The First Asian Kidney Transplantation Prediction Models for Long-term Patient and Allograft Survival

Assessing survival post-kidney transplantation in Australia: A multivariable prediction model

AIM

Kidney transplantation remains the preferred standard of care for patients with kidney failure. Most patients do not access this treatment and wide variations exist in which patients access transplantation. We sought to develop a model to estimate post-kidney transplant survival to inform more accurate comparisons of access to kidney transplantation.

METHODS

Development and validation of prediction models using demographic and clinical data from the Australia and New Zealand Dialysis and Transplant Registry. Adult deceased donor kidney only transplant recipients between 2000 and 2020 were included. Cox proportional hazards regression methods were used with a primary outcome of patient survival. Models were evaluated using Harrell's C-statistic for discrimination, and calibration plots, predicted survival probabilities and Akaike Information Criterion for goodness-of-fit.

RESULTS

The model development and validation cohorts included 11 302 participants. Most participants were male (62.8%) and Caucasian (79.2%). Glomerulonephritis was the most common cause of kidney disease (45.6%). The final model included recipient, donor, and transplant related variables. The model had good discrimination (C-statistic, 0.72; 95% confidence interval (CI) 0.70-0.74 in the development cohort, 0.70; 95% CI 0.67-0.73 in the validation cohort and 0.72; 95% CI 0.69-0.75 in the temporal cohort) and was well calibrated.

CONCLUSION

We developed a statistical model that predicts post-kidney transplant survival in Australian kidney failure patients. This model will aid in assessing the suitability of kidney transplantation for patients with kidney failure. Survival estimates can be used to make more informed comparisons of access to transplantation between units to better measure equity of access to organ transplantation.

Cellular immune response of SARS-CoV-2 vaccination in kidney transplant recipients: a systematic review and meta-analysis

Background

Evidence has demonstrated inferior humoral immune responses after SARS-CoV-2 vaccination in kidney transplant recipients compared to the general population. However, data on cellular immune responses in this population have not been established.

Methods

We searched the MEDLINE, Scopus, and Cochrane databases and included studies reporting cellular immune response rates in kidney transplant recipients after receiving SARS-CoV-2 vaccines. Studies that reported factors associated with cellular immune responders or non-responders were also included (PROSPERO: CRD42022375544).

Results

From a total of 1,494 articles searched, 53 articles were included in the meta-analysis. In all, 21 studies assessed cellular immune response by interferon-γ enzyme-linked immunosorbent spot (IFN-γ ELISPOT), 22 studies used interferon-γ release assay (IGRA), and 10 studies used flow cytometric analysis. The pooled response rate after two doses (standard regimen) and three doses of vaccination was 47.5% (95%CI 38.4-56.7%) and 69.1% (95%CI 56.3-80.6%) from IFN-γ ELISPOT, 25.8% (95%CI 19.7-32.4%) and 14.7% (95%CI 8.5-22.2%) from IGRA, and 73.7% (95%CI 55.2-88.8%) and 86.5% (95%CI 75.3-94.9%) from flow cytometry, respectively. Recipients with seroconversion were associated with a higher chance of having cellular immune response (OR 2.58; 95%CI 1.89-3.54). Cellular immune response in kidney transplant recipients was lower than in dialysis patients (OR 0.24; 95%CI 0.16-0.34) and the general population (OR 0.10; 95%CI 0.07-0.14). Age and immunosuppressants containing tacrolimus or corticosteroid were associated with inferior cellular immune response.

Conclusion

Cellular immune response after SARS-CoV-2 vaccination in kidney transplant recipients was lower than in dialysis patients and the general population. Age, tacrolimus, and corticosteroid were associated with poor response. Cellular immune response should also be prioritized in vaccination studies.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42022375544.

