Multivariate-adjusted pharmacoepidemiologic analyses of confidential information pooled from multiple health care utilization databases

Pharmacoepidemiology and Drug Safety

Volumn 19, Issue 8, 2010, Pages 848-857

  Rassen, Jeremy A ^a   Avorn, Jerry ^a   Schneeweiss, Sebastian ^a  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

Confounding factors (epidemiology); Data pooling; Meta analysis; Pharmacoepidemiology; Propensity scores

Indexed keywords

CLOPIDOGREL; PROTON PUMP INHIBITOR;

ADULT; AGED; ARTICLE; DRUG SAFETY; FEMALE; HEALTH CARE UTILIZATION; HEART INFARCTION; HOSPITALIZATION; HUMAN; MAJOR CLINICAL STUDY; MALE; PHARMACOEPIDEMIOLOGY; POSTMARKETING SURVEILLANCE; PRIORITY JOURNAL; PRIVACY; REVASCULARIZATION;

ANTI-ULCER AGENTS; CONFIDENTIALITY; DATABASES, FACTUAL; FEMALE; HUMANS; MALE; META-ANALYSIS AS TOPIC; MULTIVARIATE ANALYSIS; MYOCARDIAL INFARCTION; PHARMACOEPIDEMIOLOGY; PLATELET AGGREGATION INHIBITORS; PRIVACY; PRODUCT SURVEILLANCE, POSTMARKETING; PROPENSITY SCORE; PROTON PUMP INHIBITORS; RISK FACTORS; TICLOPIDINE; TREATMENT OUTCOME; UTILIZATION REVIEW;

EID: 77956638740     PISSN: 10538569     EISSN: 10991557     Source Type: Journal    
DOI: 10.1002/pds.1867     Document Type: Article

References (39)

