METHODS: In this 24-month, open-label study, de novo kidney transplant recipients (KTxRs) were randomized (1:1) to receive EVR+rCNI or MPA+sCNI, along with induction therapy and corticosteroids.
RESULTS: Of the 2037 patients randomized in the TRANSFORM study, 293 were Asian (EVR+rCNI, N = 136; MPA+sCNI, N = 157). At month 24, EVR+rCNI was noninferior to MPA+sCNI for the binary endpoint of estimated glomerular filtration rate (eGFR) Graft loss and death were reported for one patient each in both arms. Mean eGFR was higher in EVR+rCNI versus MPA+sCNI (72.2 vs. 66.3 ml/min/1.73 m2 , P = .0414) even after adjusting for donor type and donor age (64.3 vs. 59.3 ml/min/1.73 m2 , P = .0582). Overall incidence of adverse events was comparable. BK virus (4.4% vs. 12.1%) and cytomegalovirus (4.4% vs. 13.4%) infections were significantly lower in the EVR+rCNI arm.
CONCLUSION: This subgroup analysis in Asian de novo KTxRs demonstrated that the EVR+rCNI versus MPA+sCNI regimen provides comparable antirejection efficacy, better renal function, and reduced viral infections (NCT01950819).
METHODS: Medical records of renal transplant patients at Penang General Hospital were retrospectively analyzed. A time-dissociated PKPD model with covariate effects was developed using NONMEM to evaluate renal graft function response, quantified as estimated glomerular filtration rate (eGFR), toward the cyclosporine cumulative exposure (area under the concentration-time curve). The final model was integrated into a tool to predict the potential outcome. Individual eGFR predictions were evaluated based on the clinical response recorded as acute rejection/nephrotoxicity events.
RESULTS: A total of 1256 eGFR readings with 2473 drug concentrations were obtained from 107 renal transplant patients receiving cyclosporine. An Emax drug effect with a linear drug toxicity model best described the data. The baseline renal graft level (E0), maximum effect (Emax), area under the concentration-time curve achieving 50% of the maximum effect, and nephrotoxicity slope were estimated as 12.9 mL·min-1·1.73 m-2, 50.7 mL·min-1·1.73 m-2, 1740 ng·h·mL-1, and 0.00033, respectively. The hemoglobin level was identified as a significant covariate affecting the E0. The model discerned acute rejection from nephrotoxicity in 19/24 cases.
CONCLUSIONS: A time-dissociated PKPD model successfully described a large number of observations and was used to develop an online tool to predict renal graft response. This may help discern early rejection from nephrotoxicity, especially for patients unwilling to undergo a biopsy or those waiting for biopsy results.
METHODS: We conducted a case-control study comparing 25 patients with biopsy-proven LACR against 25 stable controls matched for age group, primary diagnosis and time post-transplant. IPV was calculated using coefficient of variance (CV) and mean absolute deviation (MAD) using tacrolimus levels in the preceding 12 months. We also assessed the percentage time for tacrolimus levels
METHODOLOGY: This is a retrospective cohort study recruiting all kidney transplant recipients in South Australia from January 2010 till December 2018. Following that, the incidence of blood transfusion within one week post-operatively were traced (transfusion group). The outcomes were compared with all other transplant recipients (non-transfusion group). Recipient's demographic, donor characteristics and immunological risk profiles were obtained from the transplant unit database, while the biopsy report, history of blood transfusion, latest serum creatinine and follow-up status was gathered from the electronic medical system (OASIS). The HLA-DSA and HLA-Ab results were collected from the NOMS database. Finally, the survival data were merged with the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry for South Australia recipients graft survival.
RESULTS: A total of 699 patients were eligible for analysis. The mean age was 50.64 ± 13.23 years old. There were more elderly (>65 years old) and females who needed transfusion. The majority had glomerulonephritis as the primary disease. There was no statistical difference in donor characteristics, cold ischemic time and immunological risk between the transfusion and non-transfusion group. There was no difference in the development of de novo HLA-DSA, HLA-Ab and rejection episodes between the group and the results were consistent in a model adjusted for all potential confounders. Median graft survival in days between the transfusion vs non-transfusion group was 1845 IQR (961,2430) and 1250 IQR (672,2013).
CONCLUSION: Blood transfusion under strong immunosuppressive cover within a one-week post-operative period is safe with no significant association with the development of de novo HLA-DSA, HLA-Ab or clinical rejection.
METHODOLOGY: All sera for AT1R-Ab were collected at the University Malaya Medical Centre (UMMC), Kuala Lumpur, Malaysia. The sera were centrifuged and kept refrigerated at -80 °C before being transported to the South Australian Transplantation and Immunogenetics Laboratory (SATIS). Enzyme-linked immunosorbent assay kit (One Lambda) was used for the detection of AT1R-Ab, and it was performed according to the manufacturer's instructions. The level of >17.1 U/mL was considered to be AT1R-Ab positive; 10.0-17.1 U/mL at risk, and <10.0 U/mL negative.
RESULTS: A total of 115 samples were collected from 99 patients pre and post-kidney transplant recipients. From the pre-transplant sera (n = 68) 17.7% were positive, 35.3% were at risk and 47.0% were negative. The positive AT1R-Ab cohort were relatively younger, with a mean age of 34.7 ± 8.3 years old and statistically significant, with a p-value of 0.028. Among the sera that were tested positive, 19.0% were from the Chinese ethnicity, 6.7% from Malay and 16.7% from Indian. There was no difference in the rejection episodes, persistent or de novo HLA-DSA, and graft function between the group (AT1R-Ab negative vs AT1R-Ab at risk and positive) and the results were consistent in a model adjusted for all potential confounders.
CONCLUSION: The prevalence of positive (>17.1 U/mL) pre-transplant AT1R-Ab was 17.7% and 35.3% were at risk (10.0-17.1 U/mL) in our pre-transplant cohort.