在乳腺癌中预测结节对新辅助治疗的反应,使用瘤微环境的核心活检生物标志物,使用数据挖掘
Nina Pislar1,2, Gorana Gasljevic3,4, Erika Matos2,5
1Department of Surgical Oncology, Institute of Oncology Ljubljana, Ljubljana, Slovenia.
Breast cancer research and treatment
|November 4, 2024
概括
一个新的模型预测了结节对结节阳性乳腺癌患者新辅助全身治疗 (NAST) 的结节反应. 结合瘤微环境 (TME) 因素,该工具有助于手术规划并提高预测准确性.
科学领域:
- 在瘤学瘤学.
- 乳腺癌研究研究 乳腺癌研究
- 瘤微环境 瘤微环境
背景情况:
- 对新辅助全身治疗 (NAST) 的结节反应的准确预测对于分期结节阳性 (cN+) 乳腺癌患者至关重要.
- 整合瘤微环境 (TME) 特性可以增强治疗反应的预测模型.
研究的目的:
- 在cN+乳腺癌患者中开发一个对NAST结节反应的预测模型.
- 该模型旨在整合TME功能,以改善手术分期规划.
主要方法:
- 追溯收集了437名cN+乳腺癌患者的临床和病理数据.
- 核心活检样本进行了分析,以检测树皮含量和瘤透淋巴细胞 (TILs).
- 色数据挖掘工具箱用于模型开发和验证.
主要成果:
- 34.6%的患者在节点 (ypN0) 中实现了病理完整反应 (pCR).
- 使用ER,Her-2,等级,树皮含量和TILs构建了一个预测模型.
- 后勤回归模型实现了AUC为0.86和F1得分为0.72.
结论:
- 开发了一种新的临床工具,用于预测NAST后cN+乳腺癌患者的节点pCR.
- 该模型有效地整合了TME生物标志物,实现了高预测性能 (AUC 0.86).
- 这种工具可以帮助改进接受NAST的乳腺癌患者的手术分期策略.
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