Construction of a Nomogram prediction model for the efficacy of Conbercept in treating diabetic macular edema
10.13389/j.cnki.rao.2024.0134
- VernacularTitle:糖尿病黄斑水肿患者康柏西普疗效诺莫图预测模型的构建
- Author:
Miao LIU
1
;
Yu JIN
;
Fangxiu YUAN
;
Ling WANG
;
Lei WU
Author Information
1. 330038 江西省南昌市,南昌市第一医院眼科
- Keywords:
diabetes mellitus;
macular edema;
Conbercept;
prediction model;
Nomogram
- From:
Recent Advances in Ophthalmology
2024;44(9):702-706
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the early warning factors for the efficacy of Conbercept in treating diabetic macular edema(DME)and build a Nomograph prediction model based on the early warning factors.Methods A total of 269 DME patients(269 eyes)treated with Conbercept at Nanchang First Hospital from January 2021 to March 2023 were se-lected and divided into an effective group and an ineffective group according to the therapeutic effect at 3 months after treatment.Single factor analysis was made on the efficacy of Conbercept.The random forest method was used to screen and reduce the dimension of the characteristic variables on the efficacy of Conbercept,Logistic regression was used to ana-lyze the relevant factors affecting the efficacy of Conbercept,and R language was used to draw the Nomograph prediction model on the efficacy of Conbercept.The decision curve analysis(DCA)was made to evaluate the clinical effectiveness of the Nomograph prediction model.Results The duration of diabetes,drinking history,fasting blood glucose,2-hour postprandial blood glucose,and glycosylated hemoglobin of patients in the ineffective group were higher than those in the effective group,while the macular central retinal thickness and vessel density in the foveal retinal deep capillary plexus were lower than those in the effective group(all P＜0.05).According to the random forest algorithm,the top five predic-tive factors for the efficacy of Conbercept were glycosylated hemoglobin,macular central retinal thickness,fasting blood glucose,2-hour postprandial blood glucose,and vessel density in the foveal retinal deep capillary plexus.Logistic regres-sion analysis showed that glycosylated hemoglobin(OR=5.012),fasting blood glucose(OR=3.877),and 2-hour post-prandial blood glucose(OR=4.231)were risk factors for the efficacy of Conbercept,while the macular central retinal thickness(OR=0.409)and vessel density in the foveal retinal deep capillary plexus(OR=0.410)were protective factors for the efficacy of Conbercept(all P＜0.05).The Nomograph showed that the C-index of the prediction model was 0.900(95％CI:0.859-0.941),the sensitivity was 90.58％,and the specificity was 75.64％.The DCA curve showed that using the Nomogram prediction model to predict the efficacy of Conbercept could obtain positive net benefit,suggesting that it had certain clinical effectiveness.Conclusion The efficacy of Conbercept for DME patients is affected by a variety of factors,including glycosylated hemoglobin,fasting blood glucose,2-hour postprandial blood glucose,macular central reti-nal thickness,and vessel density in the foveal retinal deep capillary plexus.The Nomogram model constructed based on the above factors may be used to predict patients'treatment response in early stage,providing evidence for clinical decision-making.
