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clinical-trial-finder

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Find clinical trials for a gene, variant, or condition from ClinicalTrials.gov + EUCTR, with FHIR R4 output

scientific-skills/Evidence Insight/clinical-trial-finder/SKILL.md

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> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)


## Domain Decisions

- **Source database**: ClinicalTrials.gov API v2 (`https://clinicaltrials.gov/api/v2`) — the authoritative US registry mandated by FDAAA 801 (2007) and mirrored by WHO ICTRP. Chosen over EudraCT/EUCTR because it covers the largest global trial volume (>500 000 studies), provides a stable versioned REST API, and is the primary registry for FDA-regulated interventions. Reference: Zarin et al., *NEJM* 2011; 364:852–860.

- **Query field**: `query.cond` (condition/disease field), not `query.term` (free-text across all fields). `query.cond` is indexed against MeSH descriptors by the NLM indexing pipeline, giving substantially better recall for condition queries than unstructured text search. Reference: ClinicalTrials.gov API v2 specification, `https://clinicaltrials.gov/data-api/api`.

- **MeSH condition coding**: MeSH IDs are read from `derivedSection.conditionBrowseModule.meshes` — the NLM-curated MeSH mapping that ClinicalTrials.gov computes internally during study indexing. This avoids a separate NLM API call and uses the same vocabulary that `query.cond` is indexed against, ensuring query/result consistency. Reference: NLM Medical Subject Headings, `https://www.nlm.nih.gov/mesh/`.

- **Max results**: 20 trials per query by default (configurable with `--max-results`). Clinical actionability does not scale with result volume — a clinician reviewing >20 trials without eligibility pre-screening is unlikely to act on any. The default balances coverage with usability.

- **Status display**: All statuses returned are shown — no pre-filtering. Recruiting trials are highlighted; TERMINATED and WITHDRAWN trials are flagged with a distinct visual indicator and never omitted. Selective display of only active trials would introduce reporting bias and obscure negative evidence. Reference: Chan et al., *PLoS Med* 2004; 1:e62 (trial publication bias).
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