Huang Zhen-Huan, Tu Xue-Zhao, Lin Qi, Tu Mei, Lin Guo-Cai, Zhang Kai-Ping
Department of Radiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan 364000, Fujian Province, China.
Department of Orthopedics, Longyan First Affiliated Hospital of Fujian Medical University, Longyan 364000, Fujian Province, China.
World J Radiol. 2024 Sep 28;16(9):418-428. doi: 10.4329/wjr.v16.i9.418.
Anti-vascular endothelial growth factor (anti-VEGF) therapy is critical for managing neovascular age-related macular degeneration (nAMD), but understanding factors influencing treatment efficacy is essential for optimizing patient outcomes.
To identify the risk factors affecting anti-VEGF treatment efficacy in nAMD and develop a predictive model for short-term response.
In this study, 65 eyes of exudative AMD patients after anti-VEGF treatment for ≥ 1 mo were observed using optical coherence tomography angiography. Patients were classified into non-responders ( = 22) and responders ( = 43). Logistic regression was used to determine independent risk factors for treatment response. A predictive model was created using the Akaike Information Criterion, and its performance was assessed with the area under the receiver operating characteristic curve, calibration curves, and decision curve analysis (DCA) with 500 bootstrap re-samples.
Multivariable logistic regression analysis identified the number of junction voxels [odds ratio = 0.997, 95% confidence interval (CI): 0.993-0.999, = 0.010] as an independent predictor of positive anti-VEGF treatment outcomes. The predictive model incorporating the fractal dimension, number of junction voxels, and longest shortest path, achieved an area under the curve of 0.753 (95%CI: 0.622-0.873). Calibration curves confirmed a high agreement between predicted and actual outcomes, and DCA validated the model's clinical utility.
The predictive model effectively forecasts 1-mo therapeutic outcomes for nAMD patients undergoing anti-VEGF therapy, enhancing personalized treatment planning.
抗血管内皮生长因子（抗VEGF）疗法对于治疗新生血管性年龄相关性黄斑变性（nAMD）至关重要，但了解影响治疗效果的因素对于优化患者治疗结果至关重要。
确定影响nAMD患者抗VEGF治疗效果的危险因素，并建立短期反应的预测模型。
在本研究中，使用光学相干断层扫描血管造影观察了65例接受抗VEGF治疗≥1个月的渗出性AMD患者的眼睛。患者分为无反应者（n = 22）和有反应者（n = 43）。采用逻辑回归确定治疗反应的独立危险因素。使用赤池信息准则创建预测模型，并通过受试者操作特征曲线下面积、校准曲线和500次自抽样重采样的决策曲线分析（DCA）评估其性能。
多变量逻辑回归分析确定连接体素数量[比值比 = 0.997，95%置信区间（CI）：0.993 - 0.999，P = 0.010]是抗VEGF治疗阳性结果的独立预测因子。纳入分形维数、连接体素数量和最长最短路径的预测模型的曲线下面积为0.753（95%CI：0.622 - 0.873）。校准曲线证实预测结果与实际结果高度一致，DCA验证了该模型的临床实用性。
该预测模型有效地预测了接受抗VEGF治疗的nAMD患者的1个月治疗结果，有助于加强个性化治疗方案的制定。
