The elephant in the room: failings of current clinical endpoints in kidney transplantation

Endotrophin Levels Are Associated with Allograft Outcomes in Kidney Transplant Recipients

Early prediction of kidney graft function may assist clinical management, and for this, reliable non-invasive biomarkers are needed. We evaluated endotrophin (ETP), a novel non-invasive biomarker of collagen type VI formation, as a prognostic marker in kidney transplant recipients. ETP levels were measured with the PRO-C6 ELISA in the plasma (P-ETP) of 218 and urine (U-ETP/Cr) of 172 kidney transplant recipients, one (D1) and five (D5) days, as well as three (M3) and twelve (M12) months, after transplantation. P-ETP and U-ETP/Cr at D1 (P-ETP AUC = 0.86, p < 0.0001; U-ETP/Cr AUC = 0.70, p = 0.0002) were independent markers of delayed graft function (DGF) and P-ETP at D1 had an odds ratio of 6.3 (p < 0.0001) for DGF when adjusted for plasma creatinine. The results for P-ETP at D1 were confirmed in a validation cohort of 146 transplant recipients (AUC = 0.92, p < 0.0001). U-ETP/Cr at M3 was negatively associated with kidney graft function at M12 (p = 0.007). This study suggests that ETP at D1 can identify patients at risk of delayed graft function and that U-ETP/Cr at M3 can predict the future status of the allograft. Thus, measuring collagen type VI formation could aid in predicting graft function in kidney transplant recipients.

An automated histological classification system for precision diagnostics of kidney allografts

For three decades, the international Banff classification has been the gold standard for kidney allograft rejection diagnosis, but this system has become complex over time with the integration of multimodal data and rules, leading to misclassifications that can have deleterious therapeutic consequences for patients. To improve diagnosis, we developed a decision-support system, based on an algorithm covering all classification rules and diagnostic scenarios, that automatically assigns kidney allograft diagnoses. We then tested its ability to reclassify rejection diagnoses for adult and pediatric kidney transplant recipients in three international multicentric cohorts and two large prospective clinical trials, including 4,409 biopsies from 3,054 patients (62.05% male and 37.95% female) followed in 20 transplant referral centers in Europe and North America. In the adult kidney transplant population, the Banff Automation System reclassified 83 out of 279 (29.75%) antibody-mediated rejection cases and 57 out of 105 (54.29%) T cell-mediated rejection cases, whereas 237 out of 3,239 (7.32%) biopsies diagnosed as non-rejection by pathologists were reclassified as rejection. In the pediatric population, the reclassification rates were 8 out of 26 (30.77%) for antibody-mediated rejection and 12 out of 39 (30.77%) for T cell-mediated rejection. Finally, we found that reclassification of the initial diagnoses by the Banff Automation System was associated with an improved risk stratification of long-term allograft outcomes. This study demonstrates the potential of an automated histological classification to improve transplant patient care by correcting diagnostic errors and standardizing allograft rejection diagnoses.ClinicalTrials.gov registration: NCT05306795 .

Interleukin 8 Is Overexpressed in Acute Rejection in Kidney Transplant Patients

The main complication associated with renal graft loss is immune rejection. The gold standard for the diagnosis of renal graft rejection is percutaneous renal biopsy, which is expensive and can lead to complications. Inflammation is one of the main pathogenic pathways in allograft rejection, and urine samples seem to be efficient windows to explore the allograft condition with a high cost-benefit ratio. This study aimed to evaluate the messenger ribonucleic acid (mRNA) profile expression pattern for interleukin (IL) 2, IL-4, IL-6, IL-8, and IL-10; tumor necrosis factor alfa; gamma interferon; and transforming growth factor β1 in the urine renal cells of patients with a diagnosis of humoral rejection and patients with a diagnosis of normal biopsy. METHODS: An observational, cross-sectional analytical study was performed. All kidney transplants were performed at the Organ Transplant Department between 2018 and 2019. Also, a healthy control with a normal blood test and no apparent infection was included. mRNA from urine samples and biopsies was isolated, and the expression of interleukins was analyzed in PCR real time. Data were analyzed by Shapiro-Wilk and Kruskal-Wallis tests. RESULTS: The proinflammatory IL expression pattern in urine samples of kidney rejection group showed overexpression for IL-8 (P = .0001). No differences were observed in the rest of the interleukins analyzed. When we compared the results in the rejected versus not rejected transplanted patients with a group of apparently healthy subjects, the difference remains consistent. Thus, mRNA of IL-8 could function as a diagnostic tool in cases of chronic damage secondary to fibrosis.

Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study

OBJECTIVE

To develop and validate an integrative system to predict long term kidney allograft failure.

DESIGN

International cohort study.

SETTING

Three cohorts including kidney transplant recipients from 10 academic medical centres from Europe and the United States.

PARTICIPANTS

Derivation cohort: 4000 consecutive kidney recipients prospectively recruited in four French centres between 2005 and 2014. Validation cohorts: 2129 kidney recipients from three centres in Europe and 1428 from three centres in North America, recruited between 2002 and 2014. Additional validation in three randomised controlled trials (NCT01079143, EudraCT 2007-003213-13, and NCT01873157).

MAIN OUTCOME MEASURE

Allograft failure (return to dialysis or pre-emptive retransplantation). 32 candidate prognostic factors for kidney allograft survival were assessed.

RESULTS

Among the 7557 kidney transplant recipients included, 1067 (14.1%) allografts failed after a median post-transplant follow-up time of 7.12 (interquartile range 3.51-8.77) years. In the derivation cohort, eight functional, histological, and immunological prognostic factors were independently associated with allograft failure and were then combined into a risk prediction score (iBox). This score showed accurate calibration and discrimination (C index 0.81, 95% confidence interval 0.79 to 0.83). The performance of the iBox was also confirmed in the validation cohorts from Europe (C index 0.81, 0.78 to 0.84) and the US (0.80, 0.76 to 0.84). The iBox system showed accuracy when assessed at different times of evaluation post-transplant, was validated in different clinical scenarios including type of immunosuppressive regimen used and response to rejection therapy, and outperformed previous risk prediction scores as well as a risk score based solely on functional parameters including estimated glomerular filtration rate and proteinuria. Finally, the accuracy of the iBox risk score in predicting long term allograft loss was confirmed in the three randomised controlled trials.

CONCLUSION

An integrative, accurate, and readily implementable risk prediction score for kidney allograft failure has been developed, which shows generalisability across centres worldwide and common clinical scenarios. The iBox risk prediction score may help to guide monitoring of patients and further improve the design and development of a valid and early surrogate endpoint for clinical trials.

TRIAL REGISTRATION

Clinicaltrials.gov NCT03474003.

[Multidimensional approaches for risk stratification in transplantation]

Despite considerable progress in the short-term outcomes of renal transplantation, there has been little improvement over the last 15years on long-term survival. The main limitation is the lack of precise knowledge of the determinants of renal allograft loss and robust prognostic systems providing an individual prediction. Kidney transplantation must address a pressing clinical need to accurately define the determinants of kidney renal allograft survival in order to improve risk stratification. To achieve this goal, four steps need to be considered in the development of prognostic tools: the characterization and identification of the phenotype of the pathology, the assessment of prognostic factors of the event of interest in the population, the assessment of the additional value provided by a newly identified prognostic factor to conventional factors already known in clinical practice as well as the construction of prognostic tools, on the basis of multidimensional integrative models allowing a precise stratification of the risk, at individual and population scale.

Precision Transplant Medicine: Biomarkers to the Rescue

The concept that individuals with the same disease and a similar clinical presentation may have very different outcomes and need very different therapies is not novel. With the development of many innovative tools derived from the omics technologies, transplant medicine is slowly entering the era of precision medicine. Biomarkers are the cornerstone of precision medicine, which aims to integrate biomarkers with traditional clinical information and tailor medical care to achieve the best outcome for an individual patient. Here, we discuss the basic concepts of precision medicine and biomarkers, with a specific focus on progress in renal transplantation. We delineate the different types of biomarkers and provide a general assessment of the current applications and shortcomings of previously proposed biomarkers. We also outline the potential of precision medicine in transplantation. Moving toward precision medicine in the field of transplantation will require transplant physicians to embrace the increased complexity and expanded decision algorithms and therapeutic options that are associated with improved disease nosology.

Doing it hard in the bush: Aligning what gets measured with what matters

What gets measured gets managed. Funding of health services is substantially determined by operational activity and specific outcome indicators. In day-to-day clinical decision-making, surrogate markers, such as glycosylated haemoglobin and blood pressure, are commonly used to modify risks of 'hard' outcomes that include kidney failure, ischaemic cardiac events, stroke and all-cause mortality. In many settings, surrogates are all we have to go on. As a consequence, current health funding models heavily rely on surrogate-based key performance indicators [KPIs]. While surrogates are convenient and provide immediate information, there is an obligation to ensure that they are appropriate, reliable and validated in context. In contrast, hard outcomes, the real consequences of illness, are usually realised over an extended timeframe. Additionally, and for a host of reasons, hard endpoints have the greatest social, emotional and economic impact for people at the far end of the health system; those in rural and remote settings - 'in the bush' - especially Indigenous Australians. We propose a health service assessment approach that aligns short-term decision-making with patient-centred and longer term hard outcomes, one that takes into account community, cultural and environmental factors, especially remoteness. Communities should have a major say in determining what health indicators are measured and managed.

