Improved Prediction of Survival Outcomes Using Residual Cancer Burden in Combination With Ki-67 in Breast Cancer Patients Underwent Neoadjuvant Chemotherapy

被引:8
作者
Kim, Ji-Yeon [1 ,2 ]
Oh, Jung Min [2 ]
Lee, Se Kyung [3 ]
Yu, Jonghan [3 ]
Lee, Jeong Eon [3 ,4 ]
Kim, Seok Won [3 ]
Nam, Seok Jin [3 ]
Park, Yeon Hee [1 ,2 ,4 ]
Ahn, Jin Seok [1 ]
Kim, Kyunga [5 ,6 ,7 ]
Im, Young-Hyuck [1 ,2 ,4 ]
机构
[1] Sungkyunkwan Univ, Samsung Med Ctr, Dept Med, Div Hematol Oncol,Sch Med, Seoul, South Korea
[2] Sungkyunkwan Univ, Biomed Res Inst, Samsung Med Ctr, Sch Med, Seoul, South Korea
[3] Sungkyunkwan Univ, Samsung Med Ctr, Dept Surg, Sch Med, Seoul, South Korea
[4] Sungkyunkwan Univ, Samsung Adv Inst Hlth Sci & Technol, Dept Hlth Sci & Technol, Seoul, South Korea
[5] Sungkyunkwan Univ, Samsung Med Ctr, Dept Data Convergence & Future Med, Sch Med, Seoul, South Korea
[6] Sungkyunkwan Univ, Samsung Adv Inst Hlth Sci & Technol, Dept Digital Hlth, Seoul, South Korea
[7] Samsung Med Ctr, Biomed Stat Ctr, Res Inst Future Med, Seoul, South Korea
来源
FRONTIERS IN ONCOLOGY | 2022年 / 12卷
基金
新加坡国家研究基金会;
关键词
neoadjuvant chemotherapy; Ki-67; residual cancer burden; prediction model; breast cancer; residual proliferative cancer burden; PATHOLOGICAL COMPLETE RESPONSE; TRASTUZUMAB; PERTUZUMAB; SAFETY;
D O I
10.3389/fonc.2022.903372
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
We developed a model for improving the prediction of survival outcome using postoperative Ki-67 value in combination with residual cancer burden (RCB) in patients with breast cancer (BC) who underwent neoadjuvant chemotherapy (NAC). We analyzed the data from BC patients who underwent NAC between 2010 and 2019 at Samsung Medical Center and developed our residual proliferative cancer burden (RPCB) model using semi-quantitative Ki-67 value and RCB class. The Cox proportional hazard model was used to develop our RPCB model according to disease free survival (DFS) and overall survival (OS). In total, 1,959 patients were included in this analysis. Of 1,959 patients, 905 patients were excluded due to RCB class 0, and 32 were due to a lack of Ki-67 data. Finally, an RPCB model was developed using data from 1,022 patients. The RPCB score was calculated for DFS and OS outcomes, respectively (RPCB-DFS and RPCB-OS). For further survival analysis, we divided the population into 3 classes according to the RPCB score. In the prediction of DFS, C-indices were 0.751 vs 0.670 and time-dependent areas under the receiver operating characteristic curves (AUCs) at 3-year were 0.740 vs 0.669 for RPCB-DFS and RCB models, respectively. In the prediction of OS, C-indices were 0.819 vs 0.720 and time-dependent AUCs at 3-year were 0.875 vs 0.747 for RPCB-OS and RCB models, respectively. The RPCB model developed using RCB class and semi-quantitative Ki-67 had superior predictive value for DFS and OS compared with that of RCB class. This prediction model could provide the basis to decide risk-stratified treatment plan for BC patients who had residual disease after NAC.
引用
收藏
页数:9
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