Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Front Immunol. 2022 Mar 7;13:831848. doi: 10.3389/fimmu.2022.831848. eCollection 2022.
This study aims at investigating the potential prognostic significance of the breast immune prognostic index (BIPI) in breast cancer patients who received neoadjuvant chemotherapy (NACT).
The optimal cutoff value was calculated through the receiver operating characteristic curve (ROC). The correlations between BIPI and clinicopathologic characteristics were determined by the chi-square test or Fisher's exact test. The Kaplan-Meier method was used to estimate the survival probability, and the log-rank test was used to analyze the differences in the survival probability among patients. The univariate and multivariate Cox proportional hazard regression model was used to screen the independent prognostic factors. A prognostic nomogram for disease-free survival (DFS) and overall survival (OS) was built on the basis of the multivariate analyses. Furthermore, the calibration curve and decision curve analysis (DCA) were used to assess the predictive performance of the nomogram.
All enrolled patients were split into three subgroups based on the BIPI score. The mean DFS and OS of the BIPI score 0 group and BIPI score 1 group were significantly longer than those of the BIPI score 2 group (42.02 vs. 38.61 vs. 26.01 months, 77.61 vs. 71.83 vs. 53.15 months; p < 0.05). Univariate and multivariate analyses indicated that BIPI was an independent prognostic factor for patients' DFS and OS (DFS, hazard ratio (HR): 6.720, 95% confidence interval (CI): 1.629-27.717; OS, HR: 8.006, 95% CI: 1.638-39.119). A nomogram with a C-index of 0.873 (95% CI: 0.779-0.966) and 0.801 (95% CI: 0.702-0.901) had a favorable performance for predicting DFS and OS survival rates for clinical use by combining immune scores with other clinical features. The calibration curves at 1-, 3-, and 5-year survival suggested a good consistency between the predicted and actual DFS and OS probability. The DCA demonstrated that the constructed nomogram had better clinical predictive usefulness than only BIPI in predictive clinical applications of 5-year DFS and OS prognostic assessments.
The patients with low BIPI score have better prognoses and longer DFS and OS. Furthermore, the BIPI-based nomogram may serve as a convenient prognostic tool for breast cancer and help in clinical decision-making.
本研究旨在探讨乳腺癌患者接受新辅助化疗（NACT）后，乳腺免疫预后指数（BIPI）的潜在预后意义。
通过受试者工作特征曲线（ROC）计算最佳截断值。采用卡方检验或 Fisher 确切检验确定 BIPI 与临床病理特征的相关性。采用 Kaplan-Meier 法估计生存概率，采用对数秩检验分析患者生存概率的差异。采用单因素和多因素 Cox 比例风险回归模型筛选独立预后因素。基于多因素分析建立无病生存（DFS）和总生存（OS）的预后列线图。此外，采用校准曲线和决策曲线分析（DCA）评估列线图的预测性能。
所有入组患者根据 BIPI 评分分为三组。BIPI 评分 0 组和 BIPI 评分 1 组的平均 DFS 和 OS 明显长于 BIPI 评分 2 组（42.02 个月比 38.61 个月比 26.01 个月，77.61 个月比 71.83 个月比 53.15 个月；p<0.05）。单因素和多因素分析表明，BIPI 是患者 DFS 和 OS 的独立预后因素（DFS：风险比（HR）：6.720，95%置信区间（CI）：1.629-27.717；OS：HR：8.006，95%CI：1.638-39.119）。包含免疫评分与其他临床特征的列线图的 C 指数为 0.873（95%CI：0.779-0.966）和 0.801（95%CI：0.702-0.901），对预测 DFS 和 OS 生存率具有良好的性能，可用于临床。1、3 和 5 年生存的校准曲线表明，DFS 和 OS 概率的预测值与实际值之间具有良好的一致性。DCA 表明，与仅基于 BIPI 相比，构建的列线图在 5 年 DFS 和 OS 预后评估的临床预测应用中具有更好的临床预测价值。
BIPI 评分低的患者具有更好的预后和更长的 DFS 和 OS。此外，基于 BIPI 的列线图可以作为乳腺癌的一种便捷的预后工具，有助于临床决策。
