1. Introduction
Allogeneic hematopoietic stem cell transplantation (alloHSCT) is a well-established treatment for hematologic diseases that cannot be cured with conventional therapies. The most common life-threatening complication after transplantation is graft-versus-host disease (GVHD), which occurs when immunocompetent T cells from the donor (the graft) recognize the recipient tissues (the host) as foreign. One of the cornerstones of transplant success is adequate GVHD prophylaxis [1,2]. Tacrolimus (Tac) is the main component of many current immunosuppressive regimens for the prevention of GVHD following alloHSCT [1,3]. However, Tac dosing in the setting of alloHSCT is complex due to its narrow therapeutic index and high interpatient and intrapatient pharmacokinetic variability. Excessive variations in Tac blood concentration have been associated with poor clinical outcomes in terms of GVHD incidence (underdosing) and toxicity (overdosing) [3,4,5].
In current clinical practice, Tac is usually initiated at a fixed dose based on patient weight and then titrated using therapeutic drug monitoring (TDM) employing Tac blood trough concentration (C0), which is usually maintained in the range of 5–15 ng/mL [2,3,4]. Unlike in solid organ transplantation (SOT), in alloHSCT Tac is maintained for the first 3–6 months post-transplant and then tapered and discontinued in the absence of GVHD by the 6th–12th month post-transplant [6]. Therefore, exposure to Tac during the immediate period after the HSCT period is of utmost importance to prevent subsequent GVHD [4,7,8]. Furthermore, subtherapeutic Tac trough concentrations (C0 < 5 ng/mL) at 48 h or 7 days after transplant has been associated with an increased incidence of acute GVHD (GVHD) [9,10].
During the last decade, in the context of SOT, it has been demonstrated that pharmacogenetic biomarkers influencing Tac exposure and response have the potential to enable individualization of the starting dose and favor the achievement of Tac target concentrations first days after transplantation [11,12,13]. Genetic factors including CYP3A5*3, CYP3A4*22, CYP4A4*1B, POR*28, and ABCB1 genetic variants have been reported frequently for their influence on Tac dose requirements [13,14,15]. Based on the available data, the effect of CYP4A4*1B, POR*28, and ABCB1 on Tac exposure seems to be much less clinically relevant as determinant biomarkers than the CYP3A5*3 or the cluster CYP3A5*3/CYP3A4*22 genotypes, at least in the Caucasian population [16].
A single nucleotide polymorphism in the CYP3A5 gene involving an A to G transition at position 6986 within intron 3 (rs776746) is strongly associated with CYP3A5 protein expression. Thus, the CYP3A5*3 allele causes a cryptic splice site resulting in protein truncation and a non-functional CYP3A5 protein [17]. Patients carrying at least one CYP3A5*1 allele (the wild type allele) are considered CYP3A5 expressers and this genotype may predict the metabolic phenotypes of extensive metabolizers (CYP3A5*1/*1) or intermediate metabolizers (CYP3A5*1/*1). Whereas those homozygous for the CYP3A5*3 (CYP3A5*3/*3) are non-CYP3A5 expressers and considered poor metabolizers, with a frequency around 80% in Caucasians [11,13]. Individual CYP3A5 expressers require almost double the conventional starting Tac dose to achieve target concentrations [11].
The CYP3A4*22 SNP (rs35599367) is another polymorphism that has been investigated in relation to Tac pharmacokinetics. This polymorphism is located 192 bp upstream of exon 7, the substitution C>T in this allele alters RNA splicing resulting in both decreased CYP3A4 mRNA expression (mainly in the liver) and decreased enzymatic activity. This SNP has an allele frequency of around 6% in Caucasians [18].
Other genetic variants such as the CYP3A*1B (rs2740574), and the CYP-mediated drug oxidation POR*28 (rs1057868) have been investigated. CYP3A4*1B was linked to an increased CYP3A4 activity; however, this has not been a consistent finding. Some groups have reported a higher Tac dose requirement of patients carrying the variant allele but this is largely explained by the strong linkage with the CYP3A5*1 allele [19].
Taking into account only the CYP3A5 genotype, patients who are CYP3A5 expressers (CYP3A5*1/*3, CYP3A5*1/*1) may be classified as extensive metabolizers when their genotype corresponds to CYP3A5*1/*1 and intermediate metabolizers for genotype CYP3A5*1/*3 [11]. As a result, it has been observed in kidney transplant recipients, that Tac oral clearance is about 2.4-fold higher in CYP3A5 expressers compared with non-expressers, leading to 2.5-fold higher dose requirements in CYP3A5 expressers [20]. Considering that CYP3A5 expressers require almost double the conventional Tac dose to achieve target concentrations, these patients are more susceptible to presenting a low C0/dose ratio. In solid organ transplantation (particularly in kidney transplantation), a low C0/dose ratio (inferior of 1.05 ng/mL/mg) has been associated with worse graft and patient clinical evolution [21,22].
Pharmacogenetic testing of CYP3A5*3 and CYP3A4*22 before transplant could play a role in allowing individualization of the starting dose of Tac to achieve target concentrations earlier. This concept could be referred to as “preemptive pharmacogenetics” [23]. There are few studies about the impact of CYP3A5*3 polymorphisms on alloHSCT outcomes, mainly conducted in the Asiatic population [24,25,26,27]. It has been suggested that the expression of CYP3A5 and a low C0/dose ratio seem to be similar or interchangeable factors by which to identify fast metabolizers and predict the Tac dose required to achieve target concentrations [21]. However, in the post-transplant period, other variables may also play a role: patient weight, age, hematocrit, physiopathology, and concomitant medications (drug–drug interactions) such as corticosteroids and azoles [20,23]. Standardization of antifungal prophylaxis with azoles may have a confounding effect regarding patient CYP3A5 genotype, as azoles are known to be potent inhibitors of CYP3A [28]. Similarly, corticosteroids are known to induce CYP3A enzyme activity [29] and may have the opposite clinical confounding factor. Taken together, these factors may confound the net genetic effect and its influence on Tac dose requirement.
The aim of the study was to assess the potential impact of CYP3A5 and CYP3A4 genotypes on acute GVHD incidence in alloHSCT transplant recipients. To carry out this project, we selected a group of Caucasian alloHSCT recipients with a fast metabolizer phenotype. We have identified as fast metabolizer phenotype those patients with a C0/dose ratio ≤ 1.5 ng/mL/mg, considering that, in our cohort, CYP3A5 non-expressers show a C0/dose ratio >1.5 ng/mL/mg.
2. Results
2.1. Baseline Characteristics of the Patients
Sixty-two patients were included in the study. Patient and transplant characteristics are summarized in Table 1. The mean age was 49 years (range 18–69 years, SD 15 years), and 52% were male. The most common primary diagnosis was acute leukemia (42%) or myelodysplastic syndrome (22%), followed by other malignant hematologic diseases. Thirty-five (56%) patients underwent RIC alloHSCT and the majority of patients had achieved either complete (58%) or partial (16%) remission at the time of alloHSCT. More than half of the patients (56%) had an HLA-matched donor, mostly from unrelated donors. Most of the patients received oral Tac formulations (73% QD, 24% BID), and 77% received PTCy-based for GVHD prophylaxis.
