The Nomogram Model Predicting Overall Survival and Guiding Clinical Decision in Patients With Glioblastoma Based on the SEER Database

Abstract

Background: Patients with glioblastoma have a poor prognosis. We want to develop and validate nomograms for predicting overall survival in patients with glioblastoma. Methods: Data of patients with glioblastoma diagnosed pathologically in the SEER database from 2007 to 2016 were collected by SEER * Stat software. After eliminating invalid and missing clinical information, 3,635 patients (total group) were finally identified and randomly divided into the training group (2,183 cases) and the verification group (1,452 cases). Cox proportional risk regression model was used in the training group, the verification group and the total group to analyze the prognostic factors of patients in the training group, and then the nomogram was constructed. C-indexes and calibration curves were used to evaluate the predictive value of nomogram by internal (training group data) and external validation (verification group data). Results: Cox proportional risk regression model in the training group showed that age, year of diagnosis, laterality, radiation, chemotherapy were all influential factors for prognosis of patients with glioblastoma (P < 0.05) and were all used to construct nomogram as well. The internal and external validation results of nomogram showed that the C-index of the training group was 0.729 [95% CI was (0.715, 0.743)], and the verification group was 0.734 [95% CI was (0.718, 0.750)]. The calibration curves of both groups showed good consistency. Conclusions: The proposed nomogram resulted in accurate prognostic prediction for patients with glioblastoma.

A Prognostic Model for Glioblastoma Patients Treated With Standard Therapy Based on a Prospective Cohort of Consecutive Non-Selected Patients From a Single Institution

“…This however also suggests that there remain unknown explanatory factors associated with survival. Despite advances in histological and molecular subtypes, the factors included in prognostic models are mainly clinical observations such as PS, age and corticosteroid treatment (4,(9)(10)(11)(12). Tissue biomarkers and data from imaging techniques have been suggested as independent prognostic factors (6,25,26), and may contribute to improvement of future prognostic models.…”

“…Two molecular factors, the promoter methylation of the O 6 -methylguanine-DNA methyltransferase (MGMT) gene and the mutation of the isocitrate dehydrogenase-1 (IDH-1), an indicator of progression from lower grade glioma (secondary glioblastoma), have been identified as prognostic factors associated with a favorable prognosis (6)(7)(8). The most consistent and well-described clinical prognostic factors associated with a poor survival include: increasing age, poor performance status (PS), low degree of surgical resection of tumor, and the use of corticosteroids (4,(9)(10)(11).…”

Prognostic Value of the Systemic Inflammatory Response Index in Patients Undergoing Radical Cystectomy for Bladder Cancer: A Population-Based Study

“…Then, the accuracy of the nomogram was evaluated by applying a calibration curve. In the calibration curve, if the predicted value is equal to the actual observed value, the curve will fall on the ideal 45 • slant (11). All statistical analyses of this study were performed using the IBM SPSS 20.0 software (IBM, USA) and Graphpad Prism8 software (GraphPad Software Inc., La Jolla, CA, USA).…”

Preoperative Risk-Stratification of Pediatric Malignant Brainstem Glioma based on a validated nomogram: A SEER based Analysis

“…A higher Cindex means a better predictive value. (Wang and Li et al, 2013;Zhu and Zhu et al, 2016) The nomogram utility has been assessed in many elds, like bladder cancer, (Yang and Bai et al, 2020) esthesioneuroblastomas, (Jiang and Lin et al, 2020) non-metastatic breast cancer, (Qian and Jia et al, 2020) or in neurosurgery of cancers like glioblastoma (Li and He et al, 2020) and so forth. Of note, this is the rst research to introduce nomogram into pediatric primary BSMG before the onset of therapies.…”