Prognostic Importance of Age, Tumor Location, and Tumor Grade in Grade II Astrocytomas: An Integrated Analysis of the Cancer Genome Atlas and the Surveillance, Epidemiology, and End Results Database

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

BACKGROUND

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.

Utility of Administrative Databases and Big Data on Understanding Glioma Treatment—A Systematic Review

Background Gliomas are a heterogeneous group of tumors where large multicenter clinical and genetic studies have become increasingly popular in their understanding. We reviewed and analyzed the findings from large databases in gliomas, seeking to understand clinically relevant information.

Methods A systematic review was performed for gliomas studied using large administrative databases up to January 2020 (e.g., National Inpatient Sample [NIS], National Surgical Quality Improvement Program [NSQIP], and Surveillance, Epidemiology, and End Results Program [SEER], National Cancer Database [NCDB], and others).

Results Out of 390 screened studies, 122 were analyzed. Studies included a wide range of gliomas including low- and high-grade gliomas. The SEER database (n = 83) was the most used database followed by NCDB (n = 28). The most common pathologies included glioblastoma multiforme (GBM) (n = 67), with the next category including mixes of grades II to IV glioma (n = 31). Common study themes involved evaluation of descriptive epidemiological trends, prognostic factors, comparison of different pathologies, and evaluation of outcome trends over time. Persistent health care disparities in patient outcomes were frequently seen depending on race, marital status, insurance status, hospital volume, and location, which did not change over time. Most studies showed improvement in survival because of advances in surgical and adjuvant treatments.

Conclusions This study helps summarize the use of clinical administrative databases in gliomas research, informing on socioeconomic issues, surgical outcomes, and adjuvant treatments over time on a national level. Large databases allow for some study questions that would not be possible with single institution data; however, limitations remain in data curation, analysis, and reporting methods.

Development and Validation of a Personalized Prognostic Prediction Model for Patients With Spinal Cord Astrocytoma

Background

The study aimed to investigate the prognostic factors of spinal cord astrocytoma (SCA) and establish a nomogram prognostic model for the management of patients with SCA.

Methods

Patients diagnosed with SCA between 1975 and 2016 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training and testing datasets (7:3). The primary outcomes of this study were overall survival (OS) and cancer-specific survival (CSS). Cox hazard proportional regression model was used to identify the prognostic factors of patients with SCA in the training dataset and feature importance was obtained. Based on the independent prognostic factors, nomograms were established for prognostic prediction. Calibration curves, concordance index (C-index), and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the calibration and discrimination of the nomogram model, while Kaplan-Meier (KM) survival curves and decision curve analyses (DCA) were used to evaluate the clinical utility. Web-based online calculators were further developed to achieve clinical practicability.

Results

A total of 818 patients with SCA were included in this study, with an average age of 30.84 ± 21.97 years and an average follow-up time of 117.57 ± 113.51 months. Cox regression indicated that primary site surgery, age, insurance, histologic type, tumor extension, WHO grade, chemotherapy, and post-operation radiotherapy (PRT) were independent prognostic factors for OS. While primary site surgery, insurance, tumor extension, PRT, histologic type, WHO grade, and chemotherapy were independent prognostic factors for CSS. For OS prediction, the calibration curves in the training and testing dataset illustrated good calibration, with C-indexes of 0.783 and 0.769. The area under the curves (AUCs) of 5-year survival prediction were 0.82 and 0.843, while 10-year survival predictions were 0.849 and 0.881, for training and testing datasets, respectively. Moreover, the DCA demonstrated good clinical net benefit. The prediction performances of nomograms were verified to be superior to that of single indicators, and the prediction performance of nomograms for CSS is also excellent.

Conclusions

Nomograms for patients with SCA prognosis prediction demonstrated good calibration, discrimination, and clinical utility. This result might benefit clinical decision-making and patient management for SCA. Before further use, more extensive external validation is required for the established web-based online calculators.

