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.