Dynamic early biomarkers predict outcomes in pediatric Epstein-Barr virus-associated hemophagocytic lymphohistiocytosis.

IMPORTANCE: Pediatric Epstein-Barr virus (EBV)-associated hemophagocytic lymphohistiocytosis (HLH) is a life-threatening disorder, and early identification of poor responders is critical to improving survival. However, no convenient clinical tools exist to predict individual prognosis using dynamic biomarkers during early treatment. OBJECTIVE: To investigate the predictive value of early dynamic changes in plasma biomarkers and to develop a prognostic model for children with EBV-HLH. METHODS: This retrospective study enrolled 60 newly diagnosed pediatric EBV-HLH patients. We analyzed the longitudinal changes in plasma EBV-DNA (pEBV-DNA), ferritin, and cytokine levels during the etoposide-based induction first-line therapy. Independent prognostic factors were identified using Cox multivariate regression and LASSO, followed by the construction of a prognostic nomogram. Model performance was evaluated through area under the curve (AUC), decision curve analysis, and internal cross-validation. RESULTS: Multivariate analysis identified positive pEBV-DNA at week 2 (w2) and low decreases in ferritin (ΔFerritin.w2) and interferon (IFN)-γ (ΔIFN-γ.w2) as independent predictors of adverse outcomes. A nomogram integrating these three variables demonstrated a superior AUC of 0.834 (vs. 0.677 for pEBV-DNA.w2 alone, P = 0.003). The model successfully stratified patients into low- and high-risk groups with significantly different 3-year event-free survival (84.8% vs. 33.3%, P < 0.001). INTERPRETATION: The proposed model, based on dynamic plasma biomarkers, provides a promising tool for the early risk stratification of pediatric EBV-HLH. Composed of pEBV-DNA, ΔFerritin, and ΔIFN-γ at w2, this nomogram can effectively identify patients at high risk of first-line treatment failure. Given the exploratory nature of this study, these findings require further validation in larger, independent cohorts.