دورية أكاديمية
A Nomogram and Risk Classification System Predicting the Prognosis of Patients with De Novo Metastatic Breast Cancer Undergoing Immediate Breast Reconstruction: A Surveillance, Epidemiology, and End Results Population-Based Study
العنوان: | A Nomogram and Risk Classification System Predicting the Prognosis of Patients with De Novo Metastatic Breast Cancer Undergoing Immediate Breast Reconstruction: A Surveillance, Epidemiology, and End Results Population-Based Study |
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المؤلفون: | Jingjing Zhao, Shichang Bian, Xu Di, Chunhua Xiao |
المصدر: | Current Oncology, Vol 31, Iss 1, Pp 115-131 (2023) |
بيانات النشر: | MDPI AG, 2023. |
سنة النشر: | 2023 |
المجموعة: | LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
مصطلحات موضوعية: | nomogram, de novo metastatic breast cancer, immediate breast reconstruction, breast cancer-specific survival, SEER database, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282 |
الوصف: | Background The lifespan of patients diagnosed with de novo metastatic breast cancer (dnMBC) has been prolonged. Nonetheless, there remains substantial debate regarding immediate breast reconstruction (IBR) for this particular subgroup of patients. The aim of this study was to construct a nomogram predicting the breast cancer-specific survival (BCSS) of dnMBC patients who underwent IBR. Methods A total of 682 patients initially diagnosed with metastatic breast cancer (MBC) between 2010 and 2018 in the Surveillance, Epidemiology, and End Results (SEER) database were included in this study. All patients were randomly allocated into training and validation groups at a ratio of 7:3. Univariate Cox hazard regression, least absolute shrinkage and selection operator (LASSO), and best subset regression (BSR) were used for initial variable selection, followed by a backward stepwise multivariate Cox regression to identify prognostic factors and construct a nomogram. Following the validation of the nomogram with concordance indexes (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCAs), risk stratifications were established. Results Age, marital status, T stage, N stage, breast subtype, bone metastasis, brain metastasis, liver metastasis, lung metastasis, radiotherapy, and chemotherapy were independent prognostic factors for BCSS. The C-indexes were 0.707 [95% confidence interval (CI), 0.666–0.748] in the training group and 0.702 (95% CI, 0.639–0.765) in the validation group. In the training group, the AUCs for BCSS were 0.857 (95% CI, 0.770–0.943), 0.747 (95% CI, 0.689–0.804), and 0.700 (95% CI, 0.643–0.757) at 1 year, 3 years, and 5 years, respectively, while in the validation group, the AUCs were 0.840 (95% CI, 0.733–0.947), 0.763 (95% CI, 0.677–0.849), and 0.709 (95% CI, 0.623–0.795) for the same time points. The calibration curves for BCSS probability prediction demonstrated excellent consistency. The DCA curves exhibited strong discrimination power and yielded substantial net benefits. Conclusions The nomogram, constructed based on prognostic risk factors, has the ability to provide personalized predictions for BCSS in dnMBC patients undergoing IBR and serve as a valuable reference for clinical decision making. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | English |
تدمد: | 31010008 1718-7729 1198-0052 |
Relation: | https://www.mdpi.com/1718-7729/31/1/8; https://doaj.org/toc/1198-0052; https://doaj.org/toc/1718-7729 |
DOI: | 10.3390/curroncol31010008 |
URL الوصول: | https://doaj.org/article/2d3ed11542bd463fb383ec258633f23e |
رقم الأكسشن: | edsdoj.2d3ed11542bd463fb383ec258633f23e |
قاعدة البيانات: | Directory of Open Access Journals |
تدمد: | 31010008 17187729 11980052 |
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DOI: | 10.3390/curroncol31010008 |