Clinical Outcome and Prognostic Factors in Childhood Acute Lymphoblastic Leukemia—A Retrospective Cohort Study of Patients from Southern Mexico - Francisca Morales-Vital; Diego Moreno-Loaeza; Victor Manuel Alvarado-Castro; Jennifer Meza-Miranda; César López-Camarillo; Rael Escoto-Hernández; Luis Alberto Ojeda-Campos; Olga Lilia Garibay-Cerdenares; Azucena Ocampo-Bárcenas; Eloísa Ibarra-Sierra (Journal of Clinical Medicine, 2026)
Background/Objectives: B-cell acute lymphoblastic leukemia (B-ALL) remains the most common pediatric malignancy. This study aimed to evaluate clinical outcomes in pediatric B-ALL in Southern Mexico and determine how socioeconomic vulnerabilities—specifically indigenous status and treatment non-adherence—independently drive relapse and compromise survival in a resource-limited setting. Methods: A retrospective cohort study was conducted, including 146 patients (0–17 years) treated between 2010 and 2024 using modified Total XIII and XV protocols. Survival was estimated via Kaplan–Meier. Independent prognostic factors for overall survival (OS) and relapse were identified using multivariable Cox proportional hazards models. Results: The 5-year OS was 50%, and event-free survival (EFS) was 37.6%. Survival varied significantly by clinical risk: 88% for low-risk, 77% for standard-risk, and 31% for high-risk patients. Relapse occurred in 45.8% of patients. Beyond established biological predictors like hyperleukocytosis and high-risk cytogenetics, socioeconomic vulnerabilities profoundly impacted outcomes. Documented treatment non-adherence significantly reduced 5-year OS (23.4% vs. 56.1%, p = 0.001) and disproportionately affected indigenous patients (55.5% vs. 10.1% in non-indigenous). Multivariable analysis identified indigenous status as an independent predictor of increased relapse hazard (HR = 1.89, p = 0.049), alongside male sex and high leukocyte count. Conclusions: Survival outcomes in this cohort are markedly lower than in high-income countries. The high incidence of relapse is deeply intertwined with local structural inequities. Improving survival requires complementing biological risk stratification with targeted strategies to overcome socioeconomic barriers and prevent treatment non-adherence.