Classification of Kidney Transplant Recipients Using a Combination of Estimated GFR and Albuminuria Reflects Risk

BACKGROUND

The 2012 Kidney Dialysis Initiative Global Outcomes chronic kidney disease (CKD) classification scheme subdivides stage 3 CKD and incorporates the urinary albumin-to-creatinine ratio (ACR). The aim of this study was to evaluate whether the novel scheme provides graded risk in kidney transplant recipients (KTRs).

METHODS

Prevalent KTRs with available laboratory data were included. The primary outcome was a composite of doubling of serum creatinine, graft failure, or death. Patients were stratified using the CKD-Epidemiolgic Collaboration equation, and ACR and the event rate per 1000 patient-years in each CKD category were calculated.

RESULTS

There were 269 KTRs with a mean follow-up of 4.5 ± 2.0 years. There was a graded increase in outcomes with increasing ACR and decreasing estimated glomerular filtration rate (eGFR). For the primary outcome, the event rate was 15.3 (95% confidence interval, 4.2-39.2) per 1000 patient-years for those with an eGFR greater than 60 mL/min per 1.73 m2 and an ACR less than 30 mg/g, whereas it was 375 (95% confidence interval, 193.8-655.1) for those with an eGFR less than 30 mL/min per 1.73 m2 and an ACR greater than 300 mg/g.

CONCLUSIONS

The novel Kidney Dialysis Initiative Global Outcomes classification scheme provides graded risk for important clinical events in KTRs. This information can be used to identify high-risk patients and to tailor follow-up and management strategies aimed at improving outcomes.

Long-term outcomes following sirolimus conversion after renal transplantation

Long-term outcomes following renal transplantation remain limited due to chronic progressive injury partly as a result of calcineurin inhibitor (CNI) toxicity. Thus, patients have been converted to non-CNI immunosuppressives despite the lack of evidence of long-term benefits from CNI free therapy. We now report our 10-year experience converting patients with well functioning transplants from CNI to sirolimus. We retrospectively analyzed outcomes of patients receiving continuous CNI based therapy (CNI, n = 309) or who were switched to sirolimus within the first year of post-transplantation (CONV, n = 54). The groups were similar for most recipient, graft and donor characteristics, however, diabetes was more common in the CNI group and statin use was more frequent in the CONV group. The average time to conversion was 7.2 months and the creatinine level at the time of switching was 1.4 mg/dl. Ten year graft and patient survival rates were equivalent in both groups. There were no differences in the causes of death or graft loss in both groups. Renal function was available for 5 years posttransplant and was no different between groups. Thus, there is no evidence that routinely switching patients with well functioning renal allografts to sirolimus from CNI based immunosuppression provides long-term benefit.

Kidney function endpoints in kidney transplant trials: a struggle for power

Kidney function endpoints are commonly used in randomized controlled trials (RCTs) in kidney transplantation (KTx). We conducted this study to estimate the proportion of ongoing RCTs with kidney function endpoints in KTx where the proposed sample size is large enough to detect meaningful differences in glomerular filtration rate (GFR) with adequate statistical power. RCTs were retrieved using the key word "kidney transplantation" from the National Institute of Health online clinical trial registry. Included trials had at least one measure of kidney function tracked for at least 1 month after transplant. We determined the proportion of two-arm parallel trials that had sufficient sample sizes to detect a minimum 5, 7.5 and 10 mL/min difference in GFR between arms. Fifty RCTs met inclusion criteria. Only 7% of the trials were above a sample size of 562, the number needed to detect a minimum 5 mL/min difference between the groups should one exist (assumptions: α = 0.05; power = 80%, 10% loss to follow-up, common standard deviation of 20 mL/min). The result increased modestly to 36% of trials when a minimum 10 mL/min difference was considered. Only a minority of ongoing trials have adequate statistical power to detect between-group differences in kidney function using conventional sample size estimating parameters. For this reason, some potentially effective interventions which ultimately could benefit patients may be abandoned from future assessment.

