Kidney transplant (KT) rejection is diagnosed using invasive biopsies, which present difficult logistics, risks, and costs. Therefore, noninvasive diagnostic biomarkers have been studied in this regard. The development of molecular biomarkers to detect a clinical phenotype and/or predict a related clinical outcome presents many challenges that are compounded by the technical and regulatory requirements needed to make biomarkers available for clinical practice. Indication “for-cause” biopsies are commonly used to investigate acute or persistent renal dysfunction (elevated serum creatinine, proteinuria, etc), often yielding valuable information about causality and chronicity, whereas surveillance “protocol” biopsies are used to monitor patients with stable renal function to detect “silent” or “subclinical” rejection (Figure 1).
It is now well established that in patients with stable renal function, subclinical acute rejection (subAR) can be detected in up to 25% of protocol biopsies performed in the first year following KT.1–6 In a recent prevalent multicenter study, subAR (including borderline changes) was detected in 20%–25% of protocol biopsies at 6, 12, and 24 months following KT, and overall in 35% of patients in the first 2 years following KT.7 Moreover, subAR is associated with worse graft outcomes.6,8,9 Therefore, there is a clear need for the development of noninvasive biomarkers for patients with stable renal function following KT.
Here, we provide a framework for clinicians who need to evaluate the clinical validity and utility of a putative biomarker. We further apply this framework to available and/or promising noninvasive biomarkers for kidney allograft rejection in the context of subAR.
NEED STATEMENT AND CONTEXT OF USE
The US Food and Drug Administration and the European Medicines Agency define biomarker utility according to the need and context of use (COU) statements, which are simplified to 2 elements: (1) the question or need that the biomarker is intended to address and (2) the class of biomarker proposed and the information it can provide.
The first element of the evidentiary criteria assessment map (Figure 2) is centered on the knowledge gap—what is the specific “fit-for-purpose” biomarker need? While the clinical relevance of subAR has been in question for decades, several recent publications have demonstrated its negative impact on graft outcomes.7,11–14 This confirms previous claims by these same authors and others regarding the clinical significance as well as the role of protocol biopsies on patients with stable renal function. It is now clear that the long-term impact of subAR, despite the initial absence of renal dysfunction, results in chronic graft injury and loss.15 This association is underscored by the recent observation that chronic T-cell–mediated rejection, which is a major risk factor for graft failure, is preceded by earlier, subclinical, acute T-cell–mediated rejection.9,16 In addition, although less common and less well studied, subclinical antibody-mediated rejection (AMR) also associates with graft failure.15 The inherent difficulties of performing frequent protocol biopsies combined with the risk of missing the presence of subclinical rejection illustrate the need to pursue noninvasive monitoring of patients following KT to either replace or to inform the selected use of protocol biopsies in patients with stable renal function following kidney transplantation.6
The second element of the evidentiary criteria for biomarker utility evaluation refers to the type of information a biomarker provides. Biomarkers are defined in terms of disease presence and status as susceptibility/risk, prognostic, diagnostic, monitoring (measured serially), predictive, pharmacodynamic/response, surrogate endpoint, or safety measure.17,18 While these Food and Drug Administration definitions are used primarily for drug development (as companion diagnostics) using specific terminology (Biomarkers, EndpointS, and other Tools Resource),19 many of the principles also apply outside the context of drug trials and are relevant in the development and assessment for biomarkers to monitor patients following KT.
