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Risk factors for secondary thyroid cancer in patients with breast cancer: a propensity‑matched SEER analysis

医学 乳腺癌 肿瘤科 列线图 内科学 甲状腺癌 癌症 比例危险模型 阶段(地层学) 甲状腺 妇科 生物 古生物学
作者
Yizhuo Diao,Ruiqi Wang,Jiaxue Cui,Chenxin Jin,Yongxing Chen,Xiaofeng Li
出处
期刊:Scientific Reports [Nature Portfolio]
卷期号:14 (1)
标识
DOI:10.1038/s41598-024-59209-x
摘要

Abstract With the rapid development of imaging technology and comprehensive treatment in modern medicine, the early diagnosis rate of breast cancer is constantly improving, and the prognosis is also improving; As breast cancer patients survive longer, the risk of developing second primary cancers increases. Since both breast and thyroid are Hormone receptor sensitive organs, which are regulated by hypothalamus pituitary target gland endocrine axis, changes in body endocrine status may lead to the occurrence of these two diseases in succession or simultaneously. This study extracted clinical data and survival outcomes of breast cancer patients registered in the Surveillance, Epidemiology and End Results (SEER) database between 2010 and 2019. After matching the case and controls with propensity scores, the selected patients were randomly split into training and test datasets at a ratio of 7:3. Univariate and multivariate COX proportional regression analysis is used to determine independent risk factors for secondary thyroid cancer and construct a column chart prediction model. Age, ethnicity, whether radiotherapy, tumor primary location, N stage, M stage were identified by Cox regression as independent factors affecting secondary thyroid cancer in patients with breast cancer patients, and a risk factor nomogram was established to predict patients’ 3 and 5 year survival probabilities. The AUC values for 3 and 5 years in the training set were 0.713, 0.707, and the c-index was 0.693 (95% CI 0.67144, 0.71456), and the AUC values for 3 and 5 years in the validation set were 0.681, 0.681, and the c-index was 0.673 (95% CI 0.64164, 0.70436), respectively.
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