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Towards an objective classification of pachychoroid disease and its risk of progression

Eye (2026)Cite this article

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Abstract

Purpose

To identify clinical phenotypes in pachychoroid disease (PD), characterise long-term progression patterns, and evaluate the effect of photodynamic therapy (PDT) using machine learning and longitudinal probabilistic modelling.

Methods

This retrospective cohort study included 973 eyes from 663 patients (mean age 54.4 ± 12.8 years; 80% male) diagnosed with PD. Eyes were classified based on macular fluid status into no history, primary, recurrent, or resolved fluid categories. Multimodal imaging data were analysed at baseline and at the final follow-up visit ( > 5 years). Phenotypic clusters were identified using cross-validated K-means clustering on imaging and clinical features. Longitudinal changes in phenotype were evaluated with Markov modelling, including the effect of photodynamic therapy (PDT) on cluster transitions. Visual acuity (VA) changes were estimated with linear mixed models.

Results

Four distinct clusters were defined: Cluster 1 (233 eyes) consisted of younger patients exhibiting active fluid and mild structural alterations (LogMAR 0.16); Cluster 2 (317 eyes) represented mild or resolving PD with optimal VA (LogMAR 0.05); Cluster 3 (336 eyes) featured chronic fluid accumulation, significant structural damage, and moderate visual impairment (LogMAR 0.35); Cluster 4 (87 eyes) corresponded to severe bilateral disease and worst VA (LogMAR 0.66). At baseline, Clusters 1 to 4 were distributed as follows: 22.7%, 25.5%, 39.8%, and 12.0%. Over follow-up (mean 90.2 ± 24 months), the distribution shifted to 3.7%, 32.4%, 36.6%, and 27.3%, indicating progression toward more advanced phenotypes. Cluster 1 had frequent transitions, with 53% eyes progressing to Cluster 2 and 37% to Cluster 3. Cluster 4 showed minimal transition (96% stable). Interaction indicated greater visual deterioration in more severe baseline phenotypes (p = 0.01). PDT administration did not significantly alter disease progression (p > 0.5).

Conclusion

PD exhibits distinct, dynamically evolving phenotypes with measurable probabilistic progression over time. As this represents an exploratory, data-driven analysis, the identified clusters should be interpreted as hypothesis-generating. Significant structural changes occurred despite PDT, underscoring the need for therapies capable of modifying the underlying disease course rather than its local manifestations.

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Fig. 1: Cluster distribution, changes in composition, transition probabilities, and changes in visual acuity in pachychoroid disease (PD).
Fig. 2: Multimodal imaging of a patient from Cluster 1.
Fig. 3: Multimodal imaging of a patient from Cluster 2.
Fig. 4: Multimodal imaging of a patient from Cluster 3.
Fig. 5: Multimodal imaging of a patient from Cluster 4.

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Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author upon reasonable request.

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Acknowledgements

a. Funding/Support: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. b. Financial disclosures: Maria Vittoria Cicinelli, Lorenzo Bianco, Lorenzo Caminada, Eugenio Barlocci, Chiara Giuffré, Maria Pia De Carlo, Jay Chhablani, Ugo Introini: No financial disclosures. Francesco Bandello, consultant for: Allergan Inc (Irvine, California, USA), Bayer Shering-Pharma (Berlin, Germany), Hoffmann-La-Roche (Basel, Switzerland), Novartis (Basel, Switzerland), Sanofi-Aventis (Paris, France), Thrombogenics (Heverlee, Belgium), Zeiss (Dublin, USA), Boehringer-Ingelheim, Fidia Sooft, Ntc Pharma, Sifi. c. Other acknowledgments: None.

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Authors and Affiliations

  1. School of Medicine, Vita-Salute San Raffaele University, Milan, Italy

    Maria Vittoria Cicinelli, Lorenzo Bianco, Lorenzo Caminada, Eugenio Barlocci, Maria Pia De Carlo, Ugo Introini & Francesco Bandello

  2. Department of Ophthalmology, IRCCS San Raffaele Scientific Institute, Milan, Italy

    Maria Vittoria Cicinelli, Lorenzo Bianco, Lorenzo Caminada, Eugenio Barlocci, Ugo Introini & Francesco Bandello

  3. Centro Europeo di Oftalmologia, Palermo, Italy

    Chiara Giuffré

  4. University of Pittsburgh, School of Medicine, Pittsburgh, PA, USA

    Jay Chhablani

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All the authors contributed to the conception or design of the work, the acquisition, analysis, and interpretation of data, drafting of the work, revising it critically for intellectual content. Each of the coauthors has seen and agrees with the way his or her name is listed.

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Correspondence to Maria Vittoria Cicinelli.

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Cicinelli, M.V., Bianco, L., Caminada, L. et al. Towards an objective classification of pachychoroid disease and its risk of progression. Eye (2026). https://doi.org/10.1038/s41433-026-04286-7

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