The dichotomy of central nervous system cancer burden: A global analysis revealing diagnosis-driven epidemics and therapy-resistant mortality.

Authors

Lanlan Guo, Haoyue Hu, Mingying Xiao, Wei Chen, Yuanyang Huang, Xuan Li, Ziwei Wu, Suixian Zhang, Ying Wang, Baiqiang Dong, Chenfei Wu, Yonggao Mou, Yuanyuan Chen

Published in

Neuro-oncology advances. Volume 8. Issue 1. Pages vdag171. Epub Jul 09, 2026.

Abstract

The global burden of central nervous system (CNS) cancers is rising unevenly. Existing studies lack a framework linking macro trends to underlying drivers across scales.
We constructed a "macro-meso-micro" framework, integrating Global Burden of Disease 2021 data (macro perspective) and US SEER registry data (meso perspective). Global/regional/national incidence and mortality trends (1990-2021) were analyzed using descriptive statistics and Bayesian models, alongside subtype-specific clinical patterns.
The global age-standardized incidence rate (ASIR) increased from 3.82 to 4.28 per 100,000 population (1990-2021), while the age-standardized mortality rate (ASMR) declined slowly (3.08-3.06), revealing a core "incidence-mortality decoupling." Incidence correlated positively with the socio-demographic index (SDI), but some high-SDI regions achieved superior mortality control, indicating healthcare disparities. SEER data clarified that this plateau was driven by the dismal survival of aggressive subtypes like glioblastoma (GBM), contrasting sharply with the rising detection of benign/low-grade tumors (eg, meningioma). For GBM, standard care has reached a low therapeutic ceiling, with most patients relapsing into a treatment void.
CNS cancer burden evolution resulted from multi-scale diagnostic, therapeutic, and biological interactions. Our framework connected macro trends, meso subtype heterogeneity, and micro resistance mechanisms, pinpointing the conquest of therapy-resistant, high-grade tumors (especially GBM) as the central challenge. A translational pathway of "macro surveillance for target identification-clinical problem definition-mechanistic research for breakthrough" was proposed to guide future intervention.

PMID:
42689271
Bibliographic data and abstract were imported from PubMed on 03 Sep 2026.

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