Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Condition Sponsor Repeaters

Which sponsors carry the largest missing-results backlogs inside disease families on ClinicalTrials.gov once studies are grouped by condition rather than pooled together? We analysed 249,507 eligible older closed interventional studies from the March 29, 2026 full-registry snapshot and linked sponsors to oncology, cardiovascular, and metabolic condition families. The project compares sponsor-level no-results counts, no-results rates, ghost-protocol rates, and visible shares within each selected disease family. In oncology, the National Cancer Institute carried the largest missing-results stock at 909 older studies, ahead of M.D. Anderson Cancer Center at 589. In cardiovascular studies, Assistance Publique-Hôpitaux de Paris reached 100.0 percent no results and Yonsei University 98.6 percent, while Novo Nordisk led metabolic backlogs with 391 studies. Sponsor repeaters therefore change sharply by disease family, and condition-specific audits reveal institutional pockets of silence that disappear inside whole-registry rankings. Condition families and sponsor names are derived from registry text and do not adjudicate network authorship, parent ownership, or off-platform reporting.

Outside Notes

Type: methods
Primary estimand: Sponsor-level 2-year no-results counts within selected disease families among eligible older CT.gov studies
App: CT.gov Condition Sponsor Repeaters dashboard
Data: 249,507 eligible older closed interventional studies linked to oncology, cardiovascular, and metabolic condition families and lead sponsors
Code: https://github.com/mahmood726-cyber/ctgov-condition-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.