Literature DB >> 20526200

Estimating absolute risks in the presence of nonadherence: an application to a follow-up study with baseline randomization.

Sengwee Toh1, Sonia Hernández-Díaz, Roger Logan, James M Robins, Miguel A Hernán.   

Abstract

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.

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Year:  2010        PMID: 20526200      PMCID: PMC3315056          DOI: 10.1097/EDE.0b013e3181df1b69

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


  28 in total

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Journal:  Stat Med       Date:  2001-08-15       Impact factor: 2.373

2.  Correcting for noncompliance and dependent censoring in an AIDS Clinical Trial with inverse probability of censoring weighted (IPCW) log-rank tests.

Authors:  J M Robins; D M Finkelstein
Journal:  Biometrics       Date:  2000-09       Impact factor: 2.571

3.  Marginal structural models and causal inference in epidemiology.

Authors:  J M Robins; M A Hernán; B Brumback
Journal:  Epidemiology       Date:  2000-09       Impact factor: 4.822

4.  Outcomes ascertainment and adjudication methods in the Women's Health Initiative.

Authors:  J David Curb; Anne McTiernan; Susan R Heckbert; Charles Kooperberg; Janet Stanford; Michael Nevitt; Karen C Johnson; Lori Proulx-Burns; Lisa Pastore; Michael Criqui; Sandra Daugherty
Journal:  Ann Epidemiol       Date:  2003-10       Impact factor: 3.797

5.  Adjusted survival curves with inverse probability weights.

Authors:  Stephen R Cole; Miguel A Hernán
Journal:  Comput Methods Programs Biomed       Date:  2004-07       Impact factor: 5.428

6.  A structural approach to selection bias.

Authors:  Miguel A Hernán; Sonia Hernández-Díaz; James M Robins
Journal:  Epidemiology       Date:  2004-09       Impact factor: 4.822

7.  Causal inference from longitudinal studies with baseline randomization.

Authors:  Sengwee Toh; Miguel A Hernán
Journal:  Int J Biostat       Date:  2008-10-19       Impact factor: 0.968

8.  On the treatment of grouped observations in life studies.

Authors:  W A Thompson
Journal:  Biometrics       Date:  1977-09       Impact factor: 2.571

9.  Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women's Health Initiative randomized controlled trial.

Authors:  Jacques E Rossouw; Garnet L Anderson; Ross L Prentice; Andrea Z LaCroix; Charles Kooperberg; Marcia L Stefanick; Rebecca D Jackson; Shirley A A Beresford; Barbara V Howard; Karen C Johnson; Jane Morley Kotchen; Judith Ockene
Journal:  JAMA       Date:  2002-07-17       Impact factor: 56.272

10.  Influence of estrogen plus progestin on breast cancer and mammography in healthy postmenopausal women: the Women's Health Initiative Randomized Trial.

Authors:  Rowan T Chlebowski; Susan L Hendrix; Robert D Langer; Marcia L Stefanick; Margery Gass; Dorothy Lane; Rebecca J Rodabough; Mary Ann Gilligan; Michele G Cyr; Cynthia A Thomson; Janardan Khandekar; Helen Petrovitch; Anne McTiernan
Journal:  JAMA       Date:  2003-06-25       Impact factor: 56.272

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  31 in total

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Review 2.  Is the large simple trial design used for comparative, post-approval safety research? A review of a clinical trials registry and the published literature.

Authors:  Robert F Reynolds; Joanna A Lem; Nicolle M Gatto; Sybil M Eng
Journal:  Drug Saf       Date:  2011-10-01       Impact factor: 5.606

3.  Beyond the intention-to-treat in comparative effectiveness research.

Authors:  Miguel A Hernán; Sonia Hernández-Díaz
Journal:  Clin Trials       Date:  2011-09-23       Impact factor: 2.486

4.  Prognostic value of cardiac troponin T after myocardial infarction: a contemporary community experience.

Authors:  Yariv Gerber; Allan S Jaffe; Susan A Weston; Ruoxiang Jiang; Véronique L Roger
Journal:  Mayo Clin Proc       Date:  2012-03       Impact factor: 7.616

5.  Randomized trials analyzed as observational studies.

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6.  Methodologic Issues When Estimating Risks in Pharmacoepidemiology.

Authors:  Jessie K Edwards; Laura L Hester; Mugdha Gokhale; Catherine R Lesko
Journal:  Curr Epidemiol Rep       Date:  2016-09-13

Review 7.  Measurement Error and Environmental Epidemiology: a Policy Perspective.

Authors:  Jessie K Edwards; Alexander P Keil
Journal:  Curr Environ Health Rep       Date:  2017-03

Review 8.  Statins and breast cancer prognosis: evidence and opportunities.

Authors:  Thomas P Ahern; Timothy L Lash; Per Damkier; Peer M Christiansen; Deirdre P Cronin-Fenton
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9.  Estimation of the standardized risk difference and ratio in a competing risks framework: application to injection drug use and progression to AIDS after initiation of antiretroviral therapy.

Authors:  Stephen R Cole; Bryan Lau; Joseph J Eron; M Alan Brookhart; Mari M Kitahata; Jeffrey N Martin; William C Mathews; Michael J Mugavero
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10.  Multiple Imputation to Account for Measurement Error in Marginal Structural Models.

Authors:  Jessie K Edwards; Stephen R Cole; Daniel Westreich; Heidi Crane; Joseph J Eron; W Christopher Mathews; Richard Moore; Stephen L Boswell; Catherine R Lesko; Michael J Mugavero
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