法国现实世界的faricimab转换:基于人工智能的检测难以治疗的新生血管性年龄相关性黄斑变性的渗出体征变化。

IF 2 Q2 OPHTHALMOLOGY
Vincent Gualino, Charles Sohier, Maxime Sibert, Ali Erginay, Fanny Varenne, Jacqueline Butterworth, Aude Couturier, Pierre-Henry Gabrielle, Vincent Soler, Catherine Creuzot-Garcher
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引用次数: 0

摘要

目的:一些新生血管性年龄相关性黄斑变性(nAMD)患者在玻璃体内注射抗血管内皮生长因子(VEGF)药物治疗时有持续的渗出迹象。我们检查了反应不佳的患者的真实解剖反应,并使用基于人工智能(AI)的视网膜液定量方法切换到faricimab。方法:在法国进行一项回顾性、多中心、队列研究,患者有渗出症状,在没有新的负荷期的情况下改用法昔单抗,保持相同的先前注射间隔。RetInSight Fluid Monitor AI软件在光谱域光学相干断层扫描上量化视网膜下(SRF)和视网膜内(IRF)流体。主要结果是在一次和两次注射法利昔单抗后,中央1和6 mm视网膜区域的SRF和IRF体积的变化。结果:纳入74例患者(74只眼),平均年龄81.5±8.4岁,男性49%。平均1 mm IRF显著降低(-2.9±18.3 nl;p=0.002),平均6 mm IRF(-17.7±71.1 nl;padjOR 0.965;p=0.028)和较低的基线IRF体积预测两次注射后的干反应(adjOR 0.373;p = 0.051)。结论:近一半的患者在两次注射后获得了干性反应。人工智能辅助的流体定量提供了客观监测,确定较低的基线SRF和IRF作为良好反应的预测因素。有限的患者纳入意味着现在需要更长期更大规模的前瞻性研究,使用自动视网膜液定量来进一步完善良好开关应答者的基线特征,以更好地适应开关方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-world faricimab switch in France: artificial intelligence-based detection of changes in exudative signs in difficult-to-treat neovascular age-related macular degeneration.

Purpose: Some patients with neovascular age-related macular degeneration (nAMD) have persistent signs of exudation under treatment with intravitreal injections of anti-vascular endothelial growth factor (VEGF) agents. We examined the real-world anatomical responses among patients with suboptimal response and switched to faricimab using artificial intelligence (AI)-based retinal fluid quantification.

Methods: A retrospective, multicentric, cohort study of patients in France with exudative signs and switched to faricimab without a new loading phase, maintaining the same prior injection interval. The RetInSight Fluid Monitor AI software quantified subretinal (SRF) and intraretinal (IRF) fluid on spectral domain optical coherence tomography. The primary outcome was change in SRF and IRF volumes in the central 1 and 6 mm retinal areas after one and two injections of faricimab.

Results: 74 patients (74 eyes) were included (mean age: 81.5±8.4 years, 49% male). Significant reductions were observed in mean 1 mm IRF (-2.9±18.3 nl; p=0.002), mean 6 mm IRF (-17.7±71.1 nl; p<0.001) and mean 6 mm SRF (-24.8±156.3 nl; p<0.001) volumes after one injection. The proportion of dry eyes (<5 nl for SRF and IRF in the 1 and 6 mm areas) increased from 0% at baseline to 32.4% after one injection and 48.4% after two injections. Lower baseline SRF volumes were predictive of dry response after one injection (adjOR 0.965; p=0.028) and lower baseline IRF volumes were predictive of dry response after two injections (adjOR 0.373; p=0.051).

Conclusion: Nearly half of patients achieved a dry response after two injections. AI-assisted fluid quantification provided objective monitoring, identifying lower baseline SRF and IRF as predictive factors for good response. Limited patient inclusion means longer-term and larger prospective studies are now required using automated retinal fluid quantification to further refine the baseline characteristics of good switch responders to better adapt switch protocols.

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来源期刊
BMJ Open Ophthalmology
BMJ Open Ophthalmology OPHTHALMOLOGY-
CiteScore
3.40
自引率
4.20%
发文量
104
审稿时长
20 weeks
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