Literature DB >> 29854151

Comparing and Contrasting A Priori and A Posteriori Generalizability Assessment of Clinical Trials on Type 2 Diabetes Mellitus.

Zhe He1, Arturo Gonzalez-Izquierdo2, Spiros Denaxas2, Andrei Sura3, Yi Guo3, William R Hogan3, Elizabeth Shenkman3, Jiang Bian3.   

Abstract

Clinical trials are indispensable tools for evidence-based medicine. However, they are often criticized for poor generalizability. Traditional trial generalizability assessment can only be done after the trial results are published, which compares the enrolled patients with a convenience sample of real-world patients. However, the proliferation of electronic data in clinical trial registries and clinical data warehouses offer a great opportunity to assess the generalizability during the design phase of a new trial. In this work, we compared and contrasted a priori (based on eligibility criteria) and a posteriori (based on enrolled patients) generalizability of Type 2 diabetes clinical trials. Further, we showed that comparing the study population selected by the clinical trial eligibility criteria to the real-world patient population is a good indicator of the generalizability of trials. Our findings demonstrate that the a priori generalizability of a trial is comparable to its a posteriori generalizability in identifying restrictive quantitative eligibility criteria.

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Year:  2018        PMID: 29854151      PMCID: PMC5977671     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  24 in total

Review 1.  Trends in development and approval times for new therapeutics in the United States.

Authors:  Janice M Reichert
Journal:  Nat Rev Drug Discov       Date:  2003-09       Impact factor: 84.694

2.  A distribution-based method for assessing the differences between clinical trial target populations and patient populations in electronic health records.

Authors:  C Weng; Y Li; P Ryan; Y Zhang; F Liu; J Gao; J T Bigger; G Hripcsak
Journal:  Appl Clin Inform       Date:  2014-05-07       Impact factor: 2.342

3.  Underrepresentation of women, elderly patients, and racial minorities in the randomized trials used for cardiovascular guidelines.

Authors:  Muhammad Rizwan Sardar; Marwan Badri; Catherine T Prince; Jonathan Seltzer; Peter R Kowey
Journal:  JAMA Intern Med       Date:  2014-11       Impact factor: 21.873

4.  Trial Reporting in ClinicalTrials.gov - The Final Rule.

Authors:  Deborah A Zarin; Tony Tse; Rebecca J Williams; Sarah Carr
Journal:  N Engl J Med       Date:  2016-09-16       Impact factor: 91.245

5.  Computer-aided assessment of the generalizability of clinical trial results.

Authors:  Amos Cahan; Sorel Cahan; James J Cimino
Journal:  Int J Med Inform       Date:  2017-01-06       Impact factor: 4.046

6.  Optimizing Clinical Research Participant Selection with Informatics.

Authors:  Chunhua Weng
Journal:  Trends Pharmacol Sci       Date:  2015-11       Impact factor: 14.819

7.  Generalizability of clinical trial results for major depression to community samples: results from the National Epidemiologic Survey on Alcohol and Related Conditions.

Authors:  Carlos Blanco; Mark Olfson; Renee D Goodwin; Elizabeth Ogburn; Michael R Liebowitz; Edward V Nunes; Deborah S Hasin
Journal:  J Clin Psychiatry       Date:  2008-08       Impact factor: 4.384

8.  Defining disease phenotypes using national linked electronic health records: a case study of atrial fibrillation.

Authors:  Katherine I Morley; Joshua Wallace; Spiros C Denaxas; Ross J Hunter; Riyaz S Patel; Pablo Perel; Anoop D Shah; Adam D Timmis; Richard J Schilling; Harry Hemingway
Journal:  PLoS One       Date:  2014-11-04       Impact factor: 3.240

9.  Type 2 diabetes and incidence of a wide range of cardiovascular diseases: a cohort study in 1·9 million people.

Authors:  Anoop Dinesh Shah; Claudia Langenberg; Eleni Rapsomaniki; Spiros Denaxas; Mar Pujades-Rodriguez; Chris P Gale; John Deanfield; Liam Smeeth; Adam Timmis; Harry Hemingway
Journal:  Lancet       Date:  2015-02-26       Impact factor: 79.321

10.  Data resource profile: cardiovascular disease research using linked bespoke studies and electronic health records (CALIBER).

Authors:  Spiros C Denaxas; Julie George; Emily Herrett; Anoop D Shah; Dipak Kalra; Aroon D Hingorani; Mika Kivimaki; Adam D Timmis; Liam Smeeth; Harry Hemingway
Journal:  Int J Epidemiol       Date:  2012-12-05       Impact factor: 7.196

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  3 in total

Review 1.  Contemporary use of real-world data for clinical trial conduct in the United States: a scoping review.

Authors:  James R Rogers; Junghwan Lee; Ziheng Zhou; Ying Kuen Cheung; George Hripcsak; Chunhua Weng
Journal:  J Am Med Inform Assoc       Date:  2021-01-15       Impact factor: 4.497

2.  Exploring the feasibility of using real-world data from a large clinical data research network to simulate clinical trials of Alzheimer's disease.

Authors:  Zhaoyi Chen; Hansi Zhang; Yi Guo; Thomas J George; Mattia Prosperi; William R Hogan; Zhe He; Elizabeth A Shenkman; Fei Wang; Jiang Bian
Journal:  NPJ Digit Med       Date:  2021-05-14

3.  How the clinical research community responded to the COVID-19 pandemic: an analysis of the COVID-19 clinical studies in ClinicalTrials.gov.

Authors:  Zhe He; Arslan Erdengasileng; Xiao Luo; Aiwen Xing; Neil Charness; Jiang Bian
Journal:  JAMIA Open       Date:  2021-04-20
  3 in total

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