A predictive model for identifying secondary underlying diseases of hemophagocytic lymphohistiocytosis.

Background: Secondary hemophagocytic lymphohistiocytosis (HLH) is a rare, life-threatening disease of immune hyperactivation that arises in the context of infectious, inflammatory, or neoplastic triggers. The aim of this study was to establish a predictive model for the timely differential diagnosis of the original disease resulting in HLH by validating clinical and laboratory findings to further improve the efficacy of therapeutics for HLH. Methods: We retrospectively enrolled 175 secondary HLH patients in this study, including 92 patients with hematologic disease and 83 patients with rheumatic disease. The medical records of all identified patients were retrospectively reviewed and used to generate the predictive model. We also developed an early risk score using multivariate analysis weighted points proportional to the Results: The multivariate logistic analysis revealed that lower levels of hemoglobin and platelets (PLT), lower levels of ferritin, splenomegaly and Epstein-Barr virus (EBV) positivity were associated with hematologic disease, but young age and female sex were associated with rheumatic disease. The risk factors for HLH secondary to rheumatic diseases were female sex [OR 4.434 (95% CI, 1.889-10.407), Conclusion: The established predictive model was designed to help clinicians diagnose the original disease resulting in secondary HLH during routine practice, which might be improve prognosis by enabling the timely treatment of the underlying disease.