# Accelerating evidence synthesis for safety assessment through ClinicalTrials.gov platform: a feasibility study

## TL;DR

This study explores using ClinicalTrials.gov to speed up safety evidence synthesis during public health emergencies.

## Contribution

The study demonstrates the feasibility of using ClinicalTrials.gov data for rapid meta-analysis of RCT safety outcomes.

## Key findings

- 56 out of 558 meta-analyses included RCTs not registered in ClinicalTrials.gov.
- Rapid meta-analyses using ClinicalTrials.gov achieved accurate point estimates in 77.4% to 83.1% of cases.
- 91.0% to 95.3% of rapid meta-analyses correctly predicted the direction of effects.

## Abstract

Standard systematic review can be labor-intensive and time-consuming meaning that it can be difficult to provide timely evidence when there is an urgent public health emergency such as a pandemic. The ClinicalTrials.gov provides a promising way to accelerate evidence production.

We conducted a search on PubMed to gather systematic reviews containing a minimum of 5 studies focused on safety aspects derived from randomized controlled trials (RCTs) of pharmacological interventions, aiming to establish a real-world dataset. The registration information of each trial from eligible reviews was further collected and verified. The meta-analytic data were then re-analyzed by using 1) the full meta-analytic data with all trials and 2) emulated rapid data with trials that had been registered and posted results on ClinicalTrials.gov, under the same synthesis methods. The effect estimates of the full meta-analysis and rapid meta-analysis were then compared.

The real-world dataset comprises 558 meta-analyses. Among them, 56 (10.0%) meta-analyses included RCTs that were not registered in ClinicalTrials.gov. For the remaining 502 meta-analyses, the median percentage of RCTs registered within each meta-analysis is 70.1% (interquartile range: 33.3% to 88.9%). Under a 20% bias threshold, rapid meta-analyses conducted through ClinicalTrials.gov achieved accurate point estimates ranging from 77.4% (using the MH model) to 83.1% (using the GLMM model); 91.0% to 95.3% of these analyses accurately predicted the direction of effects.

Utilizing the ClinicalTrials.gov platform for safety assessment with a minimum of 5 RCTs holds significant potential for accelerating evidence synthesis to support urgent decision-making.

The online version contains supplementary material available at 10.1186/s12874-024-02225-2.