Evidence map›Paper›PMID 40791692›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Incorporating Preprints in Systematic Reviews: A Preliminary Study of a Novel Method for Rapid Evidence Synthesis.

Jiayi Tong, Yifei Sun, Rebecca A Hubbard, M Elle Saine, Hua Xu, Xu Zuo, Lifeng Lin, Chunhua Weng, Christopher Schmid, Stephen E Kimmel and 3 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Jiayi TongThe Center for Health AI and Synthesis of Evidence (CHASE), Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA.
Yifei SunDepartment of Biostatistics, Columbia University, New York City, NY, USA.
Rebecca A HubbardDepartment of Biostatistics, Brown University School of Public Health, Providence, RI, USA.
M Elle SaineDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA.
Hua XuDepartmnet of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, USA.
Xu ZuoSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Lifeng LinDepartment of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA.
Chunhua WengDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.
Christopher SchmidDepartment of Biostatistics, Brown University School of Public Health, Providence, RI, USA.
Stephen E KimmelDepartment of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA.
Craig A UmscheidCenter for Evidence and Practice Improvement, Agency for Healthcare Research and Quality, Rockville, MD, USA.
Adam CukerDepartment of Medicine and Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Yong ChenThe Center for Health AI and Synthesis of Evidence (CHASE), Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0003-0835-0788

Funding

Coordinating Individually Measured Phenotypes to Advance Mental Health ResearchU24MH136069 · NIMH · YALE UNIVERSITY · PI Yong Chen, Cui Tao · 2024 to 2026
$9.8M
PANDA-MSD: Predictive Analytics via Networked Distributed Algorithms for Multi-System DiseasesU01TR003709 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI BIAN, JIANG, CHEN, YONG · 2022 to 2025
$4.7M
TRiPOD: Toward Reusable Phenotypes in Observational Data for AD/ADRD - managing definitions and correcting biasR01AG073435 · NIA · UNIVERSITY OF PENNSYLVANIA · PI CHEN, YONG, XU, HUA · 2021 to 2025
$3.9M
Dynamic learning for post-vaccine event prediction using temporal information in VAERSR01AI130460 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI CHEN, YONG, TAO, CUI · 2017 to 2021
$3.4M
ClinEX - Clinical Evidence Extraction, Representation, and AppraisalR01LM014344 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Yong Chen, Yifan Peng · 2023 to 2026
$2.7M
Novel evidence-accumulation-driven methods for characterizing kidney stone progressionR01DK128237 · NIDDK · UT SOUTHWESTERN MEDICAL CENTER · PI LIU, YU-LUN · 2022 to 2025
$2.7M
AI-ADRD: Accelerating interventions of AD/ADRD via Machine learning methodsRF1AG077820 · NIA · UNIVERSITY OF PENNSYLVANIA · PI BIAN, JIANG, CHEN, YONG · 2023 to 2023
$2.3M
PheBC: bias correction methods for EHR derived phenotypeR01LM013519 · NLM · UNIVERSITY OF PENNSYLVANIA · PI CHEN, YONG, XU, HUA · 2021 to 2024
$1.6M
Advancing Drug Repositioning for Alzheimer’s Disease using Real-world DataR56AG069880 · NIA · UNIVERSITY OF FLORIDA · PI BIAN, JIANG, CHEN, YONG · 2021 to 2022
$1.6M
CICADA: clinical informatics and computational approaches for drug-repositioning of AD/ADRDR56AG074604 · NIA · UNIVERSITY OF PENNSYLVANIA · PI CHEN, YONG, TAO, CUI · 2021 to 2022
$1.5M
A General Framework to Account for Outcome Reporting Bias in Systematic ReviewsR01LM012607 · NLM · UNIVERSITY OF PENNSYLVANIA · PI CHEN, YONG · 2017 to 2020
$1.4M
AI-ADRD: Accelerating interventions of AD/ADRD via Machine learning methodsR01AG077820 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Jiang Bian, Yong Chen · 2026 to 2026
$737k
NCATS NIH HHS U01 TR003709NEI NIH HHS R21 EY034179NIAID NIH HHS R01 AI130460NIAID NIH HHS R21 AI167418NIA NIH HHS R01 AG073435NIA NIH HHS R01 AG077820NIA NIH HHS R56 AG069880NIA NIH HHS R56 AG074604NIA NIH HHS RF1 AG077820NIDDK NIH HHS R01 DK128237NIMH NIH HHS U24 MH136069NLM NIH HHS R01 LM012607NLM NIH HHS R01 LM013519NLM NIH HHS R01 LM014344
6 · The paper itself

Abstract

Objectives: By October 1, 2024, over 450,000 COVID-19 manuscripts were published, with 10% posted as unreviewed preprints. While they accelerate knowledge sharing, their inconsistent quality complicates systematic studies. Materials and Methods: We propose a two-stage method to include preprints in meta-analyses. In Stage A, preprints are integrated through restriction or imputation and weighted by a confidence score reflecting their publication likelihood. In Stage B, we assess and adjust for potential publication or reporting biases. Results: This preliminary study employed a two-stage procedure validated with two COVID-19 treatment case studies. For hydroxychloroquine, the relative risk (RR) was 1.06 [95% CI: 0.62, 1.80], suggesting no mortality benefit over placebo. For corticosteroids, the RR was 0.88 [95% CI: 0.62, 1.27], which, while not statistically significant, aligns with evidence supporting a mortality benefit. Discussion: Our research aims to bridge a significant methodological gap by providing a solution for timely evidence synthesis, particularly in the face of the overwhelming number of publications surrounding COVID-19. Conclusion: This preliminary study presents a method to efficiently synthesize COVID-19 research, including non-peer-reviewed preprints, to support clinical and policy decisions amidst the information surge.

Indexed as

COVID-19evidence synthesisliving systematic reviewpreprintspublication bias

Identifiers

PMID40791692
PMCPMC12338926

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.