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

Abstract

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.

Polymorphism of XRCC7 Gene and Risk of Glioma: A Prospective Case–Control Study

“…The fact that XRCC7 gene polymorphism was also present in a significant number in control group points to the multifactorial etiology of the disease. Furthermore, some studies have found that human chromosome number 8q11 (which also contains the XRCC7 gene) can functionally correct the hyper-radiosensitivity of severe combined immunodeficiency cells, which are otherwise extremely prone to radiation induced DNA damage, [5][6][7] helping guide the treatment for different types of gliomas.…”

“…L27425) being the antisense primer. 5 The primers amplified 368-bp fragment containing the G/T variant in intron 8, which were then subjected to digestion with PvuII (New England BioLabs, Inc., Beverly, Massachusetts, United States) at 37°C overnight. The homologous GG allele had only one band of 368-bp; the heterozygous allele (GT) had three bands of 368, 274, and 94 bp; and the homozygous TT allele had two bands of 274 and 94 bp because of the gain of the restriction site.…”

New Real Dataset Creation to Develop an Intelligent System for Predicting Chemotherapy Protocols

“…Over the years, the latter type of datasets has been used in various fields to analyze actual data and obtain valuable knowledge to handle particular situations. In the medical and health-care field, clinical-administrative datasets would allow for capitalization, management and retrieval of relevant information [17].…”