Comparative survival outcomes of neoadjuvant and adjuvant therapy in patients with T1c, node-negative, triple-negative breast cancer: A population-based analysis
Background: Ongoing discussions persist concerning the precedence of neoadjuvant therapy (NAT) relative to adjuvant therapy (AT) for patients with T1c, node-negative, triple-negative breast cancer (TNBC), and pertinent guidelines for these individuals are absent. Methods: Women diagnosed with T1cN0M...
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Elsevier
2025-02-01
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| Series: | Breast |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0960977625000062 |
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| author | Yi-Zi Zheng Jia-Qi Ying Ting-Ting Wu Yong-Hui Su Ou-Chen Wang |
| author_facet | Yi-Zi Zheng Jia-Qi Ying Ting-Ting Wu Yong-Hui Su Ou-Chen Wang |
| author_sort | Yi-Zi Zheng |
| collection | DOAJ |
| description | Background: Ongoing discussions persist concerning the precedence of neoadjuvant therapy (NAT) relative to adjuvant therapy (AT) for patients with T1c, node-negative, triple-negative breast cancer (TNBC), and pertinent guidelines for these individuals are absent. Methods: Women diagnosed with T1cN0M0-stage TNBC who received chemotherapy and surgery were selected from the Surveillance, Epidemiology and End Results database (2010–2020). To balance baseline characteristics and mitigate selection bias, propensity score matching (PSM) was used to create the NAT and AT cohorts. Kaplan–Meier (KM) analysis and Cox proportional hazards models were performed to assess the prognostic factors for overall survival (OS) and breast cancer–specific survival (BCSS). Logistic regression models were utilized to identify predictive factors for response to NAT. Results: A total of 1033 patient pairs passed the PSM process, resulting in a well-balanced distribution. The KM analysis demonstrated that patients who received AT and those who underwent NAT had similar OS and BCSS, no matter before or after PSM. The multivariate Cox model showed that not achieving pathological complete response (non-pCR) following NAT, compared to AT, was associated with considerably worse OS (hazard ratio [HR], 2.207; 95 % confident intervaI [CI], 1.431–3.405; p < 0.001) and worse BCSS (HR, 2.184; 95 % CI, 1.348–3.537; p = 0.002). The logistic regression model revealed that being under 50 years old and having grade III or undifferentiated disease were independent predictors of pCR. Conclusions: In patients with T1cN0M0-stage TNBC, both NAT and AT resulted in equivalent OS and BCSS. However, NAT precisely helped select patients with worse prognosis. |
| format | Article |
| id | doaj-art-b46329112c5243a69ead8c1aa447ff6b |
| institution | Kabale University |
| issn | 1532-3080 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Breast |
| spelling | doaj-art-b46329112c5243a69ead8c1aa447ff6b2025-02-12T05:30:39ZengElsevierBreast1532-30802025-02-0179103877Comparative survival outcomes of neoadjuvant and adjuvant therapy in patients with T1c, node-negative, triple-negative breast cancer: A population-based analysisYi-Zi Zheng0Jia-Qi Ying1Ting-Ting Wu2Yong-Hui Su3Ou-Chen Wang4Department of Breast Surgery, Zhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Breast Surgery, Zhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Breast Surgery, Zhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, ChinaDepartment of Breast Surgery, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China; Corresponding author. Department of Breast Surgery, The First Affiliated Hospital of Xiamen University, Xiamen, 361003, Fujian, China.Department of Breast Surgery, Zhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China; Corresponding author. Department of Breast surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.Background: Ongoing discussions persist concerning the precedence of neoadjuvant therapy (NAT) relative to adjuvant therapy (AT) for patients with T1c, node-negative, triple-negative breast cancer (TNBC), and pertinent guidelines for these individuals are absent. Methods: Women diagnosed with T1cN0M0-stage TNBC who received chemotherapy and surgery were selected from the Surveillance, Epidemiology and End Results database (2010–2020). To balance baseline characteristics and mitigate selection bias, propensity score matching (PSM) was used to create the NAT and AT cohorts. Kaplan–Meier (KM) analysis and Cox proportional hazards models were performed to assess the prognostic factors for overall survival (OS) and breast cancer–specific survival (BCSS). Logistic regression models were utilized to identify predictive factors for response to NAT. Results: A total of 1033 patient pairs passed the PSM process, resulting in a well-balanced distribution. The KM analysis demonstrated that patients who received AT and those who underwent NAT had similar OS and BCSS, no matter before or after PSM. The multivariate Cox model showed that not achieving pathological complete response (non-pCR) following NAT, compared to AT, was associated with considerably worse OS (hazard ratio [HR], 2.207; 95 % confident intervaI [CI], 1.431–3.405; p < 0.001) and worse BCSS (HR, 2.184; 95 % CI, 1.348–3.537; p = 0.002). The logistic regression model revealed that being under 50 years old and having grade III or undifferentiated disease were independent predictors of pCR. Conclusions: In patients with T1cN0M0-stage TNBC, both NAT and AT resulted in equivalent OS and BCSS. However, NAT precisely helped select patients with worse prognosis.http://www.sciencedirect.com/science/article/pii/S0960977625000062Early-stage breast cancerTriple-negative breast cancerNeoadjuvant therapySurvival outcomesSurveillanceEpidemiology |
| spellingShingle | Yi-Zi Zheng Jia-Qi Ying Ting-Ting Wu Yong-Hui Su Ou-Chen Wang Comparative survival outcomes of neoadjuvant and adjuvant therapy in patients with T1c, node-negative, triple-negative breast cancer: A population-based analysis Breast Early-stage breast cancer Triple-negative breast cancer Neoadjuvant therapy Survival outcomes Surveillance Epidemiology |
| title | Comparative survival outcomes of neoadjuvant and adjuvant therapy in patients with T1c, node-negative, triple-negative breast cancer: A population-based analysis |
| title_full | Comparative survival outcomes of neoadjuvant and adjuvant therapy in patients with T1c, node-negative, triple-negative breast cancer: A population-based analysis |
| title_fullStr | Comparative survival outcomes of neoadjuvant and adjuvant therapy in patients with T1c, node-negative, triple-negative breast cancer: A population-based analysis |
| title_full_unstemmed | Comparative survival outcomes of neoadjuvant and adjuvant therapy in patients with T1c, node-negative, triple-negative breast cancer: A population-based analysis |
| title_short | Comparative survival outcomes of neoadjuvant and adjuvant therapy in patients with T1c, node-negative, triple-negative breast cancer: A population-based analysis |
| title_sort | comparative survival outcomes of neoadjuvant and adjuvant therapy in patients with t1c node negative triple negative breast cancer a population based analysis |
| topic | Early-stage breast cancer Triple-negative breast cancer Neoadjuvant therapy Survival outcomes Surveillance Epidemiology |
| url | http://www.sciencedirect.com/science/article/pii/S0960977625000062 |
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