ArticleBMJ open2025
An analysis of controlled human infection studies registered on ClinicalTrials.gov.
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.
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.
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.
Who cites it
2 citing papers in PubMed.
- Article
- How community members in Uganda perceive controlled human infection studies.Research ethics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
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
Identifiers
What OpenQuestion holds
Registered trials
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.