Nomogram for predicting radiation maculopathy in patients treated with Ruthenium-106 plaque brachytherapy for uveal melanoma

Purpose: To develop a predictive model and nomogram for maculopathy occurrence at 3 years after Ru-106/Rh-106 plaque brachytherapy in uveal melanoma. Material and methods: Clinical records of patients affected by choroidal melanoma and treated with Ru-106/Rh-106 plaque from December 2006 to December 2014 were retrospectively reviewed. Inclusion criteria were: dome-shaped melanoma, distance to the fovea > 1.5 mm, tumor thickness > 2 mm, and follow-up > 4 months. The delivered dose to the tumor apex was 100 Gy. Primary endpoint of this investigation was the occurrence of radiation maculopathy at 3 years. Analyzed factors were as follows: gender, age, diabetes, tumor size (volume, area, largest basal diameter and apical height), type of plaque, distance to the fovea, presence of exudative detachment, drusen, orange pigment, radiation dose to the fovea and sclera. Univariate and multivariate Cox proportional hazards analyses were used to define the impact of baseline patient factors on the occurrence of maculopathy. Kaplan-Meier curves were used to estimate freedom from the occurrence of the maculopathy. The model performance was evaluated through internal validation using area under the ROC curve (AUC), and calibration with Gronnesby and Borgan tests. Results: One hundred ninety-seven patients were considered for the final analysis. Radiation-related maculopathy at 3 years was observed in 41 patients. The proposed nomogram can predict maculopathy at 3 years with an AUC of 0.75. Distance to fovea appeared to be the main prognostic factor of the predictive model (hazard ratio of 0.83 [0.76-0.90], p < 0.01). Diabetes (hazard radio of 2.92 [1.38-6.20], p < 0.01), and tumor volume (hazard radio of 21.6 [1.66-281.14], p = 0.02) were significantly predictive for maculopathy occurrence. The calibration showed no statistical difference between actual and predicted maculopathy (p = 1). Conclusions: Our predictive model, together with its nomogram, could be a useful tool to predict the occurrence of radiation maculopathy at 3 years after the treatment.