Evaluation of the New Siemens Tacrolimus Assay on the Dimension EXL Integrated Chemistry System Analyzer: Comparison With an Ultra-Performance Liquid Chromatography–Tandem Mass Spectrometry Method

Puzzling Interference in the Siemens Tacrolimus Assay in a Renal Transplant Patient: A Case Report

BACKGROUND

Therapeutic drug monitoring is a key tool for optimizing tacrolimus therapy in transplant recipients. The modified ACMIA assay from Siemens Healthcare Diagnostics is an immunoassay commonly used for tacrolimus monitoring, but it is not known whether this assay is resistant to interference from endogenous substances in real-world use.

OBJECTIVE

To describe a case of unexpected interference in tacrolimus monitoring using the modified ACMIA method in a kidney transplant recipient, and to highlight the importance of careful interpretation of laboratory results and effective communication with clinicians in optimizing patient care.

CASE DESCRIPTION

This case report describes a significant interference in the monitoring of tacrolimus in a kidney transplant recipient using the new ACMIA method. In this case, when aberrant results for tacrolimus were found using the new ACMIA method, they were re-analyzed using the CMIA method from Abbott. The presence of positive ANCA-MPO autoantibodies was found to be the most likely cause of the interference after an extensive workup.

CONCLUSIONS

This is the first report of major interference with the modified ACMIA tacrolimus method and emphasizes the importance of proper interpretation of laboratory results and effective communication with clinicians in optimizing patient care.

Combined impact of the inter and intra-patient variability of tacrolimus blood level on allograft outcomes in kidney transplantation

Introduction

Tacrolimus (TAC) has been widely used as an immunosuppressant after kidney transplantation (KT); however, the combined effects of intra-patient variability (IPV) and inter-patient variability of TAC-trough level (C0) in blood remain controversial. This study aimed to determine the combined impact of TAC-IPV and TAC inter-patient variability on allograft outcomes of KT.

Methods

In total, 1,080 immunologically low-risk patients who were not sensitized to donor human leukocyte antigen (HLA) were enrolled. TAC-IPV was calculated using the time-weighted coefficient variation (TWCV) of TAC-C0, and values > 30% were classified as high IPV. Concentration-to-dose ratio (CDR) was used for calculating TAC inter-patient variability, and CDR < 1.05 ng•mg/mL was classified as rapid metabolizers (RM). TWCV was calculated based on TAC-C0 up to 1 year after KT, and CDR was calculated based on TAC-C0 up to 3 months after KT. Patients were classified into four groups according to TWCV and CDR: low IPV/non-rapid metabolizer (NRM), high IPV/NRM, low IPV/RM, and high IPV/RM. Subgroup analysis was performed for pre-transplant panel reactive antibody (PRA)-positive and -negative patients (presence or absence of non-donor-specific HLA-antibodies). Allograft outcomes, including deathcensored graft loss (DCGL) and biopsy-proven allograft rejection (BPAR), were compared.

Results

The incidences of DCGL, BPAR, and overall graft loss were the highest in the high-IPV/RM group. In addition, a high IPV/RM was identified as an independent risk factor for DCGL. The hazard ratio of high IPV/RM for DCGL and the incidence of active antibody-mediated rejection were considerably increased in the PRA-positive subgroup.

Discussion

High IPV combined with RM (inter-patient variability) was closely related to adverse allograft outcomes, and hence, more attention must be given to pre-transplant PRA-positive patients.

Intrapatient Variability in Tacrolimus Trough Levels Over 2 Years Affects Long-Term Allograft Outcomes of Kidney Transplantation

