Yan Li, Xiaoping Ma, Zhenhui Zhao, Li Li, Chunyan Gao, Dan Liu, Bingyu Li, Bing Zhao
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引用次数: 0
摘要
背景:髓样浸润性乳腺癌(Invasive breast cancer, BC)是一种特殊类型的乳腺癌,占浸润性乳腺癌的3 ~ 6%。目的探讨新疆地区侵袭性髓质BC的临床病理特点,并分析影响预后的因素。材料与方法:对2011年1月至2020年12月新疆省肿瘤医院收治的100例髓质浸润性BC患者的临床病理资料进行回顾性分析。计数资料采用COX回归模型及相关统计学方法进行分析。结果:100例患者均为女性,中位年龄48岁。中位随访时间为92个月。10年累积无病生存率(DFS)为84.1%。Log-Rank检验结果提示,种族、TNM分期、肿瘤大小、淋巴结转移、病理类型等可能是影响髓系浸润性乳腺癌患者的不利因素(p结论:髓系浸润性乳腺癌病理特征较差,但临床预后较好。种族、TNM分期、肿瘤大小、淋巴结转移、病理类型是影响髓样特征浸润性乳腺癌患者的可能不利因素。
Clinicopathological observation and prognostic factors of invasive breast cancer with medullary in Xinjiang.
Background: Invasive breast cancer (BC) with medullary is a special type of BC, accounting for 3 ~ 6% of invasive BC. To investigate clinicopathological characteristics concerning invasive BC with medullary in Xinjiang area and analyze the prognostic factors of patients.
Materials and methods: Clinicopathological data of100 invasive BC patients with medullary admitted to Xinjiang tumor Hospital from January 2011 to December 2020 were analyzed retrospectively via R packages. Count data were analyzed applying COX regression model and relevant statistics approaches.
Results: All 100patients that investigated were female and the median age was 48 years old. The median follow-up time was 92 months. The the cumulative disease free survival (DFS) at 10 years were 84.1%. Log-Rank test results suggest that ethnicity, TNM stage, tumor size, lymph node metastasis, and pathological type are possible adverse factors affecting patients with invasive breast cancer with myeloid features (P<0.05).
Conclusion: Despite the poor pathological features of Invasive BC with medullary, its clinical outcome is more favorable. Ethnicity, TNM stage, tumor size, lymph node metastasis, and pathological type are possible adverse factors affecting patients with invasive breast cancer with medullary features.
期刊介绍:
BMC Medical Informatics and Decision Making is an open access journal publishing original peer-reviewed research articles in relation to the design, development, implementation, use, and evaluation of health information technologies and decision-making for human health.