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Quantitative Consensus in Systematic Reviews: Current and Future Challenges in Translational Science



Francesco Chiappelli1,2,3,4*, Vandan R. Kasar5, Nicole Balenton1,3, Allen Khakshooy1,6



1Laboratory of Human Psychoneuroendocrine-Osteoimmunology; School of Dentistry, UCLA Center for the Health Sciences, Los Angeles, CA 90095-1668;

2Evidence-Based Decision Practice-Based Research Network, DGSO, Los Angeles, CA 91403;

3Department of the Health Sciences, CSUN, Northridge, CA 91330;

4Dental Group of Sherman Oaks, Los Angeles CA 91403;

5School of Dentistry, UCSF Center for the Health Sciences, San Francisco, CA 94143;

6Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel 3109601




Article Type




Received February 16, 2018; Revised February 20, 2018; Accepted February 20, 2018; Published February 28, 2018



Translational science conceptualizes healthcare as a concerted set of processes that integrate research findings from the bench to the bedside. This model of healthcare is effectiveness-focused, patient-centered, and evidence-based, and yields evidence-based revisions of practice-based guidelines, which emerge from research synthesis protocols in comparative effectiveness research that are disseminated in systematic reviews. Systematic reviews produce qualitative and quantitative consensi of the best available evidence. The quantitative consensus is derived from meta-analysis protocols that are often achieved by probabilistic approach Bayesian statistical models.



Translational science, research synthesis, PICOTS question, complex systematic reviews, meta-analysis, Bayesian statistics, additive meta-analysis



Chiappeli et al. Bioinformation 14(2): 86-92 (2018)


Edited by

P Kangueane






Biomedical Informatics



This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.