Literature DB >> 33731727

Systematic differences in effect estimates between observational studies and randomized control trials in meta-analyses in nephrology.

Miho Kimachi1, Akira Onishi2, Aran Tajika3, Kimihiko Kimachi4, Toshi A Furukawa5.   

Abstract

The limited availability of randomized controlled trials (RCTs) in nephrology undermines causal inferences in meta-analyses. Systematic reviews of observational studies have grown more common under such circumstances. We conducted systematic reviews of all comparative observational studies in nephrology from 2006 to 2016 to assess the trends in the past decade. We then focused on the meta-analyses combining observational studies and RCTs to evaluate the systematic differences in effect estimates between study designs using two statistical methods: by estimating the ratio of odds ratios (ROR) of the pooled OR obtained from observational studies versus those from RCTs and by examining the discrepancies in their statistical significance. The number of systematic reviews of observational studies in nephrology had grown by 11.7-fold in the past decade. Among 56 records combining observational studies and RCTs, ROR suggested that the estimates between study designs agreed well (ROR 1.05, 95% confidence interval 0.90-1.23). However, almost half of the reviews led to discrepant interpretations in terms of statistical significance. In conclusion, the findings based on ROR might encourage researchers to justify the inclusion of observational studies in meta-analyses. However, caution is needed, as the interpretations based on statistical significance were less concordant than those based on ROR.

Entities:  

Year:  2021        PMID: 33731727      PMCID: PMC7971062          DOI: 10.1038/s41598-021-85519-5

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  41 in total

1.  Current methods of the US Preventive Services Task Force: a review of the process.

Authors:  R P Harris; M Helfand; S H Woolf; K N Lohr; C D Mulrow; S M Teutsch; D Atkins
Journal:  Am J Prev Med       Date:  2001-04       Impact factor: 5.043

2.  Development of the RTI item bank on risk of bias and precision of observational studies.

Authors:  Meera Viswanathan; Nancy D Berkman
Journal:  J Clin Epidemiol       Date:  2011-09-29       Impact factor: 6.437

3.  Assessment of vibration of effects due to model specification can demonstrate the instability of observational associations.

Authors:  Chirag J Patel; Belinda Burford; John P A Ioannidis
Journal:  J Clin Epidemiol       Date:  2015-06-06       Impact factor: 6.437

Review 4.  Evaluating non-randomised intervention studies.

Authors:  J J Deeks; J Dinnes; R D'Amico; A J Sowden; C Sakarovitch; F Song; M Petticrew; D G Altman
Journal:  Health Technol Assess       Date:  2003       Impact factor: 4.014

Review 5.  Systematic review and meta-analysis: when one study is just not enough.

Authors:  Amit X Garg; Dan Hackam; Marcello Tonelli
Journal:  Clin J Am Soc Nephrol       Date:  2008-01       Impact factor: 8.237

6.  Randomized and observational studies in nephrology: how strong is the evidence?

Authors:  Tom Greene
Journal:  Am J Kidney Dis       Date:  2009-01-29       Impact factor: 8.860

7.  Observational studies in systematic [corrected] reviews of comparative effectiveness: AHRQ and the Effective Health Care Program.

Authors:  Susan L Norris; David Atkins; Wendy Bruening; Steven Fox; Eric Johnson; Robert Kane; Sally C Morton; Mark Oremus; Maria Ospina; Gurvaneet Randhawa; Karen Schoelles; Paul Shekelle; Meera Viswanathan
Journal:  J Clin Epidemiol       Date:  2011-06-01       Impact factor: 6.437

8.  Trial quality in nephrology: how are we measuring up?

Authors:  Suetonia C Palmer; Michela Sciancalepore; Giovanni F M Strippoli
Journal:  Am J Kidney Dis       Date:  2011-09       Impact factor: 8.860

9.  Five Steps to Successfully Implement and Evaluate Propensity Score Matching in Clinical Research Studies.

Authors:  Steven J Staffa; David Zurakowski
Journal:  Anesth Analg       Date:  2018-10       Impact factor: 5.108

Review 10.  Meta-analyses of adverse effects data derived from randomised controlled trials as compared to observational studies: methodological overview.

Authors:  Su Golder; Yoon K Loke; Martin Bland
Journal:  PLoS Med       Date:  2011-05-03       Impact factor: 11.069

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