Average Tacrolimus Trough Level in the First Month After Transplantation May Predict Acute Rejection

Infections in the first year of living related kidney transplantation in a young transplant cohort

BACKGROUND

Infection after a kidney transplant is a serious cause of morbidity and mortality. Weighing the risks and benefits of immunosuppression is of paramount importance for patient wellbeing and transplant survival.

METHODS

This is a prospective observational study exploring the variety of bacterial, viral and fungal infections occurring within the first year of living related kidney transplantation in a young transplant cohort. Fifty-one kidney transplant recipients (KTR) between the age of 18 and 45 who had a kidney transplant between Jan 2020 and Jan 2022 were enrolled and followed up for one year. Primary outcome was the occurrence of infection.

RESULTS

Twenty-four patients (47%) recorded a collective 33 episodes of infection. Seven patients had repeated infections and 17 had single infections. Twenty-seven patients had an uneventful year with no infections recorded. Commonest infection was lower urinary tract infection (UTI) (27.3%) followed by SARS-COV2 and Herpes Zoster (15.2%). The commonest pathogens causing lower UTI were Escherichia coli (E coli) (21.2%) and Klebsiella (18.2%). Median Tacrolimus level was (7.8) ng/ml in KTR with infection and (8.95) ng/ml in KTR without infection, p = 0.21. Median Haemoglobin (IQR) was (10.2) g/dl (7.8-14) gm/dl in KTR with infection compared to (10.8) g/dl (7.3-15.3) in KTR without infection odds ratio (OR) = 0.78, confidence interval (CI) (0.5-1.1); p = 0.16.In KTR with infection 25% had donors above the age of 60 compared to 11% in KTR without infection ( OR 2.6,CI (0.5-12), p = 0.2). Post transplant diabetes (PTDM) occurred in (25%) in KTR with infection compared to those without, but that was not statistically significant p = 0. 365.In KTR without infection, 59.3% had a preemptive transplant compared to 20.8% in the group with infection (OR = 0.18; 95% CI: 0.052-0.631; p = 0.007). Median tacrolimus was 7.8 ng/ml in KTR with single infection compared to 7.7 ng/ml in KTR with repeated infections.

CONCLUSION

This study shows that the commonest infection occurring in the first-year post kidney transplant was lower urinary tract infection followed by SARS-COV2 and Herpes Zoster. There was no difference in trough tacrolimus or haemoglobin levels between KTR who developed infection with those who did not.

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.

Effect of mycophenolic acid and tacrolimus on the incidence of infectious complications after kidney transplantation

INTRODUCTION

Infectious complications remain a common cause of mortality after kidney transplantation (KTx). Goal of effective immunosuppressive treatment (IS) must be balanced between decreasing incidence of acute kidney rejection (AKR) and avoiding the incidence of infections, at the same time.

MATERIALS AND METHODS

The aim of our analysis was to identify the risk of fixed daily dose (DD) of mycophenolic acid (MPA) and levels of tacrolimus (TAC) in the development of a single, recurrent infection and AKR after KTx.

RESULTS

Our analysis consisted of 100 patients after KTx (66 males, 34 females). MPA DD > 1080 mg was a risk factor (RF) for recurrent infection in general (OR 1.2964;P = 0.0277), for recurrent bacterial infection from 1^st to 6^th month (OR 1.2674;P = 0.0151), recurrent bacterial infection (OR 1.2574;P = 0.0436), single viral infection (OR 1.2640;P = 0.0398) from 6^th-12^th month after KTx. MPA DD > 1080 mg and levels of TAC above recommended levels were not independent RF for the incidence of the infection.

CONCLUSION

MPA DD > 1080 mg as a RF for recurrent infection starting in the 1^st month after KTx with significant association between the incidence of infections and MPA DD and TAC levels, without increased risk of AKR. In the centers with fixed dosing of IS, this can lead to lowering the risk of infections by decreasing MPA DD 1 month after KTx without increasing risk of infections.

Tacrolimus time-in-therapeutic range is associated with freedom from acute rejection and graft failure following intestinal transplantation

BACKGROUND

Trough-adjusted tacrolimus is commonly prescribed following intestinal transplantation to prevent allograft rejection. Despite established practice, there remains limited direct evidence linking tacrolimus levels with improved clinical outcomes.

METHODS

This was a single-center review of all adult non-liver containing intestinal allograft recipients from 2011 to 2018. Patients received lymphocyte depleting induction and maintenance immunosuppression consisting of tacrolimus and a corticosteroid taper. Tacrolimus time-in-therapeutic range (TAC-TTR) was calculated for all patients from the date of transplant until 1-year post-transplant using Rosendaal's method. Cox-Proportional hazards modeling was utilized to assess freedom from acute rejection and graft failure stratified by TAC-TTR quartile.

