Nonexperimental comparative effectiveness research using linked healthcare databases

Epidemiology

Volumn 22, Issue 3, 2011, Pages 298-301

  Stürmer, Til ^a,b   Jonsson Funk, Michele ^a   Poole, Charles ^a   Brookhart, M Alan ^a  

^a IL   (United States)

^b McGavran Greenberg   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PLACEBO;

ARTICLE; COMPARATIVE EFFECTIVENESS; DATA BASE; DRUG RESEARCH; EPIDEMIOLOGICAL DATA; FOOD AND DRUG ADMINISTRATION; HEALTH CARE; PHARMACOEPIDEMIOLOGY; PRESCRIPTION; PRIORITY JOURNAL;

COMPARATIVE EFFECTIVENESS RESEARCH; DATABASE MANAGEMENT SYSTEMS; DATABASES, FACTUAL; DELIVERY OF HEALTH CARE; FEMALE; HEALTH SERVICES RESEARCH; HUMANS; INFORMATION DISSEMINATION; MALE; PHARMACOEPIDEMIOLOGY; PROGRAM EVALUATION; QUALITY CONTROL; UNITED STATES;

EID: 79955075235     PISSN: 10443983     EISSN: None     Source Type: Journal    
DOI: 10.1097/EDE.0b013e318212640c     Document Type: Article

References (39)

