Literature DB >> 20162632

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

Jeremy A Rassen1, Jerry Avorn, Sebastian Schneeweiss.   

Abstract

PURPOSE: Mandated post-marketing drug safety studies require vast databases pooled from multiple administrative data sources which can contain private and proprietary information. We sought to create a method to conduct pooled analyses while keeping information private and allowing for full confounder adjustment.
METHODS: We propose a method based on propensity score (PS) techniques. A set of propensity scores are computed in each data-contributing center and a PS-adjusted analysis is then carried out on a pooled basis. The method is demonstrated in a study of the potentially negative effects of concurrent initiation of clopidogrel and proton pump inhibitors (PPIs) in four cohorts of patients assembled from North American claims data sources. Clinical outcomes were myocardial infarction (MI) hospitalization and hospitalization for revascularization procedure. Success of the method was indicated by equivalent performance of our PS-based method and traditional confounder adjustment. We also implemented and evaluated high-dimensional propensity scores and meta-analytic techniques.
RESULTS: On both a pooled and individual cohort basis, we saw substantially similar point estimates and confidence intervals for studies adjusted by covariates and from privacy-maintaining propensity scores. The pooled, adjusted OR for MI hospitalization was 1.20 (95% confidence interval 1.03, 1.41) with individual variable adjustment and 1.16 (1.00, 1.36) with PS adjustment. The revascularization OR estimates differed by < 1%. Meta-analysis and pooling yielded substantially similar results.
CONCLUSIONS: We observed little difference in point estimates when we employed standard techniques or the proposed privacy-maintaining pooling method. We would recommend the technique in instances where multi-center studies require both privacy and multivariate adjustment. 2010 John Wiley & Sons, Ltd.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20162632      PMCID: PMC2914827          DOI: 10.1002/pds.1867

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  28 in total

Review 1.  Traditional reviews, meta-analyses and pooled analyses in epidemiology.

Authors:  M Blettner; W Sauerbrei; B Schlehofer; T Scheuchenpflug; C Friedenreich
Journal:  Int J Epidemiol       Date:  1999-02       Impact factor: 7.196

2.  Commentary: improving pooled analyses in epidemiology.

Authors:  Christine M Friedenreich
Journal:  Int J Epidemiol       Date:  2002-02       Impact factor: 7.196

3.  Estimating exposure effects by modelling the expectation of exposure conditional on confounders.

Authors:  J M Robins; S D Mark; W K Newey
Journal:  Biometrics       Date:  1992-06       Impact factor: 2.571

4.  Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group.

Authors:  R B D'Agostino
Journal:  Stat Med       Date:  1998-10-15       Impact factor: 2.373

5.  Confounding by indication.

Authors:  A M Walker
Journal:  Epidemiology       Date:  1996-07       Impact factor: 4.822

Review 6.  Estimating causal effects from large data sets using propensity scores.

Authors:  D B Rubin
Journal:  Ann Intern Med       Date:  1997-10-15       Impact factor: 25.391

7.  Meta-analysis in clinical trials.

Authors:  R DerSimonian; N Laird
Journal:  Control Clin Trials       Date:  1986-09

Review 8.  Methods for pooled analyses of epidemiologic studies.

Authors:  C M Friedenreich
Journal:  Epidemiology       Date:  1993-07       Impact factor: 4.822

9.  Cardiovascular outcomes and mortality in patients using clopidogrel with proton pump inhibitors after percutaneous coronary intervention or acute coronary syndrome.

Authors:  Jeremy A Rassen; Niteesh K Choudhry; Jerry Avorn; Sebastian Schneeweiss
Journal:  Circulation       Date:  2009-11-23       Impact factor: 29.690

10.  Relationship between selective cyclooxygenase-2 inhibitors and acute myocardial infarction in older adults.

Authors:  Daniel H Solomon; Sebastian Schneeweiss; Robert J Glynn; Yuka Kiyota; Raisa Levin; Helen Mogun; Jerry Avorn
Journal:  Circulation       Date:  2004-04-19       Impact factor: 29.690

View more
  20 in total

1.  Applying propensity scores estimated in a full cohort to adjust for confounding in subgroup analyses.

Authors:  Jeremy A Rassen; Robert J Glynn; Kenneth J Rothman; Soko Setoguchi; Sebastian Schneeweiss
Journal:  Pharmacoepidemiol Drug Saf       Date:  2011-12-08       Impact factor: 2.890

2.  Pharmacoepidemiology.

Authors:  Stephen J W Evans
Journal:  Br J Clin Pharmacol       Date:  2012-06       Impact factor: 4.335

Review 3.  Do observational studies using propensity score methods agree with randomized trials? A systematic comparison of studies on acute coronary syndromes.

Authors:  Issa J Dahabreh; Radley C Sheldrick; Jessica K Paulus; Mei Chung; Vasileia Varvarigou; Haseeb Jafri; Jeremy A Rassen; Thomas A Trikalinos; Georgios D Kitsios
Journal:  Eur Heart J       Date:  2012-06-17       Impact factor: 29.983

4.  Privacy-maintaining propensity score-based pooling of multiple databases applied to a study of biologics.

Authors:  Jeremy A Rassen; Daniel H Solomon; Jeffrey R Curtis; Lisa Herrinton; Sebastian Schneeweiss
Journal:  Med Care       Date:  2010-06       Impact factor: 2.983

5.  On the role of marginal confounder prevalence - implications for the high-dimensional propensity score algorithm.

Authors:  Tibor Schuster; Menglan Pang; Robert W Platt
Journal:  Pharmacoepidemiol Drug Saf       Date:  2015-04-10       Impact factor: 2.890

6.  Effect Estimation in Point-Exposure Studies with Binary Outcomes and High-Dimensional Covariate Data - A Comparison of Targeted Maximum Likelihood Estimation and Inverse Probability of Treatment Weighting.

Authors:  Menglan Pang; Tibor Schuster; Kristian B Filion; Mireille E Schnitzer; Maria Eberg; Robert W Platt
Journal:  Int J Biostat       Date:  2016-11-01       Impact factor: 0.968

7.  Orphan therapies: making best use of postmarket data.

Authors:  Judith C Maro; Jeffrey S Brown; Gerald J Dal Pan; Lingling Li
Journal:  J Gen Intern Med       Date:  2014-08       Impact factor: 5.128

8.  Collaborative, pooled and harmonized study designs for epidemiologic research: challenges and opportunities.

Authors:  Catherine R Lesko; Lisa P Jacobson; Keri N Althoff; Alison G Abraham; Stephen J Gange; Richard D Moore; Sharada Modur; Bryan Lau
Journal:  Int J Epidemiol       Date:  2018-04-01       Impact factor: 7.196

9.  A modular, prospective, semi-automated drug safety monitoring system for use in a distributed data environment.

Authors:  Joshua J Gagne; Shirley V Wang; Jeremy A Rassen; Sebastian Schneeweiss
Journal:  Pharmacoepidemiol Drug Saf       Date:  2014-04-30       Impact factor: 2.890

Review 10.  Analytic and Data Sharing Options in Real-World Multidatabase Studies of Comparative Effectiveness and Safety of Medical Products.

Authors:  Sengwee Toh
Journal:  Clin Pharmacol Ther       Date:  2020-01-24       Impact factor: 6.875

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.