Related Experiment Video
Updated: May 12, 2026

In Silico Clinical Trials for Cardiovascular Disease
Published on: May 27, 2022
Publication lag in interventional, RCT-based meta-analyses within top-tier general medical journals and the CDSR: a
Jia Song1, Qin Wang1, Chongyang Zhao2
1Department of Evidence-Based Medicine and Clinical Epidemiology, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China.
Introduction:
Systematic reviews and meta-analyses serve as the cornerstone of clinical guidelines, yet their validity hinges on the currency of the included evidence. The publication lag measured as the interval from the last search date to online publication remains unclear in top-tier general medical journals and the Cochrane Database of Systematic Reviews (CDSR). Existing data are largely outdated and lack exploration of associated factors. Our study aims to fill this gap by quantifying the current publication lag in top-tier general medical journals and the CDSR and identifying its independent predictors.
Methods:
This meta-epidemiological study will analyze interventional, RCT-based meta-analyses published in top-tier general medical journals and the CDSR between 2023 and 2025. We will calculate the publication lag, assess compliance with AMSTAR 2 timeliness standards, and compare the performance between top-tier general medical journals and the CDSR. Multivariable regression analysis will be employed to determine independent factors which associated with the extent of publication delay.
Discussion:
Our study will systematically quantify the current status and determinants of publication lag in top-tier general medical journals and the CDSR. While our reliance on publicly available dates precludes a granular distinction between author-related revisions and editorial processing durations, this limitation may introduce information bias. Specifically, if certain journals attract more complex reviews requiring extensive author revisions, the observed lag may overstate editorial inefficiency. Conversely, high-performance editorial workflows might mask prolonged author delays. By acknowledging these potential directions of bias, our findings will provide a more nuanced, actionable framework for assessing evidence currency.
Systematic Review Registration:
https://osf.io/cjtk.
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