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ONCOlogy-targeted NLP-powered Federated Hyper-archItecture and Data Sharing Framework for Health Data Reusability (ONCO-FIRE)

25. oktober 2021 oppdatert av: Instituto de Investigacion Sanitaria La Fe

ONCOlogy-targeted NLP-powered Federated Hyper-archItecture and Data Sharing

ONCO-FIRE proposes to build a novel hyper-architecture and a common data model (CDM) for oncology, as well as a rich, modular toolset enabling significantly increased interoperability, exploitability, use and reuse of diverse, multi-modal health data available in electronic Health Records (EHR) and cancer big data repositories to the benefit of health professionals, healthcare providers and researchers; this will eventually lead to more efficient and cost-effective health care procedures and workflows that support improved care delivery to cancer patients encompassing support for cancer early prediction, diagnosis, and follow-up. The applicability, usefulness and usability of the proposed hyper-architecture, CDM and toolset for oncology and the high exploitability of health data will be demonstrated in diverse data exploitation scenarios related to breast and prostate cancer involving a number of Virtual Assistants (VAs) and advanced services offering to health care professionals (HCPs), hospital administration/healthcare providers and researchers data-driven decision-support and easy navigation across large amounts of cancer-related information. Through the above mentioned outcomes and the (meta)data interoperability achieved, ONCO-FIRE contributes to the exploitation of large volumes, highly heterogeneous (meta)data in EHR and data repositories including imaging data, structured data (e.g. demographics, laboratory, pathological data), as well as diverse formats of unstructured clinical reports and notes (e.g. text, pdf), including (but not limited to) temporal information related to the patient care pathway and genomics data currently "hidden" in unstructured medical reports, and more. Importantly, ONCO-FIRE interconnects, following a federated approach, large, distributed cancer imaging repositories, currently used for AI tools training and validation, with patient registries and EHRs of cancer-related data and supports exploitation of relevant unstructured data through novel Natural Language Processing (NLP) tools. The ultimate goal is to establish a patient-centric, federated multi-source and interoperable data-sharing ecosystem, where healthcare providers, clinical experts, citizens and researchers contribute, access and reuse multimodal health data, thereby making a significant contribution to the creation of the European Health Data Space.

Studieoversikt

Status

Har ikke rekruttert ennå

Forhold

Intervensjon / Behandling

Studietype

Observasjonsmessig

Registrering (Forventet)

5000

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

18 år og eldre (Voksen, Eldre voksen)

Tar imot friske frivillige

Nei

Kjønn som er kvalifisert for studier

Alle

Prøvetakingsmetode

Ikke-sannsynlighetsprøve

Studiepopulasjon

patients of breast cancer and prostate cancer

Beskrivelse

Inclusion Criteria:

  • Patients of age ≥ 18 years.
  • Individuals referred to hospitals for diagnosis and/or treatment of breast cancer or prostate cancer, either at first diagnoses, progression, or relapses.
  • Availability of radiological images: 2D mammography or 2D synthetic digital tomosynthesis, ultrasound, and magnetic resonance for breast cancer; magnetic resonance for prostate cancer.
  • Availability of pathological report (surgical specimen, including immunohistochemistry and genetic information).
  • Availability of treatment allocation (neoadjuvant/Adjuvant and Advanced disease): (scheme, duration, benefit).
  • Availability of treatment response evaluation

Exclusion Criteria:

  • Patient with incomplete or low-quality data (radiological, pathological or clinical) In relation to the use of the data already existing in the four AI4HI repositories, ONCO-FIRE will not intervene with the inclusion and exclusion criteria of each of the four projects and will select those data that fit the ONCO-FIRE research purposes.

Studieplan

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

Kohorter og intervensjoner

Gruppe / Kohort
Intervensjon / Behandling
Breast Cancer
patients diagnosed with breast cancer at any stage.
Annen: Virtual assistants offering medical recommendations to health care profesionals
the project will interconnect, following a federated approach, large, distributed cancer imaging repositories, currently used for AI tools training and validation, with patient registries and EHRs of cancer-related data and supports exploitation of relevant unstructured data through novel Natural Language Processing (NLP) tools
Prostate cancer
patients diagnosed with prostate cancer at any stage
Annen: Virtual assistants offering medical recommendations to health care profesionals
the project will interconnect, following a federated approach, large, distributed cancer imaging repositories, currently used for AI tools training and validation, with patient registries and EHRs of cancer-related data and supports exploitation of relevant unstructured data through novel Natural Language Processing (NLP) tools

Hva måler studien?

