Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Key Laboratory of Ocular Fundus Diseases, Chinese Academy of Medical Sciences, Beijing, China.
Ann Med. 2024 Dec;56(1):2393273. doi: 10.1080/07853890.2024.2393273. Epub 2024 Aug 27.
Polypoidal choroidal vasculopathy (PCV) is a hemorrhagic fundus disease that can lead to permanent vision loss. Predicting the treatment response to anti-VEGF monotherapy in PCV is consistently challenging. We aimed to conduct a prospective multicenter study to explore and identify the imaging biomarkers for predicting the anti-VEGF treatment response in PCV patients, establish predictive model, and undergo multicenter validation.
This prospective multicenter study utilized clinical characteristics and images of treatment naïve PCV patients from 15 ophthalmic centers nationwide to screen biomarkers, develop model, and validate its performance. Patients from Peking Union Medical College Hospital were randomly divided into a training set and an internal validation set. A nomogram was established by univariate, LASSO regression, and multivariate regression analysis. Patients from the other 14 centers served as an external test set. Area under the curve (AUC), sensitivity, specificity, and accuracy were calculated. Decision curve analysis (DCA) and clinical impact curve (CIC) were utilized to evaluate the practical utility in clinical decision-making.
The eye distribution for the training set, internal validation set, and external test set were 66, 31, and 71, respectively. The 'Good responder' exhibited a thinner subfoveal choroidal thickness (SFCT) (230.67 ± 61.96 314.42 ± 88.00 μm, < 0.001), lower choroidal vascularity index (CVI) (0.31 ± 0.08 0.36 ± 0.05, = 0.006), fewer choroidal vascular hyperpermeability (CVH) (31.0 62.2%, = 0.012), and more intraretinal fluid (IRF) (58.6 29.7%, = 0.018). SFCT (OR 0.990; 95% CI 0.981-0.999; = 0.033) and CVI (OR 0.844; 95% CI 0.732-0.971; = 0.018) were ultimately included as the optimal predictive biomarkers and presented in the form of a nomogram. The model demonstrated AUC of 0.837 (95% CI 0.738-0.936), 0.891 (95% CI 0.765-1.000), and 0.901 (95% CI 0.824-0.978) for predicting 'Good responder' in the training set, internal validation set, and external test set, respectively, with excellent sensitivity, specificity, and practical utility.
Thinner SFCT and lower CVI can serve as imaging biomarkers for predicting good treatment response to anti-VEGF monotherapy in PCV patients. The nomogram based on these biomarkers exhibited satisfactory performances.
息肉样脉络膜血管病变（PCV）是一种可导致永久性视力丧失的出血性眼底疾病。预测 PCV 患者对抗 VEGF 单药治疗的反应一直具有挑战性。我们旨在进行一项前瞻性多中心研究，以探索和确定预测 PCV 患者抗 VEGF 治疗反应的影像学生物标志物，建立预测模型，并进行多中心验证。
本前瞻性多中心研究利用全国 15 个眼科中心的治疗初治 PCV 患者的临床特征和图像来筛选生物标志物、建立模型并验证其性能。来自北京协和医学院医院的患者被随机分为训练集和内部验证集。通过单变量、LASSO 回归和多变量回归分析建立列线图。其他 14 个中心的患者作为外部测试集。计算曲线下面积（AUC）、灵敏度、特异性和准确性。决策曲线分析（DCA）和临床影响曲线（CIC）用于评估在临床决策中的实际效用。
训练集、内部验证集和外部测试集的眼分布分别为 66、31 和 71。“良好反应者”的中心凹下脉络膜厚度（SFCT）更薄（230.67±61.96μm 比 314.42±88.00μm，<0.001），脉络膜血管密度指数（CVI）更低（0.31±0.08 比 0.36±0.05，=0.006），脉络膜血管通透性增加（CVH）更少（31.0%比 62.2%，=0.012），视网膜内液（IRF）更多（58.6%比 29.7%，=0.018）。SFCT（OR 0.990；95%CI 0.981-0.999；=0.033）和 CVI（OR 0.844；95%CI 0.732-0.971；=0.018）最终被选为最佳预测生物标志物，并以列线图的形式呈现。该模型在训练集、内部验证集和外部测试集中预测“良好反应者”的 AUC 分别为 0.837（95%CI 0.738-0.936）、0.891（95%CI 0.765-1.000）和 0.901（95%CI 0.824-0.978），具有良好的灵敏度、特异性和实际效用。
较薄的 SFCT 和较低的 CVI 可作为预测 PCV 患者抗 VEGF 单药治疗良好反应的影像学生物标志物。基于这些生物标志物的列线图表现出令人满意的性能。
