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August 1, 2025

Predicting Pathological Complete Response in HER2+ Breast Cancer: An AI-Driven Model Using Standard Clinical Practice Parameters

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Authors

PLPaulo LuzAdministração Regional de Saúde de Lisboa e Vale do TejoEPEnrique Pérez‐Cuadrado‐RoblesUniversité Paris CitéNCNayara Ferreira CunhaCentro Universitário do Triângulo

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Overview

The predictive model demonstrates potential in assessing pathological complete response in HER2+ breast cancer, suggesting refined treatment strategies.

Key Points

  • The predictive model for pathological complete response integrates clinical and pathological parameters for HER2+ breast cancer.
  • Patients receiving neoadjuvant therapy with trastuzumab and pertuzumab showed varied pCR rates, emphasizing the need for refined models.
  • Logistic regression and machine learning techniques provided an accuracy of 62.4% to 65.9%, indicating effective prediction capabilities.
  • Validation in larger cohorts is necessary to confirm the model's robustness and its potential impact on personalized cancer treatment.

Cite This Study

Luz et al. (2025) studied this question.

synapsesocial.com/papers/689a0c65e6551bb0af8cf970https://doi.org/10.21203/rs.3.rs-6906436/v1
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Assessment of the efficacy of various neoadjuvant anti-HER2 targeted therapies combined with chemotherapy for HER2-positive breast cancer in the real-world setting and development of a predictive model for pathological complete response2025
  2. 2Abstract PS3-04-01: Prediction of pathologic complete response from histopathology images of HER2+ breast cancer using an AI foundation model2026
  3. 3Predicting Pathologic Complete Response to Neoadjuvant Treatment in HER2-positive Breast Cancer using Interpretable Classification2025
  4. 4Clinicopathology-based machine learning model for prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer.2026
  5. 5A Practical Machine Learning Model for Predicting Neoadjuvant Response in HER2-Positive Breast Cancer2026