2.2. CYP3A5 and CYP3A4 Genotypes and Tac Pharmacokinetics
Forty-nine patients (79%) were identified as poor metabolizers (CYP3A5 non-expressers) whereas thirteen (21%) patients were identified as CYP3A5 expressers, twelve were intermediate metabolizers (CYP3A5*1/*3 genotype) and one was extensive metabolizer (CYP3A5*1/*1 genotype). The minor allele frequency (MAF) of CYP3A5*1 was 11% and the MAF of CYP3A4*22 was 2%. The data were close to the MAF of CYP3A5*1 (11%) and CYP3A4*22 (4%) in the dbSNP of the Alfa database (
Both groups were comparable in all transplant-related and patient characteristics except for the use of PTCy as part of a GVHD prophylaxis regimen, with a preponderance of PTCy-based regimens in intermediate and extensive metabolizers (100% vs. 71%, p = 0.03). Clinical variables that affect Tac pharmacokinetics, such as patient weight, hematocrit, and the use of azoles and corticosteroids, were similar in both groups.
Intermediate and extensive metabolizers had lower C0 at TISS (3.7 vs. 6.2 ng/mL, p = 0.03) and at 7 days (8.6 vs. 11.4 ng/mL, p = 0.04) after Tac initiation compared to poor metabolizers and tended to take longer to reach the therapeutic range of 5–15 ng/mL (11.8 vs. 8.9 days, p = 0.16) (Figure 1). Specifically, only 23% of intermediate and extensive metabolizers achieved therapeutic range at TISS compared to 59% of poor metabolizers (p = 0.029). In addition, the group of intermediate and extensive metabolizers had a higher proportion of patients with C0 < 5 ng/mL at TISS (77% vs. 39%, p = 0.026) and at 7 days (23% vs. 2%, p = 0.03). No significant differences were observed between poor and intermediate and extensive metabolizers in Tac C0 concentrations at 14 days, 21 days, and 28 days measurements (Figure 1).
Whereas in poor metabolizers the mean Tac dose was stable from 48 h to 7 days (11.6 vs. 11.3 mg, p = 0.7), intermediate and extensive metabolizers had a mean dose increase of 3.6 mg (10 vs. 13.6 mg, p = 0.025). Accordingly, the C0/dose ratio at 48h (0.38 vs. 0.76, p = 0.16) and at 7 days (0.69 vs. 1.04, p = 0.038) were lower in intermediate and extensive metabolizers whereas there were no differences in the mean monthly C0/dose ratio (0.98 vs. 1.08, p = 0.28) or at 14 days, 21 days, and 28 days measurements.
Regarding the CYP3A4 genotype, two patients were identified as heterozygous carriers of CYP3A4*22 (CYP3A4*1/22). One of them was a concomitant expresser of CYP3A5 (CYP3A5*1/*3) and the other was a non-expresser of CYP3A5 (CYP3A5*3/*3). Any of them reached the desired Tac C0 until day 5 after Tac initiation. Whereas the first patient (extensive metabolizer) maintained a relatively stable Tac dose throughout the study period, the second patient (poor metabolizer) presented supratherapeutic concentrations at day 21 days that led to a temporary suspension of Tac administration.
2.3. CYP3A5 and CYP3A4 Genotypes and Acute GVHD Incidence
During the study period, 52% (32 patients) developed acute GVHD (grades I–IV), with a 100-day cumulative incidence of 50% (95% CI 37–62%). Out of these, 63% (20 patients) presented with clinically relevant acute GVHD (grades II-IV), with a cumulative incidence of 33% (95% CI 17–47%). Compared to poor metabolizers, intermediate and extensive metabolizers had higher incidence of both global acute GVHD (92.3% [25–52%] vs. 38.8% [95% CI 36–99%], p < 0.001) and grade II–IV acute GVHD (61.5% [95% CI 28–83%] vs. 24.5% [95% CI 14–37], p = 0.008) (Figure 2). In fact, only one extensive metabolizer patient did not develop acute GVHD during the study period. In the univariate analysis, the other variable associated with a higher incidence of acute GVHD was a lower hematocrit (referred to as <p50) at 48 h post-transplant (67% vs. 35%, p = 0.02). The remaining variables included in the univariate and multivariate analysis for clinically relevant acute GVHD incidence are shown in Table 2. Multivariate analysis confirmed CYP3A5 intermediate and extensive metabolizers as an independent risk factor for acute GVHD (HR 3.5 [95% CI 1.5–8.3], p = 0.003) as well as clinically relevant acute GVHD (grades II-IV) (HR 4.5 [95% CI 2.4–8.6], p < 0.001).
Both patients previously identified as CYP3A4*22 carriers presented grade II acute GVHD.
2.4. CYP3A5 and CYP3A4 Genotypes and Tac-Related Adverse Events
Forty-four (71%) patients presented at least one AKI episode during the study period. Of those, 25 (57%) were identified as moderate to severe AKI (KDIGO grades 2 and 3). The incidence of any grade of AKI was similar between intermediate and extensive and poor Tac metabolizers. However, intermediate and extensive metabolizers showed a trend toward a higher incidence of moderate to severe AKI (62% vs. 35%, p = 0.11) compared to poor metabolizers, and this trend was also present with respect to the incidence of severe AKI (KDIGO grade 3) (23% vs. 8%, p = 0.15). Similarly, both the mCr (1.94 vs. 1.4 mg/dL, p = 0.01) and the mCr/bCr ratio were higher among intermediate and extensive metabolizers (2.4 vs. 1.9, p = 0.11) than in the poor metabolizer group. Supratherapeutic levels of Tac C0 (>15 ng/mL) at different time points after transplant were not significantly associated with AKI incidence or severity. There were no differences in neurotoxicity, graft failure, and TMA incidence between both groups.
Both patients previously identified as CYP3A4*22 carriers presented a grade 2 AKI episode during the study period.
3. Discussion
In our study, the obtained results demonstrate that CYP3A5*1/*3 and CYP3A5*1/*1 genotypes were significantly associated with infra-therapeutic Tac concentrations at 48 h and 7 days after Tac initiation, took longer to reach the therapeutic range, and had a higher risk of acute GVHD and renal toxicity.
