Skip to main content

Advertisement

SpringerLink
Log in

Comparing a marginal structural model with a Cox proportional hazard model to estimate the effect of time-dependent drug use in observational studies: statin use for primary prevention of cardiovascular disease as an example from the Rotterdam Study

  • PHARMACO-EPIDEMIOLOGY
  • Published:
European Journal of Epidemiology Aims and scope Submit manuscript

Abstract

When studying the causal effect of drug use in observational data, marginal structural modeling (MSM) can be used to adjust for time-dependent confounders that are affected by previous treatment. The objective of this study was to compare traditional Cox proportional hazard models (with and without time-dependent covariates) with MSM to study causal effects of time-dependent drug use. The example of primary prevention of cardiovascular disease (CVD) with statins was examined using up to 17.7 years of follow-up from 4,654 participants of the observational prospective population-based Rotterdam Study. In the MSM model, the weight was based on measurements of established cardiovascular risk factors and co-morbidity. In general, we could not demonstrate important differences in results from the Cox models and MSM. Results from analysis on duration of statin use suggested that substantial residual confounding by indication was not accounted for during the period shortly after statin initiation. In conclusion, although on theoretical grounds MSM is an elegant technique, lack of data on the precise time-dependent confounders, such as indication of treatment or other considerations of the prescribing physician jeopardizes the calculation of valid weights. Confounding remains a hurdle in observational effectiveness research on preventive drugs with a multitude of prescription determinants.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Hlatky MA, Douglas PS, Cook NL, et al. Future directions for cardiovascular disease comparative effectiveness research: report of a workshop sponsored by the National Heart, Lung, and Blood Institute. J Am Coll Cardiol. 2012;60(7):569–80. doi:10.1016/j.jacc.2011.12.057.

    Article  PubMed Central  PubMed  Google Scholar 

  2. Stricker BH, Stijnen T. Analysis of individual drug use as a time-varying determinant of exposure in prospective population-based cohort studies. Eur J Epidemiol. 2010;25(4):245–51. doi:10.1007/s10654-010-9451-7.

    Article  PubMed Central  PubMed  Google Scholar 

  3. Salas M, Hofman A, Stricker BH. Confounding by indication: an example of variation in the use of epidemiologic terminology. Am J Epidemiol. 1999;149(11):981–3.

    Article  CAS  PubMed  Google Scholar 

  4. Robins JM, Hernán MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11(5):550–60.

    Article  CAS  PubMed  Google Scholar 

  5. Young JG, Hernán MA, Picciotto S, Robins JM. Relation between three classes of structural models for the effect of a time-varying exposure on survival. Lifetime Data Anal. 2010;16(1):71–84. doi:10.1007/s10985-009-9135-3.

    Article  PubMed Central  PubMed  Google Scholar 

  6. Hofman A, Grobbee DE, de Jong PTVM, van den Ouweland FA. Determinants of disease and disability in the elderly: the Rotterdam Elderly Study. Eur J Epidemiol. 1991;7(4):403–22.

    Article  CAS  PubMed  Google Scholar 

  7. Hofman A, Darwish Murad S, van Duijn CM, et al. The Rotterdam Study: 2014 objectives and design update. Eur J Epidemiol. 2013;28(11):889–926. doi:10.1007/s10654-013-9866-z.

    Article  CAS  PubMed  Google Scholar 

  8. WHO Collaborating Centre for Drug Statistics Methodology. ATC/DDD Index 2014. Norwegian Institute of Public Health. 2013. http://www.whocc.no/atc_ddd_index/. Accessed 30 Dec 2013.

  9. Leening MJG, Kavousi M, Heeringa J, et al. Methods of data collection and definitions of cardiac outcomes in the Rotterdam Study. Eur J Epidemiol. 2012;27(3):173–85. doi:10.1007/s10654-012-9668-8.

    Article  PubMed Central  PubMed  Google Scholar 

  10. Bos MJ, van Rijn MJ, Witteman JCM, Hofman A, Koudstaal PJ, Breteler MMB. Incidence and prognosis of transient neurological attacks. JAMA. 2007;298(24):2877–85. doi:10.1001/jama.298.24.2877.

    Article  CAS  PubMed  Google Scholar 

  11. Wieberdink RG, Ikram MA, Hofman A, Koudstaal PJ, Breteler MMB. Trends in stroke incidence rates and stroke risk factors in Rotterdam, the Netherlands from 1990 to 2008. Eur J Epidemiol. 2012;27(4):287–95. doi:10.1007/s10654-012-9673-y.

    Article  PubMed Central  PubMed  Google Scholar 

  12. Ferket BS, van Kempen BJ, Heeringa J, et al. Personalized prediction of lifetime benefits with statin therapy for asymptomatic individuals: a modeling study. PLoS Med. 2012;9(12):e1001361. doi:10.1371/journal.pmed.1001361.

