Click here to open the filter panel
Click a letter to view all its definitions
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

Term of the Day

Natural history study

A natural history study is a preplanned observational study intended to track the course of a disease over time, identifying demographic, genetic, environmental and other variables that correlate with its development and outcomes in the absence of intervention, or under standard of care. Designs may be retrospective (chart review of existing records) or prospective (longitudinal follow-up of a cohort or registry).

Natural history data is particularly important in rare and paediatric diseases, where randomised placebo-controlled trials may be infeasible or unethical. The FDA (guidance on rare disease natural history studies, 2019) and the EMA accept well-designed natural history studies to define endpoints and biomarkers, identify patient subgroups, estimate sample sizes and, in some cases, serve as external or historical control arms for single-arm trials supporting orphan products.

Because they are non-interventional, natural history studies fall outside the CTR and are governed by national law (for example France's MR-003 or MR-004 reference methodologies) and by the GDPR. They typically involve secondary use of medical records, long-term follow-up, genetic data and small populations in which anonymisation is rarely achievable, so pseudonymisation, a DPIA and a robust research legal basis under Art. 9(2)(j) are essential. Registries maintained by patient organisations or academic consortia raise additional questions of joint controllership and data access governance.

C

Central imaging

Central imaging refers to the collection, quality control and independent interpretation of medical images (MRI, CT, PET, X-ray, ultrasound, ophthalmic or dermatological photography) generated at investigator sites, by a specialised imaging core laboratory acting on behalf of the sponsor. Blinded independent central review (BICR) reduces inter-reader variability and investigator bias in imaging-based endpoints such as tumour response.

Imaging vendors receive DICOM files from sites, de-identify header metadata, and make images available to independent readers through a dedicated platform. Regulators (FDA guidance on clinical trial imaging endpoints, 2018; EMA) expect an imaging charter documenting acquisition standards, reader training and adjudication rules.

Medical images are health data and, where they contain faces, dental structures or embedded burned-in text, may allow re-identification even after header scrubbing. The imaging vendor is normally a processor under a data processing agreement; transfers to a US-based core lab require SCCs or DPF certification. AI-assisted reading tools must be assessed under the EU AI Act where they influence endpoint determination.