External Validation of a Bayesian Neural Network Model in Survival Analysis

This paper describes the evaluation of a regularized Bayesian neural network model in prognostic applications. A total sample size of 5442 subjects treated with ocular melanoma in two centers; Liverpool and Paris was used to carry out external validation analysis of the model. The performance of the model was benchmarked against the traditional Cox regression model and a clinically accepted TNM staging system. The cumulative hazards curve for the neural network model was much closer to the empirical curve in the test data than the one produced by the Cox model. The neural network model showed equal performance to Cox's model in terms of discrimination. However, the neural network model was better than Cox's model in terms of calibration. The paper proposes an alternative staging system based on the model, which takes into account histopathological information. The new system has many advantages over the existing staging system.