Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Sponsor Ghost Repeaters

Which named CT.gov sponsors remain most ghosted once silence is narrowed from missing results to ghost protocols and read as excess over expectation? We analysed 249,507 eligible older closed interventional studies from the March 29, 2026 full-registry snapshot. Using the wave-nine sponsor watchlist, we ranked sponsors by excess ghost-protocol stock, raw ghost counts, black-box stock, and strict-core carryover. Cairo University carried the largest sponsor ghost excess at 228 studies, followed by Sanofi at 219 and Bayer at 179. Ain Shams University also remained prominent on ghost excess, while several of the biggest ghost repeaters were large industry sponsors with substantial black-box stock. The deeper-silence sponsor table therefore differs from the adjusted no-results table and pulls several ghost-heavy institutions to the front across universities, hospital systems, and major global drug-company portfolios all alike. Ghost-protocol status here is a registry-visibility definition based on missing results and missing linked publication references, not proof of total absence of reporting elsewhere.

Outside Notes

Type: methods
Primary estimand: Excess ghost-protocol stock among named lead sponsors with at least 100 older studies
App: CT.gov Sponsor Ghost Repeaters dashboard
Data: 249,507 eligible older closed interventional studies with sponsor ghost watchlists derived from the wave-nine adjusted tables
Code: https://github.com/mahmood726-cyber/ctgov-sponsor-ghost-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.