Comparison of Breast Cancer Staging Systems After Neoadjuvant Chemotherapy
Comparison of Breast Cancer Staging Systems After Neoadjuvant Chemotherapy
复制标题
DOI：
10.1245/s10434-021-09951-7
复制
发表时间：
2021-05-06
影响因子：
3.7
通讯作者：
Mittendorf, Elizabeth A.
中科院分区：
文献类型：
--
作者：
Kantor, Olga;Laws, Alison;Mittendorf, Elizabeth A.
背景对于新辅助化疗（NAC）后的最佳分期还没有达成共识。我们比较了美国癌症联合委员会（AJCC）病理预后分期系统、残留癌症负担（RCB）指数和Neo-Bioscore在NAC后乳腺癌患者中的表现。方法对2004年至2014年在Dana-Farber癌症研究所接受NAC治疗的I-III期乳腺癌患者进行识别。Kaplan-Meier曲线用于估计无病生存期（DFS）和总生存期（OS），并使用c-统计量和DeLong检验通过受试者操作特征（ROC）曲线比较模型拟合。结果802例患者接受NAC治疗，中位年龄48岁。大多数患者表现为cT 2（n = 470，58.6%）和cN 1（n = 422，52.6%）疾病。296例（36.9%）患者的亚型为雌激素受体（ER）和/或孕激素受体（PR）阳性/人表皮生长因子受体2（HER 2）阴性，261例（32.5%）患者为HER 2阳性，245例（30.5%）患者为三阴性。中位随访时间为79.5个月。有174例复发（30例局部复发，25例局部复发，145例远处复发），676例（76.8%）患者在末次随访时存活。与Neo-Bioscore相比，AJCC病理预后分期和RCB对估计的7年DFS和OS具有更好的区分力。DFS模型拟合的ROC c-统计量对于AJCC病理预后分期（0.72）和RCB（0.71，p =非显著性）是相似的;两者与Neo-Bioscore相比具有改进的模型拟合（0.65，p < 0.01）。AJCC病理预后分期、RCB和Neo-Bioscore的OS的c统计量分别为0.74、0.71和0.70（p =无显著性）。结论这些结果证实了这些分期系统对NAC患者生存结局进行分层的能力，AJCC病理预后分期或RCB可实现最佳区分。
Background No consensus exists for optimal staging following neoadjuvant chemotherapy (NAC). We compared the performance of the American Joint Committee on Cancer (AJCC) pathologic prognostic staging system, Residual Cancer Burden (RCB) Index, and the Neo-Bioscore in breast cancer patients after NAC. Methods Patients with stage I-III breast cancer who received NAC at Dana-Farber Cancer Institute from 2004 to 2014 were identified. Kaplan-Meier curves were used to estimate disease-free survival (DFS) and overall survival (OS), and model fits were compared by receiver operator characteristic (ROC) curve using the c-statistic and DeLong's test. Results Overall, 802 patients with a median age of 48 years received NAC. Most patients presented with cT2 (n = 470, 58.6%) and cN1 (n = 422, 52.6%) disease. The subtype was estrogen receptor (ER)- and/or progesterone receptor (PR)-positive/human epidermal growth factor receptor 2 (HER2)-negative in 296 (36.9%) patients, HER2-positive in 261 (32.5%) patients, and triple-negative in 245 (30.5%) patients. Median follow-up was 79.5 months. There were 174 recurrences (30 local, 25 regional, 145 distant), with 676 (76.8%) patients alive at last follow-up. AJCC pathologic prognostic staging and RCB had better discrimination for estimated 7-year DFS and OS compared with the Neo-Bioscore. The ROC c-statistics for DFS model fit were similar for AJCC pathologic prognostic stage (0.72) and RCB (0.71, p = non-significant); both had improved model fit versus the Neo-Bioscore (0.65, p < 0.01). The c-statistics for OS were 0.74, 0.71, and 0.70 for AJCC pathologic prognostic stage, RCB, and Neo-Bioscore, respectively (p = non-significant). Conclusions These results validate the ability of these staging systems to stratify survival outcomes in NAC patients, with best discrimination achieved using AJCC pathologic prognostic stage or RCB.