Breast CancerONCO-FIRENCT05060835
ONCOlogy-targeted NLP-powered Federated Hyper-archItecture and Data Sharing Framework for Health Data Reusability
An observational study of Breast Cancer and Prostate Cancer, run by Instituto de Investigacion Sanitaria La Fe.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Breast Cancer, Prostate Cancer
- What is being tested?
- Virtual assistants offering medical recommendations to health care profesionals
- How many people
- 5,000 participants
- Where
- No sites listed yet
- Study dates
- Jun 2023to Dec 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: patients of breast cancer and prostate cancer
Who may be able to join
- 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
Who cannot join
- 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.
Trial locations and contacts
No sites are listed yet.
About this study
Official title: 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.
- Conditions
- Breast Cancer, Prostate Cancer
- Being tested
- Virtual assistants offering medical recommendations to health care profesionals
- Medical subject headings
- Breast Neoplasms, Prostatic Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Virtual assistants offering medical recommendations to health care profesionalsOther
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
| Study group | Role | What they receive |
|---|---|---|
| Breast Cancer | patients diagnosed with breast cancer at any stage. Receives: Other: Virtual assistants offering medical recommendations to health care profesionals | |
| Prostate cancer | patients diagnosed with prostate cancer at any stage Receives: Other: Virtual assistants offering medical recommendations to health care profesionals |
What is being measured
The primary outcome is the main question the study is designed to answer.
Estimation of Overall survival
The lenght (in days) of time form date of start of treatment for a disease that patients is still alive.
Measured: Date of start of treatment untill Date of death or last contact/visit, assessed up to 2 years.
Estimation of progression free survival
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.
Measured: Date of start treatment until date of progression (measured by increase size in millimeters using radiological images), assessed up to 2 years.
Secondary outcomes (1)
Estimation (%) of tumor aggressiveness non-respondents vs respondents to neoadjuvant treatment (breast):
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).
Measured: 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
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Sep 2021
- Study startJun 2023 (estimated)
- Primary completionJun 2025 (estimated)
- Study completionDec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Breast CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 5,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Instituto de Investigacion Sanitaria La Fe
- Sponsor type
- University, hospital or other
- Collaborators
- Karolinska University Hospital, University College Cork, Medical University of Gdansk
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05060835
- Sponsor's protocol ID
- ONCO-FIRE
- Acronym
- ONCO-FIRE
- Status last verified
- Sep 2021
- First submitted
- 20 Sep 2021
- Last updated
- 29 Oct 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: N/D
Study at a glance
From the registry record, last updated by the sponsor on 29 Oct 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- ONCOlogy-targeted NLP-powered Federated Hyper-archItecture and Data Sharing
- ClinicalTrials.gov ID
- NCT05060835
- Acronym / sponsor ID
- ONCO-FIRE / ONCO-FIRE
- Conditions
- Breast Cancer, Prostate Cancer
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 5,000 participants (estimated)
- Lead sponsor
- Instituto de Investigacion Sanitaria La FeUniversity, hospital or other
- Collaborators
- Karolinska University Hospital, University College Cork, Medical University of Gdansk
- Study start
- Jun 2023 (estimated)
- Primary completion
- Jun 2025 (estimated)
- Study completion
- Dec 2025 (estimated)
- First posted
- 29 Sep 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Breast Cancer | – | Other: Virtual assistants offering medical recommendations to health care profesionalspatients diagnosed with breast cancer at any stage. |
| Prostate cancer | – | Other: Virtual assistants offering medical recommendations to health care profesionalspatients diagnosed with prostate cancer at any stage |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- patients of breast cancer and prostate cancer
Key inclusion criteria (6 listed)
- 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).
Key exclusion criteria (1 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Virtual assistants offering medical recommendations to health care profesionalsthe 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 | Other | Breast Cancer, Prostate cancer |
Primary outcome
Estimation of Overall survival
Time frame: 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.
Estimation of progression free survival
Time frame: 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.
1 secondary outcome
Estimation (%) of tumor aggressiveness non-respondents vs respondents to neoadjuvant treatment (breast):
Time frame: 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
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Oct 2021.
- Individual participant dataSharing planned: No. N/D
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Questions about this trial
What is this clinical trial studying?
An observational study of Breast Cancer and Prostate Cancer, run by Instituto de Investigacion Sanitaria La Fe.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 29 Oct 2021. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Ana Penades-Blasco, M.Ec (+34 961245633, ana_penades@iislafe.es), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Estimation of Overall survival (time frame: Date of start of treatment untill Date of death or last contact/visit, assessed up to 2 years.). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 29 Oct 2021; AzTrials last refreshed its copy on 31 Oct 2026.