A Real-World Analysis of the Diagnostic Evaluation for Hemophagocytic Lymphohistiocytosis in a Pediatric Population
Authors: Meyer Lauren K. , Steen Erica A. , Keenan Camille , Olshen Adam B. , Nichols Kim E. , Zinter Matt S. 
Published: December 2023

Hemophagocytic lymphohistiocytosis (HLH) is a severe hyperinflammatory syndrome that is often fatal without immunosuppressive treatment to quell the overactive immune response. Accordingly, it is crucial to diagnose HLH promptly and accurately. Nevertheless, diagnosing HLH is challenging due to its phenotypic overlap with other inflammatory conditions. Furthermore, existing HLH diagnostic criteria consist largely of nonspecific clinical and laboratory findings. Together, these factors contribute to significant diagnostic uncertainty, which can delay initiation of treatment in patients who actually have HLH while exposing other patients who do not have HLH to unnecessary immunosuppressive therapy. We sought to better understand how these challenges manifest in a real-world setting and identify opportunities to improve upon existing diagnostic algorithms.

To this end, we queried the UCSF Electronic Medical Record Search Engine for clinical notes containing mention of HLH or the related disease, macrophage activation syndrome (MAS), in patients presenting to the UCSF Medical Center between 2008 and 2021. The resulting 2,360 patients were filtered to include only those who were admitted to an inpatient unit and managed by a pediatric care team. Patients with existing malignant, autoimmune, or immunodeficiency conditions were excluded. The resulting 635 patients were divided into an “HLH-diagnosed” group, consisting of 68 patients assigned an ICD-10 code for HLH/MAS, and an “HLH-considered” group, containing the remaining 567 patients without such a code but in whom HLH/MAS was considered on the differential diagnosis.

There was an equal distribution of males and females across the cohort. Ages ranged from 0 to 25 years, with no significant difference between groups. Patients in the HLH-diagnosed group were more likely to be deceased at the end of the admission (21% versus 5%, p&lt;0.0001). The most common presenting symptoms were fever, rash, emesis, and fatigue, and there were no differences in the frequency of any presenting features between the two groups. Among the discharge diagnoses for patients in the HLH-considered group, infections were most common (23%), followed by rheumatologic diseases (20%), new malignancies (9%), and fever of unknown origin (8%). We evaluated the performance of the two most commonly used diagnostic algorithms, namely the HLH-2004 criteria and H-score. The HLH-2004 criteria demonstrated a sensitivity of 65% and a specificity of 92%, versus 82% and 83% for the H-score. Patients in the HLH-considered group with newly-diagnosed malignancies had the highest false positivity rate, with 20% testing positive by the HLH-2004 criteria and 34% by the H-score. We also applied these algorithms to patients in the HLH-considered group who were assigned an ICD-10 code for sepsis (n=62). Fifteen and 42% had a false positive result by the HLH-2004 criteria and the H-score, respectively. Given that many HLH-considered patients tested positive by these existing algorithms but were ultimately ruled out based on other clinical data, we sought to create a new model relying only on basic laboratory parameters to help better differentiate HLH-diagnosed and HLH-considered patients. To address this, we performed multivariate logistic regression analysis. Cytopenias and levels of ferritin, triglycerides, and fibrinogen were all significant predictors in univariate analyses and independent predictors in the multivariate analysis. The resulting model produced an area under the curve of 0.86 (0.81-0.90).

HLH is commonly considered on the differential diagnosis in hospitalized children, and in our cohort, was ruled out eight times more often than it was diagnosed. Infections, malignancies, and rheumatologic diseases are the most common HLH mimics and cannot be readily distinguished from HLH on the basis of presenting features. Existing diagnostic algorithms showed suboptimal performance in this cohort, particularly in patients with malignancy and sepsis. Our alternative model consisting only of basic laboratory parameters may help streamline the initial diagnostic workup for pediatric patients with concern for HLH and more accurately identify those who require further specialized testing.