Ignite Creation Date:
2024-05-06 @ 7:22 PM
Last Modification Date:
2024-10-26 @ 3:05 PM
Study NCT ID:
NCT05981326
Status:
RECRUITING
Last Update Posted:
2023-08-08
First Post:
2023-06-19
Brief Title:
Prediction in Silico of Pathological Response in a Prospective Cohort Study of Early Breast Cancer Patients
Sponsor:
Institut Cancerologie de lOuest
Organization:
Institut Cancerologie de lOuest
Study Overview
Official Title:
Prediction in Silico of Pathological Response in a Prospective Cohort Study of Early Breast Cancer Patients
Status:
RECRUITING
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
NEOEPICURE
Brief Summary:
Breast cancer BC is the most common cancer in women in France with nearly 58500 new cases and 12150 deaths estimated in 2018
Two major achievements have been made in the last five years for breast cancer patients The first is therapeutic with the approval of immune checkpoint inhibitors in advanced and early triple-negative BC TNBC and the impressive efficacy of new antibody-drug conjugated in all BC subtypes The second is conceptual with the generalization of adaptive therapeutic strategies guided by pathological responses after neoadjuvant therapy in early TNBC HER2 HR and BRCA mutated breast cancer This new paradigm in the treatment of cancer patients completely redefined prognostic factors that were previously established with conventional approaches Pathological response remains a major prognostic factor especially for TNBC and HER2 early breast cancer However this parameter is evaluated at the end of neoadjuvant treatment and for patients with residual disease the prognosis remains poor despite some adaptative strategies
Our project is to integrate massive and heterogeneous data concerning the disease clinical and biological data imaging and histological results with multi-omics data and patients environment personal and familial history These data are multiple and have dynamic interactions overtime With the help of mathematical units with biological competences and scientific collaborations our project is to improve the prediction of treatment response based on clinical and molecular heterogeneous big data investigation
The main objective of this project is to set up a clinicobiological database prospectively by collecting prospective clinical biological pathological and multi-omic data from 300 Patients with early BC treated at the ICO in order to define an algorithm of individual decision for the prediction of the response to this treatment
Two major achievements have been made in the last five years for breast cancer patients The first is therapeutic with the approval of immune checkpoint inhibitors in advanced and early triple-negative BC TNBC and the impressive efficacy of new antibody-drug conjugated in all BC subtypes The second is conceptual with the generalization of adaptive therapeutic strategies guided by pathological responses after neoadjuvant therapy in early TNBC HER2 HR and BRCA mutated breast cancer This new paradigm in the treatment of cancer patients completely redefined prognostic factors that were previously established with conventional approaches Pathological response remains a major prognostic factor especially for TNBC and HER2 early breast cancer However this parameter is evaluated at the end of neoadjuvant treatment and for patients with residual disease the prognosis remains poor despite some adaptative strategies
Our project is to integrate massive and heterogeneous data concerning the disease clinical and biological data imaging and histological results with multi-omics data and patients environment personal and familial history These data are multiple and have dynamic interactions overtime With the help of mathematical units with biological competences and scientific collaborations our project is to improve the prediction of treatment response based on clinical and molecular heterogeneous big data investigation
The main objective of this project is to set up a clinicobiological database prospectively by collecting prospective clinical biological pathological and multi-omic data from 300 Patients with early BC treated at the ICO in order to define an algorithm of individual decision for the prediction of the response to this treatment
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None