Personalized prognosis stratification of newly diagnosed glioblastoma applying a statistical decision tree model.

PURPOSE: Glioblastoma (GBM) is the most frequent glioma in adults with a high treatment resistance resulting into limited survival. The individual prognosis varies depending on individual prognostic factors, that must be considered while counseling patients with newly diagnosed GBM. The aim of this study was to elaborate a risk stratification algorithm based on reliable prognostic factors to facilitate a personalized prognosis estimation early on after diagnosis. METHODS: A consecutive patient cohort with confirmed GBM treated between 2010 and 2021 was retrospectively analyzed. Clinical, radiological, and molecular parameters were assessed and included in the analysis. Overall survival (OS) was the primary outcome parameter. After identifying the strongest prognostic factors, a risk stratification algorithm was elaborated with estimated odds of survival. RESULTS: A total of 462 GBM patients were analyzed. The strongest prognostic factors were Charlson Comorbidity Index (CCI), extent of tumor resection, and adjuvant treatment. Patients with CCI ≤ 1 receiving tumor resection had the highest survival odds (88% for 10 months). On the contrary, patients with CCI > 3 receiving no adjuvant treatment had the lowest survival odds (0% for 10 months). The 10-months survival rate in patients with CCI > 3 receiving adjuvant treatment was 56% for patients younger than 70 years and 22% for patients older than 70 years. CONCLUSION: A risk stratification algorithm based on significant prognostic factors allowed a personalized early prognosis estimation at the time of GBM diagnosis, that can contribute to a more personalized patient counseling.

Prognostic differences and implications on treatment strategies between butterfly glioblastoma and glioblastoma with unilateral corpus callosum infiltration.

Approximately 25% of glioblastomas show at diagnosis a corpus callosum infiltration, which is associated with poor prognosis. The extent of corpus callosum involvement, however, ranges from partial unilateral to complete bilateral infiltration. The role of surgery in glioblastoma with corpus callosum involvement is controversial. In this study, we aimed to examine prognostic differences between glioblastoma with unilateral and glioblastoma with bilateral corpus callosum infiltration, and to evaluate possible treatment strategy implications. Patients with newly diagnosed glioblastoma from 2010 to 2019 were included. Corpus callosum infiltration was assessed in contrast-enhanced T1-weighted preoperative magnetic resonance imaging. Extent of resection, adjuvant treatments and overall survival were evaluated. Corpus callosum involvement was found in 96 (26.4%) out of 363 patients with newly diagnosed glioblastoma. Bilateral corpus callosum infiltration was found in 27 out of 96 patients (28%), and 69 patients had unilateral corpus callosum infiltration. Glioblastoma with corpus callosum affection had significantly lower median overall survival compared to glioblastoma without corpus callosum involvement (9 vs. 11 months, p = 0.02). A subgroup analysis of glioblastoma with unilateral corpus callosum infiltration revealed a significant difference in median overall survival dependent on extent of resection (6.5 without gross total resection vs. 11 months with gross total resection, Log-rank test p = 0.02). Our data confirms a shorter overall survival in glioblastoma subpopulation with corpus callosum involvement, especially for glioblastoma with bilateral corpus callosum infiltration. However, patients with partial corpus callosum infiltration undergoing gross total resection exhibited a significant survival benefit compared to their counterparts without gross total resection. Whenever reasonably achievable gross total resection should be considered as an integral part of the treatment strategy in glioblastoma with partial corpus callosum infiltration.