Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Sponsor Detailed-Description Gap

Which named sponsors most often leave older CT.gov study pages without detailed descriptions, removing the broad paragraph that explains what was actually studied? We analysed 249,507 eligible older closed interventional studies from the March 29, 2026 full-registry snapshot and ranked sponsors with at least 100 studies. We defined a detailed-description gap as a missing detailed description field, then compared sponsor stock, rate, and class patterns. GlaxoSmithKline led the sponsor detailed-description-gap stock table at 1,826 studies, followed by Boehringer Ingelheim at 1,600, Pfizer at 1,593, and Hoffmann-La Roche at 1,326. Novo Nordisk A/S had the highest large-sponsor detailed-description-gap rate at 97.4 percent, while Boehringer Ingelheim reached 96.0 percent and Industry reached 53.7 percent as a sponsor class. The detailed-description gap removes the larger narrative paragraph from mature registry pages, leaving readers with less context before asking about results. These counts describe missing registry text fields and do not by themselves establish legal non-compliance, concealment, or absent materials.

Outside Notes

Type: methods
Primary estimand: Detailed-description-gap stock among older studies missing the detailed description field
App: CT.gov Sponsor Detailed-Description Gap dashboard
Data: 249,507 eligible older closed interventional studies with detailed-description-gap stock and rate summaries
Code: https://github.com/mahmood726-cyber/ctgov-sponsor-detailed-description-gap
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.