ASSESSMENT OF BIOMARKER PERFORMANCE METRICS RELEVANT TO COU
In order to evaluate the diagnostic/predictive accuracy of a biomarker, specific metrics such as sensitivity and specificity, and the related area under the receiver operator characteristic curve, as well as negative predictive value (NPV) and positive predictive value (PPV) represent standard fare.20 However, these are not sufficient and may in fact be misleading. First, the biomarker must be compared with the current standard of care (SOC). Second, we have previously remarked on the need for, and proposed guidelines for high dimensional genomic studies in transplantation. We highlighted a number of requirements for the assessment of biomarker performance and interpretation, including the need for robust preselected bioinformatics, locked models and thresholds, external validation cohorts (reproducibility), and a statement of the intended COU that takes into consideration performance metrics such as PPV/NPV that are based on prevalent cohorts.21 Moreover, at the patient level, the NPV and PPV are more relevant for decision-making. For instance, a high NPV is required to rule out an ongoing disease process, thus having low number of false-negative test results, while a high PPV is required if the test is intended to pick up ongoing disease while minimizing false-positive results. In the context of noninvasive biomarkers for subAR, if the COU is to avoid or minimize performing invasive biopsies, a high NPV is required, to minimize false-negative results, that is, missed rejections.22,23 The opposite would be true if a novel biomarker would intend to provide additional justification for performing a for-cause biopsy. Such marker would ideally not have false-positive results and minimize performing futile indication biopsies. In such a COU, the biomarker would need a high PPV.
ASSESSMENT OF BIOMARKER BENEFITS AND RISKS RELEVANT TO COU
Another important aspect in the evaluation of a novel biomarker is the assessment of its potential benefits and risks.10 This is evaluated in the context of the need, the COU, the performance metrics, and the potential clinical impact of using it in clinical practice compared with the SOC. Although it is well established that histologic reading of biopsies is imperfect and dependent on pathologists’ expertise, sampling error etc, histologic reading according to the Banff classification24 remains the current gold standard for evaluation of subclinical injury in transplanted kidneys. While some transplant centers use protocol biopsies, others do not use these, or alternatively use them only in selected cases. In an ideal situation, use of a biomarker should reduce the number of invasive biopsies while allowing for the detection of subAR (benefits). The risks include missing subAR (this happens routinely—100%—in transplant centers that do not perform protocol biopsies) or subjecting patients to the unnecessary risks of a negative protocol biopsy (this happens routinely—75%–80%—in centers that perform routine protocol biopsies). Therefore, a COU that consists of using a biomarker to inform the need for a biopsy that can reduce the number of negative biopsies as well as the overall number of biopsies would be viewed positively from a risk/benefit perspective. This biomarker would require a high NPV and a reasonable PPV. Currently, invasive protocol biopsies need to be performed for diagnosis of rejection. Any novel biomarker that uses more easily accessible biomaterial, like urine or blood, will be evaluated positively on the risk side. Thus, the risks and benefits need to be assessed in reference to the COU and in comparison to the SOC.
EVIDENTIARY CRITERIA ASSESSMENT MAP: STRINGENCY BASED ON COU COMPARED WITH SOC
The stringency of evidentiary criteria required for biomarker qualification is based on a careful assessment of the statement of need, performance metrics, and potential risks and/or benefits to the patient of using the biomarker within the specified COU10 compared with the SOC. In the setting of subAR, this is complicated by the lack of established definitions of stable graft function, the lack of consensus on when to perform protocol biopsies and in which patients, and the ensuing heterogeneity in routine clinical practice,22,25 despite the uncontested evidence of the negative clinical impact of subAR. While biomarker qualification is a formal regulatory review for their use in drug development, several elements of the evidentiary criteria assessment map can provide confidence that within the stated COU, the biomarker can be relied upon to provide specific information when used to diagnose, predict, or monitor a clinical phenotype. The clinical implementation of a new biomarker will also require further discussions on the frequency of using noninvasive tests for subAR and the target population. Similar to current clinical practice with protocol biopsies, it can be anticipated that this will be largely dependent on center practice, background risk evaluation, or local logistic/economical factors. Testing frequency and definitions of the specific target populations of a test for subAR are thus unlikely to be considered in detail in the COU submitted in the formal review process, unless such information is a key element of the biomarker characteristics.
