Evidence map›Paper›PMID 39920069›Full record

ArticleBMJ open2025

An analysis of controlled human infection studies registered on ClinicalTrials.gov.

Danny Toomey, Jupiter Adams-Phipps, James Wilkinson, John Pietro, Jake Littman, Steffen Kamenicek, Daniel Kaufman, Joshua Osowicki, Meta Roestenberg, Ian J Saldanha and 1 more

Abstract read
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

11 authors.

Danny Toomey1Day Sooner Research Team, Claymont, Delaware, USA.ORCID http://orcid.org/0000-0002-0329-5698
Jupiter Adams-Phipps1Day Sooner Research Team, Claymont, Delaware, USA.
James Wilkinson1Day Sooner Research Team, Claymont, Delaware, USA.
John Pietro1Day Sooner Research Team, Claymont, Delaware, USA.
Jake Littman1Day Sooner Research Team, Claymont, Delaware, USA.
Steffen Kamenicek1Day Sooner Research Team, Claymont, Delaware, USA.
Daniel Kaufman1Day Sooner Research Team, Claymont, Delaware, USA.
Joshua OsowickiTropical Diseases Research Group, Murdoch Children's Research Institute, Parkville, Victoria, Australia.ORCID http://orcid.org/0000-0002-9432-6700
Meta RoestenbergLeiden University Medical Center, Center for Infectious Diseases, Leiden, Zuid-Holland, Netherlands.
Ian J SaldanhaDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.
Euzebiusz JamrozikEthox and Pandemic Sciences Institute, University of Oxford, Oxford, UK euzebiusz.jamrozik@ethox.ox.ac.uk.ORCID http://orcid.org/0000-0001-5940-602X

Funding

Wellcome Trust
6 · The paper itself

Abstract

objectivesControlled human infection studies (CHIS) involve intentional exposure of human volunteers to infectious agents. A previous systematic review found that adverse event (AE) reporting across CHIS is inconsistent, which makes data aggregation and reuse difficult. We hypothesised that data may be more easily aggregated using a clinical trial registry such as ClinicalTrals.gov, the largest publicly accessible registry of clinical trial data. The objectives of the current analysis were to (1) evaluate the use of ClinicalTrials.gov for CHIS data reporting and (2) compare CHIS clinical trial participant flow and AE reporting in ClinicalTrials.gov with the same data in corresponding published articles.

designClinicalTrials.gov records that described a CHIS were included and data were accessed using the Aggregated Analysis of ClinicalTrials.gov application programming interface. These data were compared with results extracted from publications associated with included records' NCT identifiers and compared in groups stratified by sponsor type, cohort size and risk of bias. Results were considered discrepant if the same number was reported unambiguously differently in the clinical trial record and its associated publications. The frequencies of these discrepancies were used to quantify the differences between reporting in ClinicalTrials.gov records and publications of the same results.

resultsWe screened 5131 ClinicalTrials.gov records for inclusion, reviewed 410 records in full and included 344 records. The overall prevalence of any discrepancy was 40%. Compared with their respective groups, significant discrepancies were observed in publicly funded trials, trials in the third quartile of study size and trials with a high risk of bias in selection of the reported result. Five studies reported a total of five serious AEs in ClinicalTrials.gov records but not in any associated publications.

conclusionWe identified an overall prevalence of discrepancy of 40% in CHIS, which is comparable with the prevalence observed in other types of clinical trials. In general, medium-sized, publicly funded trials tended to have more discrepancies in reporting, which may reflect the resources typically available to large, privately funded trials or the relative ease of reporting in smaller trials with fewer overall AEs. These results highlight the need to facilitate clear and consistent reporting in CHIS. PROSPERO REGISTRATION NUMBER: CRD42022330047.

Indexed as

Clinical Trials as TopicRegistriesHumansAdverse eventsClinical TrialMEDICAL ETHICSPublic healthSTATISTICS and RESEARCH METHODS

Identifiers

PMID39920069
PMCPMC11808890

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.