Primære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Estimation of Overall survival
Tidsramme: Date of start of treatment untill Date of death or last contact/visit, assessed up to 2 years.
The lenght (in days) of time form date of start of treatment for a disease that patients is still alive.
Date of start of treatment untill Date of death or last contact/visit, assessed up to 2 years.
Estimation of progression free survival
Tidsramme: Date of start treatment until date of progression (measured by increase size in millimeters using radiological images), assessed up to 2 years.
The length of time (days) during and after treatment of a disease that a patient lives with the disease but it does not get worse.
Date of start treatment until date of progression (measured by increase size in millimeters using radiological images), assessed up to 2 years.

Sekundære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Estimation (%) of tumor aggressiveness non-respondents vs respondents to neoadjuvant treatment (breast):
Tidsramme: Date of start of treatment until date of ending treatmen, responses will be assessed during the following 6 months after starting treatment in neoadyuvancy unless toxicity or progression has occurred
Proportion of patients who have complete response evaluating the target lesion according to Miller/Payne Grading system [Ogston et al., 2003]: 1A. Evaluation of target Tumor: G5 as pathological complete response, no tumor left; G4: more than 90% loss of tumor cells; G3: between 30-90% reduction in tumor cells; G2: loss of tumor <30%; G1: no reduction. 1B: Evaluating the lymph nodes: A: negative; B: lymph nodes with metastasis and without changes by chemotherapy; C: lymph nodes with metastasis with evidence of partial response, D: lymph nodes with changes attributed to response without residual infiltration. 1C: Using images to evaluated radiological response: Size and diameter in millimeters of the target lesion using RM and TC or PET/CT for extension analysis (lymph nodes and metastasis).
Date of start of treatment until date of ending treatmen, responses will be assessed during the following 6 months after starting treatment in neoadyuvancy unless toxicity or progression has occurred

Samarbeidspartnere og etterforskere

Det er her du vil finne personer og organisasjoner som er involvert i denne studien.

Sponsor

Instituto de Investigacion Sanitaria La Fe

Samarbeidspartnere

Karolinska University Hospital
University College Cork
Medical University of Gdansk

Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart (Forventet)

1. juni 2023

Primær fullføring (Forventet)

1. juni 2025

Studiet fullført (Forventet)

1. desember 2025

Datoer for studieregistrering

Først innsendt

20. september 2021

Først innsendt som oppfylte QC-kriteriene

20. september 2021

Først lagt ut (Faktiske)

29. september 2021

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

29. oktober 2021

Siste oppdatering sendt inn som oppfylte QC-kriteriene

25. oktober 2021

Sist bekreftet

1. september 2021

Mer informasjon

Begreper knyttet til denne studien

Ytterligere relevante MeSH-vilkår

Andre studie-ID-numre

  • ONCO-FIRE

Plan for individuelle deltakerdata (IPD)

Planlegger du å dele individuelle deltakerdata (IPD)?

NEI

IPD-planbeskrivelse

N/D

Legemiddel- og utstyrsinformasjon, studiedokumenter

Studerer et amerikansk FDA-regulert medikamentprodukt

Nei

Studerer et amerikansk FDA-regulert enhetsprodukt

Nei

Denne informasjonen ble hentet direkte fra nettstedet clinicaltrials.gov uten noen endringer. Hvis du har noen forespørsler om å endre, fjerne eller oppdatere studiedetaljene dine, vennligst kontakt register@clinicaltrials.gov. Så snart en endring er implementert på clinicaltrials.gov, vil denne også bli oppdatert automatisk på nettstedet vårt. .

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Sponsorer og samarbeidspartnere

Medisinsk tilstand

Legemiddelintervensjoner

CROs by country

CROs in Philippines

Forhold

Sjeldne sykdommer

Legemiddelintervensjoner

Kosttilskudd

Sponsor / samarbeidspartnere

Steder

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