95% confidence interval [CI] = 1.01 to 1.54), the HR for 8-year continuous estrogen-plus-progestin use versus no use was 1.68 (1.24 to 2.28). The estimated risk difference (cases/100 women) at year 8 was 0.83 (−0.03 to 1.69) in the ITT analysis, compared with 1.44 (0.52 to 2.37) in the adherence-adjusted analysis. Results were robust across various dose-response models. We also compared the dynamic treatment regimen “take hormone therapy until certain adverse events become apparent, then stop taking hormone therapy” with no use (HR = 1.64; 95% CI = 1.24 to 2.18). The methods described here are also applicable to observational studies with time-varying treatments.

From the Departments of aEpidemiology, bBiostatistics, Harvard School of Public Health, Boston, MA; and cHarvard-MIT Division of Health Sciences and Technology, Boston, MA.

Submitted 19 July 2009; accepted 4 January 2010.

Supported and partially funded by National Institutes of Health (NIH) grant R01 HL080644–01.

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Correspondence: Sengwee Darren Toh, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, 133 Brookline Avenue 6th Floor, Boston, MA 02215. E-mail: darrentoh@post.harvard.edu.

© 2010 Lippincott Williams & Wilkins, Inc.