Bacterial Urinary Tract Infection and Early Asymptomatic Bacteriuria in Kidney Transplantation Still Negatively Affect Kidney Transplant Outcomes in the Era of Modern Immunosuppression and Cotrimoxazole Prophylaxis

Risk factors and consequences of urinary tract infection (UTI) post-kidney transplant have been variously reported by studies that were heterogenous in immunosuppressants and prophylactic protocols. We aimed to clarify the risks and consequences of UTI in kidney transplant recipients with post-transplantation cotrimoxazole prophylaxis in the context of modern immunosuppression. This retrospective cohort included kidney transplant recipients receiving tacrolimus, mycophenolate, prednisolone, and cotrimoxazole for bacterial UTI prophylaxis. Recipients were categorized into non-UTI and UTI groups. Asymptomatic bacteriuria (ASB) was screened in the first 3 months and was evaluated for association with UTI. Of 348 kidney transplant recipients, 129 were in the UTI group and 219 in the non-UTI group. UTI risk factors were female sex, body mass index ≥ 25 kg/m², human leukocyte antigen mismatch, and panel reactive antibody ≥ 50%. Recipients with recurrent UTI had inferior allograft function compared with non-UTI recipients. Patient survival was significantly lower in recipients with UTI in the first post-transplant month. Higher degree of immunosuppressions was associated with recurrent UTI and drug-resistant organisms. In conclusion, UTI continues to negatively affect graft function and survival of kidney transplant recipients. Treating ASB in the first 3 months did not reduce the UTI incidence in the first transplantation year.

Individual dynamic prediction and prognostic analysis for long-term allograft survival after kidney transplantation

Background

Predicting allograft survival is vital for efficient transplant success. With dynamic changes in patient conditions, clinical indicators may change longitudinally, and doctors’ judgments may be highly variable. It is necessary to establish a dynamic model to precisely predict the individual risk/survival of new allografts.

Methods

The follow-up data of 407 patients were obtained from a renal allograft failure study. We introduced a landmarking-based dynamic Cox model that incorporated baseline values (age at transplantation, sex, weight) and longitudinal changes (glomerular filtration rate, proteinuria, hematocrit). Model performance was evaluated using Harrell’s C-index and the Brier score.

Results

Six predictors were included in our analysis. The Kaplan–Meier estimates of survival at baseline showed an overall 5-year survival rate of 87.2%. The dynamic Cox model showed the individual survival prediction with more accuracy at different time points (for the 5-year survival prediction, the C-index = 0.789 and Brier score = 0.065 for the average of all time points) than the static Cox model at baseline (C-index = 0.558, Brier score = 0.095). Longitudinal covariate prognostic analysis (with time-varying effects) was performed.

Conclusions

The dynamic Cox model can utilize clinical follow-up data, including longitudinal patient information. Dynamic prediction and prognostic analysis can be used to provide evidence and a reference to better guide clinical decision-making for applying early treatment to patients at high risk.

Using Information Available at the Time of Donor Offer to Predict Kidney Transplant Survival Outcomes: A Systematic Review of Prediction Models

Statistical models that can predict graft and patient survival outcomes following kidney transplantation could be of great clinical utility. We sought to appraise existing clinical prediction models for kidney transplant survival outcomes that could guide kidney donor acceptance decision-making. We searched for clinical prediction models for survival outcomes in adult recipients with single kidney-only transplants. Models that require information anticipated to become available only after the time of transplantation were excluded as, by that time, the kidney donor acceptance decision would have already been made. The outcomes of interest were all-cause and death-censored graft failure, and death. We summarised the methodological characteristics of the prediction models, predictive performance and risk of bias. We retrieved 4,026 citations from which 23 articles describing 74 models met the inclusion criteria. Discrimination was moderate for all-cause graft failure (C-statistic: 0.570–0.652; Harrell’s C: 0.580–0.660; AUC: 0.530–0.742), death-censored graft failure (C-statistic: 0.540–0.660; Harrell’s C: 0.590–0.700; AUC: 0.450–0.810) and death (C-statistic: 0.637–0.770; Harrell’s C: 0.570–0.735). Calibration was seldom reported. Risk of bias was high in 49 of the 74 models, primarily due to methods for handling missing data. The currently available prediction models using pre-transplantation information show moderate discrimination and varied calibration. Further model development is needed to improve predictions for the purpose of clinical decision-making.

