4.5 Article

A Baseline Score to Predict Response to Ranibizumab Treatment in Neovascular Age-Related Macular Degeneration

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Publisher

ASSOC RESEARCH VISION OPHTHALMOLOGY INC
DOI: 10.1167/tvst.10.6.11

Keywords

BCVA; anti-VEGF; ranibizumab; meta-marker

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The study analyzed the effects of ranibizumab treatment on patients with neovascular age-related macular degeneration, identifying seven baseline characteristics predictive of treatment response and disease progression, and proposed a composite score to discriminate patients' response to treatment.
Purpose: What are the patient characteristics predictive of response to ranibizumab treatment? Methods: Model-based characterization of best-corrected visual acuity (BCVA) time profiles of patients with neovascular age-related macular degeneration under ranibizumab or sham treatment based on 24-month observations of BCVA in 2419 patients from randomized multicenter phase 3 trials of ranibizumab: ANCHOR, MARINA, PIER, and HARBOR. Goodness-of-fit plots and precision of parameter estimates were used for measure of accuracy. Results: The model incorporates a long-term effect on disease progression and an additive and more potent short-term effect of ranibizumab. Response to ranibizumab treatment and progression of the disease were found to be a function of seven baseline characteristics (visual acuity, age, leakage size, central retinal lesion thickness, presence or absence of cyst, type of choroidal neovascularization (CNV), and size of pigment epithelium detachment). A composite score of these seven baseline characteristics was derived and used to categorize response to ranibizumab treatment. The ranibizumab treatment arms of two proof-of-concept studies held out from the model development were used to validate the methodology. Conclusions: A composite score based on seven patient characteristics prior to treatment could be used to discriminate patients with predicted insufficient response to anti- vascular endothelial growth factor treatment. Translational Relevance: The method could be used to create a virtual ranibizumab treatment arm in clinical trials or to reduce the size of a ranibizumab active control arm.

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