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Open Access Research article

Concordance between decision analysis and matching systematic review of randomized controlled trials in assessment of treatment comparisons: a systematic review

Rahul S Mhaskar, Hesborn Wao*, Helen Mahony, Ambuj Kumar and Benjamin Djulbegovic

Author Affiliations

Department of Internal Medicine, Division of Evidence Based Medicine and Outcomes Research, Morsani College of Medicine, University of South Florida, Tampa, FL, USA

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BMC Medical Informatics and Decision Making 2014, 14:57  doi:10.1186/1472-6947-14-57

Published: 15 July 2014

Abstract

Background

Systematic review (SR) of randomized controlled trials (RCT) is the gold standard for informing treatment choice. Decision analyses (DA) also play an important role in informing health care decisions. It is unknown how often the results of DA and matching SR of RCTs are in concordance. We assessed whether the results of DA are in concordance with SR of RCTs matched on patient population, intervention, control, and outcomes.

Methods

We searched PubMed up to 2008 for DAs comparing at least two interventions followed by matching SRs of RCTs. Data were extracted on patient population, intervention, control, and outcomes from DAs and matching SRs of RCTs. Data extraction from DAs was done by one reviewer and from SR of RCTs by two independent reviewers.

Results

We identified 28 DAs representing 37 comparisons for which we found matching SR of RCTs. Results of the DAs and SRs of RCTs were in concordance in 73% (27/37) of cases. The sensitivity analyses conducted in either DA or SR of RCTs did not impact the concordance. Use of single (4/37) versus multiple data source (33/37) in design of DA model was statistically significantly associated with concordance between DA and SR of RCTs.

Conclusions

Our findings illustrate the high concordance of current DA models compared with SR of RCTs. It is shown previously that there is 50% concordance between DA and matching single RCT. Our study showing the concordance of 73% between DA and matching SR of RCTs underlines the importance of totality of evidence (i.e. SR of RCTs) in the design of DA models and in general medical decision-making.