Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Condition Primary-Only Gap

Which condition families most often leave older CT.gov study pages without the primary outcome description while keeping the broader detailed-description field? We analysed 249,507 eligible older closed interventional studies from the March 29, 2026 full-registry snapshot using one condition-family label per study. We defined a primary-only gap as missing primary outcome description with detailed description still present, then ranked large condition families by stock and rate. Oncology led the condition-family primary-only-gap stock table at 7,102 studies, followed by Other at 5,818, Cardiovascular at 3,766, and Infectious disease at 2,584. Oncology also had the highest large-family primary-only-gap rate at 16.8 percent, ahead of Cardiovascular at 14.5 percent and Infectious disease at 14.3 percent. Condition-family primary-only gaps show where the endpoint sentence disappears most often even though the broader study narrative remains on the page. Condition families are keyword-derived registry groupings rather than formal disease ontologies or mutually exclusive diagnoses across all studies. They simplify diagnoses for readers.

Outside Notes

Type: methods
Primary estimand: Primary-only-gap stock among older studies missing the primary outcome description field while retaining the detailed description field
App: CT.gov Condition Primary-Only Gap dashboard
Data: 249,507 eligible older closed interventional studies with primary-only-gap stock and rate summaries
Code: https://github.com/mahmood726-cyber/ctgov-condition-primary-only-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.