The First Affiliated Hospital of Chongqing Medical University, No. 1 Friendship Road, Yuzhong District, Chongqing, 400000, China.
World J Surg Oncol. 2022 Jan 29;20(1):27. doi: 10.1186/s12957-022-02492-7.
Pathological complete response (pCR) is the goal of neoadjuvant chemotherapy (NACT). We aimed to develop a nomogram to predict the probability of achieving pCR in estrogen receptor-positive (ER+), HER2-negative (HER2-) breast cancer patients.
A total of 273 ER+, HER2- breast cancer patients who received 4 cycles of thrice-weekly standard NACT in the First Affiliated Hospital of Chongqing Medical University were retrospectively enrolled. Univariate and multivariate logistic regression analyses were used to screen the predictive factors to develop the nomograms. The discrimination and calibration abilities were assessed by the C-index, receiver operating characteristic curve (AUC), and calibration plot.
There were 28 patients (10.3%) with overall pCR, 38 patients (13.9%) with breast pCR after NACT. ER expression, PgR expression, the neutrophil-to-lymphocyte ratio (NLR) and the Ki-67 index were independent predictive factors for achieving overall pCR. These indicators had good discrimination and calibration ability (AUC 0.843). The nomogram for breast pCR was established based on ER expression, PgR expression, the NLR, and the Ki-67 index and showed great discriminatory ability, with an AUC of 0.810. The calibration curve showed that the predictive ability of the nomogram was a good fit to actual observations.
The nomograms exhibited a sufficient discriminatory ability for predicting pCR after NACT in ER+, HER2- breast cancer patients. Utilizing these nomograms will enable us to identify patients at high probability for pCR after NACT and provide a reference for preoperative adjuvant therapy.
病理完全缓解(pCR)是新辅助化疗(NACT)的目标。我们旨在开发一个列线图来预测雌激素受体阳性(ER+)、HER2 阴性(HER2-)乳腺癌患者实现 pCR 的概率。
回顾性纳入 273 例在重庆医科大学第一附属医院接受 4 周期每周 3 次标准 NACT 的 ER+、HER2-乳腺癌患者。采用单因素和多因素逻辑回归分析筛选预测因素,以建立列线图。通过 C 指数、受试者工作特征曲线(AUC)和校准图评估区分和校准能力。
共有 28 例(10.3%)患者总体 pCR,38 例(13.9%)患者 NACT 后乳腺 pCR。ER 表达、PgR 表达、中性粒细胞与淋巴细胞比值(NLR)和 Ki-67 指数是实现总体 pCR 的独立预测因素。这些指标具有良好的区分和校准能力(AUC 为 0.843)。基于 ER 表达、PgR 表达、NLR 和 Ki-67 指数建立的乳腺 pCR 列线图具有很好的判别能力,AUC 为 0.810。校准曲线显示,列线图的预测能力与实际观察结果拟合良好。
该列线图对 ER+、HER2-乳腺癌患者 NACT 后 pCR 具有足够的判别能力。使用这些列线图可以识别 NACT 后 pCR 概率较高的患者,为术前辅助治疗提供参考。