Characteristics of clinical trials associated with early results reporting at ClinicalTrials.gov

Contemp Clin Trials. 2022 Jun:117:106785. doi: 10.1016/j.cct.2022.106785. Epub 2022 May 5.

Abstract

Objective: We aimed to investigate the trial characteristics associated with earlier results reporting on ClinicalTrials.gov.

Study design and setting: We sampled interventional trials registered with ClinicalTrials.gov and examined the time from trial completion to results reporting on ClinicalTrials.gov as the event of interest. A Cox proportional hazards model was used to examine associations between the time to results reporting on ClinicalTrials.gov with funding type, intervention type, number of enrolled participants, trial phase, trial allocation status, and the year of trial completion. The model accounts for multiple risk factors simultaneously.

Results: Among 102,404 completed trials, the median follow-up for the result reporting event was 18.5 months (IQR 12.7-33.6), during which time 25% (26,608 of 102,404) had results available on ClinicalTrials.gov. Compared to industry funded trials (18.1 months), non-industry trials (median 18.8 months) had results reported slower (HR 0.35, 95% CI 0.34-0.36); compared to drug trials (18.4 months) non-drug trials (19.0 months) were reported slower (HR 0.61, 95% CI 0.59-0.64); compared to trials with more than 50 participants (18.0 months), smaller trials (19.3 months) were reported slower (HR 0.97, 95% CI 0.94-0.99).

Conclusion: Non-industry, non-drug, and earlier phase trials reported results on ClinicalTrials.gov more slowly if at all. Much of the efforts aimed at improving trial reporting through structured reporting on ClinicalTrials.gov have been focused on industry funded drug trials, but these results suggest that incentives and tools targeting non-industry and non-drug trials are also needed.

Keywords: Clinical trial as a topic; Clinical trial registration; ClinicalTrials.gov; Trial funding.

MeSH terms

  • Clinical Trials as Topic*
  • Databases, Factual
  • Humans
  • Proportional Hazards Models
  • Registries*