Systematic Review Registration:https://osf.io/c3ehp/l.

Dominant predictors of early post-transplant outcomes based on the Korean Organ Transplantation Registry (KOTRY)

Data for Asian kidney transplants are very limited. We investigated the relative importance of prognostic markers in Asian kidney transplants by using Korean Organ Transplantation Registry (KOTRY) cohort. Prediction models were developed by data-driven variable selection approach. The relative importance of the selected predictors was measured by dominance analysis. A total of 4854 kidney transplant donor-recipient pairs were analyzed. Overall patient survival rates were 99.8%, 98.8%, and 91.8% at 1, 3, and 5 years, respectively. Death-censored graft survival rates were 98.4%, 97.0%, and 95.8% at 1, 3, and 5 years. Biopsy-proven acute rejection free survival rates were 90.1%, 87.4%, and 87.03% at 1, 3, and 5 years. The top 3 dominant predictors for recipient mortality within 1 year were recipient cardiovascular disease history, deceased donor, and recipient age. The dominant predictors for death-censored graft loss within 1 year were acute rejection, deceased donor, and desensitization. The dominant predictors to acute rejection within 1 year were donor age, HLA mismatched numbers, and desensitization. We presented clinical characteristics of patients enrolled in KOTRY during the last 5 years and investigated dominant predictors for early post-transplant outcomes, which would be useful for clinical decision-making based on quantitative measures.

First Asian Kidney Donor Profile Index (KDPI) and Estimated Post-Transplant Survival (EPTS) Models, With Validation Against US Models in Thai Population

INTRODUCTION

Differences in transplant characteristics limit the application of kidney donor profile index (KDPI) and estimated post-transplant survival (EPTS) models developed in Western countries to Asian populations.

METHODS

We analyzed data of the Thai Transplant Registry and the Thai Red Cross Society on 2,558 DDKTs performed between 2001 and 2014. Thai KDPI and EPTS models were developed using Cox regression, and validation against the US models.

RESULTS

Thai KDPI was developed based on 7 donor factors: age, height, best estimated glomerular filtration rate, diabetes mellitus, hypertension, cerebrovascular accident, and adrenaline infusion. The Thai and US donor risk index had comparable predictive abilities for transplant survival (C-statistics 0.5871 vs 0.5548; P = 0.429). KTs from donors with a US KDPI > 70% demonstrated significantly worse 5-year transplant survival. The Thai EPTS model was developed from 4 recipient factors: age, body weight, diabetes mellitus, and hepatitis C infection. The C-statistics of the Thai and US EPTS models were comparable (0.5924 vs 0.6039; P = 0.360). A US EPTS > 70% was revealed in only 2.5% of our cohort.

CONCLUSIONS

The first simplified KDPI and EPTS models for an Asian population were developed. Our models are available at www.thai-kdpi-epts.org. This article is protected by copyright. All rights reserved.

Evaluation of Salivary Indoxyl Sulfate with Proteinuria for Predicting Graft Deterioration in Kidney Transplant Recipients

Acute kidney injury (AKI) is a significant risk factor for developing chronic kidney disease and progression to end-stage renal disease in elderly patients. AKI is also a relatively common complication after kidney transplantation (KTx) associated with graft failure. Since the lifespan of a transplanted kidney is limited, the risk of the loss/deterioration of graft function (DoGF) should be estimated to apply the preventive treatment. The collection of saliva and urine is more convenient than collecting blood and can be performed at home. The study aimed to verify whether non-invasive biomarkers, determined in saliva and urine, may be useful in the prediction of DoGF in kidney transplant recipients (KTRs) (n = 92). Salivary and serum toxins (p-cresol sulfate, pCS; indoxyl sulfate, IS) concentrations were determined using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Urinary proteins, hemoglobin, and glucose were measured using a semi-quantitative strip test. Salivary IS (odds ratio (OR) = 1.19), and proteinuria (OR = 3.69) were demonstrated as independent factors for the prediction of DoGF. Satisfactory discriminatory power (area under the receiver operating characteristic curve (AUC) = 0.71 ± 0.07) and calibration of the model were obtained. The model showed that categories of the increasing probability of the risk of DoGF are associated with the decreased risk of graft survival. The non-invasive diagnostic biomarkers are a useful screening tool to identify high-risk patients for DoGF.

