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- graft versus host disease (2)
- CYP2C9 (1)
- CYP3A4 (1)
- NK cells (1)
- Ruxolitinib (1)
- T cells (1)
- allogeneic stem cell transplantation (1)
- cytochrome P450 3A4 (CYP3A4) (1)
- drug–drug interactions (DDIs) (1)
- human cytomegalovirus (HCMV) (1)
Purpose
Knowledge on Ruxolitinib exposure in patients with graft versus host disease (GvHD) is scarce. The purpose of this prospective study was to analyze Ruxolitinib concentrations of GvHD patients and to investigate effects of CYP3A4 and CYP2C9 inhibitors and other covariates as well as concentration-dependent effects.
Methods
262 blood samples of 29 patients with acute or chronic GvHD who were administered Ruxolitinib during clinical routine were analyzed. A population pharmacokinetic model obtained from myelofibrosis patients was adapted to our population and was used to identify relevant pharmacokinetic properties and covariates on drug exposure. Relationships between Ruxolitinib exposure and adverse events were assessed.
Results
Median of individual mean trough serum concentrations was 39.9 ng/mL at 10 mg twice daily (IQR 27.1 ng/mL, range 5.6-99.8 ng/mL). Applying a population pharmacokinetic model revealed that concentrations in our cohort were significantly higher compared to myelofibrosis patients receiving the same daily dose (p < 0.001). Increased Ruxolitinib exposure was caused by a significant reduction in Ruxolitinib clearance by approximately 50%. Additional comedication with at least one strong CYP3A4 or CYP2C9 inhibitor led to a further reduction by 15% (p < 0.05). No other covariate affected pharmacokinetics significantly. Mean trough concentrations of patients requiring dose reduction related to adverse events were significantly elevated (p < 0.05).
Conclusion
Ruxolitinib exposure is increased in GvHD patients in comparison to myelofibrosis patients due to reduced clearance and comedication with CYP3A4 or CYP2C9 inhibitors. Elevated Ruxolitinib trough concentrations might be a surrogate for toxicity.
Ruxolitinib (RUX) is approved for the treatment of steroid-refractory acute and chronic graft versus host disease (GvHD). It is predominantly metabolized via cytochrome P450 (CYP) 3A4. As patients with GvHD have an increased risk of invasive fungal infections, RUX is frequently combined with posaconazole (POS), a strong CYP3A4 inhibitor. Knowledge of RUX exposure under concomitant POS treatment is scarce and recommendations on dose modifications are inconsistent. A physiologically based pharmacokinetic (PBPK) model was developed to investigate the drug–drug interaction (DDI) between POS and RUX. The predicted RUX exposure was compared to observed concentrations in patients with GvHD in the clinical routine. PBPK models for RUX and POS were independently set up using PK-Sim\(^®\) Version 11. Plasma concentration-time profiles were described successfully and all predicted area under the curve (AUC) values were within 2-fold of the observed values. The increase in RUX exposure was predicted with a DDI ratio of 1.21 (C\(_{max}\)) and 1.59 (AUC). Standard dosing in patients with GvHD led to higher RUX exposure than expected, suggesting further dose reduction if combined with POS. The developed model can serve as a starting point for further simulations of the implemented DDI and can be extended to further perpetrators of CYP-mediated PK-DDIs or disease-specific physiological changes.
Introduction
Human cytomegalovirus (HCMV) causes significant morbidity and mortality in allogeneic stem cell transplant (alloSCT) recipients. Recently, antiviral letermovir prophylaxis during the first 100 days after alloSCT replaced PCR-guided preemptive therapy as the primary standard of care for HCMV reactivations. Here, we compared NK-cell and T-cell reconstitution in alloSCT recipients receiving preemptive therapy or letermovir prophylaxis in order to identify potential biomarkers predicting prolonged and symptomatic HCMV reactivation.
Methods
To that end, the NK-cell and T-cell repertoire of alloSCT recipients managed with preemptive therapy (n=32) or letermovir prophylaxis (n=24) was characterized by flow cytometry on days +30, +60, +90 and +120 after alloSCT. Additionally, background-corrected HCMV-specific T-helper (CD4+IFNγ+) and cytotoxic (CD8+IFNγ+CD107a+) T cells were quantified after pp65 stimulation.
Results
Compared to preemptive therapy, letermovir prophylaxis prevented HCMV reactivation and decreased HCMV peak viral loads until days +120 and +365. Letermovir prophylaxis resulted in decreased T-cell numbers but increased NK-cell numbers. Interestingly, despite the inhibition of HCMV, we found high numbers of “memory-like” (CD56dimFcεRIγ- and/or CD159c+) NK cells and an expansion of HCMV-specific CD4+ and CD8+ T cells in letermovir recipients. We further compared immunological readouts in patients on letermovir prophylaxis with non/short-term HCMV reactivation (NSTR) and prolonged/symptomatic HCMV reactivation (long-term HCMV reactivation, LTR). Median HCMV-specific CD4+ T-cell frequencies were significantly higher in NSTR patients (day +60, 0.35 % vs. 0.00 % CD4+IFNγ+/CD4+ cells, p=0.018) than in patients with LTR, whereas patients with LTR had significantly higher median regulatory T-cell (Treg) frequencies (day +90, 2.2 % vs. 6.2 % CD4+CD25+CD127dim/CD4+ cells, p=0.019). ROC analysis confirmed low HCMV specific CD4+ (AUC on day +60: 0.813, p=0.019) and high Treg frequencies (AUC on day +90: 0.847, p=0.021) as significant predictors of prolonged and symptomatic HCMV reactivation.
Discussion
Taken together, letermovir prophylaxis delays HCMV reactivation and alters NK- and T-cell reconstitution. High numbers of HCMV-specific CD4+ T cells and low numbers of Tregs seem to be pivotal to suppress post-alloSCT HCMV reactivation during letermovir prophylaxis. Administration of more advanced immunoassays that include Treg signature cytokines might contribute to the identification of patients at high-risk for long-term and symptomatic HCMV reactivation who might benefit from prolonged administration of letermovir.