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Screening optimal candidates with operable, early-stage triple-negative breast cancer benefitting from capecitabine maintenance: A post-hoc analysis of the SYSUCC-001 study

dc.contributor.authorFangfang Duan
dc.contributor.authorXin Hua
dc.contributor.authorXiwen Bi
dc.contributor.authorShusen Wang
dc.contributor.authorYanxia Shi
dc.contributor.authorFei Xu
dc.contributor.authorLi Wang
dc.contributor.authorJiajia Huang
dc.contributor.authorZhongyu Yuan
dc.contributor.authorYuanyuan Huang
dc.contributor.otherDepartment of Anesthesiology, Sun Yat-Sen University Cancer Center, The State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
dc.contributor.otherDepartment of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
dc.contributor.otherDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, The State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
dc.contributor.otherDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, The State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
dc.contributor.otherDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, The State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
dc.contributor.otherDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, The State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
dc.contributor.otherDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, The State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
dc.contributor.otherDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, The State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China; Corresponding author.
dc.contributor.otherDepartment of Medical Oncology, Sun Yat-Sen University Cancer Center, The State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China; Corresponding author.
dc.contributor.otherDepartment of VIP Region, Sun Yat-Sen University Cancer Center, The State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China; Corresponding author.
dc.date.accessioned2024-05-11T04:24:27Z
dc.date.accessioned2025-10-08T09:26:02Z
dc.date.available2025-10-08T09:26:02Z
dc.date.issued01-08-2024
dc.identifier.urihttp://digilib.fisipol.ugm.ac.id/repo/handle/15717717/40370
dc.description.abstractBackground: 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.
dc.language.isoEN
dc.publisherElsevier
dc.subject.lccNeoplasms. Tumors. Oncology. Including cancer and carcinogens
dc.titleScreening optimal candidates with operable, early-stage triple-negative breast cancer benefitting from capecitabine maintenance: A post-hoc analysis of the SYSUCC-001 study
dc.typeArticle
dc.description.keywordsTriple-negative breast cancer
dc.description.keywordsIdeal patients
dc.description.keywordsCapecitabine maintenance
dc.description.keywordsDisease-free survival
dc.description.keywordsPredicting model
dc.description.doi10.1016/j.breast.2024.103740
dc.title.journalBreast
dc.identifier.e-issn1532-3080
dc.identifier.oaioai:doaj.org/journal:7921eb249b964685bf640b145064e145


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