Background: Survival prediction for patients with leptomeningeal metastasis (LM) is crucial for making proper management plans and counseling patients. Prognostic models in this patient domain have been limited, and existing models often include predictors that are not available in resource-limited settings. Our aim was to develop a practical, individualized survival prediction model for patients diagnosed with LM.
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