In our cohort, which exclusively constituted Caucasian alloHSCT recipients, there was a solid association between CYP3A5 intermediate and extensive metabolizers (CYP3A5*1/*3 and CYP3A5*1/*1 genotypes) and lower concentrations of Tac in the first measurements (48 h and 7 days) coupled with lower rates of achievement of the lower limit of therapeutic range. The mean delay to achieve a therapeutic range for intermediate and extensive metabolizers was 2.9 days with respect to poor metabolizers. Consistent with the previous findings, intermediate and extensive metabolizers had a lower C0/dose ratio at 48 h and 7 days of treatment. Regarding Tac-related outcomes, CYP3A5*1/*3 and CYP3A5*1/*1 genotypes were an independent risk factor for a higher incidence of clinically significant acute GVHD grade II-IV (OR 6.4, p = 0.009) in our cohort. This association remained significant regardless of lower hematocrit, which also was associated with a higher rate of acute GVHD. This latter fact has been previously reported and is explained because erythrocytes act as a reservoir of Tac in the organism [30,31]. Despite not achieving statistical significance, there was a trend to higher incidence of clinically relevant episodes of AKI (KDIGO 2–3) and higher worsening of serum creatinine levels after transplantation in intermediate and extensive metabolizers. This fact could be in line with the hypothesis that patients with faster metabolizer phenotypes typically receive higher doses of Tac (lower C0/D ratios) in order to achieve the desired therapeutic range. Thus, these patients are likely to be exposed to higher Tac peak concentrations and this may explain an increased risk of AKI and other Tac-related adverse events [22,32]. On the other hand, lower nephrotoxicity is expected in patients exposed to lower Tac concentrations.
These findings indicate that achieving Tac treatment goals is more difficult in intermediate and extensive Tac metabolizers (CYP3A5 expressers), as higher Tac doses are required, resulting in lower C0/Dose ratios. These pharmacokinetic differences were observed at 48 h as well as at 7-day measurements after Tac initiation. These data could have relevant clinical implications after alloHSCT. Lower Tac C0 within the early period after alloHSCT has been associated with a higher incidence of acute GVHD [9,10] despite therapeutic drug monitoring and dose adjustment. Accordingly, we have observed a higher rate of clinically significant acute GVHD and AKI in intermediate and extensive Tac metabolizers patients. These results are consistent with the findings of Khaled et al., who reported higher concentrations of Tac in patients with the CYP3A5*3/*3 genotype [24]. Onizuka et al. also reported higher Tac C0 and C0/doses in patients with CYP3A5*3/*3 genotype compared to those with CYP3A5*1/*1 and CYP3A5*1/*3 genotypes [25]. However, Yamashita [26] et al. and Hamadeh et al. [27] did not find any differences in pharmacokinetic variables between patients with CYP3A5*3/*3 genotype and those with CYP3A5*1/*1 and CYP3A5*1/*3 genotypes. Remarkably, the use of fungal prophylaxis regimens and corticosteroid use differs among the aforementioned studies. In view of the fact that alloHSCT patients usually require several medications at the same time to prevent both transplant-related complications and infectious diseases, the isolation of the net effect of the genetic role of Tac metabolism is complex. Nevertheless, due to the use of standardized conditioning and GVHD prophylaxis regimens in our center, the first determination of Tac (TISS) would be a reasonably accurate point of comparison between patients and our results show relevant differences attributable to genetic differences in this early phase of post-transplant period. The incidence of acute GVHD and its association with the CYP3A5 genotype has only been explored in the studies by Khaled and Yamashita, which also identified CYP3A5*1/*1 as an independent risk factor for acute GVHD.
In the studied population, only 21% of patients with the fast metabolizer phenotype (C0/D ratio < 1.5 ng/mL/mg) were CYP3A5 expressers (intermediate and extensive metabolizers). This suggests that additional factors such as drug–drug interactions, mainly the potent induction of Tac metabolism by corticosteroids, could notably influence the pharmacokinetics of Tac. Among the patients non-expressers of CYP3A5, 45% were receiving corticosteroids during the post-transplant period.
The study’s main limitation is the relatively small number of patients included. This may have underpowered some significant differences in the measured variables in the cohort, particularly patient and transplant characteristics known to be associated with increased acute GVHD. There are few data published in the field of alloHSCT focusing on the Caucasian population, but our cohort displays the expected genotype distribution in this ethnic population (19% of patients CYP3A5*1/*3, 2% CYP3A5*1/*1, 3% CYP3A4*1/*22) [33,34]. Furthermore, the limited number of patients with the CYP3A4*22 allele prevents drawing definitive conclusions and requires validation in future studies. In our cohort of alloHSCT patients, all individuals were treated with azoles, which are potent inhibitors of CYP3A, and 50% of them received corticosteroids, which are potent inducers of CYP3A, at some point during treatment. The distribution of azoles and corticosteroid use was comparable between the two CYP3A5 genotype groups. The CYP3A5 genotype appears to have overshadowed the potential phenoconversion effect of those medications, according to our results. During the early period after transplant, Tac concentrations were found to be more influenced by pharmacogenetic factors than drug–drug interactions.
Given the strong association found in this study between CYP3A5*1/*3 and CYP3A5*1/*1 with Tac pharmacokinetics in the immediate post-transplant period and acute GVHD incidence, these results support the adoption of preemptive pharmacogenetic testing as a tool to better predict each patient’s Tac initial dose, helping to achieve the therapeutic range and reduce the risk of acute GVHD earlier.
4. Materials and Methods
4.1. Patients and Donors
The present study was performed at the Hospital Clínic in Barcelona (Spain) between February 2015 and December 2019. The study population consisted of alloHSCT Caucasian recipients with a fast metabolizer phenotype defined by a Tac C0/Dose ratio ≤ 1.5 ng/mL/mg. Eligibility criteria for transplant were as follows: age 18 to 69 years, first alloHSCT for malignant hematological disease, an Eastern Cooperative Oncology Group performance status ≤ 2, left ventricular ejection fraction ≥ 35%, forced expiratory volume in 1 s and forced vital capacity ≥ 40% of predicted, and adequate hepatic function (total bilirubin ≤ 3.0 mg/dL or absence of clinically significant liver disease). Only those patients with available information on Tac trough concentrations were considered eligible for the study. The protocol received institutional review board approval, and all participants provided signed informed consent.
4.2. Treatment Protocol and Supportive Care
Specific conditioning regimens used were based on the type of hematological disease and patient characteristics in accordance with institutional protocols. Patients aged > 50 years or previously submitted to an autologous HSCT received a reduced-intensity conditioning (RIC) regimen instead of myeloablative conditioning (MAC). All patients received peripheral blood as stem cell source.
Tac was initiated using either the intravenous formulation (0.03 mg/kg as a 24 h perfusion), the oral twice-daily [BID: bis in die] formulation (Tacni®, 0.06 mg/kg), or the one-daily modified-release [QD: quaque die] formulation (Advagraf®, 0.12 mg/kg) from day −1 or day +5 in those patients receiving post-transplant high-dose cyclophosphamide (PTCy). Tac was continued therapeutic until day +90 and then, tapered if acute GVHD grade II-IV was absent.
