Standard Automated Perimetry (SAP) is the mainstay for monitoring glaucoma progression and has been accepted by the U.S. Food and Drug Administration (FDA) as a trial endpoint, but only under stringent criteria of ≥7 dB loss in five pre-specified test locations. Identifying such locations a priori has remained a major barrier for neuroprotection trials. We developed an attention-based graph neural network (GNN) to predict the visual field points most likely to deteriorate (High-5) using baseline SAP data. The model was trained in the Bascom Palmer Ophthalmic Registry (BPOR; 6,996 eyes, 5,405 patients, 40,914 tests) and externally validated in the Duke Glaucoma Registry (DGR; 5,211 eyes, 3,933 patients, 31,225 tests) and the University of Washington Humphrey Visual Field dataset (UWHVF; 2,030 eyes, 1,195 patients, 10,310 tests). In internal validation, the mean slope at High-5 points among progressors was −2.16±0.80 dB/year, compared to −0.55±0.44 dB/year for Low-5 and −1.02±0.40 dB/year for mean deviation (MD). Similar results were observed in DGR (–2.05 vs −0.45 vs −0.93 dB/year) and UWHVF (−2.32 vs −0.66 vs −1.14 dB/year). High-5 showed superior discrimination of progressors from non-progressors with areas under the ROC curve of 0.883, 0.898, and 0.937 across the three cohorts, consistently outperforming MD (0.871–0.911) and Low-5 (0.668–0.731). Nearly all progressing eyes exhibited a repeatable ≥7 dB loss in average High-5 sensitivity during follow-up, compared to fewer than 30% when using MD. In sample size projections, High-5 increased the absolute effect size and lowered the σ2/Δ2 ratio, translating into an estimated 42% reduction in required trial size compared to MD. In conclusion, this GNN-based framework enables data-driven identification of high-risk SAP locations, aligning with regulatory definitions of progression while substantially improving trial efficiency and sensitivity to detect meaningful visual field change.

Funding This work was supported in part by NIH R01 (EY036593) and by the Glaucoma Research Foundation (grant Endpoints2025MedeF).

DRC received consulting fees from Voiston. RS reports funding from Redcheck and holds a patent with Eyetec SlitSmart. FAM received consulting fees from Abbvie, Annexon, Carl Zeiss Meditec, Enavate Sciences, Galimedix, ONL Therapeutics, Perfuse Therapeutics, Perceive Bio, Stealth Biotherapeutics, Stuart Therapeutics, and Thea Pharmaceuticals; reports funding from Google Inc., Heidelberg Engineering, Novartis, and Reichert; and holds a patent with nGoggle Inc. These relationships are unrelated to the submitted work. All other authors declare no competing interests.

This work was supported in part by NIH R01 (EY036593) and by the Glaucoma Research Foundation (grant Endpoints2025MedeF)

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The Institutional Review Board of the University of Miami (Bascom Palmer Eye Institute) waived ethical approval for this work due to its retrospective nature. The Institutional Review Board of Duke University waived ethical approval for this work due to its retrospective nature. The University of Washington Institutional Review Board approved the creation of the publicly available Humphrey Visual Field dataset, which was de-identified in accordance with HIPAA regulations.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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The de-identified visual field data used in this study are available from the corresponding author upon reasonable request. Requests will be evaluated in accordance with institutional data-sharing policies.