Zhang Bailin, Wu Jinqi, Zheng Rongshou, Zhang Qian, Wang Margaret Zhuoer, Qi Jun, Liu Haijing, Wang Yipeng, Guo Yang, Chen Feng, Wang Jing, Lyu Wenyue, Gao Jidong, Fang Yi, Chen Wanqing, Wang Xiang
Department of Breast Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Department of Breast Surgery, Cancer Hospital of Huanxing Chaoyang District Beijing, Beijing 100122, China.
Chin J Cancer Res. 2018 Aug;30(4):468-476. doi: 10.21147/j.issn.1000-9604.2018.04.10.
In patients with chemotherapy-induced amenorrhea (CIA), the menopausal status is ambiguous and difficult to evaluate. This study aimed to establish a discriminative model to predict and classify the menopausal status of breast cancer patients with CIA.
This is a single center hospital-based study from 2013 to 2016. The menopausal age distribution and accumulated incidence rate of CIA are described. Multivariate models were adjusted for established and potential confounding factors including age, serum concentration of estradiol (E2) and follicle-stimulating hormone (FSH), feeding, pregnancy, parity, abortions, and body mass index (BMI). The odds ratio (OR) and 95% confidence interval (95% CI) of different risk factors were estimated.
A total of 1,796 breast cancer patients were included in this study, among whom, 1,175 (65.42%) were premenopausal patients and 621 (34.58%) were post-menopause patients. Five hundred and fifty patients were included in CIA analysis, and a cumulative CIA rate of 81.64% was found in them. Age (OR: 1.856, 95% CI: 1.732-1.990), serum concentration of E2 (OR: 0.976, 95% CI: 0.972-0.980) and FSH (OR: 1.060, 95% CI: 1.053-1.066), and menarche age (OR: 1.074, 95% CI: 1.009-1.144) were found to be associated with the patients' menopausal status. According to multivariate analysis, the discriminative model to predict the menopausal status is Logit (P)=-28.396+0.536Age-0.014E2+0.031FSH. The sensitivities for this model were higher than 85%, and its specificities were higher than 89%.
The discriminative model obtained from this study for predicting menstrual state is important for premenopausal patients with CIA. This model has high specificity and sensitivity and should be prudently used.
在化疗所致闭经(CIA)患者中,绝经状态不明确且难以评估。本研究旨在建立一种判别模型,以预测和分类患有CIA的乳腺癌患者的绝经状态。
这是一项基于单中心医院的2013年至2016年的研究。描述了CIA的绝经年龄分布和累积发病率。多变量模型针对已确定和潜在的混杂因素进行了调整,包括年龄、雌二醇(E2)和促卵泡激素(FSH)的血清浓度、哺乳、妊娠、产次、流产次数以及体重指数(BMI)。估计了不同危险因素的比值比(OR)和95%置信区间(95%CI)。
本研究共纳入1796例乳腺癌患者,其中1175例(65.42%)为绝经前患者,621例(34.58%)为绝经后患者。550例患者纳入CIA分析,其中CIA累积发生率为81.64%。发现年龄(OR:1.856,95%CI:1.732 - 1.990)、E2血清浓度(OR:0.976,95%CI:0.972 - 0.980)和FSH(OR:1.060,95%CI:1.053 - 1.066)以及初潮年龄(OR:1.074,95%CI:1.009 - 1.144)与患者的绝经状态相关。根据多变量分析,预测绝经状态的判别模型为Logit(P)= -28.396 + 0.536年龄 - 0.014E2 + 0.031FSH。该模型的敏感性高于85%,特异性高于89%。
本研究获得的用于预测月经状态的判别模型对患有CIA的绝经前患者很重要。该模型具有高特异性和敏感性,应谨慎使用。