Patients that received GVHD prophylaxis regimen based on high-dose PTCy received 50 mg/kg IV once daily on days +3 and +4, along with Mesna at 80% of the Cy dose (divided into three doses). No patient received ATG or alemtuzumab for GVHD prevention. Granulocyte colony-stimulating factor was routinely given in haploidentical alloHSCT starting on day +7 until the absolute neutrophil count reached 1000 cells/mm [3] for 3 consecutive days.
Antimicrobial prophylaxis was administered according to our institutional practice guidelines. Standard prophylaxis included levofloxacin at a dose of 500 mg/24 h from day 0 until neutrophil engraftment, fluconazole at a dose of 400 mg c/24 h until day +60, and acyclovir at a dose of 400 mg c/12 h until day +365 (for patients who were seropositive for herpes simplex virus). Standard Pneumocystis jirovecii prophylaxis was used until CD4+ T cell recovery (>200 cells/μL) and/or until immunosuppression was discontinued. If any deviation in standard dose of fluconazole occurred, including suspension, increment, or a change by other azoles; Tac dose was adjusted or closely followed by whole blood concentration monitoring to adapt it to new circumstances and minimize under- or over-exposure. Cytomegalovirus (CMV) quantitative polymerase chain reaction (PCR) was performed weekly trough to at least day +60, and pre-emptive therapy was initiated if viral reactivation was detected (a PCR result above 1000 IU/mL or two consecutive rising values), according to standard practice recommendations.
4.3. Tac Pharmacokinetic Parameters
Tac whole blood C0 monitoring was routinely assessed three times per week from the day following the initiation of Tac until patient hospital discharge, and then, once weekly thereafter [35]. In the absence of acute GVHD or Tac-related toxicities, Tac weekly sampling was maintained usually during the first month after transplantation. We developed and validated ultra-high-performance liquid chromatography–tandem mass spectrometry (UPLC/MS/MS) procedure, under the European Medicines Agency (EMA) guideline [36]. The method was linear from 1 to 40 ng/mL of Tac. The lower limit of quantification is 1 ng/mL of Tac. Within and between-run accuracy and precision fulfilled the validation criteria. Tac doses were adjusted in order to achieve and maintain a Tac C0 between 5 and 15 ng/mL. This technique is subject to Tac Proficiency Testing from LGC Standards as an external quality control.
The primary variables of interest for the present study were Tac target concentrations at initial steady state (TISS), C0 at 7, 14, 21, and 28 days after Tac initiation, and Tac C0/dose ratio. The Tac C0/dose ratio was calculated as a quotient and was given as a fraction of unity. TISS was defined as the first whole blood concentration at 48 h post-initiation of Tac, which is approximately 4–5 times the half-life of the drug (12 h).
Successive hematocrit levels for each patient were recorded coinciding with C0 determinations at 48 h, 7, 14, 21, and 28 days after Tac initiation.
4.4. CYP3A5 and CYP3A4 Genetic Polymorphism Analysis
Genomic DNA was obtained from blood samples of the recipients before the alloHSCT using MagNA Pure LC DNA Isolation Kit in an automatic DNA extractor (MagNa Pure® System, Roche Applied Science, Indianapolis, Indiana) according to the manufacturer’s instructions. Allelic discrimination analysis was performed to determine the allelic status of CYP3A5*3 (rs776746) and CYP3A4*22 (rs35599367). CYP3A5*3 (C_26201809_30 probe) and CYP3A4*22 (C_59013445_10 probe) polymorphisms were genotyped by quantitative PCR (qPCR), in a QuantStudio 5.0 instrument (Applied Biosystem, Foster City, CA, USA). PCR mixture consisted of a 2.5 µL TaqMan Universal PCR mastermix, 0.25 µL TaqMan Drug Metabolism Genotyping Assay mix (20×), and 2.25 µL of DNA [20 ng] completed to 50 µL with nuclease-free water. The PCR run method was as follows: an initial step at 95 °C for 10 min, followed by 40 cycles: step 1 at 95 °C for 15 s and step 2 at 60 °C for 60 s. This technique is subject to external quality control by Referenzinstitut für Bioanalytik (RfB).
According to Clinical Pharmacogenetics Implementation Consortium [11], for the purpose of this study, and to focus only on CYP3A5 genotype: patients with CYP3A5 expression were considered extensive metabolizers (CYP3A5*1/*1) or intermediate metabolizers (CYP3A5*1/*3) whereas patients with 2 copies of the variant *3 allele were considered poor metabolizers. In addition, patient carriers of CYP3A4*22 allele and CYP3A5 non-expressers were considered poor metabolizers. Whereas CYP3A4*22 noncarriers and CYP3A5 non-expressers (that account for about 80% of Caucasian population) were considered intermediate metabolizers [13].
4.5. Endpoints of the Study
The main objective of the study was to analyze the influence of CYP3A5 and CYP3A4 genotypes in Tac initial dose election to better prevent GVHD in a selected population of alloHSCT patients with fast metabolizer phenotype.
Secondary endpoints were the incidence of Tac-related toxicity events: acute kidney injury [AKI], neurotoxicity, and thrombotic microangiopathy [TMA]) according to CYP3A5 and CYP3A4 genetic polymorphisms. Diagnosis of acute GVHD was based on clinical and histopathological findings of affected organs and graded from I to IV according to MAGIC criteria [37]. AKI was defined according to the 2012 Kidney Disease: Improving Global Outcomes (KDIGO) Clinical Practice Guideline Criteria [38]. Basal (bCr) and maximum (mCr) post-alloHSCT serum creatinine levels were recorded in order to calculate AKI values (mCr/bCr ratio). The diagnosis and severity of TMA were determined following current recommendations [39,40]. Neurotoxicity severity was evaluated according to the National Cancer Institute Common Terminology Criteria for Adverse Events (AEs) (NCI CTCAE, version 4.0).
4.6. Statistical Analysis
Descriptive variables were presented using counts and percentages, and continuous variables were reported using mean and SD. The cumulative incidence of acute GVHD was calculated using cumulative incidence methods and accounting for death and relapse as competing events. Univariate and multivariate regression tests explored the impact of the primary variable of interest (CYP3A5 genotype) on cumulative incidence of GVHD. Other variables that could potentially affect the incidence of acute GVHD were included in the statistical analysis: age at transplant, sex (male vs. female), disease status at transplant (chemosensitive disease [complete response/partial response] vs. stable disease/progression), CMV donor/recipient status, HLA compatibility (match related or unrelated donors vs. mismatched unrelated or haploidentical donor), donor to recipient relation sex (female to male vs. other), and conditioning regimen (MAC vs. RIC). The multivariate regression models included those variables found to be significant in the univariate analysis or clinically relevant. All p-values were 2-sided, and a p-value of <0.05 was considered to indicate statistical significance. All statistical calculations were performed using SPSS Statistics version 25 (SPSS INC, Chicago, IL, USA) and EZR software version 1.61.
