MolDX: Molecular Testing for Solid Organ Allograft Rejection

Title XVIII of the Social Security Act (SSA), §1862(a)(1)(A), states that no Medicare payment shall be made for items or services that “are not reasonable and necessary for the diagnosis or treatment of illness or injury or to improve the functioning of a malformed body member.”

42 CFR §410.32(a) Diagnostic x-ray tests, diagnostic laboratory tests, and other diagnostic tests: Conditions

CMS Internet-Only Manual, Pub. 100-02, Medicare Benefit Policy Manual, Chapter 15, §80 Requirements for Diagnostic X-Ray, Diagnostic Laboratory, and Other Diagnostic Tests, §80.1.1 Certification Changes

DEFINITIONS

For purposes of this policy the following definitions are used:

• ACR – Acute Cellular Rejection (also referred to as TCMR: T-cell mediated rejection)
• AMR – Antibody-Mediated Rejection
• AR – Acute Rejection/Active Rejection
• AV – Analytical Validity
• CV – Clinical Validity
• dd-cfDNA – Donor-Derived Cell-Free DNA
• GEP – Gene Expression Profiling
• MOT – Multiorgan Transplantation
• Clinical suspicion of rejection – patient has specific clinical (physical and/or biological) signs or symptoms of organ injury/rejection, as defined in existing guidelines and demonstrated in the medical record.
• For-cause testing – the evaluation of a patient with clinical suspicion of rejection.
• SubAR – Subclinical acute rejection; the patient does not have clinical suspicion of rejection but may have allograft inquiry warranting evaluation by surveillance (protocol) testing.
• Surveillance (Protocol) testing – the evaluation of an asymptomatic (no clinical signs or symptoms of organ injury/rejection) patient for subAR.

This Medicare contractor will provide limited coverage for molecular and proteomic diagnostic tests used in the evaluation and management of patients who have undergone solid organ transplantation. These tests can inform decision making along with standard clinical assessments in their evaluation of organ injury for active rejection (AR). These tests may be ordered by qualified physicians or providers operating within their scope of practice considering the diagnosis of AR, helping to rule in or out this condition and when assessing the need for or results of a diagnostic biopsy. They should be considered along with other clinical evaluations and results and may be particularly useful in patients with significant contraindications to invasive procedures.

Molecular and proteomic diagnostic tests that assess a transplanted allograft for rejection status are covered when ALL of the following criteria are met:

1. The test must provide information about at least one of the two following clinical status determinations: 
   1. AR status 
   2. Acute Cellular or Antibody-mediated rejection (ACR or AMR) status
2. The intended use of the test must be to inform clinical decision- making.
3. One of the following is true:
   1. There is clinical suspicion of rejection AND the test performs one of the following functions:
      1. Assists in the evaluation of adequacy of immunosuppression or response to treatment, wherein a non-invasive or minimally invasive test can be used in lieu of a tissue biopsy, OR
      2. Serves as a rule-out test for AR in validated populations of patients with clinical suspicion of rejection with a non-invasive or minimally invasive test to make a clinical decision regarding obtaining a biopsy, OR
      3. Further evaluates allograft status for the probability of allograft rejection after a physician-assessed pretest review of clinical and biological factors concerning for risk of rejection, OR
      4. Assesses rejection status in patients who have received a biopsy, but the biopsy results are inconclusive, unexpected given the patient’s clinico-laboratory presentation, or limited by insufficient material, OR
   2. The patient does not have clinical suspicion of rejection AND is being evaluated for subclinical rejection AND both of the following are true:
      1. The patient is not being actively evaluated for rejection (i.e. has not been tested for clinical suspicion of rejection within the prior month) AND
      2. The surveillance testing service is performed according to a clinically validated cadence (in peer-reviewed published evidence or established national consensus guidelines) utilizing the number of test timepoints that have demonstrated clinical validity and utility appropriate for the specific transplant type. NOTE:
         
         • At this time, evidence demonstrating the optimal surveillance testing cadence is in development.
         • The service may include the following number of timepoints in the first year post-transplantation: Kidney (6), Heart (12), and Lung (12). Similarly, after the first year, surveillance timepoints may continue at a frequency of 4 per year in years 2 and 3 post-transplantation and with a frequency per year thereafter according to the clinical validity and utility of the analyte in later years, as demonstrated in the peer-reviewed published literature and/or national/society guidelines.
4. The test demonstrates analytical validity (AV), including an analytical and clinical validation for any given measured analytes, and has demonstrated equivalence or superiority for sensitivity or specificity (depending on intended use) of detecting allograft rejection to other already-accepted tests for the same intended use measuring the same or directly comparable analytes under this policy.
5. Clinical validity (CV) of any analytes (or expression profiles) measured must be established through a study published in the peer-reviewed literature for the intended use of the test in the intended population. The degree of validity must be similar or superior to established and covered tests under this policy (see associated coverage Articles). If conducted with concordance to tissue histologic evaluation, the appropriate Banff Classification for renal allografts or other accepted criteria (if existing) must be used.
6. The test is being used in a patient who is part of the population (disease and intended use) in which the test was analytically validated and has demonstrated CV.
7. For a given patient encounter, only one molecular test for assessing allograft status may be performed. A test may include more than one assay; however, multianalyte and combination tests must demonstrate superiority and additive benefit when compared to respective single analytes or components.
8. For minimally or non-invasive tests, the benefit to risk profile of the molecular test is considered by the ordering clinician to be more favorable than the benefit to risk profile of a tissue biopsy, or a tissue biopsy cannot be obtained, when the test and biopsy provide similar information. For example, this may be the case if a biopsy is considered medically contraindicated in a patient.
9. The test successfully completes a MolDX Technical Assessment that will ensure that AV, CV, and clinical utility criteria set in this policy are met to establish the test as reasonable and necessary.
10. A test and biopsy should not be performed simultaneously. However, in very high-risk patients with overt signs and symptoms of rejection, a molecular test and biopsy may be performed together in urgent situations ONLY when the information derived from the test is complementary to the biopsy, established to meet CV requirements outlined above for that information, and demonstrated to improve outcomes in patients when performed along with biopsies. We expect these situations to be extremely rare.

Other transplant types will also be considered for coverage according to the criteria established in this LCD.

Covered tests with AV significantly below similar services may have coverage rescinded.

Allograft solid-organ transplantation has become a standard of care in patients with end-stage organ disease. In some patients, these treatments, along with other advances in care, have transformed fatal disease into treatable and preventable disease.^1-3 Transplant patients are placed on immunosuppressant drug therapy and are routinely monitored for indicators of rejection to prolong the survival of the donor allograft. Serologic and laboratory markers aid in monitoring graft function and in the early detection of AR which may occur as ACR or AMR.⁴ Transplant recipients may also undergo (a) surveillance biopsies to detect subclinical acute rejection (subAR) and other histologic changes that precede functional allograft decline and/or (b) for-cause biopsies when clinically indicated. With early intervention, these changes may still be amenable to treatment. Early detection of AR has led to significant improvement in allograft survival in the first 12 months post-transplantation.^5,6

The importance of graft rejection and immunosuppression was discovered early on following the development of transplantation, a challenge that started to be overcome with the availability of immunosuppressants, though with the current standard-of-care for managing solid organ transplant patients, the risk of rejection remains a problem for years after transplantation.^6-9 Though organ transplant recipients remain at risk for rejection indefinitely, the risk is highest in the first year post-transplant.^10-12 Graft assessment is also used clinically to assist in the management of immunosuppression; the clinical value it brings is that it allows modification of immunosuppressive therapy to maximize graft longevity, which is a focus of post-transplant care. Histology has traditionally been used, often in conjunction with clinical and laboratory markers, as a common graft assessment tool.^9,13-19 While histology is considered the gold standard of diagnosis at this point in time, it requires a biopsy, which is invasive and may be associated with significant risks, complications and access to care barriers.