MicroRNAs as biomarkers in solid organ transplantation

Important progress has been made in improving short-term outcomes in solid organ transplantation. However, long-term outcomes have not improved during the last decades. There is a critical need for biomarkers of donor quality, early diagnosis of graft injury and treatment response. MicroRNAs (miRNAs) are a class of small single-stranded noncoding RNAs that function through translational repression of specific target mRNAs. MiRNA expression has been associated with different diseases and physiological conditions. Moreover, miRNAs have been detected in different biological fluids and these circulating miRNAs can distinguish diseased individuals from healthy controls. The noninvasive nature of circulating miRNA detection, their disease specificity and the availability of accurate techniques for detecting and monitoring these molecules has encouraged a pursuit of miRNA biomarker research and the evaluation of specific applications in the transplant field. miRNA expression might develop as excellent biomarkers of allograft injury and function. In this minireview, we summarize the main accomplishments of recently published reports focused on the identification of miRNAs as biomarkers in organ quality, ischemia-reperfusion injury, acute rejection, tolerance and chronic allograft dysfunction emphasizing their mechanistic and clinical potential applications and describing their methodological limitations.

Performance of polymerase chain reaction techniques detecting perforin in the diagnosis of acute renal rejection: a meta-analysis

Background

Studies in the past have shown that perforin expression is up-regulated during acute renal rejection, which provided hopes for a non-invasive and reliable diagnostic method to identify acute rejection. However, a systematic assessment of the value of perforin as a diagnostic marker of acute renal rejection has not been performed. We conducted this meta-analysis to document the diagnostic performance of perforin mRNA detection and to identify potential variables that may affect the performance.

Methodology/Principal Findings

Relevant materials that reported the diagnostic performance of perforin mRNA detection in acute renal rejection patients were extracted from electronic databases. After careful evaluation of the studies included in this analysis, the numbers of true positive, true negative, false positive and false negative cases of acute renal rejection identified by perforin mRNA detection were gathered from each data set. The publication year, sample origin, mRNA quantification method and housekeeping gene were also extracted as potential confounding variables. Fourteen studies with a total of 501 renal transplant subjects were included in this meta-analysis. The overall performance of perforin mRNA detection was: pooled sensitivity, 0.83 (95% confidence interval: 0.78 to 0.88); pooled specificity, 0.86 (95% confidence interval: 0.82 to 0.90); diagnostic odds ratio, 28.79 (95% confidence interval: 16.26 to 50.97); and area under the summary receiver operating characteristic curves value, 0.9107±0.0174. The univariate analysis of potential variables showed some changes in the diagnostic performance, but none of the differences reached statistical significance.

Conclusions/Significance

Despite inter-study variability, the test performance of perforin mRNA detected by polymerase chain reaction was consistent under circumstances of methodological changes and demonstrated both sensitivity and specificity in detecting acute renal rejection. These results suggest a great diagnostic potential for perforin mRNA detection as a reliable marker of acute rejection in renal allograft recipients.

MicroRNA profiles in allograft tissues and paired urines associate with chronic allograft dysfunction with IF/TA

Despite the advances in immunosuppression, renal allograft attrition over time remains unabated due to chronic allograft dysfunction (CAD) with interstitial fibrosis (IF) and tubular atrophy (TA). We aimed to evaluate microRNA (miRNA) signatures in CAD with IF/TA and appraise correlation with paired urine samples and potential utility in prospective evaluation of graft function. MiRNA signatures were established between CAD with IF/TA versus normal allografts by microarray. Validation of the microarray results and prospective evaluation of urine samples was performed using real-time quantitative-PCR (RT-qPCR). Fifty-six miRNAs were identified in samples with CAD-IF/TA. Five miRNAs were selected for further validation based on array fold change, p-value and in silico predicted mRNA targets. We confirmed the differential expression of these five miRNAs by RT-qPCR using an independent set of samples. Differential expression was detected for miR-142-3p, miR-204, miR-107 and miR-211 (p < 0.001) and miR-32 (p < 0.05). Furthermore, differential expression of miR-142-3p (p < 0.01), miR-204 (p < 0.01) and miR-211 (p < 0.05) was also observed between patient groups in urine samples. A characteristic miRNA signature for IF/TA that correlates with paired urine samples was identified. These results support the potential use of miRNAs as noninvasive markers of IF/TA and for monitoring graft function.

