An independently validated nomogram for Grade II & III gliomas enables personalized survival estimates
Introduction: Gliomas are the most common primary malignant brain tumors. Grade II and III gliomas present a therapeutic challenge due to the heterogeneity in developmental lineage, grade, biomarkers and prognosis. While patient prognosis can be estimated based on median PFS and OS, an approach to personalized prognostication has not been previously described.
Objective: We propose to develop and independently validate a survival nomogram for patients with newly diagnosed Grade II & III gliomas.
Methods: Data were obtained for newly diagnosed patients with Grade II & III gliomas from The Cancer Genome Atlas (TCGA; N= 238) and the Ohio Brain Tumor Study (OBTS; N=98) with the following variables: tumor grade, age, sex, KPS, and molecular subtype (IDH-1 WT or mutant; 1p/19q deletion status). Survival was assessed using Cox proportional hazards regression, random survival forests, and recursive partitioning analysis, with adjustment for known prognostic factors. The models were developed using TCGA data and independently validated using the OBTS data. Models were internally validated using 10-fold cross-validation and externally validated with calibration curves.
Results: A nomogram was validated for newly diagnosed Grade II & III glioma. Factors that independently influenced survival included: tumor grade; age; KPS and molecular subtype. The nomogram not only validates previous observations, but more importantly, facilitates a personalized survival estimate.
Conclusions: A nomogram that calculates personalized survival probabilities for patients with newly diagnosed Grade II & III gliomas is useful to physicians for counseling patients regarding treatment decisions and optimizing therapeutic approaches. Free online software for implementing this nomogram is provided: