PP118 A Survival Analysis Of The Lag Times In The Publication Of Network Meta-Analyses

Abstract

Introduction

The use of inconsistent and outdated information may significantly compromise healthcare decision-making. We aimed to assess the extent of lag times in the publication and indexing of network meta-analyses (NMAs).

Methods

Searches for NMAs on drug interventions were performed in PubMed (May 2020). Lag times were measured as the time between the last systematic search and the date of the article's submission, acceptance, online publication, indexing, and Medical Subject Heading (MeSH) allocation. Correlations between lag times and time trends were calculated by means of Spearman's rank correlation coefficient. Time-to-event analyses were performed considering independent variables such as geographical origin, journal impact factor, Scopus CiteScore, and open access status.

Results

We included 1,245 NMAs. The median time from last search to article submission and publication was 6.8 months and 11.6 months, respectively. Only five percent of authors updated their literature searches after submission. There was a very slight decreasing historical trend for acceptance (r =−0.087; p = 0.01), online publication (r =−0.08; p = 0.008), and indexing lag times (r =−0.080; p = 0.007). Journal impact factor influenced the MeSH allocation process (log-rank p = 0.02). Slight differences were observed for acceptance, online publication, and indexing lag times when comparing open access and subscription journals.

Conclusions

Authors need to update their literature searches before submission to reduce evidence production time. Peer reviewers and editors should ensure that authors comply with NMA standards and encourage the development of living meta-analyses.