Conceptualization, M.B. and C.M.; data curation, M.M., A.-M.G., V.F., V.-L.F.-Z., I.M.-E., G.R.-V., E.C., J.R.R., N.L., J.A., M.S.-L., L.R., F.F.-A. and M.R.; formal analysis, D.N.M. and M.-Q.S.; investigation, D.N.M.; methodology, M.-Q.S. and C.M.; resources, N.L.; supervision, M.B. and C.M.; validation, M.R.; writing—original draft, D.N.M. and J.J.; writing—review and editing, M.B. and C.M. All authors have read and agreed to the published version of the manuscript.
This study was conducted in accordance with the Declaration of Helsinki, and was approved by the Institutional Review Board (or Ethics Committee) of Hospital Clínic of Barcelona (HCB/2022/0191, date of approval 10 March 2022).
Informed consent was obtained from all subjects involved in the study.
All data are included within the article.
The authors declare no conflicts of interest.
GVHD (graft-versus-host disease); alloHSCT (allogeneic hematopoietic stem cell transplantation); AKI (acute kidney injury); ATG (antithymocyte globulin); BID (bis in die); C0 (trough concentration); CI (confidence interval); CMV (cytomegalovirus); GVHD (graft-versus-host disease); IV (intravenous); MAC (myeloablative conditioning); PCR (polymerase chain reaction); PTCy (high-dose post-transplant cyclophosphamide); QD (quaque die); RIC (reduced intensity conditioning); SD (standard deviation); Tac (tacrolimus); TDM (therapeutic drug monitoring); TISS (tacrolimus initial steady state); TMA (thrombotic microangiopathy).
Footnotes
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Enlarge this image.Figure 1. Diagram displaying the median Tac trough concentration (C0) along the study period for both poor metabolizers (non-expressers of CYP3A5) (green) and intermediate and extensive metabolizers (CYP3A5 expressers) (red). Continuous lines represent the median C0 values whereas discontinuous lines represent p25 and p75, respectively. Discontinuous dotted line signals desired therapeutic range.
Enlarge this image.Figure 2. Kaplan–Meyer analyses of the effects of CYP3A5 expression on the cumulative rates of GVHD (A) and clinically relevant (grades II–IV) GVHD (B).
Characteristics of patients and alloHSCT procedure.
| Characteristics | All Patients | CYP3A5*3/*3 | CYP3A5*1 † | p Value †† |
|---|---|---|---|---|
| Mean age, years (SD) | 49 (15) | 49 (14) | 50 (17) | 0.7 |
| Female sex | 30 (48) | 24 (49) | 6 (46) | 1 |
| Mean Weight, kg (SD) | 68.6 (12) | 69.1 (12) | 67.6 (14) | 0.7 |
| Primary diagnosis | ||||
| Acute leukemia | 26 (42) | 17 (35) | 9 (69) | 0.16 |
| Myelodysplastic syndromes | 14 (22) | 12 (25) | 2 (15) | 0.3 |
| Chronic myeloproliferative syndromes | 11 (18) | 10 (20) | 1 (8) | - |
| Lymphoma/multiple myeloma | 11 (18) | 10 (20) | 1 (8) | - |
| Disease status at transplant | ||||
| Complete response | 36 (58) | 27 (55) | 9 (69) | 0.6 |
| Partial response | 10 (16) | 8 (16) | 2 (15) | 0.9 |
| Stable disease/progression | 16 (26) | 14 (29) | 2 (15) | 0.4 |
| Conditioning regimen | ||||
| Myeloablative | 27 (44) | 21 (43) | 6 (46) | 1 |
| Reduced intensity | 35 (56) | 28 (57) | 7 (54) | - |
| Donor type | ||||
| HLA match 10/10 | 35 (56) | 28 (57) | 7 (54) | 1 |
| Identical sibling | 7 (11) | 4 (8) | 3 (23) | 0.23 |
| Haploidentical sibling | 11 (16) | 15 (31) | 1 (8) | - |
| Discordant sex ††† | 12 (19) | 9 (18) | 3 (23) | 0.7 |
| GVHD prophylaxis regimen | ||||
| PTCy-based | 48 (77) | 35 (71) | 13 (100) | 0.03 |
| Tac IV | 2 (3) | 2 (4) | 0 (0) | - |
| Tac BID | 15 (24) | 11 (22) | 4 (31) | 0.65 |
| Tac QD | 45 (73) | 36 (74) | 9 (69) | 0.8 |
| Hematocrit (SD) | ||||
| Day 0 | 0.29 (0.06) | 0.29 (0.06) | 0.29 (0.06) | 0.9 |
| At 48 h | 0.29 (0.05) | 0.29 (0.06) | 0.29 (0.06) | 0.9 |
| Mean of first month | 0.27 (0.03) | 0.27 (0.03) | 0.28 (0.03) | 0.6 |
| Change in azole regimen | 15 (24) | 11 (22) | 4 (31) | 0.72 |
| Corticosteroids treatment | 31 (50) | 22 (45) | 9 (69) | 0.21 |
Values in brackets are presented in %. PTCy, post-transplant cyclophosphamide; BID, bis in die; IV, intravenous; QD, quaque die; SD, standard deviation. † Including either CYP3A5*1/*3 or CYP3A5*1/*1. †† p-values have been omitted in boxes without enough number of patients. ††† Male receptor and female donor.
Univariate and multivariate analysis for II-IV GVHD incidence.
| Characteristics | Univariate Analysis | p-Value | Multivariate Analysis, HR (95% CI) | p-Value | |
|---|---|---|---|---|---|
| Patient age | Continuous variable (years) | 48.5 vs. 49.7 | 0.75 | 1.01 (0.97–1.03) | 0.7 |
| Conditioning regimen | RIC (vs. myeloablative) | 25.7 vs. 40.7 | 0.28 | 0.47 (0.2–1.09) | 0.08 |
| Disease status at transplant | Complete remission (vs. other) | 31.4 vs. 33.3 | 1 | ||
| Donor sex | Female donor to male (vs. other) | 41.7 vs. 30 | 0.5 | 0.81 (0.33–1.93) | 0.64 |
| Donor type | Any mismatch (vs. HLA matched) | 33.3 vs. 31.3 | 1 | 1.78 (0.9–3.51) | 0.1 |
| Tac TISS | <5 ng/mL (vs. ≥5) | 37.9 vs. 27.3 | 0.42 | ||
| Tac C0 at 7 days | <5 ng/mL (vs. ≥5) | 75 vs. 29.3 | 0.09 | 7.3 (0.7–17.1) | 0.1 |
| Tac formulation | QD (vs. other) | 31.1 vs. 35.3 | 0.7 | ||
| Hematocrit at 48 h | <25th percentile (vs. ≥25th) | 56.3 vs. 23.9 | 0.029 | 5.3 (1.4–19.7) | 0.01 |
| <50th percentile (vs. ≥50th) | 39.4 vs. 24.1 | 0.28 | |||
| <75th percentile (vs. ≥75th) | 37.8 vs. 17.6 | 0.22 | |||
| CMV status | High risk (vs. other) | 38.9 vs. 29.5 | 0.55 | 2.5 (0.3–13.1) | 0.62 |
| CYP3A5 | *1/*3 or *1/*1 (vs. *3/*3) | 61.5 vs. 24.5 | 0.019 | 4.51 (2.37–8.6) | <0.001 |
All values are displayed in % if not otherwise specified. HR, hazard ratio; RIC, reduced intensity conditioning; QD: quaque die; CMV, cytomegalovirus; Tac, tacrolimus; TISS, tacrolimus initial steady state; C0, tacrolimus trough concentration.
