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Introduction <p>Neoadjuvant chemotherapy (NACT) is a treatment option for early-stage hormone receptor-positive human epidermal growth factor receptor 2-negative (HR + /HER2−) breast cancer. Despite its use, pathological response rates in this subtype are often lower, and the impact of individual risk factors remains unclear. This study aimed to identify biomarkers and create a predictive score for NACT response.</p> Methods <p>This retrospective, single-center study included patients with stage IIA–IIIC HR + /HER2− breast cancer treated with NACT and surgery (2019–2023). Multiple logistic regression analyzed associations between clinicopathological variables and pathologic response (partial/complete vs. absent) (<i>p</i> &lt; 0.05). The best-performing model was used to develop a risk score.</p> Results <p>The study included 101 patients. Significant predictors of pathological response included tumor grade (G2/3 vs. G1), menopausal status (pre- vs. post-menopausal), and intrinsic subtype (luminal B vs. A).</p> Conclusions <p>A dynamic calculator was created incorporating grade, hormonal status, intrinsic subtype, and Ki-67. This tool provides real-time input, facilitating personalized therapeutic decision-making.</p>

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Predictive score for response to neoadjuvant chemotherapy in early-stage HR + /HER2− breast cancer

  • 期刊论文

  • 发表日期：

    2025年2月6日

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  • João Queirós Coelho,
  • Beatriz Lau,
  • Rita Pichel,
  • Laura Guerra,
  • Hugo Miranda,
  • Raquel Romão,
  • Maria João Sousa,
  • Fernando Gonçalves,
  • Joana Simões,
  • Sérgio Xavier Azevedo,
  • António Araújo

摘要

Introduction

Neoadjuvant chemotherapy (NACT) is a treatment option for early-stage hormone receptor-positive human epidermal growth factor receptor 2-negative (HR + /HER2−) breast cancer. Despite its use, pathological response rates in this subtype are often lower, and the impact of individual risk factors remains unclear. This study aimed to identify biomarkers and create a predictive score for NACT response.

Methods

This retrospective, single-center study included patients with stage IIA–IIIC HR + /HER2− breast cancer treated with NACT and surgery (2019–2023). Multiple logistic regression analyzed associations between clinicopathological variables and pathologic response (partial/complete vs. absent) (p < 0.05). The best-performing model was used to develop a risk score.

Results

The study included 101 patients. Significant predictors of pathological response included tumor grade (G2/3 vs. G1), menopausal status (pre- vs. post-menopausal), and intrinsic subtype (luminal B vs. A).

Conclusions

A dynamic calculator was created incorporating grade, hormonal status, intrinsic subtype, and Ki-67. This tool provides real-time input, facilitating personalized therapeutic decision-making.