    Article  PubMed Central  PubMed  Google Scholar 

  13. Perk J, De Backer G, Gohlke H, et al. European Guidelines on cardiovascular disease prevention in clinical practice (version 2012). The Fifth Joint Task Force of the European Society of Cardiology and other societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of nine societies and by invited experts). Eur Heart J. 2012;33(13):1635–701. doi:10.1093/eurheartj/ehs092.

    Article  CAS  PubMed  Google Scholar 

  14. van Rossum CT, van de Mheen H, Breteler MMB, Grobbee DE, Mackenbach JP. Socioeconomic differences in stroke among Dutch elderly women: the Rotterdam Study. Stroke. 1999;30(2):357–62.

    Article  PubMed  Google Scholar 

  15. D’Agostino RB, Lee ML, Belanger AJ, Cupples LA, Anderson K, Kannel WB. Relation of pooled logistic regression to time dependent Cox regression analysis: the Framingham Heart Study. Stat Med. 1990;9(12):1501–15.

    Article  PubMed  Google Scholar 

  16. Liang KY, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika. 1986;73(1):13–22.

    Article  Google Scholar 

  17. Hernán MA, Brumback B, Robins JM. Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men. Epidemiology. 2000;11(5):561–70.

    Article  PubMed  Google Scholar 

  18. Cook NR, Cole SR, Buring JE. Aspirin in the primary prevention of cardiovascular disease in the Women’s Health Study: effect of noncompliance. Eur J Epidemiol. 2012;27(6):431–8. doi:10.1007/s10654-012-9702-x.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  19. Stone NJ, Robinson J, Lichtenstein AH, et al. ACC/AHA Guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2013. doi:10.1161/01.cir.0000437738.63853.7a.

  20. Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Series B (Methodol). 1977;39(1):1–38.

    Google Scholar 

  21. Maasland L, van Oostenbrugge RJ, Franke CF, et al. Patients enrolled in large randomized clinical trials of antiplatelet treatment for prevention after transient ischemic attack or ischemic stroke are not representative of patients in clinical practice: the Netherlands Stroke Survey. Stroke. 2009;40(8):2662–8. doi:10.1161/STROKEAHA.109.551812.

    Article  CAS  PubMed  Google Scholar 

  22. Van Spall HG, Toren A, Kiss A, Fowler RA. Eligibility criteria of randomized controlled trials published in high-impact general medical journals: a systematic sampling review. JAMA. 2007;297(11):1233–40. doi:10.1001/jama.297.11.1233.

    Article  PubMed  Google Scholar 

  23. Lee PY, Alexander KP, Hammill BG, Pasquali SK, Peterson ED. Representation of elderly persons and women in published randomized trials of acute coronary syndromes. JAMA. 2001;286(6):708–13.

    Article  CAS  PubMed  Google Scholar 

  24. Kitzman DW, Rich MW. Age disparities in heart failure research. JAMA. 2010;304(17):1950–1. doi:10.1001/jama.2010.1592.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  25. Psaty BM, Koepsell TD, Lin D, et al. Assessment and control for confounding by indication in observational studies. J Am Geriatr Soc. 1999;47(6):749–54.

    CAS  PubMed  Google Scholar 

  26. Heinze G, Juni P. An overview of the objectives of and the approaches to propensity score analyses. Eur Heart J. 2011;32(14):1704–8. doi:10.1093/eurheartj/ehr031.

    Article  PubMed  Google Scholar 

  27. Stürmer T, Joshi M, Glynn RJ, Avorn J, Rothman KJ, Schneeweiss S. A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. J Clin Epidemiol. 2006;59(5):437–47. doi:10.1016/j.jclinepi.2005.07.004.

    Article  PubMed Central  PubMed  Google Scholar 

  28. Yang S, Eaton CB, Lu J, Lapane KL. Application of marginal structural models in pharmacoepidemiologic studies: a systematic review. Pharmacoepidemiol Drug Saf. 2014;. doi:10.1002/pds.3569.

    Google Scholar 

  29. Suarez D, Borras R, Basagana X. Differences between marginal structural models and conventional models in their exposure effect estimates: a systematic review. Epidemiology. 2011;22(4):586–8. doi:10.1097/EDE.0b013e31821d0507.

    Article  PubMed  Google Scholar 

  30. World Health Organization. WHO consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection. Recommendations for a public health approach., Geneva. June 2013. http://www.who.int/hiv/pub/guidelines/arv2013/download/en/index.html. Accessed 5 Nov 2013.

