Objective Aromatase inhibitor-induced arthralgia (AIA) is an adverse effect observed in patients treated with aromatase inhibitors. This study aimed to establish a predictive model for AIA in patients with breast cancer living in high-altitude regions.

Methods  A retrospective analysis was conducted on 315 patients with breast cancer who received aromatase inhibitor treatment at the Affiliated Hospital of Qinghai University between June 2021 and October 2023. Patients were randomly allocated to the training set (n=220) or validation set (n=95) in a 7:3 ratio. Variable selection was performed using the least absolute shrinkage and selection operator (LASSO) regression followed by 7-fold cross-validation. Multivariate Logistic regression analysis was conducted on the training set to identify independent risk factors for AIA, leading to the establishment of a nomogram. The performance of the model was assessed using calibration plots, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).

Results Multivariate Logistic regression analysis identified several significant independent predictors for AIA in patients with breast cancer from high-altitude regions, including prior taxane chemotherapy (odds ratio (OR)=10.174, 95% confidence interval (CI):2.008-62.69, P=0.008), years since last menstrual period (LMP) (OR=0.175, 95%CI:0.052-0.494, P=0.002), drug-induced menopause (OR=3.834, 95%CI:1.109-14.13, P =0.036), cancer stage (OR=10.423, 95%CI:4.114-32.15, P<0.001), and psychological factors (OR=25.108, 95%CI:8.430-87.95, P<0.001). The AIA incidence rate in this cohort was 58.41%, while the area under the ROC curve was 0.971.