Prediction Model of Treatment Efficacy for Age-related Macular Degeneration Based on Multi-source Imaging Modalities

NCT06583109 | Not Yet Recruiting

• 1 other identifier: BJ-2024-089
• Study Type: observational
• Target: 2,600
• Locations: 0 countries
• Sites: N/A

Brief Summary

Age-related macular degeneration (AMD) is one of the main causes of blindness in the elderly population. Intraocular injection of anti-VEGF drugs for neovascular AMD (nAMD) is the main treatment method at present. However, patients have different responses to anti-VEGF therapy, and some patients do not respond well to short - and long-term treatment. In this study, a retrospective study was adopted to collate and analyze the clinical data and imaging data of nAMD in the past, and to extract the imaging features from the multimodal modalities before and after treatment for deep learning, and to evaluate and quantify the clinical features, and to construct two multi-source feature models for predicting the short-term and long-term prognosis of nAMD patients. By verifying the accuracy of the model to predict the curative effect, the classification efficiency of the above characteristic models was compared, and the optimal model was selected. Its clinical application value was evaluated by calibration curve and decision curve. In addition, patients with poor treatment response in the study cohort were retrospectively analyzed, and the efficacy and safety of the combination of other treatment options in the actual clinic were analyzed. The purpose of this study is to provide scientific basis for early prediction, dynamic monitoring and optimization of overall treatment strategies for nAMD.

Conditions

Age-related Macular Degeneration (ARMD)

Outcome Measures

Primary Outcomes (1)

• BCVA

  best-corrected visual acuity using LogMAR

  Baseline, 3 months after anti-VEGF treatment, 1 year after anti-VEGF treatment

Secondary Outcomes (1)

• CMT

  Baseline, 3 months after anti-VEGF treatment, 1 year after anti-VEGF treatment

Eligibility Criteria

• Age: 50 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients diagnosed with nAMD who had completed routine follow-up within 1 year after standard anti-VEGF therapy with complete demographic and ophthalmological data were retrospectively collected.

You may qualify if:

• Patients diagnosed with nAMD by ophthalmic examinations including OCT, OCTA, FFA and ICGA;
• Complete clinical data and imaging data of patients were available at baseline, 3 months and 1 year after anti-VEGF treatment.

You may not qualify if:

• Medical records showed other diseases affecting visual function or fundus imaging, such as macular edema, glaucoma, ocular trauma, etc;
• Medical records showed that two or more macular lesions coexist in the affected eye;
• Medical records showed that patients received other treatments within 1 year of anti-VEGF therapy, such as intraocular laser therapy or ocular surgery;
• Medical records showed that there were ocular media opacity, dense macular hemorrhage, or severe macular atrophy, resulting in the inability to accurately measure the required parameters;
• Medical records showed the use of drugs known to cause retinal toxicity, or a history of radiation exposure.

Sponsors & Collaborators

• Beijing Hospital: lead

MeSH Terms

Conditions

Macular Degeneration

Condition Hierarchy (Ancestors)

Retinal Degeneration; Retinal Diseases; Eye Diseases

Central Study Contacts

YUE ZHANG

CONTACT

18811729626; 962693948@qq.com

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER GOV
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 1, 2024
• First Posted: September 3, 2024
• Study Start: October 1, 2024
• Primary Completion: January 1, 2026
• Study Completion (Estimated): June 1, 2026
• Last Updated: September 3, 2024

Record last verified: 2024-09

Data Sharing

• IPD Sharing: Will not share