Project
This page uses density as an analytic idea in the same spirit as your other stress-test work: when the registry outcome structure gets sparse, the public record often gets sparse too.
Studies with zero primary outcomes or missing primary-outcome descriptions sit in a near-total visibility failure zone.
A standalone E156 project on how sparse outcome structures and missing outcome descriptions track quieter CT.gov records.
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.
Closed-study actual-field analysis showing missing actual dates and counts are a strong warning sign for opacity.