MEDB-58. Risk factors and risk prediction models for medulloblastoma recurrence

BACKGROUND: There is a clear need for systematic appraisal of models/factors predicting medulloblastoma recurrence because clinical decisions about adjuvant treatment are taken on the basis of such variables. METHODS： A total of 273 patients diagnosed with medulloblastoma were retrospectively analyzed. The pre-rediotherapy neutrophile-lymphocyte ratio (NLR) was calculated, and other clinical characteristics were collected such as genetic type , whether with dissemination, degree with excision. The Kaplan-Meier method was used for survival analysis. Cox regression models was used to identify independent prognostic factors. R software was used to develop a nomogram with all the independent prognostic factors included. The prognostic predictive ability of the nomogram was evaluated by Concordance-index (C-index), area under the curve (AUC), and calibration curve. RESULTS: The median median progression-free survival time was 63.8 months in overall cohort. Univariate and multivariate cox hazards regression analysis identified independent prognostic factors associated with the PFS of patients with medulloblastoma to include age, residual tumor volume ＞1.5cm3 after excision, NLR ＞4.5, whether with dissemination before RT, and whether the genetic type is group 3,which were integrated to establish a nomogram. The C-indexes of nomogram were 0.696 and 0.676 in the training and validation cohort, respectively. The AUC of predicting 3-years PFS showed satisfactory accuracy as well (Training cohort: AUC=0.696; Validation cohort: AUC=0.676). The calibration curve showed agreement between the ideal and predicted values. Kaplan-Meier curves based on the PFS showed significant differences between nomogram predictive low-, and high groups (P < 0.001). CONCLUSIONS: We found that pre-treatment NLR was an independent prognostic factor for recurrence or metastasis of medulloblastoma after treatment. In combination with NRL and clinical factors, nomogram has a good prediction of PFS in patients with medulloblastoma after radiotherapy. It has the potential to facilitate more precise risk stratification to guide personalized treatment of medulloblastoma.