The COU of a biomarker drives the extent of evidence needed for qualification. Both analytic (performance of the assay in a laboratory setting) and clinical validation (ability of the biomarker to diagnose/predict the phenotype of interest) constitute essential components of the evidentiary criteria assessment map. Ultimately, the clinical validity (association of the test result with measurable outcomes and whether the test results will impact physician decisions in a manner that leads to measurable improved outcomes) will determine the clinical utility of each test. A candidate biomarker that has low negative consequence of failure and high benefit when correct will need less extensive evidentiary data than a biomarker with important negative consequences if incorrect and low improvement over the SOC.
FROM BIOMARKER DEVELOPMENT TO COMMERCIAL AVAILABILITY (IE, ABILITY TO USE THE TEST IN CLINICAL PRACTICE BEYOND THE INVESTIGATIONAL CONTEXT)
Several scientific reports have recently been published describing performance metrics for biomarkers at varying stages of development in kidney transplantation.14,18,20,26 Biomarker development begins with discovery and is followed by measurement of performance metrics using a locked classifier/threshold on an external and independent validation cohort.27 Beyond that, the evidentiary criteria for the proposed COU is defined to project the biomarker toward the commercial trajectory that will make the test available to patients.
In the United States, for tests offered from a single source—that is, Laboratory Developed Tests (LDTs) that are performed in hospital and/or independent Clinical Laboratory Improvement Amendments–accredited laboratories,28 the process of commercialization begins with obtaining a local coverage determination (LCD) from the Centers for Medicare and Medicaid (CMS) for coverage (reimbursement at a particular rate per test once the draft LCD is issued). This is followed by a public comment period, and if successful, a reimbursement decision is made to provide coverage at a set price for Medicare beneficiaries. Commercial payers either follow suit or alternatively go through their own technology assessment before authorizing reimbursement for the test. While not required, once this happens, the biomarker test is considered to be commercially available. Alternatively, CMS may continue to monitor the ongoing evolution of the evidence for possible changes to the coverage decision. Occasionally, a reimbursement decision establishes clinical utility expectations that may require registry studies. Clinical utility of a new diagnostic test has been defined in a number of ways but is generally accepted as meaning that a test impacts or supports a physician’s treatment decision and that physicians consider the use of the test as reasonable and necessary to provide optimal care for their patient. Finally, in addition to clinical utility evaluation, also economic assessment of a test will be included in the reimbursement decision process.
In Europe, whereas many LDTs have historically been used in hospitals without formal approval from regulatory agencies leaving safety, quality, and efficacy of these tests to the discretion of the developing laboratory, stringent guidelines have recently been published29 for companion diagnostics. The regulatory process for approval of molecular testing, which is determined according to risk stratification (severity of the disorder tested for and possible consequences of an incorrect test result), is evolving rapidly. For all in vitro diagnostic devices sold in Europe, CE marking is required to indicate conformity with the In-Vitro Diagnostic Devices Directive (98/79/EC) and the new In Vitro Diagnostic Regulation (2017/746) which will come into force in 2022. Reimbursement decisions are made by the individual European Union countries’ national health authorities, based on local demand, available evidence, and overall healthcare budget decisions.
REVIEW OF COMMERCIALLY AVAILABLE AND OTHER PROMISING subAR BIOMARKER TESTS
We have reviewed the available published data known to us at the time of submission relevant to noninvasive (blood or urine) molecular biomarkers, where the authors have suggested their putative use in the clinical management of subAR. We have applied the essential elements of the framework discussed above for each biomarker (Table 1). A more detailed review of each biomarker is provided in the Supplemental Documentation (SDC, http://links.lww.com/TP/B846). Our selection of reported tests reflects the current situation known to us and available in the scientific literature or public domain. This selection does not intend to downplay the future potential of other tests currently under development. As this is not a comprehensive and systematic review, and as the field is rapidly evolving, it is likely that promising markers currently in the pipeline are not mentioned in this overview. An example of such marker is the Allomap Kidney test (CareDx), which is mentioned in the company’s public communication, but for which no scientific publications are yet available. Another example is the urinary Common Rejection Module, which was reported as promising marker in the literature,43 but where further scientific validation is needed and where we found no evidence of commercial valorization (Supplemental Documentation, SDC, http://links.lww.com/TP/B846).
