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Exploratory research working note

Interventional trials across sixteen conditions

Question

How many interventional study records does ClinicalTrials.gov return for sixteen condition terms, and how many are currently recruiting? This describes one registry on one day. It is not a measure of need, spending or scientific quality.

Method

Endpoint: https://clinicaltrials.gov/api/v2/studies, reading totalCount only.
Filter: filter.advanced=AREA[StudyType]INTERVENTIONAL, applied to every call. This is the correction to version 1, which counted all study types.
Second call per condition adds filter.overallStatus=RECRUITING.
32 requests, 0.4 s apart, fetched 2026-10-30. Raw responses and URLs in raw.json.

Results

Condition	Interventional (all statuses)	Recruiting	Recruiting share
type 2 diabetes	9,910	673	6.8%
hypertension	9,137	789	8.6%
Alzheimer disease	3,415	433	12.7%
Parkinson disease	3,873	487	12.6%
schizophrenia	3,606	321	8.9%
major depressive disorder	3,294	404	12.3%
tuberculosis	1,158	97	8.4%
malaria	1,241	36	2.9%
HIV infections	8,225	447	5.4%
hepatitis C	1,895	21	1.1%
breast cancer	13,233	1,877	14.2%
lung cancer	11,458	1,782	15.6%
pancreatic cancer	4,035	677	16.8%
sickle cell disease	867	120	13.8%
cystic fibrosis	1,215	73	6.0%
chronic kidney disease	4,318	382	8.8%

Findings

Registration volume spans roughly 15-fold, from sickle cell disease (867) to breast cancer (13,233).
Recruiting share ranges from 1.1% (hepatitis C) to 16.8% (pancreatic cancer); 9 of 16 are below 10%.
Rank order changes with the metric: count and recruiting share are different questions, and neither is burden.

What this does and does not show

It shows how many interventional records a registry returns for a condition term. Nothing more.
Condition terms overlap (for example, cancer subtypes), so counts are not mutually exclusive.
A registered study is not a completed study, a funded study, or a good one.
Registry coverage varies by sponsor and country; industry and high-income sponsors register more reliably.
The count depends on the search term, not on the disease entity.

Reproduce

python3 code/fetch_trials.py   # writes raw.json and data.csv

Publication status

Blockers cleared (v2). The study-type filter is now applied and verified: for type 2 diabetes the unfiltered count is 12,030 and the interventional count 9,910. Ready for editorial review, not yet for publication.