A nomogram for predicting individual prognoses of patients with low-grade glioma.

OBJECTIVE: The present study aimed to develop and evaluate a nomogram for predicting the overall survival (OS) of patients with low-grade glioma (LGG).

METHODS: Patients diagnosed with LGG from 1973 to 2013 were identified using the Surveillance, Epidemiology, and End Results database（SEER）. A total of 3732 patients were randomly divided into a training set (2612) and a validation set (1120), and univariate and multivariate Cox regression analyses of clinical variables were performed to screen for significant prognostic factors. Then, a nomograph that included significant prognostic variables was formulated to predict LGG. Harrell's concordance index (C-index), calibration plots were formulated to evaluate the reliability and accuracy of the nomograph by bootstrapping based on internal (training set) and external (validation set) validity.

RESULTS: A nomogram was developed to predict 5- and 9-year OS rates based on seven variables in the training set: age, tumor site, sex, marital status, histology, tumor size, and surgery (p < 0.05). The C-index for internal validation, which the nomogram used to predict OS based on the training set, was 0.777 (0.763-0.791), and the C-index for external validation (validation set) was 0.776 (0.754-0.797). Based on calibration plots, the actual observation and prediction values obtained by the nomogram had good consistency between the two sets.

CONCLUSIONS: We developed a ready-to-use nomogram model based on clinical characteristics to predict survival outcomes and the nomogram may provide consultation and risk assessments for subsequent treatment in patients with LGG.