Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Country Sponsor Repeaters

Which sponsors hold the largest missing-results stock inside country-linked CT.gov portfolios? We analysed 249,507 eligible older closed interventional studies from the March 29, 2026 full-registry snapshot and ranked lead sponsors within selected country-linked portfolios. The project compares sponsor-level missing-results counts, no-results rates, ghost-protocol rates, and visible shares across United States, China, Egypt, Poland, Australia, and Japan footprints. In United States-linked studies, Mayo Clinic carried the largest missing-results stock at 927 studies, while Sun Yat-sen University led China with 235 and Cairo University led Egypt with 968. Poland was cleaner, with Sanofi at 47.5 percent no results and Hoffmann-La Roche at only 59 missing-results studies, while Australia and Japan also sat below China or Egypt on rate. Country-linked sponsor repeaters therefore differ sharply across national footprints, meaning the same registry backlog resolves into different institutional stories once geography is named. Country-linked sponsor tables reflect recorded study locations rather than sponsor domicile, enrollment shares, or national legal exposure.

Outside Notes

Type: methods
Primary estimand: Sponsor-level missing-results counts within selected country-linked older CT.gov portfolios
App: CT.gov Country Sponsor Repeaters dashboard
Data: 249,507 eligible older closed interventional studies exploded into selected country-linked sponsor portfolios
Code: https://github.com/mahmood726-cyber/ctgov-country-sponsor-repeaters
Version: 1.0.0
Validation: FULL REGISTRY RUN

References

1. ClinicalTrials.gov API v2. National Library of Medicine. Accessed March 29, 2026.
2. Zarin DA, Tse T, Williams RJ, Carr S. Trial reporting in ClinicalTrials.gov. N Engl J Med. 2016;375(20):1998-2004.
3. 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.

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.