Analysis of Prognostic Factors and Surgical Management of Elderly Patients with Low-Grade Gliomas

Wu, Shuaishuai; Wang, Changli; Li, Ning; Ballah, Augustine K.; Lyu, Jun; Liu, Shengming; Wang, Xiangyu

doi:10.1016/j.wneu.2023.02.099

Cited by 2 publications

(1 citation statement)

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“…This detailed classification enhances the predictive precision of our model. Consistent with the previous results (20), univariate and multivariate Cox regression analyses identified six prognostic factors: tumor site, laterality, histological type, extent of surgery, radiotherapy, and chemotherapy.…”

Section: Discussionsupporting

confidence: 87%

Development and external validation of dual online tools for prognostic assessment in elderly patients with high-grade glioma: a comprehensive study using SEER and Chinese cohorts

Zhang,

Jiang,

Ren

et al. 2023

Front. Endocrinol.

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BackgroundElderly individuals diagnosed with high-grade gliomas frequently experience unfavorable outcomes. We aimed to design two web-based instruments for prognosis to predict overall survival (OS) and cancer-specific survival (CSS), assisting clinical decision-making.MethodsWe scrutinized data from the SEER database on 5,245 elderly patients diagnosed with high-grade glioma between 2000-2020, segmenting them into training (3,672) and validation (1,573) subsets. An additional external validation cohort was obtained from our institution. Prognostic determinants were pinpointed using Cox regression analyses, which facilitated the construction of the nomogram. The nomogram’s predictive precision for OS and CSS was gauged using calibration and ROC curves, the C-index, and decision curve analysis (DCA). Based on risk scores, patients were stratified into high or low-risk categories, and survival disparities were explored.ResultsUsing multivariate Cox regression, we identified several prognostic factors for overall survival (OS) and cancer-specific survival (CSS) in elderly patients with high-grade gliomas, including age, tumor location, size, surgical technique, and therapies. Two digital nomograms were formulated anchored on these determinants. For OS, the C-index values in the training, internal, and external validation cohorts were 0.734, 0.729, and 0.701, respectively. We also derived AUC values for 3-, 6-, and 12-month periods. For CSS, the C-index values for the training and validation groups were 0.733 and 0.727, with analogous AUC metrics. The efficacy and clinical relevance of the nomograms were corroborated via ROC curves, calibration plots, and DCA for both cohorts.ConclusionOur investigation pinpointed pivotal risk factors in elderly glioma patients, leading to the development of an instrumental prognostic nomogram for OS and CSS. This instrument offers invaluable insights to optimize treatment strategies.

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Section: Discussionsupporting

confidence: 87%