This study aimed to determine the impact of tacrolimus (TAC) trough level (C0) intrapatient variability (IPV) over a period of 2 years after kidney transplantation (KT) on allograft outcomes. In total, 1,143 patients with low immunologic risk were enrolled. The time-weighted coefficient variability (TWCV) of TAC-C0 was calculated, and patients were divided into tertile groups (T1: < 24.6%, T2: 24.6%–33.7%, T3: ≥ 33.7%) according to TAC-C0-TWCV up to post-transplant 1^st year. They were classified into the low/low, low/high, high/low, and high/high groups based on a TAC-C0-TWCV value of 33.7% during post-transplant 0–1^st and 1^st–2^nd years. The allograft outcomes among the three tertile and four TAC-C0-TWCV groups were compared. The T3 group had the highest rate of death-censored allograft loss (DCGL), and T3 was considered an independent risk factor for DCGL. The low/low group had the lowest and the high/high group had the highest risk for DCGL. Moreover, patients with a mean TAC-C0 of ≥5 ng/ml in the high/high group were at the highest risk for DCGL. Thus, TAC-IPV can significantly affect allograft outcomes even with a high mean TAC-C0. Furthermore, to improve allograft outcomes, a low TAC-IPV should be maintained even after the first year of KT.

Can We Predict Individual Concentrations of Tacrolimus After Liver Transplantation? Application and Tweaking of a Published Population Pharmacokinetic Model in Clinical Practice

BACKGROUND

Various population pharmacokinetic models have been developed to describe the pharmacokinetics of tacrolimus in adult liver transplantation. However, their extrapolated predictive performance remains unclear in clinical practice. The purpose of this study was to predict concentrations using a selected literature model and to improve these predictions by tweaking the model with a subset of the target population.

METHODS

A literature review was conducted to select an adequate population pharmacokinetic model (L). Pharmacokinetic data from therapeutic drug monitoring of tacrolimus in liver-transplanted adults were retrospectively collected. A subset of these data (70%) was exploited to tweak the L-model using the $PRIOR subroutine of the NONMEM software, with 2 strategies to weight the prior information: full informative (F) and optimized (O). An external evaluation was performed on the remaining data; bias and imprecision were evaluated for predictions a priori and Bayesian forecasting.

RESULTS

Seventy-nine patients (851 concentrations) were enrolled in the study. The predictive performance of L-model was insufficient for a priori predictions, whereas it was acceptable with Bayesian forecasting, from the third prediction (ie, with ≥2 previously observed concentrations), corresponding to 1 week after transplantation. Overall, the tweaked models showed a better predictive ability than the L-model. The bias of a priori predictions was -41% with the literature model versus -28.5% and -8.73% with tweaked F and O models, respectively. The imprecision was 45.4% with the literature model versus 38.0% and 39.2% with tweaked F and O models, respectively. For Bayesian predictions, whatever the forecasting state, the tweaked models tend to obtain better results.

CONCLUSIONS

A pharmacokinetic model can be used, and to improve the predictive performance, tweaking the literature model with the $PRIOR approach allows to obtain better predictions.

Comparison of 4 Commercial Immunoassays Used in Measuring the Concentration of Tacrolimus in Blood and Their Cross-Reactivity to Its Metabolites

BACKGROUND

Therapeutic drug monitoring of tacrolimus is necessary for appropriate dose adjustment for a successful immunosuppressive therapy. Several commercial immunoassays are available for tacrolimus measurements. This study aimed at simultaneously evaluating the analytical performances of 4 such immunoassays, using liquid chromatography-tandem mass spectrometry (LC-MS/MS) as a standard. For the first time, cross-reactivity to tacrolimus metabolites was assessed at concentrations frequently observed in clinical settings, as opposed to the higher concentrations tested by assay manufacturers.

METHODS

An affinity column-mediated immunoassay (ACMIA), using upgraded flex reagents; released in 2015, a chemiluminescence immunoassay (CLIA), an electrochemiluminescence immunoassay (ECLIA), and a latex agglutination turbidimetric immunoassay (LTIA) were evaluated using frozen whole blood samples collected from transplantation patients. Cross-reactivities to 3 major tacrolimus metabolites (13-O-demethyl-tacrolimus [M-I], 31-O-demethyl-tacrolimus [M-II], and 15-O-demethyl-tacrolimus [M-III]) were evaluated.