The interpretation of relevant histopathologic findings for the purpose of guiding management also poses a challenge. For example, in kidney transplantation, there has been heterogeneity in the literature regarding the definition and treatment of borderline and subAR, making it challenging to compare results between studies.^20-25 Borderline rejection is a heterogeneous diagnosis and includes the broad range of mild “inconsequential” inflammation to clinically significant ACR that can lead to inferior graft function.²⁴ Further, subAR can be detected in up to 25% of surveillance biopsies performed in the first year following kidney transplantation (a number that may be decreasing as immunosuppressive regimens improve); however, the clinical relevance of finding borderline and subAR has been uncertain for many years.^26-28 Nevertheless, it is now generally accepted that subAR is associated with worse graft outcomes ^{20,23,26,29-31} that may be improved with early diagnosis and treatment.^32,33 In a study from the University of Wisconsin, where donor specific antibody (DSA)-based protocol biopsies were performed at months 3 and 12 for kidney transplant recipients, patients with treated subclinical acute AMR were found to have similar good outcomes as those who underwent protocol biopsy but who were without rejection.³² The treated subAR patients also fared significantly better than those who underwent a clinically indicated biopsy with or without AMR.³² Another study from Johns Hopkins University evaluated kidney transplant recipients though year 5 post-transplantation and found no statistically significant difference in graft loss for patients with treated subclinical AMR compared to their matched controls; however patients with subclinical AMR who did not receive treatment had a 3.34-fold (95% CI: 1.37–8.11; p = 0.008) higher risk of graft loss.³³ Protocol biopsies in this study, which demonstrate value for renal surveillance testing, were performed at 1, 3, 6 and 12 months following ABO- and HLA-incompatible live donor transplants.³³

Despite evidence supporting its value, up to 80% of transplant centers do not routinely perform surveillance biopsies after kidney transplantation because of the relatively low incidence of subAR, the risk–benefit ratio of protocol biopsies and the fact that protocol biopsies have not definitively been shown to improve outcomes.^23,27,28,34 Further, the most current KDIGO guidelines on the management of kidney transplant recipients (published in 2009) also do not recommend surveillance biopsies.¹² For those centers that do perform surveillance biopsies, the surveillance biopsy testing schedules are not standardized.^23,27 The current care model for monitoring patients after kidney transplantation ranges from not using surveillance biopsies at all, to using them selectively in “high-immunologic risk” patients, to routine use in all patients.^27,30,32,35 Though there is no one standard of practice regarding the performance of surveillance biopsies in kidney transplantation, some center protocols have been published.^27,36

For other transplant types such as heart and lung, surveillance biopsies have traditionally been performed more frequently for the majority of patients, given the heightened risk of rejection early in the post-transplant period, though variations in surveillance biopsy practices and interpretive histopathologic challenges of biopsy apply to these transplant types as well.^10,37-42 For example, International Society for Heart and Lung Transplantation (ISHLT) guidelines suggest that approximately 13 endomyocardial biopsies (EMBs) (or other non-invasive methods) should be performed in the first 12 months following heart transplantation.¹⁰ However, the multicenter prospective cohort study from the Genomic Research Alliance for Transplantation (GRAfT) reported that heart transplant recipients underwent approximately 8 EMBs over a median follow-up time of 17.7 months.⁴¹

Molecular diagnostic methods have emerged in an attempt to address limitations in current diagnostics including the measurement of donor-derived cell-free DNA (dd-cfDNA) and gene expression profile (GEP) assays, which have been developed for a number of organ allografts including kidney, heart, liver, and lung.^43-50 The principle underlying dd-cfDNA assays to assess rejection is that the transplantation of a new organ involves transplantation of new genetic material, and genetic material is shed into the bloodstream as part of rejection.⁵¹ The fraction of dd-cfDNA in the blood-stream may serve as a marker of rejection.^46-49 While this is a straightforward principle, DNA concentration in the bloodstream is quite small, and therefore tests relying on dd-cfDNA require advanced technological methods that can accurately capture and quantify the presence of dd-cfDNA specific to the allograft.^46,49,51 GEP tests tend to quantify expression of numerous genes indicative of immune status in the allograft recipient and use these data in algorithms developed with sophisticated modeling or machine learning to determine whether rejection is occurring.^50,52 Molecular tests can not only provide information about graft status in a minimally-invasive manner, but they can be sensitive enough to be able to detect AR before it is evident histologically or by other clinical and laboratory indicators.^41,42,51 For example, in kidney transplant recipients, dd-cfDNA values of 0.5% or more were associated with a nearly three-fold increase in risk of developing de novo DSAs; dd-cfDNA was elevated a median of 91 days prior to DSA detection, suggesting a role for dd-cfDNA as an early identifier of AR.^36,53 Further, for various transplant types, an improvement in dd-cfDNA has been reported in patients who receive treatment for rejection and have biopsy evidence of resolution.^25,41,49

Circulating Donor-Derived Cell-Free DNA tests have also demonstrated the ability to identify subclinical recurrence in a surveillance setting. The Circulating Donor-Derived Cell-Free DNA in blood for diagnosing Acute Rejection in Kidney Transplant Recipients (DART) study by Bloom et. al demonstrated the performance of dd-cfDNA in detecting allograft injury and AR; however, this study was not able to estimate the performance of dd-cfDNA to discriminate AR in patients who may have had subclinical rejection because there were only 34 surveillance biopsies and only one finding of active rejection.⁴⁷ The Assessing Donor-derived cell-free DNA Monitoring Insights of kidney Allografts with Longitudinal surveillance (ADMIRAL) study by Bu et. al subsequently compared 45 surveilled patients with findings of AR on protocol biopsy with dd-cfDNA findings.³⁶ This study found that elevation of dd-cfDNA (≥0.5%) was significantly correlated with clinical and subclinical allograft rejection in kidney transplants and that persistently elevated dd-cfDNA predicted over a 25% decline in the estimated glomerular filtration rate (eGFR) over three years.³⁶ Mantios et. al, who tested dd-cfDNA at months 1, 2, 3, and 5 post-transplantation also found that in a surveillance group, high levels of dd-cfDNA from the second month post-kidney transplantation were correlated with non-increasing eGFR one year post-transplantation; moreover, in patients with AR, levels of dd-cfDNA decreased substantially after initiation of treatment.⁵⁴ In a study of 2,882 kidney allograft recipients from 14 transplantation centers in Europe and the United States, Aubert et. al found that the inclusion of dd-cfDNA to a standard-of-care prediction model showed improved discrimination (area under the curve (AUC) 0.777 - 0.821; P = 0.0011); results were confirmed in external validation cohorts (n = 1,748).⁵⁵ Importantly, dd-cfDNA was independently associated with subclinical rejection (OR = 2.200; 95% CI 1.663-2.947, P< 0.001), showing a reclassification of 66.3% of cases with subAR (both subclinical AMR and subclinical TCMR in patients with stable kidney function and no proteinuria) over standard of care (net reclassification improvement (NRI) 0.6254; 95% CI 0.408-0.843; P< 0.001).⁵⁵ There were no statistically significant differences in dd-cfDNA levels between AMR and ACR and higher levels of dd-cfDNA were associated with higher degrees of severity of both AMR and ACR.⁵⁵ Importantly, the authors found that the independent association of dd-cfDNA with AR remained significant when dd-cfDNA was tested in the first 3 months post-transplantation (OR = 2.370; 95% CI 1.505–3.730, P < 0.001), between 3 months and 1 year post-transplantation (OR = 1.882; 95% CI 1.381–2.566, P < 0.001) and after 1 year post-transplantation (OR = 2.521; 95% CI 1.944–3.316, P < 0.001).⁵⁵ A retrospective analysis of the multicenter, prospective, observational ProActive registry study found that dd-cfDNA was significantly elevated 5 months before AMR, and 2 months before TCMR biopsies, compared with nonrejection biopsies, whereas serum creatinine did not discriminate between rejection and nonrejection in advance of, or even concurrent, with biopsy.⁵⁶ A recent study analyzing 1070 biopsies from 1743 kidney transplant recipients enrolled in the prospective, multicenter Kidney Allograft Outcomes AlloSure Registry (KOAR) again showed that dd-cfDNA levels were elevated up to 4 months and 1 month before biopsy-confirmed AMR and TCMR, respectively, and improved the pretest probability of AR in both the surveillance and for-cause settings.⁵⁷ In this study, 93.5% of samples were obtained as part of a surveillance schedule and 77.2% of the patients tested had ≥4 dd-cfDNA measurements within the first year following transplantation. In the surveillance setting, the rejection yield increased nearly 6-fold, from 7% in patients with non-elevated dd-cfDNA to 39% in patients who had elevated dd-cfDNA (P < .0001); in the for-cause group, the rejection yield increased 4-fold, from 12% in patients with non-elevated dd-cfDNA to 47% in patients with an elevated dd-cfDNA (P < .001).⁵⁷

