由于术前新辅助化疗后获得病理完全缓解的三阴性乳腺癌患者预后较好，故有必要对新辅助化疗病理完全缓解进行预测。不过，现有预测方法大多过于复杂。
7月29日，美国乳腺外科医师学会和美国肿瘤外科学会《肿瘤外科学报》在线发表中国科学院肿瘤与基础医学研究所、中国科学院大学附属肿瘤医院、浙江省肿瘤医院、中国科学院大学杭州临床医学院、浙江中医药大学第二临床医学院苏丹和邹德宏等学者的研究报告，根据简单实验室指标建立了预测三阴性乳腺癌患者标准新辅助化疗病理完全缓解的直观列线图。
该研究对1月～12月浙江省肿瘤医院术前每周3次标准新辅助化疗（蒽环类＋环磷酰胺→紫杉类）8个周期随后进行手术的80例三阴性乳腺癌患者治疗前临床特征数据和多个简单实验室指标进行回顾分析。通过敏感度与特异度曲线分析正确指数，确定实验室指标的最佳临界值。通过递进逻辑回归分析似然比，确定新辅助化疗病理完全缓解的预测因素。随后根据逻辑回归模型建立列线图，并且通过自助重复抽样法进行内部验证。
结果，新辅助化疗后39例（48.8%）患者获得病理完全缓解。根据多因素分析，确定了预测病理完全缓解的4个独立指标：
临床肿瘤分期
淋巴细胞与单核细胞之比
纤维蛋白原水平
D-二聚体水平
根据4个独立指标建立列线图，其敏感度与特异度曲线下面积为0.803（95%置信区间：0.706～0.899），偏倚校正后曲线下面积为0.771。校准曲线和逻辑回归模型拟合检验表明，该列线图的预测能力非常符合病理完全缓解实际观察结果。
因此，该研究结果表明，该列线图可以预测三阴性乳腺癌患者新辅助化疗的病理完全缓解。
Ann Surg Oncol. Jul 29. [Epub ahead of print]
A Nomogram to Predict the Pathologic Complete Response of Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer Based on Simple Laboratory Indicators.
Fanrong Zhang, Minran Huang, Huanhuan Zhou, Kaiyan Chen, Jiaoyue Jin, Yingxue Wu, Lisha Ying, Xiaowen Ding, Dan Su, Dehong Zou.
Institute of Cancer Research and Basic Medical Sciences of Chinese Academy of Sciences, Hangzhou, China; Cancer Hospital of University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China; The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, China.
BACKGROUND: Triple-negative breast cancer (TNBC) patients who achieve a pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) have better prognoses.
OBJECTIVE: This study aimed to develop an intuitive nomogram based on simple laboratory indexes to predict the pCR of standard NAC in TNBC patients.
METHODS: A total of 80 TNBC patients who received eight cycles of thrice-weekly standard NAC (anthracycline and cyclophosphamide followed by taxane) and subsequently underwent surgery in Zhejiang Cancer Hospital were retrospectively enrolled, and data on their pretreatment clinical features and multiple simple laboratory indexes were collected. The optimal cut-off values of the laboratory indexes were determined by the Youden index using receiver operating characteristic (ROC) curve analyses. Forward stepwise logistic regression (likelihood ratio) analysis was applied to identify predictive factors for a pCR of NAC. A nomogram was then developed according to the logistic model, and internally validated using the bootstrap resampling method.
RESULTS: pCR was achieved in 39 (48.8%) patients after NAC. Multivariate analysis identified four independent indicators: clinical tumor stage, lymphocyte to monocyte ratio, fibrinogen level, and D-dimer level. The nomogram established based on these factors showed its discriminatory ability, with an area under the curve (AUC) of 0.803 (95% confidence interval 0.706-0.899) and a bias-corrected AUC of 0.771. The calibration curve and Hosmer-Lemeshow test showed that the predictive ability of the nomogram was a good fit to actual observation.
CONCLUSIONS: The nomogram proposed in the present study exhibited a sufficient discriminatory ability for predicting pCR of NAC in TNBC patients.
DOI: 10.1245/s10434-019-07655-7
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