Literature DB >> 7407321

Why data bases should not replace randomized clinical trials.

D P Byar.   

Abstract

Advances in computer technology have made it possible to store large amounts of observational data concerning treatment of patients for medical disorders. It has been suggested that these data banks might replace randomized clinical trials as a means of evaluating the efficacy of therapies. A review of the methodological problems likely to arise in analyzing such data for the purpose of comparing treatments suggests that sound inferences would not generally be possible because of difficulties with bias in treatment assignment, nonstandard definitions, definitions changing in time, specification of groups to be compared, missing data, and multiple comparisons.

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Year:  1980        PMID: 7407321

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  27 in total

1.  Dynamic random effects models for times between repeated events.

Authors:  D Y Fong; K F Lam; J F Lawless; Y W Lee
Journal:  Lifetime Data Anal       Date:  2001-12       Impact factor: 1.588

2.  Has adjuvant treatment of breast cancer had an unfair trial?

Authors:  I Mittra
Journal:  BMJ       Date:  1990-12-08

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

Review 4.  Randomised placebo controlled trials in HIV infection: to be or not to be?

Authors:  K Gelmon; I V Weller
Journal:  Genitourin Med       Date:  1989-06

5.  Six paths for the future of social epidemiology.

Authors:  Sandro Galea; Bruce G Link
Journal:  Am J Epidemiol       Date:  2013-09-05       Impact factor: 4.897

Review 6.  A framework for the analysis of heterogeneity of treatment effect in patient-centered outcomes research.

Authors:  Ravi Varadhan; Jodi B Segal; Cynthia M Boyd; Albert W Wu; Carlos O Weiss
Journal:  J Clin Epidemiol       Date:  2013-05-04       Impact factor: 6.437

7.  Assessing prognosis from nonrandomized studies: an example from brain arteriovenous malformations.

Authors:  J Raymond; O Naggara; F Guilbert; D G Altman
Journal:  AJNR Am J Neuroradiol       Date:  2011-04-14       Impact factor: 3.825

8.  Unruptured intracranial aneurysms: why clinicians should not resort to epidemiologic studies to justify interventions.

Authors:  J Raymond; T E Darsaut; M Kotowski; M W Bojanowski
Journal:  AJNR Am J Neuroradiol       Date:  2011-09-08       Impact factor: 3.825

9.  An introduction to the fundamentals of cohort and case-control studies.

Authors:  John-Michael Gamble
Journal:  Can J Hosp Pharm       Date:  2014-09

Review 10.  Addressing multimorbidity in evidence integration and synthesis.

Authors:  Thomas A Trikalinos; Jodi B Segal; Cynthia M Boyd
Journal:  J Gen Intern Med       Date:  2014-01-18       Impact factor: 5.128

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