Despite the fact that elevated dd-cfDNA may be a predictor of AR and decreased eGFR, some kidney transplant recipients with elevated dd-cfDNA remain clinically stable and it is not clear how to differentiate them from those who will develop adverse outcomes.⁵⁸ Further, dd-cfDNA has been reported to have a limited sensitivity for detecting borderline and early ACR, raising concern that reliance on this analyte could miss cases of rejection (though AMR is thought to be the more important cause of transplant failure).⁵⁹ dd-cfDNA also has a limited positive predictive value (PPV) (approximately 50-60%), suggesting that routine surveillance could potentially result in the performance of unnecessary biopsies, though this impact has not been observed in clinical utility studies to-date.⁵⁸ Nevertheless, many transplant programs in the United States are routinely surveilling kidney transplant patients with dd-cfDNA and treating both subclinical AMR and ACR, despite the fact that there continues to be significant heterogeneity in the classification and treatment of subclinical borderline and early ACR.²² dd-cfDNA tests have been proposed to reduce variance in interpretive approaches in order to better identify those patients with subclinical borderline and early ACR who are at elevated risk of graft injury.⁶⁰ In a retrospective single-center study of kidney transplant recipients, addition of dd-cfDNA to Banff biopsy scores provided better prognostic assessment over certain biopsy findings alone.⁶¹ However, that study was limited by a number of factors including the lack of standardized treatment protocols and the potential for bias introduced by exclusion of dd-cfDNA tests assessed without a biopsy.⁶¹

Most recently, studies have reported on the use of dd-cfDNA for monitoring allograft health and detecting AR in multiorgan transplantation (MOT), particularly in simultaneous pancreas-kidney (SPK) transplants.⁶² A recent multicenter study evaluated the median dd-cfDNA thresholds in pancreas and SPK transplant recipients as well as their levels in infection and AR.⁶³ Smaller single-center studies have also correlated increases in dd-cfDNA levels in patients with biopsy-proven AR and infection.^64,65 In a retrospective single-center pilot study, in SPK biopsies performed >45 days post-transplantation, dd-cfDNA quantity discriminated between those with biopsy-proven AR and those without, with a sensitivity and specificity of 85.7% and 93.7%, respectively.⁶⁴ However, in MOT involving the heart, dd-cfDNA was found to be chronically elevated in most transplant recipients with a high degree of within-patient variability in levels, which may limit the utility of dd-cfDNA in monitoring transplant recipients involving heart MOT.⁶⁶

In heart transplantation, molecular biomarker testing with GEP has been used for over a decade and, unlike the outdated Banff guidelines for kidney transplantation (at the time of this work), the ISHLT guidelines do recommend the use of molecular biomarker testing in the surveillance of heart transplant recipients without signs or symptoms of graft dysfunction.^10,67 Testing by GEP was validated for use in stable low-risk patients and for the detection of ACR.^67,68 In 2023, the guidelines expanded the use of GEP from 6 months to approximately 2 months post-transplantation based on further validation studies; it is now recommended for use between 2 months and 5 years after transplantation.^10,69,70 However, despite longstanding clinical experience with Allomap (CareDx, Brisbane, CA), ISHLT guidelines affirm that the impact of GEP-guided surveillance on long-term clinical outcomes in heart transplantation still needs further study.¹⁰ Additionally, the optimal monitoring schedule using molecular methods is unknown, though ISHLT-recommended schedules for heart transplantation have been published for the performance of DSA and biopsy “or other non-invasive methods as appropriate.”¹⁰ In recent years, dd-cfDNA testing has become more widely utilized in heart and lung transplant recipients as studies have shown good performance for the detection of AR. Studies evaluating dd-cfDNA have shown high sensitivity (78.5%-81%), specificity (76.9%-85%) and NPV (97.3%-99.2%) for AR in heart transplant recipients.^41,71 Importantly, these studies also showed good performance for clinically significant ACR, despite its lower sensitivity for ACR relative to GEP tests. Further, they have shown that dd-cfDNA levels may rise weeks to months before AR is diagnosed on biopsy.^41,42,72-74 For example, in the GRAfT study, 80% of dd-cfDNA elevations in heart transplant recipients were associated with a negative EMB.⁴¹ Importantly, the majority of these (76%) were considered clinically significant because they were associated with allograft dysfunction or preceded histopathologic rejection by up to 3.2 months.⁴¹ In lung transplant recipients, higher dd-cfDNA values were associated with a significantly higher hazard of chronic lung allograft dysfunction (CLAD) or death than those with lower levels.⁷⁵ Moreover, during the COVID-19 pandemic, a home-based surveillance program using plasma dd-cfDNA instead of surveillance bronchoscopy identified early episodes of AR and infection that would not have been identified using a clinically indicated biopsy strategy alone.⁴⁰ As a result, some heart and lung transplant centers have adopted dd-cfDNA for surveillance alongside reduction in the number of biopsies during the first years post-transplantation, when the risk of AR is highest and when levels of molecular markers such as dd-cfDNA are predictable.^{10,11,39,40,42,74,76}

Given the acceptance of GEP testing, studies subsequently attempted to evaluate the value of adding dd-cfDNA to GEP in heart transplant patients, as both approaches are thought to measure different indicators of graft injury and rejection and consequently have different strengths and weaknesses in ACR vs AMR detection.⁴² In a single-center retrospective review of combined GEP and dd-cfDNA testing for AR surveillance, Gondi et. al found that combination testing at 6 months post-transplant resulted in the cancellation of 83.9% EMBs as opposed to 71.2% using a GEP-only surveillance approach.⁷⁷ This decrease was driven primarily by the 87 GEP (+) and dd-cfDNA (-) results that would have previously resulted in an EMB but were reassigned to a lower risk group with the addition of dd-cfDNA. Notably, there were very few rejections in the cohort (two AMR and two grade 2 ACR), and dd-cfDNA detected them all while GEP missed the cases with AMR.⁷⁷ Another single center, retrospective analysis by Henricksen et. al found that at one year post transplantation, there were no differences between the paired testing with dd-cfDNA/GEP testing and GEP/biopsy-only cohorts in terms of survival or rejection-free survival, though paired testing was associated with fewer EMBs. However, their paired testing cohort only included 3 episodes of clinically significant ACR, two of which were detected by both dd-cfDNA and GEP and one of which was not detected by either test, and there was not a standard protocol for reacting to the results of the noninvasive surveillance.⁷⁸ In a retrospective observational study of more than 400 samples from 112 unique heart transplant patients who underwent combination testing with both dd-cfDNA and GEP, Rodgers et. al observed a significantly improved specificity without a significant change in sensitivity when using dd-cfDNA instead of a combination testing approach (sensitivity: 36.8% dd-cfDNA vs 50.5% combination testing, p=0.99; specificity: 86.3% dd-cfDNA vs 46.8% combination testing, p < 0.0001); this study identified 13 samples associated with AR, 10 of which were ACR.⁷⁹ Based on their findings, the authors conclude that dd-cfDNA testing without GEP is sufficient, agreeing with other reports that dd-cfDNA alone has the potential to replace or significantly reduce the need for EMB.^{41,42,71,72,79} In a more recent analysis of that study, Moayedi and Teuteberg showed that in a low-risk population, combination testing was associated with an elevated specificity for ACR (combination testing 92.5% (89.1-95.0) vs. GEP 52.1% (46.5-57.7) vs dd-cfDNA 81.8% (78.0-85.4)), with a positive likelihood ratio (LR) of 4.97 (1.87-13.21), while the LRs for GEP and dd-cfDNA alone were 1.04 (0.52-2.11) and 1.66 (0.63-4.37), respectively, raising the analogous post-test probabilities from 2.4 (1.2-4.8) and 3.7 (1.5-9.3) to 10.5 (4.2-23.7).⁸⁰

