Literature DB >> 23070833

A new "Comparative Effectiveness" assessment strategy using the THIN database: comparison of the cardiac complications of pioglitazone and rosiglitazone.

Richard Tannen1, Dawei Xie, Xingmei Wang, Menggang Yu, Mark G Weiner.   

Abstract

PURPOSE: Examine feasibility of a new strategy to perform Electronic Medical Record database valid Comparative Effectiveness Research (CER), using determination of whether rosiglitazone (ROS) treatment increases Acute myocardial infarction (MI) in comparison to pioglitazone (PIO) as a model question.
METHODS: Using the UK The Health Improvement Network Database, a retrospective cohort design replicated the proactive RCT of diabetics with ischemic cardiovascular disease (CVD). Replication studies using PIO or ROS, as well as expanded studies of subjects not requiring CVD, were performed. MI assessment used multiple analytics comparing ROS and PIO exposed patients including: unexposed subjects, the proactive RCT, and directly between ROS to PIO exposed cohorts.
RESULTS: PIO replication studies did not affect MI [HR 0.88 (0.49 to 1.42)], but ROS increased MI, with prior event rate ratio (PERR) adjusted HR (which overcomes unmeasured confounding) results of: [HR 1.31 (0.94 to 1.74)] versus proactive RCT [HR 0.83 (0.65 to 1.06)] (p = 0.02). Direct ROS to PIO exposed cohort comparisons yielded PERR adj HR of 1.55 (0.98 to 2.65). By contrast, expanded studies showed no differences between ROS and PIO exposure.
CONCLUSIONS: These results provide new insight regarding the effects of ROS and PIO on MI. In a population with established ischemic CVD, ROS increased MI in contrast to PIO; whereas in an unselected population, ROS and PIO have reasonably comparable effects. Most importantly, this study demonstrates the feasibility and advantages of a new strategy to perform reliable "CER" using an EMR database.
Copyright © 2012 John Wiley & Sons, Ltd.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 23070833     DOI: 10.1002/pds.3360

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


  12 in total

Review 1.  Methods to control for unmeasured confounding in pharmacoepidemiology: an overview.

Authors:  Md Jamal Uddin; Rolf H H Groenwold; Mohammed Sanni Ali; Anthonius de Boer; Kit C B Roes; Muhammad A B Chowdhury; Olaf H Klungel
Journal:  Int J Clin Pharm       Date:  2016-04-18

2.  Risk prediction for heterogeneous populations with application to hospital admission prediction.

Authors:  Jared D Huling; Menggang Yu; Muxuan Liang; Maureen Smith
Journal:  Biometrics       Date:  2017-10-26       Impact factor: 2.571

3.  Do we still need pioglitazone for the treatment of type 2 diabetes? A risk-benefit critique in 2013.

Authors:  Guntram Schernthaner; Craig J Currie; Gerit-Holger Schernthaner
Journal:  Diabetes Care       Date:  2013-08       Impact factor: 19.112

4.  Can analyses of electronic patient records be independently and externally validated? The effect of statins on the mortality of patients with ischaemic heart disease: a cohort study with nested case-control analysis.

Authors:  David Reeves; David A Springate; Darren M Ashcroft; Ronan Ryan; Tim Doran; Richard Morris; Ivan Olier; Evangelos Kontopantelis
Journal:  BMJ Open       Date:  2014-04-23       Impact factor: 2.692

5.  Pathways targeted by antidiabetes drugs are enriched for multiple genes associated with type 2 diabetes risk.

Authors:  Ayellet V Segrè; Nancy Wei; David Altshuler; Jose C Florez
Journal:  Diabetes       Date:  2014-11-03       Impact factor: 9.461

Review 6.  The risk of heart failure associated with the use of noninsulin blood glucose-lowering drugs: systematic review and meta-analysis of published observational studies.

Authors:  Cristina Varas-Lorenzo; Andrea V Margulis; Manel Pladevall; Nuria Riera-Guardia; Brian Calingaert; Lorna Hazell; Silvana Romio; Susana Perez-Gutthann
Journal:  BMC Cardiovasc Disord       Date:  2014-09-26       Impact factor: 2.298

7.  Prior event rate ratio adjustment for hidden confounding in observational studies of treatment effectiveness: a pairwise Cox likelihood approach.

Authors:  Nan Xuan Lin; William Edward Henley
Journal:  Stat Med       Date:  2016-08-01       Impact factor: 2.373

8.  A new method to address unmeasured confounding of mortality in observational studies.

Authors:  Richard Tannen; Menggang Yu
Journal:  Learn Health Syst       Date:  2016-12-14

9.  Current clinical evidence on pioglitazone pharmacogenomics.

Authors:  Marina Kawaguchi-Suzuki; Reginald F Frye
Journal:  Front Pharmacol       Date:  2013-11-26       Impact factor: 5.810

10.  Cardiovascular risk associated with the use of glitazones, metformin and sufonylureas: meta-analysis of published observational studies.

Authors:  Manel Pladevall; Nuria Riera-Guardia; Andrea V Margulis; Cristina Varas-Lorenzo; Brian Calingaert; Susana Perez-Gutthann
Journal:  BMC Cardiovasc Disord       Date:  2016-01-15       Impact factor: 2.298

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.