Analyse mathématique prédictive de l'efficacité de la chimiothérapie néoadjuvante chez les patientes ayant un cancer du sein

Translated title of the contribution: Mathematical analysis of predictivity of chemosensitivity in the neoadjuvant setting in breast cancer patients

R. Rouzier*, Roberto Incitti

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The concept of primary chemotherapy for patients with operable breast cancer is attractive because it provides the chemosensitivity of the tumour in vivo. Mathematical models, such as logistic regression, give the opportunity to determine chemosensitivity before any treatment by combining clinical and pathological data. Other models, such as machine learning (recursive partitoning, artificial neural network) provides concepts and can be improved by the integration of biological translational data.

Translated title of the contributionMathematical analysis of predictivity of chemosensitivity in the neoadjuvant setting in breast cancer patients
Original languageFrench
Pages (from-to)227-233
Number of pages7
JournalOncologie
Volume8
Issue number3
DOIs
StatePublished - Mar 1 2006

Keywords

  • Artificial intelligence
  • Breast cancer
  • Chemosensitivity
  • Mathematical model
  • Neoadjuvant chemotherapy
  • Nomogram

ASJC Scopus subject areas

  • Oncology

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