Fangfang Duan , Xin Hua , Xiwen Bi , Shusen Wang , Yanxia Shi , Fei Xu , Li Wang , Jiajia Huang , Zhongyu Yuan , Yuanyuan Huang , South China Breast Cancer Group (SCBCG)
{"title":"筛选可手术的早期三阴性乳腺癌患者的最佳候选者，使其从卡培他滨维持治疗中获益：SYSUCC-001 研究的事后分析","authors":"Fangfang Duan , Xin Hua , Xiwen Bi , Shusen Wang , Yanxia Shi , Fei Xu , Li Wang , Jiajia Huang , Zhongyu Yuan , Yuanyuan Huang , South China Breast Cancer Group (SCBCG)","doi":"10.1016/j.breast.2024.103740","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>To explore whether specific clinicopathological covariates are predictive for a benefit from capecitabine maintenance in early-stage triple-negative breast cancer (TNBC) in the SYSUCC-001 phase III clinical trial.</p></div><div><h3>Methods</h3><p>Candidate covariates included age, menstrual status, type of surgery, postoperative chemotherapy regimen, Ki-67 percentage, histologic grade, primary tumor size, lymphovascular invasion, node status, and capecitabine medication. Their nonlinear effects were modeled by restricted cubic spline. The primary endpoint was disease-free survival (DFS). A survival prediction model was constructed using Cox proportional hazards regression analysis.</p></div><div><h3>Results</h3><p>All 434 participants (306 in development cohort and 128 in validation cohort) were analyzed. The estimated 5-year DFS in development and validation cohorts were 77.8 % (95 % CI, 72.9%–82.7 %) and 78.2 % (95 % CI, 70.9%–85.5 %), respectively. Age and node status had significant nonlinear effects on DFS. The prediction model constructed using four covariates (node status, lymphovascular invasion, capecitabine maintenance, and age) demonstrated satisfactory calibration and fair discrimination ability, with C-index of 0.722 (95 % CI, 0.662–0.781) and 0.764 (95 % CI, 0.668–0.859) in development and validation cohorts, respectively. Moreover, patient classification was conducted according to their risk scores calculated using our model, in which, notable survival benefits were reported in low-risk subpopulations. An easy-to-use online calculator for predicting benefit of capecitabine maintenance was also designed.</p></div><div><h3>Conclusions</h3><p>The evidence-based prediction model can be readily assessed at baseline, which might help decision making in clinical practice and optimize patient stratification, especially for those with low-risk, capecitabine maintenance might be a potential strategy in the early-disease setting.</p></div>","PeriodicalId":9093,"journal":{"name":"Breast","volume":"76 ","pages":"Article 103740"},"PeriodicalIF":5.7000,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0960977624000717/pdfft?md5=b730cbcca6c33356795ce29d270dc38e&pid=1-s2.0-S0960977624000717-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Screening optimal candidates with operable, early-stage triple-negative breast cancer benefitting from capecitabine maintenance: A post-hoc analysis of the SYSUCC-001 study\",\"authors\":\"Fangfang Duan , Xin Hua , Xiwen Bi , Shusen Wang , Yanxia Shi , Fei Xu , Li Wang , Jiajia Huang , Zhongyu Yuan , Yuanyuan Huang , South China Breast Cancer Group (SCBCG)\",\"doi\":\"10.1016/j.breast.2024.103740\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>To explore whether specific clinicopathological covariates are predictive for a benefit from capecitabine maintenance in early-stage triple-negative breast cancer (TNBC) in the SYSUCC-001 phase III clinical trial.</p></div><div><h3>Methods</h3><p>Candidate covariates included age, menstrual status, type of surgery, postoperative chemotherapy regimen, Ki-67 percentage, histologic grade, primary tumor size, lymphovascular invasion, node status, and capecitabine medication. Their nonlinear effects were modeled by restricted cubic spline. The primary endpoint was disease-free survival (DFS). A survival prediction model was constructed using Cox proportional hazards regression analysis.</p></div><div><h3>Results</h3><p>All 434 participants (306 in development cohort and 128 in validation cohort) were analyzed. The estimated 5-year DFS in development and validation cohorts were 77.8 % (95 % CI, 72.9%–82.7 %) and 78.2 % (95 % CI, 70.9%–85.5 %), respectively. Age and node status had significant nonlinear effects on DFS. The prediction model constructed using four covariates (node status, lymphovascular invasion, capecitabine maintenance, and age) demonstrated satisfactory calibration and fair discrimination ability, with C-index of 0.722 (95 % CI, 0.662–0.781) and 0.764 (95 % CI, 0.668–0.859) in development and validation cohorts, respectively. Moreover, patient classification was conducted according to their risk scores calculated using our model, in which, notable survival benefits were reported in low-risk subpopulations. An easy-to-use online calculator for predicting benefit of capecitabine maintenance was also designed.</p></div><div><h3>Conclusions</h3><p>The evidence-based prediction model can be readily assessed at baseline, which might help decision making in clinical practice and optimize patient stratification, especially for those with low-risk, capecitabine maintenance might be a potential strategy in the early-disease setting.</p></div>\",\"PeriodicalId\":9093,\"journal\":{\"name\":\"Breast\",\"volume\":\"76 \",\"pages\":\"Article 103740\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2024-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0960977624000717/pdfft?md5=b730cbcca6c33356795ce29d270dc38e&pid=1-s2.0-S0960977624000717-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Breast\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0960977624000717\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OBSTETRICS & GYNECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Breast","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0960977624000717","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
Screening optimal candidates with operable, early-stage triple-negative breast cancer benefitting from capecitabine maintenance: A post-hoc analysis of the SYSUCC-001 study
Background
To explore whether specific clinicopathological covariates are predictive for a benefit from capecitabine maintenance in early-stage triple-negative breast cancer (TNBC) in the SYSUCC-001 phase III clinical trial.
Methods
Candidate covariates included age, menstrual status, type of surgery, postoperative chemotherapy regimen, Ki-67 percentage, histologic grade, primary tumor size, lymphovascular invasion, node status, and capecitabine medication. Their nonlinear effects were modeled by restricted cubic spline. The primary endpoint was disease-free survival (DFS). A survival prediction model was constructed using Cox proportional hazards regression analysis.
Results
All 434 participants (306 in development cohort and 128 in validation cohort) were analyzed. The estimated 5-year DFS in development and validation cohorts were 77.8 % (95 % CI, 72.9%–82.7 %) and 78.2 % (95 % CI, 70.9%–85.5 %), respectively. Age and node status had significant nonlinear effects on DFS. The prediction model constructed using four covariates (node status, lymphovascular invasion, capecitabine maintenance, and age) demonstrated satisfactory calibration and fair discrimination ability, with C-index of 0.722 (95 % CI, 0.662–0.781) and 0.764 (95 % CI, 0.668–0.859) in development and validation cohorts, respectively. Moreover, patient classification was conducted according to their risk scores calculated using our model, in which, notable survival benefits were reported in low-risk subpopulations. An easy-to-use online calculator for predicting benefit of capecitabine maintenance was also designed.
Conclusions
The evidence-based prediction model can be readily assessed at baseline, which might help decision making in clinical practice and optimize patient stratification, especially for those with low-risk, capecitabine maintenance might be a potential strategy in the early-disease setting.
期刊介绍：
The Breast is an international, multidisciplinary journal for researchers and clinicians, which focuses on translational and clinical research for the advancement of breast cancer prevention, diagnosis and treatment of all stages.
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