A systematic review and meta-analysis of enzyme-linked immunosorbent spot (ELISPOT) assay for BK polyomavirus immune response monitoring after kidney transplantation

BK virus (BKV) infection after kidney transplantation can cause BKV nephropathy (BKVAN) resulting in graft dysfunction and allograft loss. The treatment for BKVAN is reduction of the immunosuppressive load which increases the risk of kidney transplant rejection. There is no biomarker to monitor BKV activity besides BK viral load. The value of the Enzyme-Linked Immunosorbent Spot (ELISPOT) assay as a tool to monitor the recipient's anti-BKV immune response after transplantation was investigated systematically. Electronic databases, including MEDLINE, Scopus, and the Cochrane Central Register of Controlled Trials were searched for studies of ELISPOT evaluating the immune response against BKV. BKV status was categorized as "active BKV infection" and as "resolving BKV infection". Random-effects model meta-analysis was performed to determine the diagnostic performance of the ELISPOT assay, after stratifying patients into groups based on positive and negative ELISPOT results. One-hundred twenty-seven articles were identified of which nine were included. Patients with negative ELISPOT had an increased risk of having active BKV replication (odds ratio of 71.9 (95%-CI 31.0-167.1). Pooled sensitivity was 0.95 (95%-CI 0.89-0.98) and specificity was 0.88 (95%-CI 0.78-0.94). The standardized mean difference of the number of IFN-γ producing cells between patients with active BKV infection compared with patients who had resolving BKV infection was -2.09 (95%-CI -2.50, -1.68). The ELISPOT assay is a useful tool for BKV risk assessment and in combination with BKV load may support clinicians in guiding immunosuppressive therapy in patients with BKV replication.

Donor-specific ELISPOT assay for predicting acute rejection and allograft function after kidney transplantation: A systematic review and meta-analysis

Acute rejection remains an important problem after kidney transplantation. Enzyme-linked immunosorbent spot (ELISPOT) assay has been investigated extensively and has shown promising results as a predictor of allograft rejection. The objective of this study was to systematically review and analyze the predictive value of the donor-specific ELISPOT assay to identify recipients at risk for acute rejection. Electronic databases were searched for studies reporting donor-specific ELISPOT and kidney transplantation outcomes. Odds ratio (OR) for acute rejection was calculated, along with standardized mean difference (SMD) of cytokine producing-cells between recipients with and without acute rejection. Pooled estimates were calculated using random-effect models. The positive ELISPOT cutoff frequencies were extracted from each study. From 665 articles found, 32 studies were included in the meta-analysis. IFN-γ was the most investigated cytokine (30 out of 32 studies). Patients with positive pre-transplantation donor-reactive IFN-γ ELISPOT had an OR of 3.3 for acute rejection (95%-CI 2.1 to 5.1), and OR of 6.8 (95%-CI 2.5 to 18.9) for post-transplantation ELISPOT. Recipients with rejection had significantly higher frequencies of pre- and post-transplantation cytokine producing-cells (SMD 0.47, 95%-CI 0.07 to 0.87 and SMD 3.68, 95%-CI 1.04 to 6.32, respectively). Pre-transplantation ELISPOT had a positive predictive value of 43% and a negative predictive value of 81% for acute rejection. A positive ELISPOT result was associated with a lower estimated glomerular filtration rate (SMD -0.59, 95%-CI -0.83 to -0.34). In conclusion, patients with a high frequency of donor-reactive IFN-γ ELISPOT are at higher risk for acute rejection. The donor-specific IFN-γ ELISPOT assay can serve as an immune-monitoring tool in kidney transplantation.