Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Completion-Timing Repeaters

Which named sponsors most often leave older CT.gov study pages without actual primary completion or actual completion timing fields? We analysed 249,507 eligible older closed interventional studies from the March 29, 2026 full-registry snapshot. We defined a completion-timing gap as missing actual primary completion or missing actual completion among older closed studies, then ranked sponsors with at least 100 studies. Boehringer Ingelheim led the named-sponsor table at 930 studies, followed by National Cancer Institute at 601, Novartis Pharmaceuticals at 271, and EORTC at 166. Gynecologic Oncology Group had the highest large-sponsor completion-timing gap rate at 83.1 percent, while NETWORK reached 19.2 percent and NIH 17.2 percent as sponsor classes. Completion-timing gaps obscure when older studies truly finished, making the reporting window harder to read even before results, publications, or outcome text are evaluated. These counts reflect missing registry timing fields among older closed studies and do not by themselves establish concealment, intent, or legal breach alone.

Outside Notes

Type: methods
Primary estimand: Completion-timing gap stock among older studies missing actual primary completion or actual completion fields
App: CT.gov Completion-Timing Repeaters dashboard
Data: 249,507 eligible older closed interventional studies with completion-timing sponsor, component, and class summaries
Code: https://github.com/mahmood726-cyber/ctgov-completion-timing-repeaters
Version: 1.0.0
Validation: FULL REGISTRY RUN

References

1. ClinicalTrials.gov API v2. National Library of Medicine. Accessed March 29, 2026.
2. DeVito NJ, Bacon S, Goldacre B. Compliance with legal requirement to report clinical trial results on ClinicalTrials.gov: a cohort study. Lancet. 2020;395(10221):361-369.
3. Zarin DA, Tse T, Williams RJ, Carr S. Trial reporting in ClinicalTrials.gov. N Engl J Med. 2016;375(20):1998-2004.

AI Disclosure

This work represents a compiler-generated evidence micro-publication built from structured registry data and deterministic summary code. AI was used as a constrained coding and drafting assistant for interface generation, packaging, and prose refinement, not as an autonomous author. The analytical choices, interpretation, and final outputs were reviewed by the author, who takes responsibility for the content.