A prospective cohort study of 565 plasma samples collected longitudinally from 65 adult and pediatric transplant recipients also reported that dd-cfDNA showed superior test performance when compared to AlloMap [AUC dd-cfDNA = 0.83; AUC AlloMap = 0.72];⁷² notably, they compared the performance of dd-cfDNA from their study with that of AlloMap as reported in another study by Deng et. al.⁶⁸ Finally, the performance of combination testing for ACR surveillance was evaluated in the Surveillance HeartCare Outcomes Registry (SHORE) study.⁸¹ The reported sensitivity, specificity, and (LR) for combination testing was 32.3%, 91.7% and 3.90 (95% CI: 3.08-4.96); sensitivities, specificities and LRs for testing with GEP alone were 59%, 56.8% and 1.37 (95% CI: 1.20-1.56) and 44.7%, 84.6% and 2.91 (95% CI: 2.43-3.49) for dd-cfDNA alone.⁸¹ Of the 156 grade 2 ACR events reported, only 31.4% were dual positive (49/156) while another 30% were dual negative (46/156) by molecular testing.⁸¹ The incidence of ACR in the GEP negative/dd-cfDNA negative group (1.5%; 95% CI: 1.1%-2.0%) was not significantly different from that of the GEP positive/dd-cfDNA negative group (1.9%; 95% CI: 1.4%- 2.6%); however, in the GEP negative/dd-cfDNA positive and dual positive groups it was 4.3% (95% CI: 2.8%-6.6%) and 9.2% (95% CI: 7.1%-11.9%), respectively.⁸¹ Of the dd-cfDNA positive tests (n=1026), 72 (7%) showed clinically significant ACR, similar to the dual positive tests (9.2%). Notably, ACR was observed most frequently in the first 30 days post-transplant. Follow-up biopsies were performed after 8.8% of dual negative molecular tests, 14.2% of GEP positive/dd-cfDNA negatives, 22.8% of GEP negative/dd-cfDNA positives, and 35.4% of dual positives, and the number of overall biopsies performed declined over the course of the study period. At two years, survival was 94.9%, and only 2.7% had graft dysfunction.⁸¹

There is considerably limited evidence for combination testing using dd-cfDNA and GEP in kidney transplantation.^82,83 While there is literature evaluating the use of GEPs in kidney transplant recipients,^30,84,85 to-date the American Society of Transplant Surgeons (ASTS) and the European Society of Organ Transplantation (including expert members from the United States) do not support GEP or combination testing for this indication.^86,87

Just as there is no one standard of practice regarding the performance of surveillance biopsies, particularly in kidney transplantation, there is also not a standard practice for the performance of surveillance molecular tests, though some center protocols have been published in the literature.^36,88 Questions remain regarding which patients would benefit most from routine serial testing, how often to test, and the appropriate steps to further evaluate an elevated dd-cfDNA.^25,89 Minimally invasive testing should “allow for a biomarker stratified approach for those at a higher risk of harboring subAR.”³⁰

Importantly, these molecular tests are not meant to be used in isolation. Rather, they are part of a constellation of clinico-laboratory data used to evaluate the patient.⁵⁹ Accordingly, the 2022 Banff-Canadian Society of Transplantation Joint Meeting and the Banff Minimally Invasive Diagnostics Working Group have concluded that these biomarkers should not be used alone to monitor patients in the setting of stable allograft function.^59,90

While these technologies are newer, large and multicenter studies have supported their use in renal, heart, and lung transplantation as minimally and non-invasive methods to assess allograft status, modify immunosuppression regimens, and avoid unnecessary biopsies.^{11,40,46,47,50} Evidence continues to develop for other transplant allograft organs and other analytes.^45,91-94

Contractor Advisory Committee (CAC) Summary

Kidney and Liver Allograft CAC

On November 16, 2022, Noridian and Palmetto jointly facilitated a CAC to discuss molecular testing for the diagnosis of acute rejection in kidney or liver transplant recipients where GEP, dd-cfDNA, and multiomic tests were discussed. The subject matter experts (SMEs) expressed a high degree of certainty that there is sufficient evidence to support the use of molecular tests like dd-cfDNA in kidney allograft patients.

Heart and Lung Allograft CAC

On November 17, 2022, Noridian and Palmetto jointly facilitated a CAC to discuss molecular testing for the diagnosis of acute rejection in heart or lung transplant recipients where GEP and dd-cfDNA tests were discussed. The SMEs were unanimous that the evidence is sufficient to support the use of GEP and/or dd-cfDNA for surveillance of acute organ injury to help replace an unnecessary biopsy. However, they also agreed that there is a lack of data to support the routine use of molecular combination testing. Moreover, they did not endorse the use of molecular diagnostic tests in lieu of biopsy in patients with a very high clinical and laboratory suspicion for acute rejection and who can also safely tolerate a biopsy. All SMEs agreed that these tests do not discern the etiology of organ injury, indicating that they had a high degree of confidence in the detection of allograft injury, but additional clinical testing was necessary to discern the cause.

Notably, additional evidence regarding the use of non-invasive allograft rejection testing has been developed since the time of the CAC meetings and has been incorporated into this LCD.

Documents associated with the CAC meetings can be found here:

Contractor Advisory Committee (CAC) - JE Part B - Noridian (noridianmedicare.com)

Graft assessment is a well-accepted part of solid organ transplant management. Evidence clearly shows that patients are living with functioning organs transplanted from immunologically and genetically distinct individuals using current transplant management techniques, which may demonstrate significant heterogeneity among centers or even among individual physicians. For example, the CAC SMEs acknowledged that only approximately 18% of transplant centers perform routine surveillance biopsies in kidney transplant patients, because the evidence on the benefit of that practice is conflicting. Similarly, some centers have moved away from performing protocol biopsies in other transplant types due to the highly invasive nature of the procedures and the high risk of complications.

It is also well accepted within the transplant community that the management of immunosuppression is an important component of post-transplant care to both optimize graft longevity while avoiding side effects and toxicity of immunosuppressive therapies. Graft assessment is an important decision tool used to help clinicians optimize immunosuppressive treatment. The gold standard for assessing rejection or injury has historically been and remains a biopsy in conjunction with clinical and laboratory criteria. However, given the invasive nature and risks associated with a biopsy, tests that can potentially mitigate the need for a biopsy while still providing clinicians with actionable information that can be used to help optimize immunosuppressive therapy are reasonable and necessary. Additionally, studies have supported that dd-cfDNA and GEP can accurately determine allograft status in several organ types, and that molecular characterization can both precede and enhance histologic and other laboratory findings of AR. As such, these approaches, as a service type, are reasonable and necessary for graft assessment.

Optimal outcomes of the use of molecular biomarkers in the context of allograft rejection monitoring include the reduction in the number of overall and negative biopsies and the accurate detection and exclusion of AR and subAR. Potential risks of using these biomarkers include missing subAR (particularly subclinical ACR) or other causes of graft injury and, on the other side, subjecting patients to the unnecessary risks of a negative surveillance biopsy because of a false positive result. Nevertheless, the evidence to-date has not shown an increase in such negative early outcomes. Rather, reports have shown that these tests can safely obviate the need for invasive biopsy in many cases. Further, the sensitivity of some of these molecular tests (i.e., dd-cfDNA in heart transplantation) for the early detection of rejection events has challenged the gold-standard status of the biopsy altogether.