Urine Gene Expression Profile
Suthanthiran et al30 reported a 3-gene signature in urine samples capable of detecting clinical acute KT rejection. Cohorts with prevalent incidence of rejection were used for both discovery and validation cohorts. Standardized polymerase chain reaction (PCR) assays developed in the discovery cohort were used for the validation cohort. While the authors included analyses of samples obtained before the clinical event suggesting the potential to detect subAR, only few urine samples paired with protocol biopsies were used in the regression analyses, which did not allow assessing the diagnostic performance for subAR. No effort to link the gene expression profile (GEP) to outcomes was made. To our knowledge, there is no current effort underway to commercialize the assay and, therefore, no COU has been proposed.
Urine CXCL9 Protein
Hricik et al31 reported that urine CXCL9 protein, in the absence of coincident infection, was able to detect clinically evident acute rejection (≥Banff grade I). These authors also noted that the presence of this protein frequently preceded renal dysfunction, but subAR was not the focus of the study. Cohorts with prevalent incidence of rejection were used for both discovery and validation cohorts. Standardized ELISA assays developed in the discovery cohort were used for the validation cohort. No effort to link the emergence of urinary CXCL9 to outcomes was made. To our knowledge, no efforts have been made to commercialize the assay and, therefore, no COU has been proposed. Nevertheless, further development of CXCL9 ELISA in urine seems possible and could be pursued, as LDT in the United States and as in vitro diagnostic test in Europa, provided that CE marking is obtained.
Blood Kidney Solid Organ Response Test (Immucor Dx)
Roedder et al32 reported on the performance of a PCR-based GEP test in the peripheral blood that was able to “detect renal transplant patients at high risk for acute rejection.” The study used a retrospective analysis of archived samples, including both protocol and indication biopsies, using “best-fit” bioinformatics. A subsequent editorial raised a number of questions about the study design, methodology, bioinformatics, and about the study’s conclusions.27 The diagnostic performance for subAR was not assessed separately. Their product website44 states that kidney solid organ response test was “developed for the detection and surveillance of renal transplant rejection with the goal of driving preemptive clinical interventions and improved outcomes” and ”to detect renal transplant patients at high risk for acute rejection.” While Immucor Dx announced in 2014 that the test was to become soon available, the further commercialization plan is currently unclear.
Plasma Allosure (CareDx)
The detection of donor-derived cell free DNA (ddcfDNA) in the recipient’s plasma has been evaluated as a potential biomarker for allograft injury. Bloom et al33 reported that ddcfDNA could be detected in patients following KT reflecting graft dysfunction, in the setting of for-cause biopsies. The ddcfDNA test discriminated rejection from no rejection, and better for AMR than for T cell-mediated rejection (TCMR). As only 1 case with rejection was diagnosed in a protocol biopsy, subAR was not the focus of this study. More recently, Huang et al34 reported a similar finding in patients undergoing graft biopsies to investigate renal dysfunction. In this second study, it was confirmed that the assay was better in detecting AMR while it did not detect TCMR. In a third study, Bromberg et al35 reported on the range of ddcfDNA levels in a population of stable patients, but no metrics of diagnostic performance for subAR were provided. The authors reported that 96% of levels in a prevalent population were below the positive threshold of 1%, potentially indicating that a substantial number of patients with subAR could have negative tests, as the point prevalence of subAR is significantly higher than 4%, when both AMR and TCMR are considered. Whether these samples below the threshold indeed had good outcome remains to be studied. While collectively, samples used in these studies were often paired with biopsies, most of these biopsies were performed for-cause with very few protocol biopsies in patients with stable renal function, which makes it difficult to assess the diagnostic potential of this test for subAR. The test is commercially available. According to available product information on Allosure, the test’s COU is to assess the probability of “active” allograft rejection in KT recipients with clinical suspicion of rejection and to inform clinical decision-making about the necessity of renal biopsy in such patients at least 2 weeks posttransplant in conjunction with standard clinical assessment.45 A large registry study is currently enrolling patients.