RESULTS

47 patients were included in the review. Mean TAC-TTR for the cohort was 30.2% ± 11.4. Fifteen episodes of acute rejection were observed, 8 of which were severe. Patients in the highest TAC-TTR quartile >36% had a lower incidence of acute rejection and graft failure relative to patients with a TAC-TTR <20%. Cox-Proportional hazards modeling found a 10% decrease in TAC-TTR was associated with an increased hazard for acute rejection (2.03), severe acute rejection (2.19), and graft loss (3.33).

CONCLUSION

The results of this study suggest that decreasing TAC-TTR is a risk factor for both acute rejection as well as intestinal allograft failure.

BK Polyomavirus Nephropathy in Kidney Transplantation: Balancing Rejection and Infection

BK polyomavirus nephropathy (BKVN) and allograft rejection are two closely-associated diseases on opposite ends of the immune scale in kidney transplant recipients. The principle of balancing the immune system remains the mainstay of therapeutic strategy. While patient outcomes can be improved through screening, risk factors identification, and rapid reduction of immunosuppressants, a lack of standard curative therapy is the primary concern during clinical practice. Additionally, difficulty in pathological differential diagnosis and clinicopathology’s dissociation pose problems for a definite diagnosis. This article discusses the delicate evaluation needed to optimize immunosuppression and reviews recent advances in molecular diagnosis and immunological therapy for BKVN patients. New biomarkers for BKVN diagnosis are under development. For example, measurement of virus-specific T cell level may play a role in steering immunosuppressants. The development of cellular therapy may provide prevention, even a cure, for BKVN, a complex post-transplant complication.

CYP and SXR gene polymorphisms influence in opposite ways acute rejection rate in pediatric patients with renal transplant

Background

We evaluated the role of CYP3A5, ABCB1 and SXR gene polymorphisms in the occurrence of acute kidney rejection in a cohort of pediatric renal transplant recipients.

Methods

Forty-nine patients were genotyped for CYP3A5, ABCB1 and SXR polymorphisms and evaluated with tacrolimus through levels in a retrospective monocenter study.

Results

Patients with the A allele of CYP3A5 treated with tacrolimus had a higher risk of acute rejection than those without the A allele, while patients carrying the homozygous GG variant for SXR A7635GG did not show any episode of acute rejection.

Conclusion

Genetic analysis of polymorphisms implicated in drug metabolism and tacrolimus trough levels may help to forecast the risk of acute rejection and individualize drug dosage in children undergoing renal transplantation.

Non-linear Relationship between Tacrolimus Blood Concentration and Acute Rejection After Kidney Transplantation: A Systematic Review and Dose-Response Meta-Analysis of Cohort Studies

BACKGROUND

Maintaining the exposure of tacrolimus (Tac) after kidney transplantation (KT) must be necessary to prevent acute rejection (AR) and improve graft survival，but there is still no clear consensus on the optimal Tac target blood concentration and concentration-effect relationship is poorly defined.

METHODS

We conducted a dose-response meta-analysis to quantitatively assess the association between Tac blood concentration and (AR) or adverse effects after KT. A comprehensive search of PubMed, Embase and Cochrane library databases was conducted to find eligible studies up to 10th September 2018. Unpublished data from patients receiving KT in West China Hospital (Sichuan University, China) were also collected. Both twostage dose-response and one-stage dose-response meta-analysis models were used to improve the statistical power.

RESULTS

A total of 4967 individuals from 10 original studies and 1453 individuals from West China Hospital were eligible for the ultimate analysis. In the two-stage dose-response meta-analysis model, we observed a significant non-linear relationship between Tac blood concentration and AR (P < 0.001) with moderate heterogeneity (I2 = 46.0%, P = 0.08). Tac blood concentration at 8ng/ml was associated with the lowest risk of AR (RR: 0.26, 95%CI: 0.13 - 0.54) by reference to 2ng/ml. Tac concentration at 7.0 - 11.0 ng/ml reduced the risk of AR by at least 70%, 5-14 ng/ml by at least 60%, and 4.5 - 14 ng/ml at least 50%. In the one-stage dose-response model, we also found a strong non-linear relationship between Tac and AR (P < 0.001) with moderate heterogeneity (I2 = 41.2%, P = 0.10). Tac concentration of 7.5 ng/ml was associated with the lowest risk of AR (RR: 0.35, 95%CI: 0.16 - 0.77). The blood concentration at 5.5 - 9.5 ng/ml was associated with the reduced AR by at least 60% and 4.5 - 10.5 ng/ml by at least 50% by reference to 2 ng/ml.