This contractor recognizes the newer literature supporting the use of surveillance biopsies as well as molecular testing for surveillance to identify subclinical rejection and allow for early intervention, even where surveillance using biopsy for the same purpose might not be worth the attendant risk and morbidity. However, the optimal interval of surveillance monitoring with molecular tests has not been defined for any transplant type and prospective studies are still ongoing to assess the impact of serial dd-cfDNA surveillance in transplant recipients. An additional challenge is the wide variability in practice among transplant centers. Physicians know best how to manage the care of their patients. However, as a Medicare Administrative Contractor (MAC), we are required by statute to provide coverage for and reimburse services determined to be reasonable and necessary (R&N) according to the published medical evidence. As such, this contractor will issue coverage for molecular tests used for the purpose of surveillance according to a cadence that is R&N based on the prevalence of acute rejection for a given transplant type as well as the available (albeit limited) evidence on outcomes associated with surveillance testing approaches. In kidney transplantation, the DART study established the clinical validity of dd-cfDNA by demonstrating its value over serum creatinine in the discrimination of AR using a testing schedule developed empirically based on the KDIGO recommended testing frequencies for non-molecular noninvasive monitoring tests.^12,47 While this focused the most frequent testing at the time of highest immunologic risk, it was not clear that this testing schedule improved patient outcomes. Moreover, the study findings were only relevant to patients with clinical suspicion of rejection. Since then, studies have correlated dd-cfDNA with clinical indicators such as eGFR and response to treatment using less frequent surveillance testing schedules.^54,55,95 ADMIRAL and more recent large-scale studies, including the prospective multicenter KOAR study, have shown a significant yield for detecting AR, with KOAR also showing a substantial lead time using dd-cfDNA surveillance (with levels rising months before antibody detection and preceding both AMR and TCMR) with ≥4 testing timepoints in the first-year post-transplantation; however, it is not clear whether patients with more than 4 tests achieved better outcomes than those who received 4, nor is it clear what the optimal number would be if more than 4. Nevertheless, given that the lead time for TCMR detection is approximately 60 days and that the subclinical rejection rate is front-loaded in the first 6 months post-transplantation, this contractor recognizes that a 6 timepoint schedule in the first year is likely to detect subclinical rejection during periods when the risk of rejection is greatest and when clinical and diagnostic blindspots exist. A similar logic follows for other covered transplant types such as heart and lung, for which the maximum allowable surveillance test limit is twelve in the first year post transplantation.^10,39-42 After the first year, surveillance testing may continue at a decreased frequency, as supported by evidence of analyte predictability, improved patient outcomes, and mirroring current surveillance schedules.^{10,40,42,96,97} This approach is expected to identify patients at high risk of AR months before clinical signs and symptoms develop, allowing for intervention before irreversible damage to the graft occurs. Further, given the limited but evolving evidence regarding the frequency of surveillance testing, this contractor recognizes that evidence may be generated that demonstrates improved outcomes using a different schedule or number of testing timepoints; these altered schedules would be compliant with this policy without need for amendment as they would fulfill existing coverage requirements listed above.

Although the use of combined GEP and dd-cfDNA testing in heart transplant patients has been previously covered and broadly used, it should be noted that initial coverage was set without supporting peer reviewed published evidence. At this time, there is insufficient compelling evidence to support the routine use of molecular combination testing (i.e. with dd-cfDNA and GEP) for any transplant type, with the possible exception of heart. While the ASTS position statement does support combination testing (in heart transplantation only), it does not supply compelling evidence of improved patient outcomes to support this recommendation.⁸⁶ Most of the studies that evaluated combination testing with both biomarkers compared that approach with testing by GEP alone. Some of those studies (such as the ones by Gondi et. al and Henricksen et. al) had very few episodes of AR and were underpowered to draw meaningful conclusions regarding any long-term outcomes-based benefit from combination testing, although Henrickson et al. did show a statistically significant reduction in the number of biopsies performed in patients who had undergone combination testing, from a median of 10 to a median of 4 biopsies per patient (p<0.01) in the first year.⁷⁸ Further, publications have suggested that testing by dd-cfDNA alone may provide a superior alternative to GEP, as supported by Rodgers et. al who showed a decrease in specificity with no change in sensitivity or NPV when GEP was added to dd-cfDNA testing for heart transplant recipients, though that study was also limited by few episodes of ACR.⁷⁹ Similarly, Saeyeldin et al. states that, “we utilize the HeartCare panel (CareDx, Inc.) which combines GEP testing (Allomap) and dd-cfDNA (Allosure) for surveillance of asymptomatic patients; however, GEP testing generally played little role in decision making.”⁹⁷ dd-cfDNA was also the apparent driver of improved performance in the SHORE registry study as the GEP-positive/dd-cfDNA-negative group did not perform better than the dual negative group. Additionally, combination testing still missed the majority of ACRs (sensitivity was only 33%) without any clear benefit in specificity when compared to dd-cfDNA alone. Of note, the prevalence of AR was highest in the first 30 days, making predictive values very different early versus later in the study, particularly when GEP is also not validated for use prior to 55 days post-transplant. Moreover, it is unclear whether the difference between the 7% vs 9% incidences of ACR reported in the SHORE study (for dd-cfDNA positive vs dual positive results, respectively), while statistically significant, is truly meaningful from a clinical management standpoint. However, the study also found that clinicians biopsied those with a positive dd-cfDNA but negative GEP less frequently compared to patients with a dual positive test, and dual negative dd-cfDNA-GEP tests resulted in the fewest biopsies performed with no adverse outcomes.⁸¹ Further, in a more recent analysis of the Rodgers study, combination testing was associated with greater specificity and positive LR for ACR than those from GEP and dd-cfDNA alone, raising the analogous post-test probabilities.⁸⁰ Though the LR confidence intervals were wide and overlapping, the 10.5% post-test probability of ACR has been deemed a clinically meaningful increase above the 2-3% pre-test probability observed in asymptomatic patients in the first two years post-transplantation.⁸⁰

Studies evaluating dd-cfDNA alone have shown high sensitivity, specificity and NPV for AR as well as ACR in heart transplant recipients; further, they have also shown that dd-cfDNA can detect clinically significant but histologically silent allograft injury.^41,42,71-74 These studies affirm that dd-cfDNA can independently and significantly reduce the need for surveillance biopsies, and potentially replace such biopsies altogether. In sum, the evidence developed shows that dd-cfDNA is, at a minimum, non-inferior to GEP for the detection of allograft injury and rejection and that the addition of GEP to dd-cfDNA provides modest incremental additional value in specificity and in moderating the risk for ACR. However, it is unclear whether this additional incremental value is only applicable to certain clinical situations (such as for use in further stratifying patients with intermediate dd-cfDNA values) rather than to all clinical scenarios as part of a routinely performed combination test, as proposed by Saeyeldin et al.⁹⁷ Importantly, ISHLT guidelines assign a class IIa recommendation to use of GEP in low-risk patients between 2 months and 5 years, though there is no specific guidance on the interpretation of these results in different clinical scenarios, including those involving discrepant dd-cfDNA test results.¹⁰ Moreover, the studies evaluating dd-cfDNA and GEP have used “varying thresholds for both analytes, and there is no generally-agreed upon protocol for paired testing.”⁸⁰ Nevertheless, studies have shown that the use of GEP/dd-cfDNA noninvasive testing has been associated with lower biopsy rates over time, as well as non-inferior outcomes in survival and graft dysfunction, compared to surveillance using a GEP/biopsy strategy.^80.81 This likely reflects (1) physician behavior, comfort with the long-standing GEP test, and confidence in the results of combination testing rather than a sizeable difference in performance (between combination testing and testing with dd-cfDNA alone) and (2) the generally excellent survival after cardiac transplantation, even without an overabundance of molecular rejection surveillance tests or biopsies. Nevertheless, given the overall impact from the use of combination testing on decreasing the number of heart biopsies performed without any negative patient outcomes, this contractor will maintain coverage of combination testing for the purpose of surveillance in heart transplant patients. Further, while GEP will continue to be covered in heart transplantation as it has become a standard of practice, providers should be aware that they may be performing an inferior service if performed alone. Should evolving literature clearly support dd-cfDNA as superior to GEP or combination testing or demonstrate no clear value for GEP testing, this coverage decision will be modified to reflect the new evidence.

While the literature regarding the use of dd-cfDNA in MOT is newer, it is evolving rapidly, and findings suggest it may be a useful tool for surveillance in select MOTs as it has become for certain single-organ transplants.

Non-invasive graft assessment remains an actively evolving area of medicine as does the assessment of graft rejection via histology. As such, this contractor will continue to monitor new evidence that may impact this coverage decision, and may reconsider this policy in light of new evidence development.

