3.3 Predictors for R/R HLH at the time of diagnosis
In this study, potential risk factors were evaluated to identify predictors for R/R HLH at the time of diagnosis. To achieve this, the ROC curve was utilized for each variable. The optimal cutoff point for each variable was defined as the value that yielded the maximum area under the curve (AUC). Fig. 1A and 1B showed the ROC curves for age and pSOFA score. In our cohort, an age of less than 3 years and a pSOFA score of 8 or higher were identified as the optimal cutoff points for predicting R/R HLH, with AUC values of 0.69 and 0.76, respectively.
Table 3 illustrated the results of both univariable and multivariable logistic regression analyses conducted to identify predictive factors for R/R HLH. The univariable logistic regression analysis identified several potential risk factors for R/R HLH, including younger age, severe disease status, higher HLH-2004 criteria scores, higher H-scores, overt DIC (modified ISTH-DIC score of ≥ 5), higher pSOFA score, and increased levels of AST, total bilirubin, and direct bilirubin. Subsequently, a multivariable logistic regression analysis was performed to further explore these factors. This analysis revealed that a pSOFA score of ≥ 8 and age less than 3 years were independent risk factors for R/R HLH, with adjusted odds ratios of 6.35 (95% CI, 1.18 – 34.19; p = 0.032) and 3.62 (95% CI, 1.04 – 12.63; p = 0.044), respectively.
Regarding the risk factors for mortality in children with HLH, the multivariable logistic regression analysis identified R/R HLH and the pSOFA score as independent predictors, as shown in Supplemental Table S5.