Automated Capture of Core Data for Rare Diseases and Glucocorticoid Complications: Biomarkers and Patient-Reported Outcomes (CDE-AI-Patient)
Automated Capture of Core Data Elements for Monitoring Rare Diseases and Glucocorticoid Complications: Biomarker Research and Patient-Reported Outcomes Assessment - CDE-AI-Patients
Main goal: Looking for biological markers (molecular and biochemical) that predict glucocorticoid complications using blood and urine samples.
Evaluation criterion: statistical association between biological markers and the occurrence of glucocorticoid complications.
Glucocorticoid-related complications are collected in a research program called "CDE.AI" (common data elements, artificial intelligence). CDE.AI aims at processing unstructured medical reports with natural language processing tools to fill in automatically forms reporting the outcome of patients with glucoocorticoid excess.
Studieöversikt
Status
Betingelser
Detaljerad beskrivning
CDE.AI is initially aiming to build a form auto-fill tool using automatic language processing from unstructured medical reports, applied to monitoring the follow-up of rare diseases in France, with a specific focus on glucocorticoid complications (Glucocorticoids Complications-Core Data Elements, GC-CDE). Data from 10,000 patients will be processed. French regulations clearance was obtained for this part of the project, which falls under the reuse of health data.
The second part of the project aims to measure biomarkers in a sub-population of 300 patients to identify biomarkers associated with glucocorticoid complications and collect patient-reported outcomes, which constitutes research involving humans.
CDE.AI_patients is an ancillary part of the CDE.AI project that will look for biological markers (molecular and biochemical) associated with glucocorticoid-related complications. Patients will also fill in a form reflecting their perception of their disease, and their opinion on the use of AI-based tools to extract their clinical data. This prospective inclusion targets 300 patients.
Studietyp
Inskrivning (Beräknad)
Kontakter och platser
Studiekontakt
- Namn: Guillaume ASSIE, MD, PhD
- Telefonnummer: +33158411878
- E-post: guillaume.assie@aphp.fr
Studera Kontakt Backup
- Namn: Malha BERRAH
- Telefonnummer: +33156095822
- E-post: malha.berrah@aphp.fr
Studieorter
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-
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Bron, Frankrike, 69500
- Hospices Civils de Lyon, Groupe hospitalier Est - Hôpital Femme Mère Enfant
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Kontakt:
- Alexandre BELOT
- Telefonnummer: +334 27 85 61 28
- E-post: alexandre.belot@inserm.fr
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Marseille, Frankrike, 13385
- Assistance publique Hôpitaux de Marseille (Hôpital de la Timone)
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Kontakt:
- Attarian SHARAM
- Telefonnummer: +334 91 38 65 79
- E-post: shahram.attarian@ap-hm.fr
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Paris, Frankrike, 75014
- Hôpital Cochin
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Kontakt:
- Jérôme BERTHERAT, MD,PHD
- Telefonnummer: 01 58 41 18 95
- E-post: jerome.bertherat@aphp.fr
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Kontakt:
- Telefonnummer: +33156095822
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-
Deltagandekriterier
Urvalskriterier
Åldrar som är berättigade till studier
Tar emot friska volontärer
Kön som är behöriga för studier
Testmetod
Studera befolkning
Adults with an excess of endogenous or exogenous glucocorticoids, managed in one of the three French rare disease networks FIRENDO, FILNEMUS, and FAI2R.
Beskrivning
Inclusion Criteria:
- Patient at least 18 years old
- Currently exposed to an excess of endogenous or exogenous glucocorticoids (corticosteroid therapy) for an estimated duration of at least 3 months
- Patient who has not opposed the research being conducted
- Patient affiliated with a French social security scheme or a beneficiary of such a scheme
Exclusion Criteria:
- Patients with a progressive malignant disease
- Pregnant or breastfeeding women
- Patients under guardianship or curatorship
- Patients under legal protection
Studieplan
Hur är studien utformad?
Designdetaljer
- Observationsmodeller: COHORT
- Tidsperspektiv: CROSS_SECTIONAL
Kohorter och interventioner
Grupp / Kohort |
|---|
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Patients
Patients with glucocorticoid excess (endogenous or exogenous) |
Vad mäter studien?
Primära resultatmått
Resultatmått |
Åtgärdsbeskrivning |
Tidsram |
|---|---|---|
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biomarkers associated with glucocorticoid-excess complications
Tidsram: Single-spot assay (at inclusion) for biological samples.
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Association of molecular (whole blood transcriptome, DNA methylome, and DNA variants) and biochemical (mass spectrometry profiles from blood and urine) markers associated with glucocorticoid-induced complications |
Single-spot assay (at inclusion) for biological samples.
|
Samarbetspartners och utredare
Samarbetspartners
Utredare
- Studierektor: Guillaume ASSIE, MD, PhD, Assistance Publique - Hôpitaux de Paris (AP-HP)
Studieavstämningsdatum
Studera stora datum
Studiestart (Beräknad)
Primärt slutförande (Beräknad)
Avslutad studie (Beräknad)
Studieregistreringsdatum
Först inskickad
Först inskickad som uppfyllde QC-kriterierna
Första postat (Faktisk)
Uppdateringar av studier
Senaste uppdatering publicerad (Faktisk)
Senaste inskickade uppdateringen som uppfyllde QC-kriterierna
Senast verifierad
Mer information
Termer relaterade till denna studie
Andra studie-ID-nummer
- APHP251481
- 2025-A02873-46 (Annan identifierare: ANSM)
Plan för individuella deltagardata (IPD)
Planerar du att dela individuella deltagardata (IPD)?
IPD-planbeskrivning
Individual participant data (IPD) that underlie results in publication could be shared. IPD detailed in the protocol of a planned metaanalysis could be shared
Tidsram för IPD-delning
Two years after the last publication
Kriterier för IPD Sharing Access
Data sharing must be accepted by the sponsor and the PI based on a scientific project and scientific involvement of the PI team. Collaboration will be fostered. Data sharing must respect the agreements made with funders. Teams wishing obtain IPD must meet the sponsor and IP team to present scientific (and commercial) purpose, IPD needed, format of data transmission, and timeframe. Technical feasibility and financial support will be discussed before mandatory contractual agreement. Processing of shared data must comply with European General Data Protection Regulation (GDPR).
IPD-delning som stöder informationstyp
- STUDY_PROTOCOL
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