Abstract
Diabetic retinopathy (DR) is a common complication of type II diabetes mellitus (T2DM) and a leading cause of blindness in the working population. Apolipoprotein levels have been reported to be associated with the risk of DR. This study aimed to develop a predictive model for DR based on apolipoproteins (apoA and apoB) and menopausal status in Chinese Han women with T2DM and to evaluate the model's effectiveness. Data from 2339 T2DM women were collected between January 2018 and June 2022. Multilevel regression was used to explore the independent effect of apolipoproteins and interaction between apolipoproteins and menopausal status on DR and proliferative diabetic retinopathy (PDR). Receiver operating characteristic (ROC) analysis was performed to compare the fitting degree and predictive efficiency of different models. Results showed that both apoA and apoB were independent influencing factors for DR and PDR and interacted significantly with menopausal status. The interaction between apoA and menopausal status had a protective effect on DR [OR (95% CI) = 0.925 (0.858-0.996), P = 0.040] and PDR [OR (95% CI) = 0.937 (0.895-0.981), P = 0.006]. In contrast, the interaction between apoB and menopausal status was a risk factor for DR [OR (95% CI) = 1.684 (1.141-2.379), P = 0.008)] and PDR [OR (95% CI) = 3.377 (1.148-9.937), P = 0.027]. ROC analysis demonstrated that the interaction model outperformed models without interaction terms (P < 0.01). The area under the curve for the interaction model was 0.879 (95% CI 0.864-0.893) for DR and 0.930 (95% CI 0.915-0.945) for PDR. These findings suggest that the interaction model is highly efficient in predicting DR, particularly PDR, in Chinese Han women with T2DM.