Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Industry Disclosure Gap

How large is the industry-specific disclosure gap inside the live ClinicalTrials.gov registry? We analysed the March 29, 2026 full-registry snapshot, focusing on 128,464 industry-linked studies and 87,296 closed interventional industry studies. We derived sponsor-level omission flags for missing results, missing actual dates, missing actual enrollment, missing IPD statements, missing publication links, and missing detailed descriptions, while preserving sponsor-level counts so absolute backlog and rate-based silence could be read together across named firms globally. Among eligible older closed interventional industry studies, 58.1 percent still had no posted results, leaving 44,007 unresolved two-year no-results records in the industry bucket alone. The biggest absolute backlogs sat with GlaxoSmithKline, AstraZeneca, Boehringer Ingelheim, Sanofi, and Pfizer, while several smaller sponsors exceeded 95 percent on the same rate metric. Industry records were also structurally sparse, with 63.2 percent lacking IPD statements, 66.6 percent lacking publication links, and 53.8 percent lacking detailed descriptions. These estimates identify registry-visible non-disclosure rather than adjudicated legal breach.

Outside Notes

Type: methods
Primary estimand: 2-year no-results rate among eligible older closed interventional industry studies
App: CT.gov Industry Disclosure Gap dashboard
Data: 128,464 industry-linked studies from the March 29, 2026 full-registry snapshot
Code: https://github.com/mahmood726-cyber/ctgov-industry-disclosure-gap
Version: 1.0.0
Validation: FULL REGISTRY RUN

References

1. ClinicalTrials.gov API v2. National Library of Medicine. Accessed March 29, 2026.
2. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement. BMJ. 2021;372:n71.
3. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to Meta-Analysis. 2nd ed. Wiley; 2021.

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.