References
1. Penack, O.; Marchetti, M.; Aljurf, M.; Arat, M.; Bonifazi, F.; Duarte, R.F.; Giebel, S.; Greinix, H.; Hazenberg, M.D.; Kröger, N. et al. Prophylaxis and management of graft-versus-host disease after stem-cell transplantation for haematological malignancies: Updated consensus recommendations of the European Society for Blood and Marrow Transplantation. Lancet Haematol.; 2024; 11, pp. e147-e159. [DOI: https://dx.doi.org/10.1016/S2352-3026(23)00342-3] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/38184001]
2. De Jong, C.N.; Meijer, E.; Bakunina, K.; Nur, E.; Kooij, M.V.M.; De Groot, M.R.; Van Gelder, M.; Maertens, J.A.; Kuball, J.H.; Deeren, D. et al. Post-Transplantation Cyclophosphamide after Allogeneic Hematopoietic Stem Cell Transplantation: Results of the Prospective Randomized HOVON-96 Trial in Recipients of Matched Related and Unrelated Donors. Blood; 2019; 134, (Suppl. S1), 1. [DOI: https://dx.doi.org/10.1182/blood-2019-124659]
3. Wingard, J.R.; Nash, R.A.; Przepiorka, D.; Klein, J.L.; Weisdorf, D.J.; Fay, J.W.; Zhu, J.; Maher, R.M.; Fitzsimmons, W.E.; Ratanatharathorn, V. Relationship of tacrolimus (FK506) whole blood concentrations and efficacy and safety after HLA-identical sibling bone marrow transplantation. Biol. Blood Marrow Transplant.; 1998; 4, pp. 157-163. [DOI: https://dx.doi.org/10.1053/bbmt.1998.v4.pm9923414]
4. Przepiorka, D.; Devine, S.M.; Fay, J.W.; Uberti, J.P.; Wingard, J.R. Practical considerations in the use of tacrolimus for allogeneic marrow transplantation. Bone Marrow Transplant.; 1999; 24, pp. 1053-1056. [DOI: https://dx.doi.org/10.1038/sj.bmt.1702032]
5. Przepiorka, D.; Nash, R.A.; Wingard, J.R.; Zhu, J.; Maher, R.M.; Fitzsimmons, W.E.; Fay, J.W. Relationship of Tacrolimus Whole Blood Levels to Efficacy and Safety Outcomes after Unrelated Donor Marrow Transplantation. Biol. Blood Marrow Transplant.; 1999; 5, pp. 94-97. [DOI: https://dx.doi.org/10.1053/bbmt.1999.v5.pm10371361]
6. Penack, O.; Marchetti, M.; Ruutu, T.; Aljurf, M.; Bacigalupo, A.; Bonifazi, F.; Ciceri, F.; Cornelissen, J.; Malladi, R.; Duarte, R.F. et al. Prophylaxis and management of graft versus host disease after stem-cell transplantation for haematological malignancies: Updated consensus recommendations of the European Society for Blood and Marrow Transplantation. Lancet Haematol.; 2020; 7, pp. e157-e167. [DOI: https://dx.doi.org/10.1016/S2352-3026(19)30256-X]
7. Mori, T.; Kato, J.; Shimizu, T.; Aisa, Y.; Nakazato, T.; Yamane, A.; Ono, Y.; Kunimoto, H.; Okamoto, S. Effect of Early Posttransplantation Tacrolimus Concentration on the Development of Acute Graft-versus-Host Disease after Allogeneic Hematopoietic Stem Cell Transplantation fromUnrelated Donors. Biol. Blood Marrow Transplant.; 2012; 18, pp. 229-234. [DOI: https://dx.doi.org/10.1016/j.bbmt.2011.06.008] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21708109]
8. Ganetsky, A.; Shah, A.; Miano, T.A.; Hwang, W.-T.; He, J.; Loren, A.W.; Hexner, E.O.; Frey, N.V.; Porter, D.L.; Reshef, R. Higher tacrolimus concentrations early after transplant reduce the risk of acute GvHD in reduced-intensity allogeneic stem cell transplantation. Bone Marrow Transplant.; 2016; 51, pp. 568-572. [DOI: https://dx.doi.org/10.1038/bmt.2015.323] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26691423]
9. Marco, D.N.; Salas, M.Q.; Gutiérrez-García, G.; Monge, I.; Riu, G.; Carcelero, E.; Roma, J.R.; Llobet, N.; Arcarons, J.; Suárez-Lledó, M. et al. Impact of Early Intrapatient Variability of Tacrolimus Concentrations on the Risk of Graft-Versus-Host Disease after Allogeneic Stem Cell Transplantation Using High-Dose Post-Transplant Cyclophosphamide. Pharmaceuticals; 2022; 15, 1529. [DOI: https://dx.doi.org/10.3390/ph15121529]
10. Yao, J.M.; Yang, D.; Clark, M.C.; Otoukesh, S.; Cao, T.; Ali, H.; Arslan, S.; Aldoss, I.; Artz, A.; Amanam, I. et al. Tacrolimus initial steady state level in post-transplant cyclophosphamide-based GvHD prophylaxis regimens. Bone Marrow Transplant.; 2022; 57, pp. 232-242. [DOI: https://dx.doi.org/10.1038/S41409-021-01528-Y]
11. Birdwell, K.A.; Decker, B.; Barbarino, J.M.; Peterson, J.; Stein, C.; Sadee, W.; Wang, D.; Vinks, A.; He, Y.; Swen, J. et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for CYP3A5 genotype and tacrolimus dosing. Clin. Pharmacol. Ther.; 2015; 98, pp. 19-24. [DOI: https://dx.doi.org/10.1002/cpt.113] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25801146]
12. Sissung, T.M.; Baum, C.E.; Kirkland, C.T.; Gao, R.; Gardner, E.R.; Figg, W.D. Pharmacogenetics of membrane transporters: An update on current approaches. Mol Biotechnol.; 2010; 44, pp. 152-167. [DOI: https://dx.doi.org/10.1007/s12033-009-9220-6] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/19950006]
13. Brunet, M.; Van Gelder, T.; Åsberg, A.; Haufroid, V.; Hesselink, D.A.; Langman, L.; Lemaitre, F.; Marquet, P.; Seger, C.; Shipkova, M. et al. Therapeutic Drug Monitoring of Tacrolimus-Personalized Therapy: Second Consensus Report. Ther. Drug Monit.; 2019; 41, pp. 261-307. [DOI: https://dx.doi.org/10.1097/FTD.0000000000000640] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31045868]