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1. The United States Renal Data System (USRDS) 2021 Annual Data Report (ADR). https://usrds-adr.niddk.nih.gov/2021/end-stage-renal-disease/7-transplantation. Accessed 4/24/2026.
2. Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail. 2016;18(8):891-975. doi:10.1002/ejhf.592
3. Yancy CW, Jessup M, Bozkurt B, et al. 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. J Am Coll Cardiol. 2013;62(16):e147-e239. doi:10.1016/j.jacc.2013.05.019
4. McManigle W, Pavlisko EN, Martinu T. Acute cellular and antibody-mediated allograft rejection. Semin Respir Crit Care Med. 2013;34(3):320-335. doi:10.1055/s-0033-1348471
5. Serón D, Arns W, Chapman JR. Chronic allograft nephropathy—clinical guidance for early detection and early intervention strategies. Nephrol Dial Transplant. 2008;23(8):2467-2473. doi:10.1093/ndt/gfn130
6. Lamb KE, Lodhi S, Meier-Kriesche HU. Long-term renal allograft survival in the United States: a critical reappraisal. Am J Transplant. 2011;11(3):450-462. doi:10.1111/j.1600-6143.2010.03283.x
7. United States Government Accountability Office. End-Stage Renal Disease: Characteristics of Kidney Transplant Recipients, Frequency of Transplant Failures, and Cost to Medicare. GAO-07-1117. Published: 2007.
8. Stegall MD, Gaston RS, Cosio FG, Matas A. Through a glass darkly: seeking clarity in preventing late kidney transplant failure. J Am Soc Nephrol. 2015;26(1):20-29. doi:10.1681/asn.2014040378
9. Stehlik J, Kobashigawa J, Hunt SA, Reichenspurner H, Kirklin JK. Honoring 50 years of clinical heart transplantation in Circulation: in-depth state-of-the-art review. Circulation. 2018;137(1):71-87. doi:10.1161/circulationaha.117.029753
10. Velleca A, Shullo MA, Dhital K, et al. The International Society for Heart and Lung Transplantation (ISHLT) guidelines for the care of heart transplant recipients. J Heart Lung Transplant. 2023;42(5):e1-e141. doi:10.1016/j.healun.2022.10.015
11. Khush KK, Patel J, Pinney S, et al. Noninvasive detection of graft injury after heart transplant using donor-derived cell-free DNA: a prospective multicenter study. Am J Transplant. 2019;19(10):2889-2899. doi:10.1111/ajt.15339
12. Kidney Disease: Improving Global Outcomes (KDIGO) Transplant Work Group. KDIGO clinical practice guideline for the care of kidney transplant recipients. Am J Transplant. 2009;9 Suppl 3:S1-S155. doi:10.1111/j.1600-6143.2009.02834.x
13. Haas M, Loupy A, Lefaucheur C, et al. The Banff 2017 Kidney Meeting Report: revised diagnostic criteria for chronic active T cell-mediated rejection, antibody-mediated rejection, and prospects for integrative endpoints for next-generation clinical trials. Am J Transplant. 2018;18(2):293-307. doi:10.1111/ajt.14625
14. Solez K, Axelsen RA, Benediktsson H, et al. International standardization of criteria for the histologic diagnosis of renal allograft rejection: the Banff working classification of kidney transplant pathology. Kidney Int. 1993;44(2):411-422. doi:10.1038/ki.1993.259
15. Bruneval P, Angelini A, Miller D, et al. The XIIIth Banff Conference on Allograft Pathology: The Banff 2015 Heart Meeting Report: improving antibody-mediated rejection diagnostics: strengths, unmet needs, and future directions. Am J Transplant. 2017;17(1):42-53. doi:10.1111/ajt.14112
16. Stewart S, Fishbein MC, Snell GI, et al. Revision of the 1996 working formulation for the standardization of nomenclature in the diagnosis of lung rejection. J Heart Lung Transplant. 2007;26(12):1229-1242. doi:10.1016/j.healun.2007.10.017
17. Stewart S, Winters GL, Fishbein MC, et al. Revision of the 1990 working formulation for the standardization of nomenclature in the diagnosis of heart rejection. J Heart Lung Transplant. 2005;24(11):1710-1720. doi:10.1016/j.healun.2005.03.019
18. Mehra MR. Heart transplantation at 50. Lancet. 2017;390(10111):e43-e45. doi:10.1016/s0140-6736(17)33093-3
19. Nankivell BJ, Alexander SI. Rejection of the kidney allograft. N Engl J Med. 2010;363(15):1451-1462. doi:10.1056/NEJMra0902927
20. Seifert ME, Agarwal G, Bernard M, et al. Impact of subclinical borderline inflammation on kidney transplant outcomes. Transplant Direct. 2021;7(2):e663. doi:10.1097/txd.0000000000001119
21. Seron D, Rabant M, Becker JU, et al. Proposed definitions of T cell-mediated rejection and tubulointerstitial inflammation as clinical trial endpoints in kidney transplantation. Transpl Int. 2022;35:10135. doi:10.3389/ti.2022.10135
22. Loupy A, Haas M, Roufosse C, et al. The Banff 2019 Kidney Meeting Report (I): updates on and clarification of criteria for T cell- and antibody-mediated rejection. Am J Transplant. 2020;20(9):2318-2331. doi:10.1111/ajt.15898
23. Rush DN, Gibson IW. Subclinical inflammation in renal transplantation. Transplantation. 2019;103(6):e139-e145. doi:10.1097/TP.0000000000002682
24. Nankivell BJ, Agrawal N, Sharma A, et al. The clinical and pathological significance of borderline T cell-mediated rejection. Am J Transplant. 2019;19(5):1452-1463. doi:10.1111/ajt.15197
25. Gupta G, Moinuddin I, Kamal L, et al. Correlation of donor-derived cell-free DNA with histology and molecular diagnoses of kidney transplant biopsies. Transplantation 2022;106(5):1061-1070. doi:10.1097/tp.0000000000003838
26. Naesens M, Friedewald J, Mas V, Kaplan B, Abecassis MM. A practical guide to the clinical implementation of biomarkers for subclinical rejection following kidney transplantation. Transplantation. 2020;104(4):700-707. doi:10.1097/TP.0000000000003064
27. Mehta R, Cherikh W, Sood P, Hariharan S. Kidney allograft surveillance biopsy practices across US transplant centers: a UNOS survey. Clin Transplant. 2017;31(5):10.1111/ctr.12945. doi:10.1111/ctr.12945
28. Rush D, Arlen D, Boucher A, et al. Lack of benefit of early protocol biopsies in renal transplant patients receiving TAC and MMF: a randomized study. Am J Transplant. 2007;7(11):2538-45. doi:10.1111/j.1600-6143.2007.01979.x
29. Ortiz F, Gelpi R, Helanterä I, et al. Decreased kidney graft survival in low immunological risk patients showing inflammation in normal protocol biopsies. PLoS One. 2016;11(8):e0159717. doi:10.1371/journal.pone.0159717
30. Friedewald JJ, Kurian SM, Heilman RL, et al. Development and clinical validity of a novel blood-based molecular biomarker for subclinical acute rejection following kidney transplant. Am J Transplant. 2019;19(1):98-109. doi:10.1111/ajt.15011
31. Mehta R, Bhusal S, Randhawa P, et al. Short-term adverse effects of early subclinical allograft inflammation in kidney transplant recipients with a rapid steroid withdrawal protocol. Am J Transplant. 2018;18(7):1710-1717. doi:10.1111/ajt.14627
32. Parajuli S, Joachim E, Alagusundaramoorthy S, et al. Subclinical antibody-mediated rejection after kidney transplantation: treatment outcomes. Transplantation. 2019;103(8):1722-1729. doi:10.1097/tp.0000000000002566
33. Orandi BJ, Chow EHK, Hsu A, et al. Quantifying renal allograft loss following early antibody-mediated rejection. Am J Transplant. 2015;15(2):489-498. doi:10.1111/ajt.12982
34. Lee DM, Abecassis MM, Friedewald JJ, Rose S, First MR. Kidney graft surveillance biopsy utilization and trends: results from a survey of high-volume transplant centers. Transplant Proc. 2020;52(10):3085-3089. doi:10.1016/j.transproceed.2020.04.1816
35. Naesens M. The special relativity of noninvasive biomarkers for acute rejection. Am J Transplant. 2019;19(1):5-8. doi:10.1111/ajt.15078
