Low-grade Gliomas in Argentina: Incidence, Survival, and Therapeutic Strategies

Overview

Low-grade gliomas (LGG) are slow-growing primary brain tumors (WHO grades I-II), and their incidence, survival, and treatment patterns in middle-income settings such as Argentina remain poorly characterized. This retrospective, multicenter study comprises two complementary cohorts: 1. Cohort 1: The "captive" population covered under the Hospital Italiano de Buenos Aires Health Plan (January 2011-December 2023) to estimate LGG incidence density. 2. Cohort 2: Histologically confirmed LGG patients treated at the major referral centers to describe overall survival (OS) and disease-free survival (DFS) at 1 and 5 years. Demographic, clinical, pathological, and treatment data will be collected in a centralized REDCap database. The primary objective is to describe LGG incidence in Argentina and estimate survival using Kaplan-Meier curves. The secondary objectives include characterizing therapeutic strategies, molecular mutations, and prognostic factors through Cox regression analysis. This registry will fill a critical gap in LGG epidemiology in middle-income countries and generate hypotheses for future research.

Background Low-grade gliomas (LGG) represent approximately 6% of primary central nervous system tumors in adults and exhibit unpredictable biological behavior. Although high-income countries have published LGG incidence and survival data stratified by age, sex, and molecular profile, data from Argentina and other middle-income regions are scarce. IDH mutations and other molecular markers, along with clinical factors (age, seizures, tumor volume, and location) and treatment modalities, influence disease progression and prognosis in these patients. Objectives * Primary (Cohort 1): Estimate LGG incidence density in the Hospital Italiano Health Plan population (2011-2023), expressed as cases per 100,000 person-years. * Primary (Cohort 2): Describe OS and DFS at 1 and 5 years post-diagnosis. * Secondary: Characterize therapeutic strategies (surgical, chemoradiotherapy, monotherapy), molecular profile (IDH, P53, 1p/19q mutations), and identify prognostic factors associated with OS and DFS using multivariable Cox regression. Design and Scope This is a retrospective, multicenter, observational cohort study with two cohorts: * Cohort 1 (incidence): Retrospective analysis of the Hospital Italiano de Buenos Aires database to identify new LGG cases from January 2011 to December 2023. * Cohort 2 (survival): Consecutive inclusion of all patients with histologically confirmed LGG treated at the participating centers during the same period. Population * Inclusion (Cohort 1): Age ≥ 18 years, HIBA affiliates, ≥ 1 year of documented follow-up. * Inclusion (Cohort 2): Age ≥ 18 years, histologically confirmed LGG (WHO I-II), ≥ 1 year of documented follow-up. * Exclusion (both cohorts): Incomplete or uncertain diagnosis per histopathological/genetic criteria. Data Collection \& Management Local investigators will extract demographic, clinical, radiological, pathological, and treatment data from electronic health records. All data will be entered retrospectively into a secure, centralized REDCap database with individual user credentials. Quality control checks (cross-validation with source records) will be performed periodically. After analysis and publication, the database will be permanently deleted to preserve confidentiality. Key Variables * Demographics: age, sex, comorbidities, functional status, care setting. * Tumor Characteristics: volume, location (supra-/infratentorial, hemisphere), histology, IDH/P53 mutation status. * Treatment Details: extent of resection (total/partial), chemotherapy (agents, cycles, toxicities), radiotherapy (type, dose, fractions). * Outcomes: time to progression, OS, DFS, postoperative complications, adverse events. Statistical Analysis * Cohort 1: Calculate incidence density (cases/person-years) with 95 % confidence intervals by age and sex. Standardization will use INDEC population data. * Cohort 2: Estimate OS and DFS at 1, and 5 years using Kaplan-Meier methods; report proportions with 95 % CIs. Perform multivariable Cox regression to identify prognostic factors (age, tumor volume, mutation status, treatment type), reporting hazard ratios with 95 % CIs. * Sample Size: Approximately 180 000 person-years in Cohort 1 (projected 13-14 LGG cases); ≥ 40 patients in Cohort 2 to estimate a 30 % survival rate with ± 10 % precision. Ethical Considerations The study has a waiver of informed consent under local regulations and CIOMS guidelines. All data will be anonymized using numeric codes and stored on encrypted servers until study completion. In addition, each participating center must obtain approval from its respective ethics committee (IRB/EC) before initiating data collection and provide documentation of such approvals.