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Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: a protocol
Evan Mayo-Wilson1, Susan Hutfless2,3, Tianjing Li2
1Center for Clinical Trials and Evidence Synthesis, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD, 21205, USA. evan.mayo-wilson@jhu.edu.
Systematic Reviews
|November 4, 2015
Summary
Systematic reviews face challenges from selective reporting. This study develops methods to integrate multiple data sources for more reliable evidence on gabapentin and quetiapine effectiveness.
Area of Science:
- Clinical Medicine
- Evidence-Based Medicine
- Pharmacology
Background:
- Systematic reviews are crucial for decision-making but face credibility issues due to selective reporting of trial results.
- Incomplete publication of trials and selective reporting of outcomes undermine the reliability of systematic reviews.
- Lack of established methods for selecting among multiple data sources for the same trial complicates systematic review processes.
Purpose of the Study:
- To conduct systematic reviews on the effectiveness and safety of gabapentin for neuropathic pain and quetiapine for bipolar depression.
- To develop and apply methods for integrating diverse data sources, including published and unpublished trial data, into systematic reviews.
- To assess the impact of including multiple data sources on the results of systematic reviews and identify patient-centered outcomes.
Main Methods:
- Systematic reviews following Institute of Medicine guidelines for gabapentin and quetiapine.
- Highly sensitive electronic searches with dual independent reviewer assessment of results.
- Extraction and analysis of data from multiple sources, including published articles, conference abstracts, clinical study reports, and individual participant data, using meta-analysis.
Main Results:
- The study will compare results from meta-analyses using different data source combinations.
- Differences in the reporting of patient-centered outcomes across various data sources will be identified.
- The impact of integrating diverse data sources on the synthesized evidence will be evaluated.
Conclusions:
- Establishing robust methods for data synthesis is essential for enhancing the trustworthiness of systematic reviews.
- This research aims to provide a framework for more comprehensive and reliable evidence synthesis in medical research.
- The findings will contribute to improved decision-making for treatments like gabapentin and quetiapine.
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