36. Bu L, Gupta G, Pai A, et al. Clinical outcomes from the assessing donor-derived cell-free DNA monitoring insights of kidney allografts with longitudinal surveillance (ADMIRAL) study. Kidney Int. 2022;101(4):793-803. doi:10.1016/j.kint.2021.11.034
37. Goldberg JF, Truby LK, Agbor-Enoh S, et al. Selection and interpretation of molecular diagnostics in heart transplantation. Circulation. 2023;148(8):679-694. doi:10.1161/circulationaha.123.062847
38. Parulekar AD, Kao CC. Detection, classification, and management of rejection after lung transplantation. J Thorac Dis. 2019;11(Suppl 14):S1732-S1739. doi:10.21037/jtd.2019.03.83
39. Martinu T, Koutsokera A, Benden C, et al. International Society for Heart and Lung Transplantation consensus statement for the standardization of bronchoalveolar lavage in lung transplantation. J Heart Lung Transplant. 2020;39(11):1171-1190. doi:10.1016/j.healun.2020.07.006
40. Keller M, Sun J, Mutebi C, et al. Donor-derived cell-free DNA as a composite marker of acute lung allograft dysfunction in clinical care. J Heart Lung Transplant. 2022;41(4):458-466. doi:10.1016/j.healun.2021.12.009
41. Agbor-Enoh S, Shah P, Tunc I, et al. Cell-free DNA to detect heart allograft acute rejection. Circulation. 2021;143(12):1184-1197. doi:10.1161/circulationaha.120.049098
42. Holzhauser L, DeFilippis EM, Nikolova A, et al. The end of endomyocardial biopsy?: A practical guide for noninvasive heart transplant rejection surveillance. JACC Heart Fail. 2023;11(3):263-276. doi:10.1016/j.jchf.2022.11.002
43. Rosenheck JP, Ross DJ, Botros M, et al. Clinical validation of a plasma donor-derived cell-free DNA assay to detect allograft rejection and injury in lung transplant. Transplant Direct. 2022;8(4):e1317. doi:10.1097/txd.0000000000001317
44. Richmond ME, Zangwill SD, Kindel SJ, et al. Donor fraction cell-free DNA and rejection in adult and pediatric heart transplantation. J Heart Lung Transplant. 2020;39(5):454-463. doi:10.1016/j.healun.2019.11.015
45. Levitsky J, Asrani SK, Schiano T, et al. Discovery and validation of a novel blood-based molecular biomarker of rejection following liver transplantation. Am J Transplant. 2020;20(8):2173-2183. doi:10.1111/ajt.15953
46. Sigdel TK, Archila FA, Constantin T, et al. Optimizing detection of kidney transplant injury by assessment of donor-derived cell-free DNA via massively multiplex PCR. J Clin Med. 2018;8(1):19. doi:10.3390/jcm8010019
47. Bloom RD, Bromberg JS, Poggio ED, et al. Cell-free DNA and active rejection in kidney allografts. J Am Soc Nephrol. 2017;28(7):2221-2232. doi:10.1681/asn.2016091034
48. Bromberg JS, Brennan DC, Poggio E, et al. Biological variation of donor-derived cell-free DNA in renal transplant recipients: clinical implications. J Appl Lab Med. 2017;2(3):309-321. doi:10.1373/jalm.2016.022731
49. Grskovic M, Hiller DJ, Eubank LA, et al. Validation of a clinical-grade assay to measure donor-derived cell-free DNA in solid organ transplant recipients. J Mol Diagn. 2016;18(6):890-902. doi:10.1016/j.jmoldx.2016.07.003
50. Marsh CL, Kurian SM, Rice JC, et al. Application of TruGraf v1: a novel molecular biomarker for managing kidney transplant recipients with stable renal function. Transplant Proc. 2019;51(3):722-728. doi:10.1016/j.transproceed.2019.01.054
51. Beck J, Oellerich M, Schulz U, et al. Donor-derived cell-free DNA is a novel universal biomarker for allograft rejection in solid organ transplantation. Transplant Proc. 2015;47(8):2400-2403. doi:10.1016/j.transproceed.2015.08.035
52. Kurian SM, Velazquez E, Thompson R, et al. Orthogonal comparison of molecular signatures of kidney transplants with subclinical and clinical acute rejection: equivalent performance is agnostic to both technology and platform. Am J Transplant. 2017;17(8):2103-2116. doi:10.1111/ajt.14224
53. Mayer KA, Doberer K, Tillgren A, et al. Diagnostic value of donor-derived cell-free DNA to predict antibody-mediated rejection in donor-specific antibody-positive renal allograft recipients. Transpl Int. 2021;34(9):1689-1702. doi:10.1111/tri.13970
54. Mantios E, Filiopoulos V, Constantoulakis P, et al. Assessment of donor derived cell free DNA (dd-cfDNA) at surveillance and at clinical suspicion of acute rejection in renal transplantation. Transpl Int. 2023;36:11507. doi:10.3389/ti.2023.11507
55. Aubert O, Ursule-Dufait C, Brousse R, et al. Cell-free DNA for the detection of kidney allograft rejection. Nat Med. 2024;30(8)2320-2327. doi:10.1038/s41591-024-03087-3
56. Bromberg JS, Bunnapradist S, Samaniego-Picota M, et al. Elevation of donor-derived Cell-free DNA before biopsy-proven rejection in kidney transplant. Transplantation. 2024;108(9):1994-2004. doi:10.1097/TP.0000000000005007
57. Bromberg JS, Brennan DC, Taber DJ, et al. Donor-derived cell-free DNA significantly improves rejection yield in kidney transplant biopsies. Am J Transplant. 2025;25(12):2529-2542. doi:10.1016/j.ajt.2025.07.2484
58. Huang E, Haas M, Gillespie M, et al. An assessment of the value of donor-derived cell-free DNA surveillance in patients with preserved kidney allograft function. Transplantation. 2023;107(1):274-282. doi:10.1097/tp.0000000000004267
59. Huang E, Mengel M, Clahsen-van Groningen MC, Jackson AM. Diagnostic potential of minimally invasive biomarkers: a biopsy-centered viewpoint from the Banff Minimally Invasive Diagnostics Working Group. Transplantation. 2023;107(1):45-52. doi:10.1097/tp.0000000000004339
60. Stites E, Kumar D, Olaitan O, et al. High levels of dd-cfDNA identify patients with TCMR 1A and borderline allograft rejection at elevated risk of graft injury. Am J Transplant. 2020;20(9):2491-2498. doi:10.1111/ajt.15822
61. Huang E, Gillespie M, Ammerman N, et al. Donor-derived cell-free DNA combined with histology improves prediction of estimated glomerular filtration rate over time in kidney transplant recipients compared with histology alone. Transplant Direct. 2020;6(8):e580. doi:10.1097/txd.0000000000001027
62. Drachenberg CB, Buettner-Herold M, Aguiar PV, et al. Banff 2022 pancreas transplantation multidisciplinary report: refinement of guidelines for T cell-mediated rejection, antibody-mediated rejection and islet pathology. Assessment of duodenal cuff biopsies and noninvasive diagnostic methods. Am J Transplant. 2024;24(3):362-379. doi:10.1016/j.ajt.2023.10.011
63. Yoo A, Riedel A, Qian I, et al. An initial analysis of the baseline levels of dd-cfDNA sfter pancreas transplantation: a prospective study from high-volume centers in the United States. Transplant Direct. 2023;9(4):e1459. doi:10.1097/TXD.0000000000001459
64. Ventura-Aguiar P, Ramirez-Bajo MJ, Rovira J, et al. Donor-derived cell-free DNA shows high sensitivity for the diagnosis of pancreas graft rejection in simultaneous pancreas-kidney transplantation. Transplantation. 2022;106(8):1690-1697. doi:10.1097/TP.0000000000004088
65. Williams MD, Fei M, Schadde E, Hollinger EF, Chan EY, Olaitan O. Early experience using donor-derived cell-free DNA for surveillance of rejection following simultaneous pancreas and kidney transplantation. Transplant Direct. 2022;8(5):e1321. doi:10.1097/TXD.0000000000001321
66. Moeller CM, Oren D, Fernandez Valledor A, et al. Clinical utility of donor-derived cell-free DNA in heart transplant recipients with multi-organ transplants. Clin Transplant. 2024;38(10):e15479. doi:10.1111/ctr.15479
