Preoperative Breast Immune Prognostic Index as Prognostic Factor Predicts the Clinical Outcomes of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

被引:4
作者
Chen, Li [1 ,2 ]
Kong, Xiangyi [2 ]
Huang, Shaolong [3 ]
Su, Zhaohui [4 ]
Zhu, Mengliu [2 ]
Fang, Yi [2 ]
Zhang, Lin [5 ,6 ,7 ]
Li, Xingrui [1 ]
Wang, Jing [2 ]
机构
[1] Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Dept Thyroid & Breast Surg, Wuhan, Peoples R China
[2] Chinese Acad Med Sci & Peking Union Med Coll, Natl Clin Res Ctr Canc, Canc Hosp, Natl Canc Ctr, Beijing, Peoples R China
[3] Tongren City Peoples Hosp, Dept Thyroid & Breast Burn & Plast Surg, Tongren, Peoples R China
[4] Univ Texas UT Hlth San Antonio, Ctr Smart & Connected Hlth Technol, Mays Canc Ctr, Sch Nursing, San Antonio, TX USA
[5] Univ Melbourne, Melbourne Sch Populat & Global Hlth, Melbourne, Vic, Australia
[6] Victorian Comprehens Canc Ctr, Ctr Canc Res, Melbourne, Vic, Australia
[7] Chinese Acad Med Sci & Peking Union Med Coll, Sch Populat Med & Publ Hlth, Beijing, Peoples R China
来源
FRONTIERS IN IMMUNOLOGY | 2022年 / 13卷
基金
国家重点研发计划;
关键词
breast cancer; breast immune prognostic index; nomogram; neoadjuvant chemotherapy; survival; SERUM LACTATE-DEHYDROGENASE; TO-LYMPHOCYTE RATIO; RETROSPECTIVE ANALYSIS; INFLAMMATION; NEUTROPHIL; SURVIVAL; TARGET; IMMUNOTHERAPY; ASSOCIATION; MECHANISMS;
D O I
10.3389/fimmu.2022.831848
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
ObjectiveThis study aims at investigating the potential prognostic significance of the breast immune prognostic index (BIPI) in breast cancer patients who received neoadjuvant chemotherapy (NACT). MethodsThe 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. ResultsAll 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. ConclusionsThe 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.
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页数:16
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