Novel models by machine learning to predict prognosis of breast cancer brain metastases

Autor: Chaofan Li, Mengjie Liu, Yinbin Zhang, Yusheng Wang, Jia Li, Shiyu Sun, Xuanyu Liu, Huizi Wu, Cong Feng, Peizhuo Yao, Yiwei Jia, Yu Zhang, Xinyu Wei, Fei Wu, Chong Du, Xixi Zhao, Shuqun Zhang, Jingkun Qu
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Journal of Translational Medicine, Vol 21, Iss 1, Pp 1-18 (2023)
Druh dokumentu: article
ISSN: 1479-5876
DOI: 10.1186/s12967-023-04277-2
Popis: Abstract Background Breast cancer brain metastases (BCBM) are the most fatal, with limited survival in all breast cancer distant metastases. These patients are deemed to be incurable. Thus, survival time is their foremost concern. However, there is a lack of accurate prediction models in the clinic. What’s more, primary surgery for BCBM patients is still controversial. Methods The data used for analysis in this study was obtained from the SEER database (2010–2019). We made a COX regression analysis to identify prognostic factors of BCBM patients. Through cross-validation, we constructed XGBoost models to predict survival in patients with BCBM. Meanwhile, a BCBM cohort from our hospital was used to validate our models. We also investigated the prognosis of patients treated with surgery or not, using propensity score matching and K–M survival analysis. Our results were further validated by subgroup COX analysis in patients with different molecular subtypes. Results The XGBoost models we created had high precision and correctness, and they were the most accurate models to predict the survival of BCBM patients (6-month AUC = 0.824, 1-year AUC = 0.813, 2-year AUC = 0.800 and 3-year survival AUC = 0.803). Moreover, the models still exhibited good performance in an externally independent dataset (6-month: AUC = 0.820; 1-year: AUC = 0.732; 2-year: AUC = 0.795; 3-year: AUC = 0.936). Then we used Shiny-Web tool to make our models be easily used from website. Interestingly, we found that the BCBM patients with an annual income of over USD$70,000 had better BCSS (HR = 0.523, 95%CI 0.273–0.999, P
Databáze: Directory of Open Access Journals
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