67. Pham MX, Teuteberg JJ, Kfoury AG, et al. Gene-expression profiling for rejection surveillance after cardiac transplantation. N Engl J Med. 2010;362(20):1890-1900. doi:10.1056/NEJMoa0912965
68. Deng MC, Eisen HJ, Mehra MR, et al. Noninvasive discrimination of rejection in cardiac allograft recipients using gene expression profiling. Am J Transplant. 2006;6(1):150-160. doi:10.1111/j.1600-6143.2005.01175.x
69. Kobashigawa J, Patel J, Azarbal B, et al. Randomized pilot trial of gene expression profiling versus heart biopsy in the first year after heart transplant: early invasive monitoring attenuation through gene expression trial. Circ Heart Fail. 2015;8(3):557-564. doi:10.1161/CIRCHEARTFAILURE.114.001658
70. Crespo-Leiro MG, Stypmann J, Schulz U, et al. Clinical usefulness of gene-expression profile to rule out acute rejection after heart transplantation: CARGO II. Eur Heart J. 2016;37(33):2591-2601. doi:10.1093/eurheartj/ehv682
71. Kim PJ, Olymbios M, Siu A, et al. A novel donor-derived cell-free DNA assay for the detection of acute rejection in heart transplantation. J Heart Lung Transplant. 2022;41(7):919-927. doi:10.1016/j.healun.2022.04.002
72. De Vlaminck I, Valantine HA, Snyder TM, et al. Circulating cell-free DNA enables noninvasive diagnosis of heart transplant rejection. Sci Transl Med. 2014;6(241):241ra77. doi:10.1126/scitranslmed.3007803
73. Jang MK, Tunc I, Berry GJ, et al. Donor-derived cell-free DNA accurately detects acute rejection in lung transplant patients, a multicenter cohort study. J Heart Lung Transplant. 2021;40(8):822-830. doi:10.1016/j.healun.2021.04.009
74. Keller M, Agbor-Enoh S. Donor-derived cell-free DNA for acute rejection monitoring in heart and lung transplantation. Curr Transplant Rep. 2021;8(4):351-358. doi:10.1007/s40472-021-00349-8
75. Agbor-Enoh S, Wang Y, Tunc I, et al. Donor-derived cell-free DNA predicts allograft failure and mortality after lung transplantation. EBioMedicine. 2019;40:541-553. doi:10.1016/j.ebiom.2018.12.029
76. Keller M, Agbor-Enoh S. Cell-free DNA in lung transplantation: research tool or clinical workhorse? Curr Opin Organ Transplant. 2022;27(3):177-183. doi:10.1097/mot.0000000000000979
77. Gondi KT, Kao A, Linard J, et al. Single-center utilization of donor-derived cell-free DNA testing in the management of heart transplant patients. Clin Transplant. 2021;35(5):e14258. doi:10.1111/ctr.14258
78. Henricksen EJ, Moayedi Y, Purewal S, et al. Combining donor derived cell free DNA and gene expression profiling for non-invasive surveillance after heart transplantation. Clin Transplant. 2023;37(3):e14699. doi:10.1111/ctr.14699
79. Rodgers N, Gerding B, Cusi V, et al. Comparison of two donor-derived cell-free DNA tests and a blood gene-expression profile test in heart transplantation. Clin Transplant. 2023;37(6):e14984. doi:10.1111/ctr.14984
80. Moayedi Y, Teuteberg JJ. Rejection surveillance after heart transplantation: is paired noninvasive testing the new gold standard?. Transplantation. 2025;109(2):285-291. doi:10.1097/TP.0000000000005113
81. Khush K, Hall S, Kao A, et al. Surveillance with dual noninvasive testing for acute cellular rejection after heart transplantation: outcomes from the Surveillance HeartCare Outcomes Registry. J Heart Lung Transplant. 2024;43(9):1409-1421. doi:10.1016/j.healun.2024.05.003
82. Park S, Guo K, Heilman RL, et al. Combining blood gene expression and cellfree DNA to diagnose subclinical rejection in kidney transplant recipients. Clin J Am Soc Nephrol. 2021;16(10):1539-1551. doi:10.2215/cjn.05530421
83. Cheung R, Xu H, Jin X, et al. Validation of a gene expression signature to measure immune quiescence in kidney transplant recipients in the CLIA setting. Biomark Med. 2022;16(8):647-661. doi:10.2217/bmm-2022-0113
84. Peddi VR, Patel PS, Schieve C, Rose S, First MR. Serial peripheral blood gene expression profiling to assess immune quiescence in kidney transplant recipients with stable renal function. Ann Transplant. 2020;25:e920839. doi:10.12659/AOT.920839
85. Bestard O, Augustine J, Wee A, et al. Prospective observational study to validate a next-generation sequencing blood RNA signature to predict early kidney transplant rejection. Am J Transplant. 2024;24(3):436-447. doi:10.1016/j.ajt.2023.09.021
86. American Society of Transplant Surgeons (ASTS) Executive Committee. 2024. ASTS Statement on donor-derived cell-free DNA (dd-cfDNA). American Society of Transplantation. Published 2023; Updated 2024. https://www.asts.org/docs/default-source/position-statements/asts-statement-on-donor-derived-cell-free-dna-(dd-cfdna)—-updated-oct.-2024.pdf?sfvrsn=19314fd3_3. Accessed 4/24/2026.
87. Park S, Sellares J, Tinel C, Anglicheau D, Bestard O, Friedewald JJ. European Society of Organ Transplantation Consensus Statement on testing for non-invasive diagnosis of kidney allograft rejection. Transpl Int. 2024;36:12115. doi:10.3389/ti.2023.12115
88. Pai A, Swan JT, Wojciechowski D, et al. Clinical rationale for a routine testing schedule using donor-derived cell-free DNA after kidney transplantation. Ann Transplant. 2021;26:e932249. doi:10.12659/aot.932249
89. Gupta G, Tanriover B. Donor-derived cell-free DNA measurement in kidney transplant patients without allograft dysfunction: more evidence and more questions. Transplantation. 2023;107(1):25-26. doi:10.1097/tp.0000000000004268
90. Carrigan I, Mathur S, Bourgeois N, et al. Updates in kidney transplantation from the 2022 Banff-Canadian Society of Transplantation Joint Meeting: conference report. Can J Kidney Health Dis. 2023;10:20543581231209185. doi:10.1177/20543581231209185
91. Sigdel T, Nguyen M, Liberto J, et al. Assessment of 19 genes and validation of CRM gene panel for quantitative transcriptional analysis of molecular rejection and inflammation in archival kidney transplant biopsies. Front Med (Lausanne). 2019;6:213. doi:10.3389/fmed.2019.00213
92. Schütz E, Fischer A, Beck J, et al. Graft-derived cell-free DNA, a noninvasive early rejection and graft damage marker in liver transplantation: a prospective, observational, multicenter cohort study. PLoS Med. 2017;14(4):e1002286. doi:10.1371/journal.pmed.1002286
93. Guzzi F, Cirillo L, Buti E, et al. Urinary biomarkers for diagnosis and prediction of acute kidney allograft rejection: a systematic review. Int J Mol Sci. 2020;21(18):6889. doi:10.3390/ijms21186889
94. Adam B, Afzali B, Dominy KM, et al. Multiplexed color-coded probe-based gene expression assessment for clinical molecular diagnostics in formalin-fixed paraffin-embedded human renal allograft tissue. Clin Transplant. 2016;30(3):295-305. doi:10.1111/ctr.12689
95. Parajuli S, Garg N, Dodin B, et al. Changes in donor-derived cell-free DNA before and after rejection and de novo DSA detection in primary and repeat kidney transplant recipients. Clin Transplant. 2024;38(11):e70019. doi:10.1111/ctr.70019
96. Chen CC, Lin WC, Lee CY, Yang CY, Tsai MK. Two-year protocol biopsy after kidney transplantation in clinically stable recipients - a retrospective study. Transpl Int. 2021;34(1):185-193. doi:10.1111/tri.13785
97. Saeyeldin A, McKean S, Van Zyl J, Darst V, Hall S. A modern heart transplant rejection surveillance protocol utilizing cell-free DNA: a single-center experience. JHLT Open. 2024;4:100076. doi:10.1016/j.jhlto.2024.100076

• Solid Organ Allograft Rejection