14. Yu, M.; Liu, M.; Zhang, W.; Ming, Y. Pharmacokinetics, Pharmacodynamics and Pharmacogenetics of Tacrolimus in Kidney Transplantation. Curr. Drug Metab.; 2018; 19, pp. 513-522. [DOI: https://dx.doi.org/10.2174/1389200219666180129151948] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29380698]
15. Degraeve, A.L.; Moudio, S.; Haufroid, V.; Eddour, D.C.; Mourad, M.; Bindels, L.B.; Elens, L. Predictors of tacrolimus pharmacokinetic variability: Current evidences and future perspectives. Expert Opin. Drug Metab. Toxicol.; 2020; 16, pp. 769-782. [DOI: https://dx.doi.org/10.1080/17425255.2020.1803277] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32721175]
16. Hesselink, D.A.; Bouamar, R.; Elens, L.; Van Schaik, R.H.N.; Van Gelder, T. The role of pharmacogenetics in the disposition of and response to tacrolimus in solid organ transplantation. Clin. Pharmacokinet.; 2014; 53, pp. 123-139. [DOI: https://dx.doi.org/10.1007/S40262-013-0120-3] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24249597]
17. Kuehl, P.; Zhang, J.; Lin, Y.; Lamba, J.; Assem, M.; Schuetz, J.; Watkins, P.B.; Daly, A.; Wrighton, S.A.; Hall, S.D. et al. Sequence diversity in CYP3A promoters and characterization of the genetic basis of polymorphic CYP3A5 expression. Nat. Genet.; 2001; 27, pp. 383-391. [DOI: https://dx.doi.org/10.1038/86882]
18. Wang, D.; Guo, Y.; Wrighton, S.A.; Cooke, G.E.; Sadee, W. Intronic polymorphism in CYP3A4 affects hepatic expression and response to statin drugs. Pharm. J.; 2011; 11, pp. 274-286. [DOI: https://dx.doi.org/10.1038/TPJ.2010.28] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20386561]
19. Staatz, C.E.; Goodman, L.K.; Tett, S.E. Effect of CYP3A and ABCB1 single nucleotide polymorphisms on the pharmacokinetics and pharmacodynamics of calcineurin inhibitors: Part I. Clin. Pharmacokinet.; 2010; 49, pp. 141-175. [DOI: https://dx.doi.org/10.2165/11317350-000000000-00000]
20. De Jonge, H.; De Loor, H.; Verbeke, K.; Vanrenterghem, Y.; Kuypers, D.R. In Vivo CYP3A4 Activity, CYP3A5 Genotype, and Hematocrit Predict Tacrolimus Dose Requirements and Clearance in Renal Transplant Patients. Clin. Pharmacol. Ther.; 2012; 92, pp. 366-375. [DOI: https://dx.doi.org/10.1038/CLPT.2012.109]
21. Thölking, G.; Gerth, H.U.; Schuette-Nuetgen, K.; Reuter, S. Influence of tacrolimus metabolism rate on renal function after solid organ transplantation. World J. Transplant.; 2017; 7, pp. 26-33. [DOI: https://dx.doi.org/10.5500/WJT.V7.I1.26] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28280692]
22. van Gelder, T.; Meziyerh, S.; Swen, J.J.; de Vries, A.P.J.; Moes, D.J.A.R. The Clinical Impact of the C0/D Ratio and the CYP3A5 Genotype on Outcome in Tacrolimus Treated Kidney Transplant Recipients. Front. Pharmacol.; 2020; 11, 1142. [DOI: https://dx.doi.org/10.3389/FPHAR.2020.01142] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32848756]
23. Brunet, M.; Pastor-Anglada, M. Insights into the Pharmacogenetics of Tacrolimus Pharmacokinetics and Pharmacodynamics. Pharmaceutics; 2022; 14, 1755. [DOI: https://dx.doi.org/10.3390/pharmaceutics14091755] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36145503]
24. Khaled, S.K.; Palmer, J.M.; Herzog, J.; Stiller, T.; Tsai, N.-C.; Senitzer, D.; Liu, X.; Thomas, S.H.; Shayani, S.; Weitzel, J. et al. Influence of Absorption, Distribution, Metabolism, and Excretion Genomic Variants on Tacrolimus/Sirolimus Blood Levels and Graft-versus-Host Disease after Allogeneic Hematopoietic Cell Transplantation. Biol. Blood Marrow Transplant.; 2016; 22, pp. 268-276. [DOI: https://dx.doi.org/10.1016/j.bbmt.2015.08.027] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26325438]
25. Onizuka, M.; Kunii, N.; Toyosaki, M.; Machida, S.; Ohgiya, D.; Ogawa, Y.; Kawada, H.; Inoko, H.; Ando, K. Cytochrome P450 genetic polymorphisms influence the serum concentration of calcineurin inhibitors in allogeneic hematopoietic SCT recipients. Bone Marrow Transplant.; 2011; 46, pp. 1113-1117. [DOI: https://dx.doi.org/10.1038/bmt.2010.273]
26. Yamashita, T.; Fujishima, N.; Miura, M.; Niioka, T.; Abumiya, M.; Shinohara, Y.; Ubukawa, K.; Nara, M.; Fujishima, M.; Kameoka, Y. et al. Effects of CYP3A5 polymorphism on the pharmacokinetics of a once-daily modified-release tacrolimus formulation and acute kidney injury in hematopoietic stem cell transplantation. Cancer Chemother. Pharmacol.; 2016; 78, pp. 111-118. [DOI: https://dx.doi.org/10.1007/s00280-016-3060-4]
27. Hamadeh, I.S.; Zhang, Q.; Steuerwald, N.; Hamilton, A.; Druhan, L.J.; McSwain, M.; Diez, Y.; Rusin, S.; Han, Y.; Symanowski, J. et al. Effect of CYP3A4, CYP3A5, and ABCB1 Polymorphisms on Intravenous Tacrolimus Exposure and Adverse Events in Adult Allogeneic Stem Cell Transplant Patients. Biol. Blood Marrow Transplant.; 2019; 25, pp. 656-663. [DOI: https://dx.doi.org/10.1016/j.bbmt.2018.12.766]
28. Zhang, S.; Pillai, V.C.; Mada, S.R.; Strom, S.; Venkataramanan, R. Effect of voriconazole and other azole antifungal agents on CYP3A activity and metabolism of tacrolimus in human liver microsomes. Xenobiotica; 2012; 42, pp. 409-416. [DOI: https://dx.doi.org/10.3109/00498254.2011.631224]
