Active-comparator design and new-user design in observational studies (original) (raw)

References

1. Chan, K. A. & Hernandez-Diaz, S. Pharmacoepidemiology and rheumatic disorders. Rheum. Dis. Clin. North Am. 30, 835–850 (2004).
   Article Google Scholar
2. Schneeweiss, S., Gagne, J. J., Glynn, R. J., Ruhl, M. & Rassen, J. A. Assessing the comparative effectiveness of newly marketed medications: methodological challenges and implications for drug development. Clin. Pharmacol. Ther. 90, 777–790 (2011).
   Article CAS Google Scholar
3. Strom, B. L., Kimmel, S. E. & Hennessy, S. (Eds) Textbook of Pharmacoepidemiology (Wiley-Blackwell, 2013).
   Book Google Scholar
4. Walker, A. M. & Stampfer, M. J. Observational studies of drug safety. Lancet 348, 489 (1996).
   Article CAS Google Scholar
5. Psaty, B. M. & Siscovick, D. S. Minimizing bias due to confounding by indication in comparative effectiveness research: the importance of restriction. JAMA 304, 897–898 (2010).
   Article CAS Google Scholar
6. Rosenbaum, P. R. & Rubin, D. B. The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41–55 (1983).
   Article Google Scholar
7. Crump, R. K., Hotz, V. J., Imbens, G. W. & Mitnik, O. A. Dealing with limited overlap in estimation of average treatment effects. Biometrika 96, 187–199 (2009).
   Article Google Scholar
8. Petersen, M. L., Porter, K. E., Gruber, S., Wang, Y. & van der Laan, M. J. Diagnosing and responding to violations in the positivity assumption. Stat. Methods Med. Res. 21, 31–54 (2012).
   Article Google Scholar
9. Dixon, W. G. et al. Drug-specific risk of tuberculosis in patients with rheumatoid arthritis treated with anti-TNF therapy: results from the British Society for Rheumatology Biologics Register (BSRBR). Ann. Rheum. Dis. 69, 522–528 (2010).
   Article CAS Google Scholar
10. Sternberg, S. A., Wershof Schwartz, A., Karunananthan, S., Bergman, H. & Clarfield, A. M. The identification of frailty: a systematic literature review. J. Am. Geriatr. Soc. 59, 2129–2138 (2011).
    Article Google Scholar
11. Glynn, R. J., Knight, E. L., Levin, R. & Avorn, J. Paradoxical relations of drug treatment with mortality in older persons. Epidemiology 12, 682–689 (2001).
    Article CAS Google Scholar
12. Eurich, D. T., Marrie, T. J., Johnstone, J. & Majumdar, S. R. Mortality reduction with influenza vaccine in patients with pneumonia outside 'flu' season: pleiotropic benefits or residual confounding? Am. J. Respir. Crit. Care Med. 178, 527–533 (2008).
    Article Google Scholar
13. Camelo Castillo, W., Delaney, J. A. C. & Stürmer, T. The challenges of comparing results between placebo controlled randomized trials and non-experimental new user, active comparator cohort studies: the example of olmesartan. Pharmacoepidemiol. Drug Saf. 23, 357–360 (2014).
    Article CAS Google Scholar
14. Ray, W. A. Evaluating medication effects outside of clinical trials: new-user designs. Am. J. Epidemiol. 158, 915–920 (2003).
    Article Google Scholar
15. Johnson, E. S. et al. The incident user design in comparative effectiveness research. Pharmacoepidemiol. Drug Saf. 22, 1–6 (2013).
    Article Google Scholar
16. Strangfeld, A. et al. Treatment benefit or survival of the fittest: what drives the time-dependent decrease in serious infection rates under TNF inhibition and what does this imply for the individual patient? Ann. Rheum. Dis. 70, 1914–1920 (2011).
    Article CAS Google Scholar
17. Choi, H. K., Nguyen, U.-S., Niu, J., Danaei, G. & Zhang, Y. Selection bias in rheumatic disease research. Nat. Rev. Rheumatol. 10, 403–412 (2014).
    Article Google Scholar
18. Curtis, J. R. et al. Risk of serious bacterial infections among rheumatoid arthritis patients exposed to tumor necrosis factor α antagonists. Arthritis Rheum. 56, 1125–1133 (2007).
    Article CAS Google Scholar
19. Dixon, W. G. et al. Serious infection following anti-tumor necrosis factor α therapy in patients with rheumatoid arthritis: lessons from interpreting data from observational studies. Arthritis Rheum. 56, 2896–2904 (2007).
    Article CAS Google Scholar
20. Askling, J. et al. Cancer risk in patients with rheumatoid arthritis treated with anti-tumor necrosis factor α therapies: does the risk change with the time since start of treatment? Arthritis Rheum. 60, 3180–3189 (2009).
    Article CAS Google Scholar
21. Schisterman, E. F., Cole, S. R. & Platt, R. W. Overadjustment bias and unnecessary adjustment in epidemiologic studies. Epidemiology 20, 488–495 (2009).
    Article Google Scholar
22. Suissa, S. Immortal time bias in observational studies of drug effects. Pharmacoepidemiol. Drug Saf. 16, 241–249 (2007).
    Article Google Scholar
23. Levesque, L. E., Hanley, J. A., Kezouh, A. & Suissa, S. Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes. BMJ 340, b5087 (2010).
    Article Google Scholar
24. Rothman, K. J., Greenland, S. & Lash, T. L. Modern Epidemiology (Lippincott Williams & Wilkins, 2012).
    Google Scholar
25. Grijalva, C. G. et al. Initiation of tumor necrosis factor-α antagonists and the risk of hospitalization for infection in patients with autoimmune diseases. JAMA 306, 2331–2339 (2011).
    Article CAS Google Scholar
26. Strangfeld, A. et al. Risk of incident or recurrent malignancies among patients with rheumatoid arthritis exposed to biologic therapy in the German biologics register RABBIT. Arthritis Res. Ther. 12, R5 (2010).
    Article Google Scholar

Download references