1. Federal Coordinating Council for Comparative Effectiveness Report to the President and Congress; 2009. Available at: http://www.hhs.gov/ recovery/programs/cer/cerannualrpt.pdf. Accessed 9 September 2010.
2. Institute of Medicine. Initial National Priorities for Comparative Effectiveness Research. Washington, DC: National Academies Press; 2009.
3. American Recovery and Reinvestment Act. Comparative Effectiveness Research Funding. Available at: http://www.hhs.gov/recovery/ programs/cer/. Accessed 9 September 2010.
4. Brookhart MA, Wang PS, Solomon DH, Schneeweiss S. Evaluating short-term drug effects using a physician-specific prescribing preference as an instrumental variable. Epidemiology. 2006;17:268-275.
5. FDA Workshop: Methodologies for Post-Approval Studies of Medical Devices; 2009. Available at: http://www.fda.gov/MedicalDevices/ NewsEvents/ WorkshopsConferences/ucm177140.htm. Accessed 9 September .2010.
6. Temple R. Problems in the use of large data sets to assess effectiveness. Int J Technol Assess Health Care. 1990;6:211-219. (Pubitemid 20347841)
7. Miettinen OS. The need for randomization in the study of intended drug effects. Stat Med. 1983;2:267-271. (Pubitemid 13020139)
8. Salim Yusuf, Rory Collins, Richard Peto. Why do we need some large, simple randomized trials? Stat Med. 1984;3:409-420. (Pubitemid 15167913)
9. The Social Medicine Portal. FDA abandons Declaration of Helsinki for international clinical trials. Available at: http://www.socialmedicine.org/ 2008/06/01/ethics/fda-abandons-declaration-of-helsinki-for- internationalclinical- trials/. Accessed 9 September 2010.
10. Agency for Healthcare Research and Quality. Effective Health Care Program. About the DEcIDE Network. Available at: http://www. effectivehealthcare.ahrq.gov/index.cfm/who-is-involved-in-the-effectivehealth- care-program1/about-the-decide-network/. Accessed 9 September .2010.
11. Strom BL. Pharmacoepidemiology. 4th ed. Chichester, UK: John Wiley & Sons Ltd; 2005.
12. Sesso HD, Gaziano JM, VanDenburgh M, Hennekens CH, Glynn RJ, Buring JE. Comparison of baseline characteristics and mortality experience of participants and nonparticipants in a randomized clinical trial: the Physicians' Health Study. Control Clin Trials. 2002;23:686-702. (Pubitemid 36005478)
13. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. 3rd ed. Philadelphia: Lippincott Williams & Wilkins; 2008.
14. Redelmeier DA, Tan SH, Booth GL. The treatment of unrelated disorders in patients with chronic medical diseases. N Engl J Med. 1998;338: 1516-1520. (Pubitemid 28226280)
15. Welch HG, Albertsen PC, Nease RF, Bubolz TA, Wasson JH. Estimating treatment benefits for the elderly: the effect of competing risks. Ann Intern Med. 1996;124:577-584. (Pubitemid 26085060)
16. Glynn RJ, Knight EL, Levin R, Avorn J. Paradoxical relations of drug treatment with mortality in older persons. Epidemiology. 2001;12:682-689. (Pubitemid 33134531)
17. Jackson LA, Jackson ML, Nelson JC, Neuzil KM, Weiss NS. Evidence of bias in estimates of influenza vaccine effectiveness in seniors. Int J Epidemiol. 2006;35:337-344.
18. Stürmer T, Rothman KJ, Avorn J, Glynn RJ. Treatment effects in the presence of unmeasured confounding: dealing with observations in the tails of the propensity score distribution-a simulation study. Am J Epidemiol. 2010;172:843-854.
19. Brookhart MA, Patrick AR, Dormuth C, Avorn J, Shrank W, Cadarette SM, Solomon DH. Adherence to lipid-lowering therapy and the use of preventive health services: an investigation of the healthy user effect. Am J Epidemiol. 2007;166:348-354. (Pubitemid 47216808)
20. Brookhart MA, Stürmer T, Glynn RJ, Rassen J, Schneeweiss S. Confounding control in healthcare database research: challenges and potential approaches. Med Care. 2010;48(6 suppl):S114-S120.
21. Andersen M, Brookhart MA, Glynn RJ, Stovring H, Stürmer T. Practical issues in measuring cessation and re-initiation of drug use in databases. Pharmacoepidemiol Drug Saf. 2008;17(suppl 1):S27.
22. Simpson SH, Eurich DT, Majumdar SR, et al. A meta-analysis of the association between adherence to drug therapy and mortality. BMJ. 2006;333:15.
23. Suissa S. Immortal time bias in observational studies of drug effects. Pharmacoepidemiol Drug Saf. 2007;16:241-249. (Pubitemid 46431687)
24. Pearce N, Checkoway H, Kriebel D. Bias in occupational epidemiology studies. Occup Environ Med. 2007;64:562-568. (Pubitemid 47195177)
25. Ray WA. Evaluating medication effects outside of clinical trials: Newuser designs. Am J Epidemiol. 2003;158:915-920. (Pubitemid 37323253)
26. Glynn RJ, Schneeweiss S, Stürmer T. Indications for propensity scores and review of their use in pharmacoepidemiology. Basic Clin Pharmacol Toxicol. 2006;98:253-259.
27. Brookhart MA, Wang PS, Solomon DH, Schneeweiss S. Evaluating short-term drug effects using a physician-specific prescribing preference as an instrumental variable. Epidemiology. 2006;17:268-275.
28. Messer LC, Oakes JM, Mason S. Effects of socioeconomic and racial residential segregation on preterm birth: a cautionary tale of structural confounding. Am J Epidemiol. 2010;171:664-673.
29. Westreich D, Cole SR. Invited commentary: positivity in practice-commentary. Am J Epidemiol. 2010;171:674-677.
30. Robins JM, Hernán MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11:550-560. (Pubitemid 30660034)
31. 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;11:561-570. (Pubitemid 30660035)
32. Cole SR, Hernán MA. Constructing inverse probability weights for marginal structural models. Am J Epidemiol. 2008;168:656-664.
33. Hernán MA, Alonso A, Logan R, et al. Observational studies analyzed like randomized experiments: an application to postmenopausal hormone therapy and coronary heart disease. Epidemiology. 2008;19:766-779.
34. Hemkens LG, Grouven U, Bender R, et al. Risk of malignancies in patients with diabetes treated with human insulin or insulin analogues: a cohort study. Diabetologia. 2009;52:1732-1744.
35. Sipahi I, Debanne SM, Rowland DY, Simon DI, Fang JC. Angiotensin-receptor blockade and risk of cancer: meta-analysis of randomised controlled trials. Lancet Oncol. 2010;11:627-636.
36. Pocock SJ, Smeeth L. Insulin glargine and malignancy: an unwarranted alarm letter. The Lancet. 2009;374:511-513.
37. Jan P. Vandenbroucke. Observational research, randomized trials, and two views of medical science. PLoS Medicine. 2008;5:e67.
38. ISPE. Guidelines for good pharmacoepidemiology practices (GPP). Pharmacoepidemiol Drug Saf. 2008;17:200-208.
39. Frank L. Epidemiology: When an entire country is a cohort. Science. 2000;287:2398-2399. (Pubitemid 30185417)