[Histomolecular diagnosis of glial and glioneuronal tumours]

While rare compared to extra-cranial neoplasms, glial and glioneuronal tumors are responsible of high morbidity and mortality. In 2016, the World Health Organization introduced histo-molecular ("integrated") diagnostics for central nervous system tumors based on morphology, immunohistochemistry and the presence of key genetic alterations. This combined phenotypic-genotypic classification allows for a more objective diagnostic of brain tumors. The implementation of such a classification in daily practice requires immunohistochemical surrogates to detect common genetic alterations and sometimes expensive and not widely available molecular biology techniques. The first step in brain tumor diagnostics is to inquire about the clinical picture and the imaging findings. When dealing with a glial tumor, the pathologist needs to assess its nature, infiltrative or circumscribed. If the tumor is infiltrative, IDH1/2 genes (prognostic marker) and chromosomes 1p/19q (diagnosis of oligodendroglioma) need to be assessed. If the tumor appears circumscribed, the pathologist should look for a neuronal component associated with the glial component (glioneuronal tumor). A limited immunohistochemistry panel will help distinguish between diffuse glioma (IDH1-R132H, ATRX, p53) and circumscribed glial/glioneuronal tumor (CD34, neuronal markers, BRAF-V600E), and some antibodies may reliably detect genetic alterations (IDH1-R132H, BRAF-V600E and H3-K27M mutations). Chromosomal imbalances (1p/19q codeletion in oligodendroglioma; chromosome 7 gain/chromosome 10 loss and EGFR amplification in glioblastoma) and gene rearrangements (BRAF fusion, FGFR1 fusion) will be identified by molecular biology techniques. The up-coming edition of the WHO classification of the central nervous system tumors will rely more heavily on molecular alterations to accurately diagnose and treat brain tumors.

Top Ten Tips Palliative Care Clinicians Should Know When Caring for Patients with Brain Cancer

The diagnosis of an aggressive, primary brain tumor is life altering for those affected and too often portends a poor prognosis. Despite decades of research, neither a cure nor even a therapy that reliably and dramatically prolongs survival has been found. Fortunately, there are a number of treatments that may prolong the life of select brain tumor patients although the symptom burden can sometimes be high. This article brings together neuro-oncologists, neurologists, and palliative care (PC) physicians to help shine a light on these diseases, their genetics, treatment options, and the symptoms likely to be encountered both from the underlying illness and its treatment. We hope to increase the understanding that PC teams have around these illnesses to improve care for patients and families.

Receipt of brachytherapy is an independent predictor of survival in glioblastoma in the Surveillance, Epidemiology, and End Results database

INTRODUCTION

There has been a resurgence of interest in brachytherapy as a treatment for glioblastoma, with several currently ongoing clinical trials. To provide a foundation for the analysis of these trials, we analyze the Surveillance, Epidemiology, and End Results (SEER) database to determine whether receipt of brachytherapy conveys a survival benefit independent of traditional prognostic factors.

MATERIALS AND METHODS

We identified 60,456 glioblastoma patients, of whom 362 underwent brachytherapy. We grouped patients based on receipt of brachytherapy and compared clinical and demographic variables between groups using Student's t-test and Pearson's chi-squared test. We assessed survival using Kaplan-Meier curves and Cox proportional hazards models.

RESULTS

Median overall survival was 16 months in patients who received brachytherapy compared to 9 months in those who did not (log-rank p < 0.001). Patients who underwent brachytherapy tended to be younger (p < 0.001), suffered from smaller tumors (< 4 cm, p < 0.001), and were more likely to have undergone gross total resection (GTR, p < 0.001). In univariable Cox models, these variables were independently associated with improved overall survival. Additionally, improved survival was associated with known receipt of chemotherapy (HR 0.459, p < 0.001), external beam radiation (HR 0.447, p < 0.001), and brachytherapy (HR 0.637, p < 0.001). The association between brachytherapy and improved survival remained robust (HR 0.859, p = 0.031) in a multivariable model that adjusted for patient age, tumor size, tumor location, GTR, receipt of chemotherapy, and receipt of external beam radiation.

CONCLUSION

Our SEER analysis indicates that brachytherapy is associated with improved survival in glioblastoma after controlling for age, tumor size/location, extent of resection, chemotherapy, and external beam radiation.