Literature DB >> 32193818

Benchmarking Observational Analyses Against Randomized Trials: a Review of Studies Assessing Propensity Score Methods.

Shaun P Forbes1,2, Issa J Dahabreh3,4,5.   

Abstract

BACKGROUND: Observational analysis methods can be refined by benchmarking against randomized trials. We reviewed studies systematically comparing observational analyses using propensity score methods against randomized trials to explore whether intervention or outcome characteristics predict agreement between designs.
METHODS: We searched PubMed (from January 1, 2000, to April 30, 2017), the AHRQ Scientific Resource Center Methods Library, reference lists, and bibliographies to identify systematic reviews that compared estimates from observational analyses using propensity scores against randomized trials across three or more clinical topics; reported extractable relative risk (RR) data; and were published in English. One reviewer extracted data from all eligible systematic reviews; a second reviewer verified the extracted data.
RESULTS: Six systematic reviews matching published observational studies to randomized trials, published between 2012 and 2016, met our inclusion criteria. The reviews reported on 127 comparisons overall, in cardiology (29 comparisons), surgery (49), critical care medicine and sepsis (46), nephrology (2), and oncology (1). Disagreements were large (relative RR < 0.7 or > 1.43) in 68 (54%) and statistically significant in 12 (9%) of the comparisons. The degree of agreement varied among reviews but was not strongly associated with intervention or outcome characteristics. DISCUSSION: Disagreements between observational studies using propensity score methods and randomized trials can occur for many reasons and the available data cannot be used to discern the reasons behind specific disagreements. Better benchmarking of observational analyses using propensity scores (and other causal inference methods) is possible using observational studies that explicitly attempt to emulate target trials.

Entities:  

Keywords:  benchmarking; comparative effectiveness; observational studies; propensity score; randomized controlled trials

Mesh:

Year:  2020        PMID: 32193818      PMCID: PMC7210373          DOI: 10.1007/s11606-020-05713-5

Source DB:  PubMed          Journal:  J Gen Intern Med        ISSN: 0884-8734            Impact factor:   5.128


  35 in total

1.  A comparison of observational studies and randomized, controlled trials.

Authors:  K Benson; A J Hartz
Journal:  N Engl J Med       Date:  2000-06-22       Impact factor: 91.245

2.  Prospective observational studies to assess comparative effectiveness: the ISPOR good research practices task force report.

Authors:  Marc L Berger; Nancy Dreyer; Fred Anderson; Adrian Towse; Art Sedrakyan; Sharon-Lise Normand
Journal:  Value Health       Date:  2012 Mar-Apr       Impact factor: 5.725

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.  The clinical trial as a paradigm for epidemiologic research.

Authors:  O S Miettinen
Journal:  J Clin Epidemiol       Date:  1989       Impact factor: 6.437

Review 5.  Healthcare outcomes assessed with observational study designs compared with those assessed in randomized trials.

Authors:  Andrew Anglemyer; Hacsi T Horvath; Lisa Bero
Journal:  Cochrane Database Syst Rev       Date:  2014-04-29

6.  Observational studies using propensity score analysis underestimated the effect sizes in critical care medicine.

Authors:  Zhongheng Zhang; Hongying Ni; Xiao Xu
Journal:  J Clin Epidemiol       Date:  2014-04-26       Impact factor: 6.437

Review 7.  The efficacy of psychological, educational, and behavioral treatment. Confirmation from meta-analysis.

Authors:  M W Lipsey; D B Wilson
Journal:  Am Psychol       Date:  1993-12

Review 8.  Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses.

Authors:  Miguel A Hernán; Brian C Sauer; Sonia Hernández-Díaz; Robert Platt; Ian Shrier
Journal:  J Clin Epidemiol       Date:  2016-05-27       Impact factor: 6.437

Review 9.  Randomisation to protect against selection bias in healthcare trials.

Authors:  R Kunz; G Vist; A D Oxman
Journal:  Cochrane Database Syst Rev       Date:  2007-04-18

10.  Agreement of treatment effects for mortality from routinely collected data and subsequent randomized trials: meta-epidemiological survey.

Authors:  Lars G Hemkens; Despina G Contopoulos-Ioannidis; John P A Ioannidis
Journal:  BMJ       Date:  2016-02-08
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Journal:  J Am Nutr Assoc       Date:  2021-09-02

2.  Do P2Y12 receptor inhibitors prescribed poststroke modify the risk of cognitive disorder or dementia? Protocol for a target trial using multiple national Swedish registries.

Authors:  Georg Hans Kuhn; Frederick R Walker; Michael Nilsson; Madeleine Hinwood; Jenny Nyberg; Lucy Leigh; Sara Gustavsson; John Attia; Christopher Oldmeadow; Marina Ilicic; Thomas Linden; N David Åberg; Chris Levi; Neil Spratt; Leeanne M Carey; Michael Pollack; Sarah J Johnson
Journal:  BMJ Open       Date:  2022-05-09       Impact factor: 3.006

Review 3.  Alcohol, Drinking Pattern, and Chronic Disease.

Authors:  María Barbería-Latasa; Alfredo Gea; Miguel A Martínez-González
Journal:  Nutrients       Date:  2022-05-07       Impact factor: 6.706

4.  Timing Is Everything. The Importance of Alignment of Time Anchors for Observational Causal Inference Research.

Authors:  Stephanie Parks Taylor; Marc A Kowalkowski; Andrew J Admon
Journal:  Ann Am Thorac Soc       Date:  2021-05

5.  Effects of ACE inhibitors and angiotensin receptor blockers: protocol for a UK cohort study using routinely collected electronic health records with validation against the ONTARGET trial.

Authors:  Paris J Baptiste; Angel Y S Wong; Anna Schultze; Marianne Cunnington; Johannes F E Mann; Catherine Clase; Clémence Leyrat; Laurie A Tomlinson; Kevin Wing
Journal:  BMJ Open       Date:  2022-03-08       Impact factor: 3.006

Review 6.  Comparative effectiveness and safety of pharmaceuticals assessed in observational studies compared with randomized controlled trials.

Authors:  Yoon Duk Hong; Jeroen P Jansen; John Guerino; Marc L Berger; William Crown; Wim G Goettsch; C Daniel Mullins; Richard J Willke; Lucinda S Orsini
Journal:  BMC Med       Date:  2021-12-06       Impact factor: 8.775

7.  Conducting Real-world Evidence Studies on the Clinical Outcomes of Diabetes Treatments.

Authors:  Sebastian Schneeweiss; Elisabetta Patorno
Journal:  Endocr Rev       Date:  2021-09-28       Impact factor: 19.871

  7 in total

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