Meta-analysis of calcineurin-inhibitor-sparing regimens in kidney transplantation

Calcineurin-inhibitor-sparing strategies in kidney transplantation may spare patients the adverse effects of these drugs, but the efficacy of these strategies is unknown. Here, we conduct a meta-analysis to assess outcomes associated with reducing calcineurin inhibitor exposure from the time of transplantation. We search Medline, Embase, and Cochrane Register of Controlled Trials for randomized controlled trials published between 1966 and 2010 that compared de novo calcineurin-inhibitor-sparing regimens to calcineurin-inhibitor-based regimens. In this analysis, we include 56 studies comprising data from 11337 renal transplant recipients. Use of the contemporary agents belatacept or tofacitinib, in combination with mycophenolate, decreased the odds of overall graft failure (OR 0.61; 95% CI 0.39-0.96; P = 0.03). Similarly, minimization of calcineurin inhibitors in combination with various induction and adjunctive agents reduces the odds of graft failure (OR 0.73; 95% CI 0.58-0.92; P = 0.009). Conversely, the use of inhibitors of mammalian target of rapamycin (mTOR), in combination with mycophenolate, increases the odds of graft failure (OR 1.43; 95% CI 1.08-1.90; P = 0.01). Calcineurin-inhibitor-sparing strategies are associated with less delayed graft function (OR 0.89; 95% CI 0.80-0.98; P = 0.02), improved graft function, and less new-onset diabetes. The more contemporary protocols did not seem to increase rates of acute rejection. In conclusion, this meta-analysis suggests that reducing exposure to calcineurin inhibitors immediately after kidney transplantation may improve clinical outcomes.

Pretransplant transcriptome profiles identify among kidneys with delayed graft function those with poorer quality and outcome

Robust biomarkers are needed to identify donor kidneys with poor quality associated with inferior early and longer-term outcome. The occurrence of delayed graft function (DGF) is most often used as a clinical outcome marker to capture poor kidney quality. Gene expression profiles of 92 preimplantation biopsies were evaluated in relation to DGF and estimated glomerular filtration rate (eGFR) to identify preoperative gene transcript changes associated with short-term function. Patients were stratified into those who required dialysis during the first week (DGF group) versus those without (noDGF group) and subclassified according to 1-month eGFR of >45 mL/min (eGFR(hi)) versus eGFR of ≤45 mL/min (eGFR(lo)). The groups and subgroups were compared in relation to clinical donor and recipient variables and transcriptome-associated biological pathways. A validation set was used to confirm target genes. Donor and recipient characteristics were similar between the DGF versus noDGF groups. A total of 206 probe sets were significant between groups (P < 0.01), but the gene functional analyses failed to identify any significantly affected pathways. However, the subclassification of the DGF and noDGF groups identified 283 probe sets to be significant among groups and associated with biological pathways. Kidneys that developed postoperative DGF and sustained an impaired 1-month function (DGF(lo) group) showed a transcriptome profile of significant immune activation already preimplant. In addition, these kidneys maintained a poorer transplant function throughout the first-year posttransplant. In conclusion, DGF is a poor marker for organ quality and transplant outcome. In contrast, preimplant gene expression profiles identify "poor quality" grafts and may eventually improve organ allocation.

Identifying biomarkers as diagnostic tools in kidney transplantation

There is a critical need for biomarkers for early diagnosis, treatment response, and surrogate end point and outcome prediction in organ transplantation, leading to a tailored and individualized treatment. Genomic and proteomic platforms have provided multiple promising new biomarkers during the last few years. However, there is still no routine application of any of these markers in clinical transplantation. This article will discuss the existing gap between biomarker discovery and clinical application in the kidney transplant setting. Approaches to implementing biomarker monitoring into clinical practice will also be discussed.

Assessment of kidney organ quality and prediction of outcome at time of transplantation

The critical importance of donor organ quality, i.e., number of surviving nephrons, ability to withstand injury, and capacity for repair in determining short- and long-term outcomes is becoming increasingly clear. This review provides an overview of studies to assess donor kidney quality and subsequent transplant outcomes based on clinical pathology and transcriptome-based variables available at time of transplantation. Prediction scores using clinical variables function when applied to large data sets but perform poorly for the individual patient. Histopathology findings in pre-implantation or post-reperfusion biopsies help to assess structural integrity of the donor kidney, provide information on pre-existing donor disease, and can serve as a baseline for tracking changes over time. However, more validated approaches of analysis and prospective studies are needed to reduce the number of discarded organs, improve allocation, and allow prediction of outcomes. Molecular profiling detects changes not seen by morphology or captured by clinical markers. In particular, molecular profiles provide a quantitative measurement of inflammatory burden or immune activation and reflect coordinated changes in pathways associated with injury and repair. However, description of transcriptome patterns is not an end in itself. The identification of predictive gene sets and the application to an individualized patient management needs the integration of clinical and pathology-based variables, as well as more objective reference markers of transplant function, post-transplant events, and long-term outcomes.