Literature DB >> 23818199

Design and analysis of post-marketing research.

Xiao-Hua Andrew Zhou1, Wei Yang.   

Abstract

A post-marketing study is an integral part of research that helps to ensure a favorable risk-benefit profile for approved drugs used in the market. Because most of post-marketing studies use observational designs, which are liable to confounding, estimation of the causal effect of a drug versus a comparative one is very challenging. This article focuses on methodological issues of importance in designing and analyzing studies to evaluate the safety of marketed drugs, especially marketed traditional Chinese medicine (TCM) products. Advantages and limitations of the current designs and analytic methods for postmarketing studies are discussed, and recommendations are given for improving the validity of postmarketing studies in TCM products.

Mesh:

Substances:

Year:  2013        PMID: 23818199     DOI: 10.1007/s11655-013-1501-z

Source DB:  PubMed          Journal:  Chin J Integr Med        ISSN: 1672-0415            Impact factor:   1.978


  8 in total

1.  The U.S. Food and Drug Administration's Mini-Sentinel program: status and direction.

Authors:  Richard Platt; Ryan M Carnahan; Jeffrey S Brown; Elizabeth Chrischilles; Lesley H Curtis; Sean Hennessy; Jennifer C Nelson; Judith A Racoosin; Melissa Robb; Sebastian Schneeweiss; Sengwee Toh; Mark G Weiner
Journal:  Pharmacoepidemiol Drug Saf       Date:  2012-01       Impact factor: 2.890

2.  [Case study of Chinese medicine after listing of pharmacovigilance].

Authors:  Yongyang Xiang; Yanming Xie; Danhui Yi
Journal:  Zhongguo Zhong Yao Za Zhi       Date:  2011-10

3.  Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership.

Authors:  Paul E Stang; Patrick B Ryan; Judith A Racoosin; J Marc Overhage; Abraham G Hartzema; Christian Reich; Emily Welebob; Thomas Scarnecchia; Janet Woodcock
Journal:  Ann Intern Med       Date:  2010-11-02       Impact factor: 25.391

Review 4.  Potential for conflict of interest in the evaluation of suspected adverse drug reactions: use of cerivastatin and risk of rhabdomyolysis.

Authors:  Bruce M Psaty; Curt D Furberg; Wayne A Ray; Noel S Weiss
Journal:  JAMA       Date:  2004-11-22       Impact factor: 56.272

5.  Communication of findings in pharmacovigilance: use of the term "signal" and the need for precision in its use.

Authors:  Manfred Hauben; Lester Reich
Journal:  Eur J Clin Pharmacol       Date:  2005-07-01       Impact factor: 2.953

Review 6.  The role of data mining in pharmacovigilance.

Authors:  Manfred Hauben; David Madigan; Charles M Gerrits; Louisa Walsh; Eugene P Van Puijenbroek
Journal:  Expert Opin Drug Saf       Date:  2005-09       Impact factor: 4.250

7.  Confounding adjustment via a semi-automated high-dimensional propensity score algorithm: an application to electronic medical records.

Authors:  Sengwee Toh; Luis A García Rodríguez; Miguel A Hernán
Journal:  Pharmacoepidemiol Drug Saf       Date:  2011-06-30       Impact factor: 2.890

8.  High-dimensional propensity score adjustment in studies of treatment effects using health care claims data.

Authors:  Sebastian Schneeweiss; Jeremy A Rassen; Robert J Glynn; Jerry Avorn; Helen Mogun; M Alan Brookhart
Journal:  Epidemiology       Date:  2009-07       Impact factor: 4.822

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.