Viracor's licensed aGVHD Algorithm testing — utilizing the Mount Sinai Acute GVHD International Consortium (MAGIC) algorithm — was developed by Drs. James Ferrara and John Levine, and validated in conjunction with 17 hematopoietic cell transplantation (HCT) centers to help predict the risk of non-relapse mortality (NRM) and aGVHD in HCT patients. 1,2
The new algorithms have clinically validated cutoffs to help healthcare providers definitively identify patients at risk, delivering actionable data that could improve outcomes.
|Test Name||Clinical Situation for Use||Test Results / Reporting|
|aGVHD Pre-Symptomatic Algorithm||
Patient is not yet showing symptoms for aGVHD post transplant
Interpretation of results, based on clinically validated cutoffs, is provided for each application. Interpretation consists of risk for severe acute GVHD and non-relapse mortality.
|aGVHD Symptomatic Onset Algorithm||
Patient begins displaying symptoms for aGVHD post transplant
|aGVHD Post-Treatment Algorithm||
Patient has been given treatment for aGVHD post transplant
About Viracor's Licensed Algorithm:
Drs. James Ferrara and John Levine, in conjunction with 17 HCT centers, developed and validated the Mount Sinai Acute GVHD International Consortium (MAGIC) Algorithm – which is now commercially available solely through Viracor Eurofins Clinical Diagnostics Laboratory.
Using the pre-symptomatic algorithm with a blood sample taken approximately 7 days after transplant, physicians can identify a patient at high risk for severe aGVHD and NRM, when the patient is not actively displaying symptoms, and can potentially adjust therapy to mitigate identified risks.
“…the use of the MAGIC algorithm could facilitate preemptive intervention for GVHD prior to the onset of clinical disease in a substantial number of patients.” 1
With the symptomatic onset algorithm, results predict the pathology of some of the most severe forms of aGVHD — for example, presentation in the gastrointestinal tract — before disease progression becomes serious.
“We now appreciate that both ST2 and REG3α are closely associated with GI GVHD and we speculate further that the levels of these biomarkers’ concentrations both on day 7 and at the onset of overall symptoms reflect GI pathology that is not yet clinically apparent.” 1
Evaluate Steroid Resistant Patients
The post-treatment algorithm allows healthcare providers to identify high-risk patients for treatment resistance with increased odds of NRM.
"The algorithm analysis identified an unexpectedly large proportion (48%-72%) of the early treatment–resistant patients as low probability and who experienced strikingly less NRM than the high probability group in all 3 cohorts." 2
HR [high risk] patients were 3 times more likely to die from GVHD than LR [low risk] patients when all 1,287 patients were considered (HR 19% vs. LR 6%, P < 0.001) and the difference was statistically significant within each set.Hartwell MJ, Ozbek U, Holler E, et al. An early-biomarker algorithm predicts lethal graft-versus-host-disease and survival. JCI Insight. 2017;2(3):e89798.
Validation of an interpretive algorithm based on serum ST2 and REG3α levels accurately predicts risks for allo-HCT patients when testing is performed at 7 days post-transplant, at the onset of aGVHD symptoms, and ≥ one week after the initiation of systemic therapy.Steve Kleiboeker, PhD, Vice President Research & Development
...accurate prediction of durable responses and long-term outcomes is key to escalation and de-escalation of immunosuppressive therapy.Major-Monfried H, Renteria AS, Pwarode A, et al. MAGIC biomarkers predict long-term outcomes for steroid-resistant acute GVHD. Blood. 2018 Jun 21;131(25):2846-2856. [PubMed]
By Steve Kleiboeker, PhD, Vice President of Research and Development
Application of clinically validated cutoffs has allowed stratification of patients into risk categories at approximately 7 days post-transplant, at the onset of clinical signs, and following 1 week of treatment. Knowledge of a patient’s individual risk will allow adjustments to therapy with a goal of improved outcomes.
Ward-Coleman Chair in Cancer Medicine
Professor of Pediatrics & Medicine, Ichan School of Medicine Mount Sinai
Dr. James Ferrara is a physician-scientist whose clinical and research career has focused on the immunology of bone marrow transplantation (BMT), particularly its major complication graft versus host disease (GVHD). Using trailblazing proteomic techniques, his team has identified and validated unexpected biomarkers for skin, gut and steroid-resistant GVHD. He has created exceptionally large and informative biorepositories and then mined them to meld these biomarkers into the first algorithm that predicts response to treatment and that can guide GVHD therapy. Dr. Ferrara’s pioneering mechanistic studies have illuminated unexpected interactions between the innate and adaptive immune systems and have led to both conceptual breakthroughs and the discovery of novel therapeutic targets. A superb clinician and world-class clinical investigator, his decades-long focus on GVHD has significant potential impact in making BMT safer and more effective for all patients.
Dr. Ferrara graduated Cum laude from Georgetown Medical School and then completed his pediatric residency and fellowship at Boston’s Children’s and the Dana-Farber Cancer Institute. After 19 years he went to the University of Michigan to direct the combined adult and pediatric BMT program. The Icahn School of Medicine at Mount Sinai recruited Dr. Ferrara in 2014 to become the Ward-Coleman professor of Cancer medicine and to direct the Center for Translational Research in Hematologic Malignancies.
|Test Name - Specimen Type||Test Code||CPT Code(s)||Turnaround Time|
|NEW aGVHD Pre-Symptomatic Algorithm - serum||403571||83006, 83520||
Same day (within 24 hours from receipt of specimen), Monday through Friday.
|NEW aGVHD Symptomatic Onset Algorithm - serum||403572||83006, 83520|
|NEW aGVHD Post-Treatment Algorithm - serum||403573||83006, 83520|
|Elafin - serum||30140||83520||
3 business days from receipt of specimen
|Elafin - plasma||30141||83520|
|Hepatocyte growth factor (HGF) - serum||30142||83520|
|Hepatocyte growth factor (HGF) - plasma||30143||83520|
|Interleukin-8 (IL-8) - serum||1219||83520||3-5 business days from receipt of specimen|
|Interleukin-8 (IL-8) - plasma||1229||83520|
|Soluble IL-2 Receptor (sIL-2R) - serum||30057||84238||7 business days from receipt of specimen|
|Soluble TNF receptor 1 (sTNF RI) - serum||30144||84238||3 business days from receipt of specimen|
|Soluble TNF receptor 1 (sTNF RI) - plasma||30145||84238|
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1 Hartwell MJ, Ozbek U, Holler E, et al. An early-biomarker algorithm predicts lethal graft-versus-host-disease and survival. JCI Insight. 2017;2(3):e89798.
2 Major-Monfried H, Renteria AS, Pwarode A, et al. MAGIC biomarkers predict long-term outcomes for steroid-resistant acute GVHD. Blood. 2018 Jun 21;131(25):2846-2856.
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