Abstract Introduction Pediatric low-grade gliomas (pLGGs) are the most common childhood brain tumors and are generally associated with excellent long-term survival. However, intratumoral hemorrhage represents a rare but potentially devastating complication. Existing data on hemorrhage risk in pLGG are limited to small, heterogeneous series, and the impact of molecular alterations and modern targeted therapies remains poorly defined. We sought to determine the incidence, timing, and independent risk factors for hemorrhage in a large contemporary pLGG cohort. Methods We conducted a retrospective cohort study of 236 patients with pLGG treated at a single academic center between 2011 and 2025. Clinical, radiographic, molecular, and treatment-related variables were systematically abstracted. The primary endpoint was spontaneous tumoral hemorrhage. Time-to-event analyses were performed in Python using Kaplan–Meier methods and Cox proportional hazards modeling. Given the rarity of hemorrhage events, parsimonious multivariable models and penalized Cox regression were used to mitigate overfitting. Results Twelve patients (5.1%) experienced hemorrhage over 2,234 person-years of follow-up, yielding an incidence rate of 0.54 per 100 person-years. Hemorrhage typically occurred years after initial tumor diagnosis (median 6.4 years). The presence of a BRAF–KIAA1549 fusion in the tumor was the strongest independent predictor of hemorrhage across all multivariable models, conferring a sixfold increased risk. MAPK inhibitor exposure, particularly binimetinib and tovorafenib, was associated with hemorrhage in univariate analysis, though partially confounded by fusion status. Previous CSF diversion procedures independently increased hemorrhage risk in tumors located in the brainstem, optic pathway, or hypothalamus compared to other locations. No hemorrhages occurred among patients with underlying genetic syndromes, including neurofibromatosis type 1 and tuberous sclerosis. Conclusion Hemorrhage in pLGG is an uncommon but late complication driven primarily by tumor biology. BRAF–KIAA1549 fusion identifies a high-risk subgroup in whom treatment-related and procedural factors further modify risk, enabling biology-informed surveillance and management strategies.
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