A data-constrained survival stratification model for surgically managed glioblastoma across public and real-world cohorts.
- 1Department of Neurosurgery, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
- 2Department of Neurology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Abstract
Background
Glioblastoma (GBM) has highly heterogeneous postoperative survival. Although contemporary prognostic assessment ideally requires molecular, functional, and surgical-detail variables, these data are often unavailable in population-based and multicenter real-world datasets.Methods
Adults with histologically recorded GBM and tumor-directed surgery (resection or biopsy) in SEER formed the derivation cohort. A multivariable Cox model estimated 6-, 12-, and 18-month overall survival and was externally evaluated in CGGA and an independent institutional cohort without refitting. Because extent of resection, biopsy details, performance status, MGMT promoter methylation, IDH status, and treatment-regimen details were unavailable or non-harmonizable, the model was explicitly intended for registry-based survival stratification when contemporary core prognostic variables are absent.Results
The study included 3, 842 patients in the SEER derivation cohort, 512 in the CGGA validation cohort, and 96 in the institutional validation cohort. Age, marital status, year of diagnosis, tumor location, tumor size, radiotherapy, and chemotherapy were retained in the final model. The model showed acceptable discrimination and calibration in the derivation cohort and reproducible risk stratification in both validation cohorts. In the independent non-public institutional validation cohort, the 6-, 12-, and 18-month AUCs were 0.748, 0.721, and 0.694, respectively, with a Harrell's C-index of 0.708, supporting reproducible risk stratification in a real-world clinical patient cohort.Conclusions
This multicohort study developed a registry-compatible survival stratification model for surgically managed glioblastoma for GBM using routinely available variables. The model may support survival estimation under data-constrained conditions, but should not be interpreted as a comprehensive neuro-oncology prognostic system or treatment decision-support tool.
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BibTeX
@article{zeng2026dataconstrained,
title = {{A data-constrained survival stratification model for surgically managed glioblastoma across public and real-world cohorts.}},
author = {Lin Zeng and DingJun Li and Yun Liao and Mengyu Du and Tao Wu and Yuxing Huang and Lisha Deng and Qizheng Li},
journal = {Frontiers in oncology},
year = {2026},
month = oct,
doi = {10.3389/fonc.2026.1908021},
url = {https://europepmc.org/article/MED/42908729},
note = {CC BY},
}
RIS
TY - JOUR
TI - A data-constrained survival stratification model for surgically managed glioblastoma across public and real-world cohorts.
AU - Lin Zeng
AU - DingJun Li
AU - Yun Liao
AU - Mengyu Du
AU - Tao Wu
AU - Yuxing Huang
AU - Lisha Deng
AU - Qizheng Li
PY - 2026
DA - 2026/10/07
JO - Frontiers in oncology
DO - 10.3389/fonc.2026.1908021
UR - https://europepmc.org/article/MED/42908729
AB - Background Glioblastoma (GBM) has highly heterogeneous postoperative survival. Although contemporary prognostic assessment ideally requires molecular, functional, and surgical-detail variables, these data are often unavailable in population-based and multicenter real-world datasets.Methods Adults with histologically recorded GBM and tumor-directed surgery (resection or biopsy) in SEER formed the derivation cohort. A multivariable Cox model estimated 6-, 12-, and 18-month overall survival and was externally evaluated in CGGA and an independent institutional cohort without refitting. Because extent of resection, biopsy details, performance status, MGMT promoter methylation, IDH status, and treatment-regimen details were unavailable or non-harmonizable, the model was explicitly intended for registry-based survival stratification when contemporary core prognostic variables are absent.Results The study included 3, 842 patients in the SEER derivation cohort, 512 in the CGGA validation cohort, and 96 in the institutional validation cohort. Age, marital status, year of diagnosis, tumor location, tumor size, radiotherapy, and chemotherapy were retained in the final model. The model showed acceptable discrimination and calibration in the derivation cohort and reproducible risk stratification in both validation cohorts. In the independent non-public institutional validation cohort, the 6-, 12-, and 18-month AUCs were 0.748, 0.721, and 0.694, respectively, with a Harrell's C-index of 0.708, supporting reproducible risk stratification in a real-world clinical patient cohort.Conclusions This multicohort study developed a registry-compatible survival stratification model for surgically managed glioblastoma for GBM using routinely available variables. The model may support survival estimation under data-constrained conditions, but should not be interpreted as a comprehensive neuro-oncology prognostic system or treatment decision-support tool.
SN - 2234-943X
ER -