Abstract
OBJECTIVE: 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. METHODS: 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. RESULTS: 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%. CONCLUSIONS: 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.