A novel nomogram to predict overall survival in head and neck cancer survivors with radiation-induced brain necrosis.

BACKGROUND AND PURPOSE: The study aimed to develop and validate a novel nomogram to predict overall survival in head and neck cancer survivors following the diagnosis of radiation-induced brain necrosis (RN).

MATERIALS AND

METHODS

We included head and neck cancer survivors with RN from a radiation complications registry study. A total of 495 eligible patients were 7:3 randomly allocated to a training cohort and an internal validation cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select significant predictors of post-RN survival in the training cohort, and a multivariable Cox model was used to develop the nomogram. The performance of the nomogram was assessed using the internal validation cohort and externally validated using additional 88 RN patients.

RESULTS

We identified five predictors of post-RN survival using the training data: age, tumor progression before RN, lower cranial nerves injury, bilateral necrosis, and history of stroke. The nomogram showed favorable performance in the internal validation cohort (C-index 0.761, 95% CI 0.676 to 0.847) and in the external validation cohort (C-index 0.795, 95% CI 0.717 to 0.874). The decision curve analysis indicated that the nomogram was clinically useful when the probabilities of death ranging from 1% to 48% at 1 year, from 3% to 50% at 3 years, and exceeding 2% at 5 years after being diagnosed with RN.

CONCLUSION

In this LASSO-Cox model-based nomogram study, we developed and validated an easily applied model to predict overall survival in head and neck cancer survivors following an RN diagnosis.