An Analysis of Controlled Human Infection Studies Registered on ClinicalTrials.gov
OBJECTIVES: Controlled human infection studies (CHIS) involve intentional exposure of human volunteers to infectious agents. Given the small size of CHIS, aggregating data across studies is critical to the field. 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. DESIGN: ClinicalTrials.gov records that described a CHIS were included and data were accessed using the AACT API. 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 in selection of the reported result as determined by Domain 5 of the Cochrane Risk of Bias 2.0 tool. RESULTS: We screened 5,131 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 3rd 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 SAEs in ClinicalTrials.gov records but not in any associated publications. CONCLUSION: We identified an overall prevalence of discrepancy of 40% in CHIS, which is comparable to 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..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
bioRxiv.org - (2024) vom: 15. März Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Toomey, Danny [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.1101/2024.03.13.24304104 |
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| PPN (Katalog-ID): |
XBI042924375 |
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| 520 | |a OBJECTIVES: Controlled human infection studies (CHIS) involve intentional exposure of human volunteers to infectious agents. Given the small size of CHIS, aggregating data across studies is critical to the field. 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. DESIGN: ClinicalTrials.gov records that described a CHIS were included and data were accessed using the AACT API. 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 in selection of the reported result as determined by Domain 5 of the Cochrane Risk of Bias 2.0 tool. RESULTS: We screened 5,131 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 3rd 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 SAEs in ClinicalTrials.gov records but not in any associated publications. CONCLUSION: We identified an overall prevalence of discrepancy of 40% in CHIS, which is comparable to 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. | ||
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| 700 | 1 | |a Kamenicek, Steffen |4 aut | |
| 700 | 1 | |a Kaufman, Daniel |4 aut | |
| 700 | 1 | |a Jamrozik, Euzebiusz |4 aut | |
| 700 | 1 | |a Osowicki, Joshua |4 aut | |
| 700 | 1 | |a Roestenberg, Meta |4 aut | |
| 700 | 1 | |a Saldanha, Ian |4 aut | |
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