Title

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

Authors

Francesco Chiappelli^1,2,3,4*, Vandan R. Kasar⁵, Nicole Balenton^1,3, Allen Khakshooy^1,6

Affiliation

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

Email

fchiappelli@dentistry.ucla.edu;

Article Type

Review

Date

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.

Keywords

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

Citation

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

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

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.