Ruxolitinib as adjunctive therapy for secondary hemophagocytic lymphohistiocytosis: A case series
Bibliographic record
Abstract
INTRODUCTION: Hemophagocytic lymphohistiocytosis (HLH) is a cytokine storm syndrome associated with mortality rates of up to 88%. Standard therapy with high-dose glucocorticoids and etoposide used in adults is extrapolated from pediatric trials, with significant toxicity in older patients and those with poor performance status. The JAK1/2 inhibitor ruxolitinib has recently gained attention as a treatment option for HLH due to its broad cytokine-modulating abilities and safety profile. Herein we report our center's experience using ruxolitinib in the treatment of adult-onset secondary HLH. CASE SERIES: We report four patients with profound secondary HLH provoked by diverse triggers, including invasive pulmonary aspergillosis on background systemic lupus erythematosus, disseminated tuberculosis, and T-cell lymphoma treated with ruxolitinib as monotherapy or combination therapy in upfront and salvage settings. RESULTS: All four patients had rapid, sustained improvement in clinical status, inflammatory markers, and hematological cell counts followed by durable remission. Three patients developed manageable infectious complications postruxolitinib. CONCLUSIONS: This series demonstrates the effective use of JAK inhibition with ruxolitinib to control pathological immune activation in critically ill patients with secondary HLH and otherwise limited therapeutic options. JAK inhibition is also an area of urgent investigation for the treatment of cytokine storm associated with COVID-19.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".