Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Description-Black-Box Repeaters

Which named sponsors accumulate the most CT.gov pages that are overdue, unlinked, and missing both detailed descriptions and primary outcome descriptions? We analysed 249,507 eligible older closed interventional studies from the March 29, 2026 full-registry snapshot. We defined a description black-box study as one with a two-year results gap, no linked publication, no detailed description, and no primary outcome description, then ranked sponsors with at least 100 studies. Boehringer Ingelheim led the named-sponsor table at 661 studies, followed by Pfizer at 408, Hoffmann-La Roche at 383, and AstraZeneca at 357. Mylan Pharmaceuticals Inc reached the highest large-sponsor rate at 93.7 percent, while industry reached 13.6 percent and OTHER 4.2 percent as sponsor classes. This definition isolates a stricter narrative blackout where registry pages remain silent on descriptive text and dissemination, not only on results status. Description black-box status is a registry visibility measure and does not prove the study lacked protocols, manuscripts, or documentation outside CT.gov.

Outside Notes

Type: methods
Primary estimand: Description black-box stock among older studies with no results, no linked publication, no detailed description, and no primary outcome description
App: CT.gov Description-Black-Box Repeaters dashboard
Data: 249,507 eligible older closed interventional studies with description-black-box sponsor and class summaries
Code: https://github.com/mahmood726-cyber/ctgov-description-black-box-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.