29. Anglicheau, D.; Flamant, M.; Schlageter, M.H.; Martinez, F.; Cassinat, B.; Beaune, P.; Legendre, C.; Thervet, E. Pharmacokinetic interaction between corticosteroids and tacrolimus after renal transplantation. Nephrology Dialysis Transplantation.; 2003; 18, pp. 2409-2414. [DOI: https://dx.doi.org/10.1093/ndt/gfg381]
30. Limsrichamrern, S.; Chanapul, C.; Mahawithitwong, P.; Sirivatanauksorn, Y.; Kositamongkol, P.; Asavakarn, S.; Tovikkai, C.; Dumronggittigule, W. Correlation of Hematocrit and Tacrolimus Level in Liver Transplant Recipients. Transplant. Proc.; 2016; 48, pp. 1176-1178. [DOI: https://dx.doi.org/10.1016/J.TRANSPROCEED.2015.12.096]
31. Sikma, M.A.; Hunault, C.C.; Huitema, A.D.R.; De Lange, D.W.; Van Maarseveen, E.M. Clinical Pharmacokinetics and Impact of Hematocrit on Monitoring and Dosing of Tacrolimus Early after Heart and Lung Transplantation. Clin. Pharmacokinet.; 2020; 59, pp. 403-408. [DOI: https://dx.doi.org/10.1007/S40262-019-00846-1] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31820394]
32. Schütte-Nütgen, K.; Thölking, G.; Steinke, J.; Pavenstädt, H.; Schmidt, R.; Suwelack, B.; Reuter, S. Fast Tac Metabolizers at Risk—It is Time for a C/D Ratio Calculation. J. Clin. Med.; 2019; 8, 587. [DOI: https://dx.doi.org/10.3390/JCM8050587] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31035422]
33. Hustert, E.; Haberl, M.; Burk, O.; Wolbold, R.; He, Y.-Q.; Klein, K.; Nuessler, A.C.; Neuhaus, P.; Klattig, J.; Eiselt, R. et al. The genetic determinants of the CYP3A5 polymorphism. Pharmacogenetics; 2001; 11, pp. 773-779. [DOI: https://dx.doi.org/10.1097/00008571-200112000-00005]
34. Lee, S.J.; Usmani, K.A.; Chanas, B.; Ghanayem, B.; Xi, T.; Hodgson, E.; Mohrenweiser, H.W.; Goldstein, J.A. Genetic findings and functional studies of human CYP3A5 single nucleotide polymorphisms in different ethnic groups. Pharmacogenetics; 2003; 13, pp. 461-472. [DOI: https://dx.doi.org/10.1097/00008571-200308000-00004]
35. Pascual, J.; Del Castillo, D.; Cabello, M.; Pallardó, L.; Grinyó, J.M.; Fernández, A.M.; Brunet, M. Interaction between everolimus and tacrolimus in renal transplant recipients: A pharmacokinetic controlled trial. Transplantation; 2010; 89, pp. 994-1000. [DOI: https://dx.doi.org/10.1097/TP.0B013E3181CCD7F2] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20335831]
36. ICH M10 on Bioanalytical Method Validation—Scientific Guideline|European Medicines Agency. Available online: https://www.ema.europa.eu/en/ich-m10-bioanalytical-method-validation-scientific-guideline (accessed on 16 April 2024).
37. Levine, J.E.; Hogan, W.J.; Harris, A.C.; Litzow, M.R.; Efebera, Y.A.; Devine, S.M.; Reshef, R.; Ferrara, J.L. Improved accuracy of acute graft-versus-host disease staging among multiple centers. Best Pract. Res. Clin. Haematol.; 2014; 27, pp. 283-287. [DOI: https://dx.doi.org/10.1016/J.BEHA.2014.10.011]
38. Kellum, J.A.; Lameire, N.; Aspelin, P.; Barsoum, R.S.; Burdmann, E.A.; Goldstein, S.L.; Herzog, C.A.; Joannidis, M.; Kribben, A.; Levey, A.S. et al. Kidney disease: Improving global outcomes (KDIGO) acute kidney injury work group. KDIGO clinical practice guideline for acute kidney injury. Kidney Int. Suppl.; 2012; 2, pp. 1-138. Available online: https://experts.umn.edu/en/publications/kidney-disease-improving-global-outcomes-kdigo-acute-kidney-inju (accessed on 16 April 2024).
39. Jodele, S.; Laskin, B.L.; Dandoy, C.E.; Myers, K.C.; El-Bietar, J.; Davies, S.M.; Goebel, J.; Dixon, B.P. A new paradigm: Diagnosis and management of HSCT-associated thrombotic microangiopathy as multi-system endothelial injury. Blood Rev.; 2015; 29, pp. 191-204. [DOI: https://dx.doi.org/10.1016/J.BLRE.2014.11.001]
40. Cho, B.S.; Yahng, S.A.; Lee, S.E.; Eom, K.-S.; Kim, Y.-J.; Kim, H.-J.; Lee, S.; Min, C.-K.; Cho, S.-G.; Kim, D.-W. et al. Validation of recently proposed consensus criteria for thrombotic microangiopathy after allogeneic hematopoietic stem-cell transplantation. Transplantation; 2010; 90, pp. 918-926. [DOI: https://dx.doi.org/10.1097/TP.0B013E3181F24E8D]
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Details
; Molina, Mònica 1 ; Ana-María Guio 1 ; Julian, Judit 2
; Fortuna, Virginia 2 ; Fabregat-Zaragoza, Virginia-Lucila 3 ; María-Queralt Salas 1
; Monge-Escartín, Inés 4
; Riu-Viladoms, Gisela 4
; Carcelero, Esther 4 ; Roma, Joan Ramón 4 ; Llobet, Noemí 1 ; Arcarons, Jordi 1 ; Suárez-Lledó, María 1 ; Rosiñol, Laura 1
; Fernández-Avilés, Francesc 1
; Rovira, Montserrat 1 ; Brunet, Mercè 2 ; Martínez, Carmen 1
1 Hematopoietic Stem Cell Transplantation Unit, Hematology Department, Institute of Cancer and Hematological Diseases, Instituto de Investigación Biomédica August Pi i Sunyer (IDIBAPS), Hospital Clínic, 08036 Barcelona, Spain;
2 Pharmacology and Toxicology Laboratory, Biochemistry and Molecular Genetics Department, Biomedical Diagnostic Center, IDIBAPS, CIBERehd, Hospital Clínic, 08036 Barcelona, Spain;
3 Department of Immunology, Hospital Clínic, 08036 Barcelona, Spain;
4 Department of Pharmacy, Pharmacy Service, Hospital Clínic, 08036 Barcelona, Spain;