Project
This page sits between the disease-family projects and the geography work. The main question is whether a condition looks quiet because of the condition itself or because of where that condition is being run.
Across three major disease families, mixed U.S.-global studies are the cleanest bucket and no-U.S. studies are the quietest.
A standalone E156 project on how geography buckets reshape the visibility profile of oncology, cardiovascular, and metabolic CT.gov studies.
Across The Series
The split projects are meant to be read together because each isolates a different dimension of registry opacity rather than forcing every question into one leaderboard.
Industry-focused missing-results stock, sponsor backlogs, and structural sparsity inside CT.gov.
Sponsor-class comparisons on rate, stock, and structural hiddenness rather than one flattened ranking.
Phase-by-phase disclosure gaps showing how silence changes along the development pathway.
Field-level missingness across publication links, IPD statements, descriptions, and locations.
Results-plus-publication visibility states showing how many older trials are fully visible, partly visible, or ghosted.
Completion-era reporting debt showing how older eligible cohorts drift on no-results and ghost-protocol rates.
Keyword-classified therapeutic-area hiddenness mapping across common condition families.
Concentration and inequality analysis showing how much unresolved stock sits inside a thin sponsor slice.
Policy-era comparisons across pre-FDAAA, FDAAA, and later CT.gov completion cohorts.
Sample-based external PubMed NCT audit testing how often CT.gov no-link records hide an external paper trail.
Oncology-specific CT.gov hiddenness showing where cancer-trial stock, phases, and sponsors still go quiet.
Cardiovascular CT.gov hiddenness showing how heart and vascular studies remain quiet across major phases and sponsors.
Metabolic CT.gov hiddenness across obesity, diabetes, and related trial portfolios with large late-phase and NA stock.
Enrollment-size gradients showing how older small trials remain much quieter than larger registered studies.
Site and country footprint analysis showing how larger trial geographies map onto much better public visibility.
Primary-purpose and allocation analysis showing which trial intents remain most obscured on CT.gov.
Registration-to-completion delay analysis showing short-cycle studies carry the heaviest reporting debt.
Arm-count and intervention-count analysis showing simpler trial architectures are often the quietest.
Intervention-family analysis showing which declared treatment modalities remain quietest on older CT.gov records.
Named-country visibility analysis showing large geographic divides in older CT.gov reporting debt.
Final-status analysis showing how withdrawn, suspended, and terminated studies remain structurally quieter than completed trials.
Outcome-count and outcome-description analysis showing sparse protocols are often the quietest CT.gov segment.
Closed-study actual-field analysis showing missing actual dates and counts are a strong warning sign for opacity.
Geography-bucket analysis showing how U.S.-only, mixed, and non-U.S. portfolios diverge sharply on visibility.
Intervention-family sponsor audit showing that repeat offenders change sharply once modality is held fixed.
Country-by-condition splits showing how disease-specific visibility changes once specific national footprints are named.
Condition-family sponsor audit showing who carries the biggest hiddenness stock within oncology, cardiovascular, and metabolic studies.