Plasma Prospera (Natera)
Prospera is a ddcfDNA test commercialized by Natera and uses a different technology platform than Allosure.46 Sigdel et al36 recently reported on a retrospective cohort of archived plasma samples, some with paired biopsies for “active” rejection. Based on data from a discovery cohort, using posthoc analyses in the subset of protocol biopsies, the authors concluded that the study validated the use of ddcfDNA for detection of graft injury allowing for targeted biopsies. No validation was done yet to evaluate the performance of the test on an independent external cohort. While the technology platform for Prospera is different than that used for Allosure, no formal validation comparisons were made between Allosure and Prospera. The COU proposed in the LCD draft submission (currently pending final approval by CMS) as a “me-too” test (compared with Allosure) states that when used with all other clinical and laboratory data, the test detects “subclinical active rejection” and therefore may be useful in patients with significant contraindications to biopsies.47 The LCD is pending and a registry study is planned.
Blood TruGraf (Viracor–Eurofins)
The TruGraf assay is a microarray-based test that analyzes GEP in the peripheral blood.37 The GEP associates with either a normal protocol kidney biopsy (Transplant eXcellent [TX]) or the absence of a normal biopsy (not-TX) in stable patients. All aspects of discovery and external validation of the TruGraf test were performed on blood samples paired with biopsies from prevalent cohorts. For the purpose of validation, the model derived from preselected bioinformatics and the threshold used to test performance on the discovery cohort were locked. Clinical utility was assessed through both retrospective and prospective surveys of physician decision impact when used.38 The test and its proposed threshold had a high NPV for subAR, which illustrates its value to rule out subAR.7 The PPV for subAR was lower, which limits the value of a single positive test. A recent study demonstrated a correlation with graft outcomes at 24 months following KT.7 It was not yet studied whether the kinetics of the test offer any predictive value, and whether therapeutic decisions on, for example, increasing or decreasing immunosuppression could be informed by a single value of the test or its kinetics. The COU proposed in the LCD draft submission (currently pending final approval by CMS) states that “The TruGraf test is intended for use in KT recipients with stable renal function as an alternative to surveillance biopsies in facilities that utilize surveillance biopsies.”48 While primarily used to rule out subAR, it is expected that both centers that perform or do not perform surveillance biopsies can use the test to inform the need for a surveillance biopsy in a relatively small number of stable patients.23 A registry study is planned.
Blood GEP (Quest Diagnostics)
Christakoudi et al39 took an in silico approach to biomarker development wherein they identified a gene expression panel from the literature. This 7-gene panel was then applied to a small number of patients with and without clinical acute rejection (renal dysfunction) and patients with stable creatinine (without paired protocol biopsies). The diagnostic performance of the test for subAR could not be assessed, inherent to the study design as no protocol biopsies were performed. Following this, using quantitative PCR, they tested the performance of the GEP on a cohort of patients using random cross-sectional and longitudinal samples finding that 24% of cross-sectional stable samples demonstrated a positive GEP and 40% of longitudinal serially collected samples preceding histologic rejection also demonstrated a positive GEP. There is no evidence yet of attempt to commercialize, or statement of COU, or plans for a registry study.
Blood GEP–Transcriptome–Predictive (RenalytixAI)
Zhang et al40 used samples from a prospective multicenter cohort to develop a 23 gene set derived from whole blood RNA sequencing in pretransplant samples to predict early acute rejection in patients following KT. The study was not designed to report diagnostic accuracy for ongoing subAR at the time of testing. The cohort was randomly divided into a discovery and a validation cohort, with retained accuracy also in the validation cohort for prediction of future histologic rejection. Independent validation was not yet performed. Paired protocol biopsies were not routinely performed by all participating centers, but by some especially later in the study. They then combined the discovery and validation sets to demonstrate that the gene set associated with worse graft outcome (clinical validity), including histologic findings on protocol biopsies. To our knowledge, there is no evidence yet of external validation of these findings. The authors mentioned a US Provisional Patent Application related to this biomarker, suggesting potential for further commercialization of the test. The potential COU could be inferred from the authors’ statement that the test, performed at the time of transplant, may risk-stratify patients in terms of immune reactivity following KT.
