PurposeTo study the status quo of the cognitive function of the breast cancer patients with (who went through) the endocrine therapy by the epidemiological investigation, analyze the key factor of the cognition impairment and explore the impact of the endocrine therapy time on the cognition decline after using Propensity Score Matching to balance the covariates.MethodsIn this study, the epidemiological questionnaire information was collected from 226 female breast cancer endocrine treatment patients who visited the Breast Clinic of Longhua Hospital Affiliated to Shanghai University of Chinese Medicine from November 2020 to February 2022, and the results of the overall cognitive function, the function test of each cognitive domain, the patient’s self-cognition, quality of life, and emotional status evaluation of the patients. In this study, according to the principle of random matching, the nearest matching method with a matching tolerance of 0.2 and a matching ratio of 1:2 was used for orientation score matching. After the covariant such as age, BMI, and duration of education were balanced, the effects of the duration of endocrine therapy on the overall cognitive function and the functions of each cognitive domain were analyzed.ResultsIn 226 cases of female breast cancer patients (who went through) the endocrine therapy, the propensity score matching was performed, ultimately, 99 were ruled out, successful matched ones were 49 of the cognition-decline group and 78 of the standard group. With age, education time, BMI and other covariates balanced, the endocrine therapy duration was the risk factor of the cognition impairment (P < 0.05, OR = 1.296, 95% CI = 1.008−1.665), with the extension of endocrine treatment time, there was a rising risk of the cognition impairment (LLA statistic = 5.872, P < 0.05). The cognitive domain scores in the cognition-decline group were lower than the standard group (P < 0.05), but there was a difference in self-report cognition.ConclusionThe endocrine therapy duration was the risk factor for the cognition impairment of the breast cancer patients, and with prolonged endocrine treatment, there was a rising (an increasing) risk for the cognition impairment.

PurposeTo establish a high-risk prediction model for aromatase inhibitor-associated bone loss (AIBL) in patients with hormone receptor-positive breast cancer.MethodsThe study included breast cancer patients who received aromatase inhibitor (AI) treatment. Univariate analysis was performed to identify risk factors associated with AIBL. The dataset was randomly divided into a training set (70%) and a test set (30%). The identified risk factors were used to construct a prediction model using the eXtreme gradient boosting (XGBoost) machine learning method. Logistic regression and least absolute shrinkage and selection operator (LASSO) regression methods were used for comparison. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the model in the test dataset.ResultsA total of 113 subjects were included in the study. Duration of breast cancer, duration of aromatase inhibitor therapy, hip fracture index, major osteoporotic fracture index, prolactin (PRL), and osteocalcin (OC) were found to be independent risk factors for AIBL (p < 0.05). The XGBoost model had a higher AUC compared to the logistic model and LASSO model (0.761 vs. 0.716, 0.691).ConclusionThe XGBoost model outperformed the logistic and LASSO models in predicting the occurrence of AIBL in patients with hormone receptor-positive breast cancer receiving aromatase inhibitors.

No abstract