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

World Neurosurg. (2023) 176:e20-e31

The number of elderly patients with low-grade glioma (LGG) is increasing, but their prognostic factors and surgical treatment are still controversial. This paper aims to investigate the prognostic factors of overall survival and cancer-specific survival in elderly patients with LGG and analyze the optimal surgical treatment strategy.

METHODS: Patients in the study were obtained from the Surveillance, Epidemiology, and End Results database and patients were randomized into a training and a test set (7:3). Clinical variables were analyzed by univariate and multivariate Cox regression analysis to screen for significant prognostic factors, and nomograms visualized the prognosis. In addition, survival analysis of elderly patients regarding different surgical management was also analyzed by Kaplan-Meier curves.

RESULTS: Six prognostic factors were screened by univariate and multivariate Cox regression analysis on the training set: tumor site, laterality, histological type, the extent of surgery, radiotherapy, and chemotherapy, and all factors were visualized by nomogram. And we evaluated the accuracy of the nomogram model using consistency index, calibration plots, receiver operator characteristic curves, and decision curve analysis, showing that the nomogram has strong accuracy and applicability. We also found that gross total resection improved overall survival and cancer-specific survival in patients with LGG aged ‡65 years relative to those who did not undergo surgery (P < 0.001).

CONCLUSIONS: Based on the Surveillance, Epidemiology, and End Results database, we created and validated prognostic nomograms for elderly patients with LGG, which can help clinicians to provide personalized treatment services and clinical decisions for their patients. More importantly, we found that older age alone should not preclude aggressive surgery for LGGs.

Nomogram for predicting an individual prospective hemorrhage risk in untreated brainstem cavernous malformations

J Neurosurg 138:910–921, 2023

In this study, the authors aimed to create a nomogram for precisely predicting the 5-year prospective hemorrhage risk in brainstem cavernous malformations (BSCMs).

METHODS Patients with confirmed BSCMs in a single-center prospective observational series from January 2012 to December 2016 were included in the present study for nomogram building and validation. The concordance index (C-index), calibration curves, and decision curve analysis were used to evaluate the predictive accuracy, discriminative ability, and clinical usefulness of the nomogram. Then, a nomogram-based risk stratification model for untreated BSCMs was developed.

RESULTS In total, 600 patients were included in the study; 417 patients who had been enrolled before July 2015 were divided into the training and validation cohorts, and 183 subsequently enrolled patients were used as the external validation cohort. By applying a backward stepwise procedure in the multivariable Cox model, variables, including prior hemorrhage (HR 1.69), hemorrhage on admission (HR 3.33), lesion size > 1.5 cm (HR 1.84), lesion depth (HR 2.35), crossing the axial midpoint (HR 1.94), and developmental venous anomaly (HR 2.62), were incorporated to develop a nomogram. The Harrell C-index values for a 5-year prospective hemorrhage were 0.752 (95% CI 0.687–0.816), 0.801 (95% CI 0.665–0.936), and 0.758 (95% CI 0.674–0.842) in the training, internal validation, and external validation cohorts, respectively. The nomogram performed well in terms of consistency between prediction and actual observation according to the calibration curve. The patients could be classified into three distinct (low, medium, and high) risk groups using the final score of this nomogram.

CONCLUSIONS Independent predictors of the 5-year hemorrhage risk in untreated BSCMs were selected to create the first nomogram for predicting individual prospective hemorrhage. The nomogram was able to stratify patients into different risk groups and assist in clinical decision-making.

Prognostic nomogram for microvascular decompression–treated trigeminal neuralgia

Neurosurgical Review (2021) 44:571–577

This study aimed to establish an effective prognostic nomogram for microvascular decompression (MVD)–treated trigeminal neuralgia (TN). The nomogram was based on a retrospective cohort study of 1054 patients with TN.

During the period 2005– 2014, 845 patients at our department treated TN with MVD and served as a development cohort. The predictive accuracy and discriminative ability of the nomogram were determined by concordance index (C-index) and calibration curve. The model was externally validated by 209 TN patients during 2014–2016.

Multivariate cox analysis suggested that the patient’s age, atypical pain, vascular type, number of offending vessels, and second MVD were significant factors influencing the prognosis of MVDtreated TN. The C index of nomogram in the development cohort was 0.767 (95%CI, 0.739–0.794), and 0.749 (95%CI, 0.688– 0.810) in the validation cohort.

We developed and validated a nomogram to predict 3-year overall remission rate after MVD treatment of TN. The nomogram can be used in clinical trials to determine the likelihood of pain recurrence in TN patients treated with MVD for 3 years to aid in the comprehensive treatment of TN.

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