CONCLUSION

Maintaining Tac blood concentration at 5 - 9.5 ng/ml within the first year may prevent AR most effectively.

Tacrolimus Trough Level at the First Month May Predict Renal Transplantation Outcomes Among Living Chinese Kidney Transplant Patients: A Propensity Score-Matched Analysis

Supplemental Digital Content is Available in the Text.

Background:

Monitoring and maintaining a stable tacrolimus trough level is essential because of its narrow therapeutic window and considerable fluctuation in the early phase after kidney transplantation. However, optimal tacrolimus exposure early after transplantation remains unclear among Chinese patients.

Methods:

In this propensity score–matched cohort study, we thoroughly investigated the association between tacrolimus trough level at the first month and acute rejection (AR) as well as infection within the first year after kidney transplantation.

Results:

In a first step, a total of 1415 patients were divided into 3 groups according to the receiver operating characteristic curve: low-level group (410 patients with a tacrolimus trough level <5.35 ng/mL at the first month), median-level group (466 patients with a tacrolimus trough level from 5.35 to 7.15 ng/mL), and high-level group (539 patients with a tacrolimus trough level >7.15 ng/mL). Ultimately, 363 and 459 pairs of cases were enrolled by using 2 propensity score matches between low- and median-level groups and between high- and median-level groups, respectively. Compared with patients in the low-level group, patients in the median-level group had lower risk of AR without increased incidence of infection (AR, 12.4% versus 5.7%, P = 0.02; infection, 13.2% versus 13.2%, P = 1.00 for low- and median-level groups, respectively) within the first year. Compared with patients in the high-level group, patients in the median-level group had lower incidence of infection without the growing risk of AR (infection, 17.6% versus 12.2%, P = 0.021; AR, 4.6% versus 5.4%, P = 0.545 for high- and median-level groups, respectively) within the first year. Multilogistic analysis showed that tacrolimus trough levels were an independent factor for AR (odds ratio, 0.749, 95% confidence interval, 0.632–0.888, P = 0.001). Tacrolimus trough levels were also associated with infection (odds ratio 1.110, 95% confidence interval, 1.013–1.218, P = 0.001). Serum creatinine levels were similar among groups. No difference was found in 1-, 3-, and 5-year graft survival and patient survival among groups.

Conclusions:

The tacrolimus trough level maintained between 5.35 and 7.15 ng/mL at the first posttransplant month may prevent AR without increasing the incidence of infection within the first year after living kidney transplantation among Chinese patients.

Acute Rejection in Kidney Transplantation and Early Beginning of Tacrolimus

BACKGROUND

Although tacrolimus is an effective immunosuppressive drug used for preventing biopsy proven acute rejection (BPAR) in kidney transplanted patients, its nephrotoxicity may compromise renal function and lead to delayed initiation because of its side effects. This study aimed to evaluate the safety of early initiation of tacrolimus in the occurrence of BPAR during the first 90 days post transplant.

METHODS

We conducted a retrospective cohort study involving 315 patients who underwent kidney transplantation from 2015 to 2017. Comparisons were performed between 2 groups according to whether the start time of tacrolimus therapy was delayed or not delayed. Cox proportional hazards models were used to examine the association between variables and the occurrence of BPAR.

RESULTS

The incidence of BPAR was 14.9% (n = 47) and it was significantly higher in the delayed group (19.4% vs 6.4%; P = .002). Delayed initiation tacrolimus group was significantly associated with the risk of BPAR (hazard ratio: 2.95; P < .036). The overall mortality rate was 2.5% (n = 8) and there was no association between delayed initiation therapy and death (P = .56).

CONCLUSION

Our study confirmed that delayed initiation of tacrolimus in patients with delayed graft function is associated with a high risk of BPAR.

Long-term Clinical Significance of Tacrolimus Trough Level at the Early Period After Kidney Transplantation

BACKGROUND

The stable immunosuppressant level at the early period after kidney transplantation (KT) is one of the most important factors for the prognosis of KT. However, the extent of immunosuppression varies according to the policies of each KT center. We investigated the relationship between the clinical outcome and tacrolimus trough level (TTL) at the early post-transplant period.

MATERIALS AND METHODS

We retrospectively analyzed medical records of patients who underwent KT between July 2007 and June 2016. We investigated TTLs at 3 months after KT. We evaluated the incidence of biopsy-proven acute rejection (BPAR), cytomegalovirus infection, and graft survival according to the TTLs.