RESULTS

Each immunoassay correlated well with LC-MS/MS, and the Pearson's correlation coefficients (R) were 0.974, 0.977, 0.978, and 0.902 for ACMIA, CLIA, ECLIA, and LTIA, respectively. Using Bland-Altman difference plots to compare the immunoassays with LC-MS/MS, the calculated average biases were -6.73%, 6.07%, 7.46%, and 12.27% for ACMIA, CLIA, ECLIA, and LTIA, respectively. The cross-reactivities of ACMIA to the tacrolimus metabolites M-II and M-III were 81% and 78%, respectively, when blood was spiked at 2 ng/mL, and 94% and 68%, respectively, when it was spiked at 5 ng/mL.

CONCLUSIONS

Each immunoassay was useful, but had its own characteristics. ACMIA cross-reactivities to M-II and M-III were much higher than the respective 18% and 15% reported on its package insert, suggesting that cross-reactivity should be examined at clinically relevant concentrations.

A Nucleic Acid Nanostructure Built through On-Electrode Ligation for Electrochemical Detection of a Broad Range of Analytes

For an assay to be most effective in point-of-care clinical analysis, it needs to be economical, simple, generalizable, and free from tedious workflows. While electrochemistry-based DNA sensors reduce instrumental costs and eliminate complicated procedures, there remains a need to address probe costs and generalizability, as numerous probes with multiple conjugations are needed to quantify a wide range of biomarkers. In this work, we have opened a route to circumvent complicated multiconjugation schemes using enzyme-catalyzed probe construction directly on the surface of the electrode. With this, we have created a versatile DNA nanostructure probe and validated its effectiveness by quantification of proteins (streptavidin, anti-digoxigenin, anti-tacrolimus) and small molecules (biotin, digoxigenin, tacrolimus) using the same platform. Tacrolimus, a widely prescribed immunosuppressant drug for organ transplant patients, was directly quantified with electrochemistry for the first time, with the assay range matching the therapeutic index range. Finally, the stability and sensitivity of the probe was confirmed in a background of minimally diluted human serum.

Tacrolimus: A Review of Laboratory Detection Methods and Indications for Use

Tacrolimus (Tac) is an immunosuppressive drug that is used in preventing organ and tissue rejection in patients after transplantation. Tac administration requires frequent and diligent monitoring by physicians to ensure proper dosage and to limit the potential for harmful adverse effects, which can include renal damage, neurotoxicity, and other serious adverse events. Tac is a calcineurin inhibitor, which suppresses the function of T-cells. Its success as an immunosuppressive agent has been well documented in preventing graft-vs-host disease in several types of organ transplants. This literature review will discuss Tac metabolism and its role in preventing tissue and organ transplant rejection. A variety of detection techniques used in the clinical laboratory, including dried-blood-spot analysis, liquid chromatography-tandem mass spectrometry, and immunoassay also will be discussed.

Performance of the Dimension TAC assay and comparison of multiple platforms for the measurement of tacrolimus

BACKGROUND

Therapeutic monitoring of tacrolimus is essential for reducing organ rejection and adverse effects. The measurement of tacrolimus in whole blood is taken by many automated platforms. We evaluated the analytical performance of the Dimension TAC assay, which is an upgraded reagent from the previous Dimension TACR assay.

METHODS

The evaluations involved determination of precision, linearity, detection capability, and reagent lot-to-lot variability between three lot numbers. Correlation studies were conducted using the Dimension TACR assay, Architect, Elecsys assay, and MassTrak LC-MS/MS.

RESULTS

The total coefficient of variation was below 10%. Acceptable linearity was observed in their respective reportable ranges. The limit of blank, limit of detection, and limit of quantification were 0.29, 0.47, and 0.81 ng/mL, respectively. Correlation analysis indicated that the Dimension TAC assay results were comparable to that of the Dimension TACR assay, Architect, and Elecsys results in liver and heart transplant patients. In kidney transplant patients, the Dimension TAC assay showed the poor correlation with Architect and Elecsys. The results from these assays were slightly higher than that of MassTrak. We found little lot-to-lot reagent variation among the reagents evaluated.

CONCLUSION

The overall analytical performance of the Dimension TAC assay is acceptable for therapeutic monitoring in clinical practice. Our study that compared different platforms may provide some useful information regarding which test method to use.