Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Actual-Discipline Repeaters

Which named sponsors fail the CT.gov actual-field discipline test on missing actual completion and actual enrollment fields? We analysed 249,507 eligible older closed interventional studies from the March 29, 2026 full-registry snapshot. We ranked named sponsors with at least 100 older studies by any actual-field gap, then compared rate outliers, sponsor-class rates, and counts across actual completion and actual enrollment fields. Boehringer Ingelheim carried the largest actual-discipline stock at 943 studies, followed by NCI at 615 and Novartis Pharmaceuticals at 292. Gynecologic Oncology Group had the sharpest large-sponsor actual-discipline rate at 83.8 percent, while NIH and NETWORK were highest among sponsor classes at 24.5 and 23.4 percent. The actual-field problem is not cosmetic because it obscures whether closed studies reported real completion timing and realized sample size with the discipline expected from mature trial records. These counts reflect missing registry fields among older closed studies and do not by themselves establish rule violations or intentional concealment.

Outside Notes

Type: methods
Primary estimand: Any actual-field gap stock and rate among named lead sponsors with at least 100 older studies
App: CT.gov Actual-Discipline Repeaters dashboard
Data: 249,507 eligible older closed interventional studies with actual-field discipline fields derived from missing actual completion and actual enrollment markers
Code: https://github.com/mahmood726-cyber/ctgov-actual-discipline-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.