RESULTS

A total of 426 patients who received KT during the study period were enrolled. The mean age of KT recipients was 46.3 ± 11.5 years, and 55.5% of patients were men. The incidence of BPAR within 1 year after KT was significantly higher when TTLs at 3 months were less than 4.0 ng/mL (P = .020). Death-censored graft survival rates were significantly lower in KT recipients with BPAR and TTL less than 4.0 ng/mL (P < .001, P < .001, respectively). In multivariate analysis, BPAR and TTL less than 4.0 ng/mL at 3 months after KT were independent risk factors for graft failure.

CONCLUSION

BPAR and TTL less than 4.0 ng/mL at 3 months after KT are important risk factors for allograft failure. Therefore, TTL should be kept at least 4.0 ng/mL or more at 3 months after KT to reduce the incidence of BPAR within 1 year after KT.

Risk factors and etiology of repeat infection in kidney transplant recipients

Kidney transplantation (KT) is the best therapy available for patients with end-stage renal disease, but postoperative infections are a significant cause of mortality.In this retrospective study the frequency, risk factors, causative pathogens, and clinical manifestations of infection in KT recipients from Beijing Chao-Yang Hospital, Capital Medical University were investigated. Ninety-seven KT recipients who were hospitalized with infection between January 2010 and December 2016 were included. Clinical characteristics, surgery details, laboratory results, and etiology were compared in patients who developed single infection and patients who developed repeated infection (2 or more) after KT.A total of 161 infections were adequately documented in a total of 97 patients, of which 57 patients (58.8%) had 1 infection, 24 (24.7%) had 2, 11 (11.3%) had 3; 3 (3.1%) had 4, and 2 (2.1%) had 5 or more. The most common infection site was the urinary tract (90 infections; 56%), both overall and in the repeated infection group. The most frequently isolated pathogen was Pseudomonas aeruginosa. In the repeated infection patients, in most cases of P. aeruginosa infection (54%) it was cultured from urine. For first infections, a time between KT and infection of ≤ 21 days (area under receiver operating characteristic curve [AUC] 0.636) and a tacrolimus level ≥ 8 ng/mL (AUC 0.663) independently predicted repeat infection. The combination of these two predictive factors yielded an AUC of 0.716, which did not differ statistically significantly from either predictor alone.With regard to first infections after KT, a time between KT and infection of ≤ 21 days, and a tacrolimus level ≥ 8 ng/mL each independently predicted repeated infection in KT recipients.

Epidemiology, Risk Factors, and Outcomes After Early Posttransplant Clostridiodes difficile Infection in Renal Transplant Recipients

BACKGROUND

Modifiable risk-factors associated with Clostridioides difficile infection (CDI) in renal-transplant (RTX) have not been clearly established and peri-transplant risk has not been described.

OBJECTIVE

Evaluate epidemiology, risk-factors and outcomes after CDI occurring in the first 90 days after RTX (CDI-90).Methods: Observational cohort study/survival analysis of adult RTX recipients from 1/1/2012-12/31/2015. Primary outcome was CDI-90 incidence/risk-factors. Secondary outcome was evaluation of post-90 day transplant outcomes.

RESULTS

982 patients met inclusion criteria; 46 with CDI-90 and 936 without (comparator). CDI incidence in the total population was 4.7% at 90 days, 6.3% at 1 year, and 6.4% at 3 years. Incidence of CDI-90 was 5%; time to diagnosis was 19.4±25 days (median 7). Risk-factors for CDI-90 were alemtuzumab induction (Hazard ratio [HR] 1.5, 95% CI(1.1-2.0), p = 0.005) and age at transplant (HR 1.007/year, 95% CI (1.002-1.012), p= 0.007). However, risk-factors for CDI at any time were different; donation-after-circulatory-death (DCD) donor (HR 2.5 95% CI (1.3-4.9), p = 0.008) and female gender (HR 1.6 95% CI (1.0-2.7), p = 0.049). On Kaplan-Meier, CDI-90 appeared to have an impact on patient/graft survival, however when analyzed in a multivariable stepwise Cox proportional hazards model, only age was significantly associated with survival (p = 0.002).

CONCLUSION AND RELEVANCE

Incidence of CDI-90 is low, mostly occurring in the first post-operative month. Risk-factors vary temporally based on time from transplant. In the early post-op period induction agent and age at transplant are significant, but not after. Associations between CDI and negative graft outcomes appear to be largely driven by age. Future studies validating these risk-factors as well as targeted prophylaxis strategies and their effect on long term graft outcomes and the host microbiome are needed.