%0 Journal Article %1 Stuermer2011 %A Stürmer, Til %A Funk, Michele Jonsson %A Poole, Charles %A Brookhart, M Alan %D 2011 %J Epidemiology (Cambridge, Mass.) %K ComparativeEffectivenessResearch DatabaseManagementSystems Databases DeliveryofHealthCare DeliveryofHealthCare:organization&administra Factual Female HealthServicesResearch Humans InformationDissemination InformationDissemination:methods Male Pharmacoepidemiology Pharmacoepidemiology:organization&administratio ProgramEvaluation QualityControl UnitedStates %N 3 %P 298-301 %R 10.1097/EDE.0b013e318212640c %T Nonexperimental comparative effectiveness research using linked healthcare databases. %U http://ovidsp.ovid.com/ovidweb.cgi?T=JS&CSC=Y&NEWS=N&PAGE=fulltext&D=ovftl&AN=00001648-201105000-00006 http://www.ncbi.nlm.nih.gov/pubmed/21464649 %V 22 %X References: 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. 7. Miettinen OS. The need for randomization in the study of intended drug effects. Stat Med. 1983;2:267-271. 8. Salim Yusuf, Rory Collins, Richard Peto. Why do we need some large, simple randomized trials? Stat Med. 1984;3:409-420. 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-international-clinical-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-effective-health-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. 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. 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. 16. Glynn RJ, Knight EL, Levin R, Avorn J. Paradoxical relations of drug treatment with mortality in older persons. Epidemiology. 2001;12:682-689. 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. Sturmer 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. 20. Brookhart MA, Sturmer 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, Sturmer T. Practical issues in measuring cessation and re-initiation of drug use in databases abstract. 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. 24. Pearce N, Checkoway H, Kriebel D. Bias in occupational epidemiology studies. Occup Environ Med. 2007;64:562-568. 25. Ray WA. Evaluating medication effects outside of clinical trials: Newuser designs. Am J Epidemiol. 2003;158:915-920. 26. Glynn RJ, Schneeweiss S, Sturmer 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, Hernan MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11:550-560. 31. Hernan 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. 32. Cole SR, Hernan MA. Constructing inverse probability weights for marginal structural models. Am J Epidemiol. 2008;168:656-664. 33. Hernan 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. %@ 1044-3983

@article{Stuermer2011, abstract = {References: 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. 7. Miettinen OS. The need for randomization in the study of intended drug effects. Stat Med. 1983;2:267-271. 8. Salim Yusuf, Rory Collins, Richard Peto. Why do we need some large, simple randomized trials? Stat Med. 1984;3:409-420. 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-international-clinical-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-effective-health-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. 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. 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. 16. Glynn RJ, Knight EL, Levin R, Avorn J. Paradoxical relations of drug treatment with mortality in older persons. Epidemiology. 2001;12:682-689. 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. Sturmer 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. 20. Brookhart MA, Sturmer 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, Sturmer T. Practical issues in measuring cessation and re-initiation of drug use in databases [abstract]. 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. 24. Pearce N, Checkoway H, Kriebel D. Bias in occupational epidemiology studies. Occup Environ Med. 2007;64:562-568. 25. Ray WA. Evaluating medication effects outside of clinical trials: Newuser designs. Am J Epidemiol. 2003;158:915-920. 26. Glynn RJ, Schneeweiss S, Sturmer 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, Hernan MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11:550-560. 31. Hernan 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. 32. Cole SR, Hernan MA. Constructing inverse probability weights for marginal structural models. Am J Epidemiol. 2008;168:656-664. 33. Hernan 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.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Stürmer, Til and Funk, Michele Jonsson and Poole, Charles and Brookhart, M Alan}, biburl = {https://www.bibsonomy.org/bibtex/2bbbd9f50d7b7693fc1f46740f0009d9b/jepcastel}, city = {From the Pharmacoepidemiology Program, Department of Epidemiology, UNC Gillings School of Global Public Health University of North Carolina at Chapel Hill, Chapel Hill, NC.}, doi = {10.1097/EDE.0b013e318212640c}, interhash = {58a66cd7f7e21dfc652ab12b39adc5ba}, intrahash = {bbbd9f50d7b7693fc1f46740f0009d9b}, isbn = {1044-3983}, issn = {1531-5487}, journal = {Epidemiology (Cambridge, Mass.)}, keywords = {ComparativeEffectivenessResearch DatabaseManagementSystems Databases DeliveryofHealthCare DeliveryofHealthCare:organization&administra Factual Female HealthServicesResearch Humans InformationDissemination InformationDissemination:methods Male Pharmacoepidemiology Pharmacoepidemiology:organization&administratio ProgramEvaluation QualityControl UnitedStates}, month = {5}, note = {6101<br/>[Miscellaneous]; NLM Journal Code: a2t, 9009644;<br/>CER; Databases}, number = 3, pages = {298-301}, pmid = {21464649}, timestamp = {2023-02-03T11:44:35.000+0100}, title = {Nonexperimental comparative effectiveness research using linked healthcare databases.}, url = {http://ovidsp.ovid.com/ovidweb.cgi?T=JS&CSC=Y&NEWS=N&PAGE=fulltext&D=ovftl&AN=00001648-201105000-00006 http://www.ncbi.nlm.nih.gov/pubmed/21464649}, volume = 22, year = 2011 }