  31. Penning-van Beest FJ, Termorshuizen F, Goettsch WG, Klungel OH, Kastelein JJ, Herings RM. Adherence to evidence-based statin guidelines reduces the risk of hospitalizations for acute myocardial infarction by 40%: a cohort study. Eur Heart J. 2007;28(2):154–9. doi:10.1093/eurheartj/ehl391.

    Article  CAS  PubMed  Google Scholar 

  32. Danaei G, Rodriguez LA, Cantero OF, Logan R, Hernán MA. Observational data for comparative effectiveness research: an emulation of randomised trials of statins and primary prevention of coronary heart disease. Stat Methods Med Res. 2013;22(1):70–96. doi:10.1177/0962280211403603.

    Article  PubMed Central  PubMed  Google Scholar 

  33. Haukka J, Niskanen L, Partonen T, Lonnqvist J, Tiihonen J. Statin usage and all-cause and disease-specific mortality in a nationwide study. Pharmacoepidemiol Drug Saf. 2012;21(1):61–9. doi:10.1002/pds.2255.

    Article  CAS  PubMed  Google Scholar 

  34. Taylor F, Huffman MD, Macedo AF, et al. Statins for the primary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2013;1:CD004816. doi:10.1002/14651858.CD004816.pub5.

  35. Mauri L. Why we still need randomized trials to compare effectiveness. N Engl J Med. 2012;366(16):1538–40. doi:10.1056/NEJMe1202866.

    Article  CAS  PubMed  Google Scholar 

  36. Mills EJ, O’Regan C, Eyawo O, et al. Intensive statin therapy compared with moderate dosing for prevention of cardiovascular events: a meta-analysis of >40,000 patients. Eur Heart J. 2011;32(11):1409–15. doi:10.1093/eurheartj/ehr035.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

The invaluable contribution of inhabitants, general practitioners, and pharmacists of the Ommoord district to the Rotterdam Study is gratefully acknowledged. We thank Miguel A. Hernán, MD MPH ScM DrPH (Harvard School of Public Health, Boston, MA, U.S.), for providing valuable comments on earlier versions of the manuscript. The Rotterdam Study is supported by the Erasmus MC and Erasmus University Rotterdam; the Netherlands Organisation for Scientific Research (NWO); the Netherlands Organisation for Health Research and Development (ZonMw); the Research Institute for Diseases in the Elderly (RIDE); the Netherlands Genomics Initiative (NGI); the Ministry of Education, Culture and Sciences; the Ministry of Health Welfare and Sports; the European Commission (DG XII); and the Municipality of Rotterdam. This work was supported by a grant from and the Netherlands Organisation for Health Research and Development (ZonMw) [HTA Grant 80-82500-98-10208]. None of the funders had any role in design and conduct of the study; collection, management, analysis, and interpretation of the data; and review, or approval of the manuscript.

Conflict of interest

Oscar H. Franco reports receiving grants from Nestlé Nutrition (Nestec Ltd.), Metagenics Inc., and the AXA Research Fund to establish a center on ageing research (ErasmusAGE). The other authors declare that they have no conflict of interest.

Author information

Authors and Affiliations

  1. Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands

    Catherine E. de Keyser, Maarten J. G. Leening, Albert Hofman, M. Arfan Ikram, Oscar H. Franco & Bruno H. Stricker

  2. The Health Care Inspectorate, The Hague, The Netherlands

    Catherine E. de Keyser & Bruno H. Stricker

  3. Department of Cardiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands

    Maarten J. G. Leening

  4. Department of Medical Informatics, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands

    Silvana A. Romio

  5. Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy

    Silvana A. Romio

  6. Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands

    J. Wouter Jukema

  7. Department of Neurology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands

    M. Arfan Ikram

  8. Department of Radiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands

    M. Arfan Ikram

  9. Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands

    Theo Stijnen

  10. Department of Internal Medicine, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands

    Bruno H. Stricker

Authors
  1. Catherine E. de Keyser
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maarten J. G. Leening
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Silvana A. Romio
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. J. Wouter Jukema
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Albert Hofman
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M. Arfan Ikram
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Oscar H. Franco
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Theo Stijnen
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Bruno H. Stricker
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Catherine E. de Keyser.

Additional information

Catherine E. de Keyser and Maarten J. G. Leening have contributed equally to this work.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 107 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

de Keyser, C.E., Leening, M.J.G., Romio, S.A. et al. Comparing a marginal structural model with a Cox proportional hazard model to estimate the effect of time-dependent drug use in observational studies: statin use for primary prevention of cardiovascular disease as an example from the Rotterdam Study. Eur J Epidemiol 29, 841–850 (2014). https://doi.org/10.1007/s10654-014-9951-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10654-014-9951-y

Keywords

Search

Navigation