1. Blettner M, Sauerbrei W, Schlehofer B, Scheuchenpflug T, Friedenreich C. Traditional reviews, meta-analyses and pooled analyses in epidemiology. Int J Epidemiol 1999; 28(1): 1-9.
2. Friedenreich CM. Methods for pooled analyses of epidemiologic studies. Epidemiology 1993; 4(4): 295-302.
3. Smith-Warner SA, Spiegelman D, Ritz J, et al., Methods for pooling results of epidemiologic studies: the Pooling Project of Prospective Studies of Diet and Cancer. Am J Epidemiol 2006; 163(11): 1053-1064.
4. Maro JC, Platt R, Holmes JH, et al., Design of a National Distributed Health Data Network. Ann Intern Med 2009; 151(5): 341-4.
5. Lieu TA, Kulldorff M, Davis RL, et al., Real-time vaccine safety surveillance for the early detection of adverse events. Med Care 2007; 45 (10 Supl 2): S89-S95.
6. Food and Drug Administration Amendments Act of2007, Public Law 110-85 (2007).
7. The Sentinel Initiative:. A National Strategy for Monitoring Medical Product Safety. 2008; http://www.fda.gov/downloads/Safety/FDAs- SentinelInitiative/UCM124701.pdf. Accessed November 25, 2009.
8. Hennessy S, Strom BL. PDUFA reauthorization - drug safety's golden moment of opportunity? N Engl J Med 2007; 356(17): 1703-1704.
9. Health Insurance Portability and Accountability Act, 42 USC 201 et seq. (1996).
10. Chawla S, Dwork C, McSherry F, Smith A, Wee H. Toward privacy in public databases. 2nd Theory of Cryptography Conference. 2005, 363-385.
11. Barak B, Chaudhurii K, Dwork C, Kale S, McSherry F, Talwar K. Privacy, Accuracy, and Consistency Too: A Holistic Solution to Contingency Table Release PODS '07. 2007.
12. Walker AM. Confounding by indication. Epidemiology 1994; 7(4): 335-336.
13. Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol 2005; 58(4): 323-337.
14. Sturmer 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): 437-447.
15. Rubin DB. Estimating causal effects from large data sets using propensity scores. Ann Intern Med 1997; 127(8 Pt 2): 757-763.
16. Robins JM, Mark SD, Whitney KN. Estimating exposure effects by modelling the expectation of exposure conditional on confounders. Biometrics 1992; 48: 479-495.
17. D'Agostino RB. Jr., Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Stat Med 1998; 17(19): 2265-2281.
18. Summary of HIPAA Privacy Rule. 2008; http://www.hhs.gov/ocr/ privacysummary. pdf. Accessed July 11, 2008.
19. Schneeweiss S, Rassen JA, Glynn RJ, Avorn J, Mogun H, Brookhart MA. High-dimensional proxy adjustment in studies of treatment effects using health care claims data. Epidemiology 2009; 20(4): 512-522.
20. Rosenbaum PR, Rubin DB. The central role of propensity scores in observational studies for causal effects. Biometrika 1983; 70(1): 41-55.
21. Parsons LS. Reducing bias in a propensity score matched-pair sample using greedy matching techniques. 2001; www2.sas.com/proceedings/ sugi26/p214-26.pdf.
22. Sturmer T, Schneeweiss S, Brookhart MA, Rothman KJ, Avorn J, Glynn RJ. Analytic strategies to adjust confounding using exposure propensity scores and disease risk scores: nonsteroidal antiinflammatory drugs and short-term mortality in the elderly. Am J Epidemiol 2005; 161(9): 891-898.
23. Gilard M, Arnaud B, Cornily JC, et al., Influence of omeprazole on the antiplatelet action of clopidogrel associated with aspirin: the randomized, double-blind OCLA (Omeprazole CLopidogrel Aspirin) study. J Am Coll Cardiol 2008; 51(3): 256-260.
24. Pezalla E, Day D, Pulliadath I. Initial assessment of clinical impact of a drug interaction between clopidogrel and proton pump inhibitors. J Am College Cardiol 2008; 52(12): 1038-1039.
25. Ray WA. Evaluating medication effects outside of clinical trials: new-user designs. Am J Epidemiol 2003; 158(9): 915-920.
26. Suissa S. Immortal time bias in pharmaco-epidemiology. Am J Epidemiol 2008; 167(4): 492-499.
27. Rassen JA, Choudhry NK, Avorn J, Schneeweiss S. Cardiovascular outcomes and mortality in patients using clopidogrel with proton pump inhibitors after percutaneous coronary intervention or acute coronary syndrome. Circulation 2009; 120(23): 2310-12.
28. Wang PS, Schneeweiss S, Avorn J, et al., Risk of death in elderly users of conventional vs. atypical antipsychotic medications. N Engl J Med 2005; 353(22): 2335-2341.
29. Schneeweiss S, Setoguchi S, Brookhart MA, Dormuth CA, Wang PS. Mortality in users of conventional and atypical antipsychotic medications in British Columbia seniors. Can Med Assoc J 2007; 126(5): 627-632.
30. Solomon DH, Schneeweiss S, Glynn RJ, et al., Relationship between selective cyclooxygenase-2 inhibitors and acute myocardial infarction in older adults. Circulation 2004; 109(17): 2068-2073.
31. Solomon DH, Katz JN, Finkelstein JS, et al., Osteoporosis improvement: a large-scale randomized controlled trial of patient and primary care physician education. J Bone Miner Res 2007; 22(11): 1808-1815.
32. Friedenreich CM. Commentary: improving pooled analyses in epidemiology. Int J Epidemiol 2002; 31(1): 86-87.
33. Weitzen S, Lapane KL, Toledano AY, Hume AL, Mor V. Weaknesses of goodness-of-fit tests for evaluating propensity scoremodels: the case of the omitted confounder. Pharmacoepidemiol Drug Saf 2005; 14(4): 227-238.
34. DerSimonian R, Laird N. Meta-analysis in clinical trials. Controlled Clin Trials 1986; 7(3): 177-188.
35. Sharp S, Sterne J. Stata meta command "STB-43 sbe16-2"London, UK 1998.
36. Lyman GH, Kuderer NM. The strengths and limitations of meta-analyses based on aggregate data. BMC Med Res Methodol 2005; 5(1): 14.
37. Velentgas P, Bohn RL, Brown JS, et al., A distributed research network model for post-marketing safety studies: the Meningococcal Vaccine Study. Pharmacoepidemiol Drug Saf 2008; 17(12): 1226-1234.
38. Arbogast PG, Kaltenbach L, Ding H, Ray WA. Adjustment for multiple cardiovascular risk factors using a summary risk score. Epidemiology 2008; 19(1): 30-37.
39. Hansen BB. The prognostic analogue of the propensity score. Biometrika 2008; 95(2): 481-488.