Evidence map›Paper›PMID 35996832›Full record

SynthesisPharmacoepidemiology and drug safety2022

A systematic review of whether COVID-19 randomized controlled trials reported on demographic and clinical characteristics.

Joyce Pak, Jennifer L Lund, Alexander Keil, Daniel Westreich, Til Stürmer, David Wohl, Claire Farel, M Bradley Drummond, Michael Webster-Clark

Abstract readSystematic Review
In one paragraph

Synthesis in Pharmacoepidemiology and drug safety, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Joyce PakDepartment of Epidemiology, UNC Gillings School of Global Public health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0003-2443-7971
Jennifer L LundDepartment of Epidemiology, UNC Gillings School of Global Public health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0002-1108-0689
Alexander KeilDepartment of Epidemiology, UNC Gillings School of Global Public health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Daniel WestreichDepartment of Epidemiology, UNC Gillings School of Global Public health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Til StürmerDepartment of Epidemiology, UNC Gillings School of Global Public health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0002-9204-7177
David WohlDepartment of Medicine, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Claire FarelDepartment of Medicine, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
M Bradley DrummondDepartment of Medicine, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Michael Webster-ClarkDepartment of Epidemiology, UNC Gillings School of Global Public health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Funding

Propensity scores and preventive drug use in the elderlyR01AG056479 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Til Sturmer · 2017 to 2026
$5.0M
NIA NIH HHS R01 AG056479
6 · The paper itself

Abstract

purposeWe aim to assess the reporting of key patient-level demographic and clinical characteristics among COVID-19 related randomized controlled trials (RCTs).

methodsWe queried English-language articles from PubMed, Web of Science, clinicaltrials.gov, and the CDC library of gray literature databases using keywords of "coronavirus," "covid," "clinical trial" and "randomized controlled trial" from January 2020 to June 2021. From the search, we conducted an initial review to rule-out duplicate entries, identify those that met inclusion criteria (i.e., had results), and exclude those that did not meet the definition of an RCT. Lastly, we abstracted the demographic and clinical characteristics reported on within each RCT.

resultsFrom the initial 43 627 manuscripts, our final eligible manuscripts consisted of 149 RCTs described in 137 articles. Most of the RCTs (113/149) studied potential treatments, while fewer studied vaccines (29), prophylaxis strategies (5), and interventions to prevent transmission among those infected (2). Study populations ranged from 10 to 38 206 participants (median = 100, IQR: 60-300). All 149 RCTs reported on age, 147 on sex, 50 on race, and 110 on the prevalence of at least one comorbidity. No RCTs reported on income, urban versus rural residence, or other indicators of socioeconomic status (SES).

conclusionsLimited reporting on race and other markers of SES make it difficult to draw conclusions about specific external target populations without making strong assumptions that treatment effects are homogenous. These findings highlight the need for more robust reporting on the clinical and demographic profiles of patients enrolled in COVID-19 related RCTs.

Indexed as

COVID-19Aged, 80 and overDemographyHumansRandomized Controlled Trials as TopicCOVID-19generalizabilityrandomized controlled trials

Identifiers

PMID35996832
PMCPMC9538362

What OpenQuestion holds

Textmetadata
LicenceTDM
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.