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重度非增殖性糖尿病视网膜病变患者抗VEGF联合激光治疗反应的预测因素:基于回顾性数据的列线图模型的构建与验证

Predictors of response to anti-VEGF combined with laser therapy in severe non-proliferative diabetic retinopathy: development and validation of a nomogram model from retrospective data.

作者信息

Cui Chunmei, Li Yuehua, Zhang Qian

机构信息

Department of Ophthalmology, Beijing Chaoyang Hospital Affiliated to Capital Medical University, Beijing, China.

出版信息

Front Endocrinol (Lausanne). 2025 Sep 3;16:1648425. doi: 10.3389/fendo.2025.1648425. eCollection 2025.

Abstract

BACKGROUND

Anti-vascular endothelial growth factor (anti-VEGF) and laser combination therapy demonstrates variable efficacy in severe non-proliferative diabetic retinopathy, with 30-45% of patients experiencing suboptimal outcomes. This study aimed to develop and validate a clinically deployable nomogram integrating multimodal predictors to quantify individualized treatment response probabilities.

METHODS

A retrospective cohort study analyzed 280 severe non-proliferative diabetic retinopathy patients (Early Treatment Diabetic Retinopathy Study levels 43-53) receiving combined anti-VEGF (ranibizumab/aflibercept) and laser therapy (2018-2023). The primary outcome was a 12-month composite response (no proliferative diabetic retinopathy progression, ≥2-step Diabetic Retinopathy Severity Scale improvement or ≥30% retinal lesion reduction, and no rescue therapy). Least absolute shrinkage and selection operator regression with the "one standard error" rule selected key predictors from 15 candidate variables. A multivariable logistic regression model was translated into a nomogram, validated temporally (70%/30% split) using area under the curve, calibration curves, and decision curve analysis.

RESULTS

Four predictors were retained: glycated hemoglobin variability (adjusted odds ratio 0.63 per 5% increase; 95% confidence interval 0.51-0.78), fluorescein angiography non-perfusion area (adjusted odds ratio 0.68 per 10% increase; 95% confidence interval 0.55-0.84), Diabetic Retinopathy Severity Scale severity (adjusted odds ratio 0.72 per grade; 95% confidence interval 0.55-0.94), and serum albumin (adjusted odds ratio 1.85 per 0.5 g/dL; 95% confidence interval 1.22-2.81). The nomogram achieved robust discrimination (derivation area under the curve 0.821, validation area under the curve 0.754) and calibration (slopes 0.98-0.95; Hosmer-Lemeshow P > 0.60). Decision curve analysis confirmed clinical utility at 15-40% threshold probabilities (net benefit 0.28), outperforming "treat-all" strategies.

CONCLUSIONS

This validated nomogram-integrating glycemic stability, retinal ischemia, baseline severity, and systemic nutrition-provides individualized response probabilities for anti-VEGF and laser therapy. It enables risk stratification to guide treatment intensification in severe non-proliferative diabetic retinopathy, addressing a critical unmet need in personalized retinopathy management.

摘要

背景

抗血管内皮生长因子(抗VEGF)与激光联合治疗在重度非增殖性糖尿病视网膜病变中的疗效存在差异,30%-45%的患者预后不理想。本研究旨在开发并验证一种可临床应用的列线图,整合多模式预测指标以量化个体化治疗反应概率。

方法

一项回顾性队列研究分析了280例接受抗VEGF(雷珠单抗/阿柏西普)与激光联合治疗的重度非增殖性糖尿病视网膜病变患者(糖尿病视网膜病变早期治疗研究43-53级)(2018-2023年)。主要结局为12个月的综合反应(无增殖性糖尿病视网膜病变进展、糖尿病视网膜病变严重程度量表改善≥2级或视网膜病变减少≥30%,且无需挽救治疗)。采用最小绝对收缩和选择算子回归及“一个标准误”规则从15个候选变量中筛选关键预测指标。将多变量逻辑回归模型转化为列线图,使用曲线下面积、校准曲线和决策曲线分析进行时间验证(70%/30%划分)。

结果

保留了4个预测指标:糖化血红蛋白变异性(每增加5%,调整后的比值比为0.63;95%置信区间为0.51-0.78)、荧光素血管造影无灌注区(每增加10%,调整后的比值比为0.68;95%置信区间为0.55-0.84)、糖尿病视网膜病变严重程度量表严重程度(每增加1级,调整后的比值比为0.72;95%置信区间为0.55-0.94)和血清白蛋白(每增加0.5 g/dL,调整后的比值比为1.85;95%置信区间为1.22-2.81)。该列线图具有较强的区分度(推导曲线下面积为0.821,验证曲线下面积为0.754)和校准度(斜率为0.98-0.95;Hosmer-Lemeshow P>0.60)。决策曲线分析证实了在阈值概率为15%-40%时的临床实用性(净效益为0.28),优于“全治疗”策略。

结论

这种经过验证的整合血糖稳定性、视网膜缺血、基线严重程度和全身营养状况的列线图,可为抗VEGF与激光治疗提供个体化反应概率。它能够进行风险分层,以指导重度非增殖性糖尿病视网膜病变的治疗强化,满足个性化视网膜病变管理中一项关键的未满足需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a720/12440731/966f30edda10/fendo-16-1648425-g001.jpg

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