摘要
Objective： In patients with chemotherapy-induced amenorrhea （CIA）, the menopausal status is ambiguous anddifficult to evaluate. This study aimed to establish a discriminative model to predict and classify the menopausalstatus of breast cancer patients with CIA.Methods： This is a single center hospital-based study from 2013 to 2016. The menopausal age distribution andaccumulated incidence rate of CIA are described. Multivariate models were adjusted for established and potentialconfounding 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% confidenceinterval （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%） werepremenopausal patients and 621 （34.58%） were post-menopause patients. Five hundred and fifty patients wereincluded 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-i.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 isLogit （P）=-28.396＋0.536Age-0.014E2＋0.031FSH. The sensitivities for this model were higher than 85%, and itsspecificities were higher than 89%.Conclusions： The discriminative model obtained from this study for predicting menstrual state is important forpremenopausal patients with CIA. This model has high specificity and sensitivity and should be prudently used.
Objective： In patients with chemotherapy-induced amenorrhea （CIA）, the menopausal status is ambiguous anddifficult to evaluate. This study aimed to establish a discriminative model to predict and classify the menopausalstatus of breast cancer patients with CIA.Methods： This is a single center hospital-based study from 2013 to 2016. The menopausal age distribution andaccumulated incidence rate of CIA are described. Multivariate models were adjusted for established and potentialconfounding 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% confidenceinterval （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%） werepremenopausal patients and 621 （34.58%） were post-menopause patients. Five hundred and fifty patients wereincluded 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-i.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 isLogit （P）=-28.396＋0.536Age-0.014E2＋0.031FSH. The sensitivities for this model were higher than 85%, and itsspecificities were higher than 89%.Conclusions： The discriminative model obtained from this study for predicting menstrual state is important forpremenopausal patients with CIA. This model has high specificity and sensitivity and should be prudently used.
基金
supported by Chinese Medical Foundation (CMF, No. 313.2215)
