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Incorporating Preprints in Systematic Reviews: A Preliminary Study of a Novel Method for Rapid Evidence Synthesis
Jiayi Tong1,2,3, Yifei Sun4, Rebecca A Hubbard5
1The Center for Health AI and Synthesis of Evidence (CHASE), Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA.
This study introduces a two-stage method to incorporate COVID-19 preprints into meta-analyses, improving evidence synthesis for critical health decisions. The approach addresses the challenge of inconsistent preprint quality in rapid research dissemination.
Area of Science:
- Medical Research
- Evidence Synthesis
- Biostatistics
Background:
- Over 450,000 COVID-19 manuscripts exist, with 10% as unreviewed preprints.
- Preprints accelerate knowledge sharing but have variable quality, complicating systematic reviews.
- Timely evidence synthesis is crucial for clinical and policy decisions during health crises.
Purpose of the Study:
- To develop and validate a method for including preprints in meta-analyses.
- To address the methodological gap in synthesizing rapidly emerging research.
- To support informed decision-making amidst a surge of scientific publications.
Main Methods:
- A two-stage approach for integrating preprints into meta-analyses.
- Stage A: Preprint integration via restriction/imputation with confidence weighting.
- Stage B: Assessment and adjustment for publication and reporting biases.
Main Results:
- Preliminary validation using two COVID-19 treatment case studies.
- Hydroxychloroquine showed no mortality benefit (RR 1.06 [95% CI: 0.62, 1.80]).
- Corticosteroids suggested a potential mortality benefit (RR 0.88 [95% CI: 0.62, 1.27]), aligning with existing evidence.
Conclusions:
- The proposed method efficiently synthesizes COVID-19 research, including preprints.
- This approach aids clinical and policy decisions by providing timely, synthesized evidence.
- The method offers a solution for managing the overwhelming volume of scientific literature.
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