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Flexible Marginal Structural Models for Estimating the Cumulative Effect of a Time-Dependent Treatment on the Hazard: Reassessing the Cardiovascular Risks of Didanosine Treatment in the Swiss HIV Cohort Study

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  • Yongling Xiao
  • Michal Abrahamowicz
  • Erica E. M. Moodie
  • Rainer Weber
  • James Young

Abstract

The association between antiretroviral treatment and cardiovascular disease (CVD) risk in HIV-positive persons has been the subject of much debate since the Data collection on Adverse events of Anti-HIV Drugs (D:A:D) study reported that recent use of two antiretroviral drugs, abacavir (ABC) and didanosine (DDI), was associated with increased risk. We focus on the potential impact of DDI use, as this drug has not been as studied intensively as ABC. We propose a flexible marginal structural Cox model with weighted cumulative exposure modeling (Cox WCE MSM) to address two key challenges encountered when using observational longitudinal data to assess the adverse effects of medication: (1) the need to model the cumulative effect of a time-dependent treatment and (2) the need to control for time-dependent confounders that also act as mediators of the effect of past treatment. Simulations confirm that the Cox WCE MSM yields accurate estimates of the causal treatment effect given complex exposure effects and time-dependent confounding. We then use the new flexible Cox WCE MSM to assess the association between DDI use and CVD risk in the Swiss HIV Cohort Study. In contrast to the nonsignificant results obtained with conventional parametric Cox MSMs, our new Cox WCE MSM identifies a significant short-term risk increase due to DDI use in the previous year. Supplementary materials for this article are available online.

Suggested Citation

  • Yongling Xiao & Michal Abrahamowicz & Erica E. M. Moodie & Rainer Weber & James Young, 2014. "Flexible Marginal Structural Models for Estimating the Cumulative Effect of a Time-Dependent Treatment on the Hazard: Reassessing the Cardiovascular Risks of Didanosine Treatment in the Swiss HIV Coho," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 455-464, June.
    • Handle: RePEc:taf:jnlasa:v:109:y:2014:i:506:p:455-464
    DOI: 10.1080/01621459.2013.872650
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    References listed on IDEAS

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    1. Clay Bavinger & Eran Bendavid & Katherine Niehaus & Richard A Olshen & Ingram Olkin & Vandana Sundaram & Nicole Wein & Mark Holodniy & Nanjiang Hou & Douglas K Owens & Manisha Desai, 2013. "Risk of Cardiovascular Disease from Antiretroviral Therapy for HIV: A Systematic Review," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-14, March.
    2. Chris T. Volinsky & Adrian E. Raftery, 2000. "Bayesian Information Criterion for Censored Survival Models," Biometrics, The International Biometric Society, vol. 56(1), pages 256-262, March.
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    Cited by:

    1. Liangyuan Hu & Joseph W. Hogan & Ann W. Mwangi & Abraham Siika, 2018. "Modeling the causal effect of treatment initiation time on survival: Application to HIV/TB co†infection," Biometrics, The International Biometric Society, vol. 74(2), pages 703-713, June.
    2. Mélanie Prague & Daniel Commenges & Jon Michael Gran & Bruno Ledergerber & Jim Young & Hansjakob Furrer & Rodolphe Thiébaut, 2017. "Dynamic models for estimating the effect of HAART on CD4 in observational studies: Application to the Aquitaine Cohort and the Swiss HIV Cohort Study," Biometrics, The International Biometric Society, vol. 73(1), pages 294-304, March.

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