Blood GEP–Transcriptome–Diagnostic (RenalytixAI)
Using the same cohort of patients as in their previous study40 where they identified a 23 gene set to predict graft outcomes, at the time of transplant, Zhang et al41 have more recently identified a 17 gene set that associates with rejection, including subAR, on a 3-month biopsy. Similarly to their previous study,40 they randomly selected samples from the cohort for both discovery and validation, but this time, added samples from an independent external cohort to the validation cohort. The patients were stratified into 3 groups based on biomarker data—“tertile probability cutoffs” (high, intermediate, and low) to illustrate potential usefulness in different clinical scenarios, with clinically useful NPV and PPV associated with these thresholds. While RNA sequencing was primarily used, the authors also confirmed their findings using microarrays. The authors mentioned a US Provisional Patent Application related to this biomarker, suggesting potential for further commercialization of the test. To our knowledge, no detailed COU has been proposed, other than a statement by the authors that the “assay offers the potential to be used as an immune-monitoring tool to guide the use of immunosuppression.”
URINE 4-METABOLITE PROFILE (NUMARES)
The Numares AXINON renalTX-SCORE assay is a test that analyzes a urinary metabolite profile by the measurement of 4 metabolites (alanine, citrate, lactate, and urea) using nuclear magnetic resonance on spot urine samples, normalized to creatinine.42 The test compared acute/active rejection versus no rejection, defined according to the Banff 97 classification (which thus encompasses acute TCMR but not borderline changes or AMR). The independent test set consisted of prospectively collected, prevalent, and repetitive samples obtained in the same single center as the training cohort. As also samples without concomitant biopsies were included, it could be deducted that also samples at the time of stable graft function were included in this study. However, no data were presented on the inclusion of protocol biopsies, which makes it unclear whether this test could be used for subAR or is positioned as test for clinical rejection. The test set was used for final model selection, which implies that an independent validation study of the model is still needed. Thresholds have not been proposed for this test, implicating that also the PPV and NPV remain unclear. The AXINON renalTX-SCORE assay has received CE marking in the European Union as in vitro diagnostic test and is a Research-Use-Only product in the United States. The COU of the AXINON renalTX-SCORE mentioned on the product website states that this “is a non-invasive test intended to support the diagnosis of a kidney allograft rejection in conjunction with other measurements and clinical evaluations.”49 Also, it is mentioned that the test can indicate rejection 1–7 days before a documented rejection, could be used for evaluating therapeutic success, and monitor the response to antirejection therapy. An independent, prospective validation study is ongoing.
The field of molecular biomarkers is evolving rapidly in general, and for transplant applications in particular. Therefore, the current review, a snapshot in time, may not capture novel biomarkers that may come on line in the near future. Moreover, the focus of this review is subAR (acute T-cell–mediated rejection in a patient with stable renal function); we have not taken other forms of subclinical rejection into consideration (eg, subclinical AMR) that while less frequent, is known to have a significant negative impact on graft outcome.50 Both can only currently be detected using protocol biopsies. We did not discuss the issue of the time required between submission of a sample and test result report. Given that the patients have stable renal function, we do not feel that there is the same type of urgency for this as for patients with graft dysfunction and therefore omitted this factor from the evaluation. It should also be noted that we did not discuss technical considerations of blood versus urine samples including potential difficulties with collection, processing, stability, and intrapatient or interpatient variability as these are all taken into consideration in the commercialization process. We have also not discussed clinical rejection, either T-cell or antibody-mediated (or both) in the setting of graft dysfunction. Notwithstanding these limitations, the current review provides a framework that can be used by clinicians as a practical guide for any current or future biomarkers, as well as a contemporary review of all available and/or promising biomarkers designed to detect subAR.
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