Uveal melanoma survival prediction system: a multi-center database study

Area of Science:

• Ophthalmology
• Oncology
• Biostatistics

Background:

• Uveal Melanoma (UM) is a rare but aggressive eye cancer.
• Accurate prediction of overall survival (OS) is crucial for effective patient management.
• Existing prognostic models may require refinement for personalized treatment approaches.

Purpose of the Study:

• To develop and validate a competing risk nomogram for predicting OS in UM patients.
• To identify independent risk factors influencing survival in UM.
• To assess the clinical utility and accuracy of the developed nomogram.

Main Methods:

• Utilized a large cohort of 14,688 UM patients from the SEER database (2000-2020).
• Employed univariate and multivariate Cox regression analyses to identify risk factors.
• Validated the nomogram using calibration curves, ROC curves, and decision curve analysis (DCA).

Main Results:

• Identified six independent risk factors: chemotherapy, radiation, tumor burden, pathological type, grade, and diagnostic confirmation.
• The nomogram demonstrated excellent discriminative ability with high AUC values (e.g., 5-year AUCs of 0.91 in training and 0.90 in testing).
• Calibration plots and DCA confirmed good predictive accuracy and clinical utility.

Conclusions:

• The developed nomogram provides a highly accurate tool for assessing survival prognosis in UM patients.
• This tool can enhance the precision of UM patient survival evaluation.
• The nomogram serves as a valuable guide for developing personalized treatment plans for uveal melanoma.