Predictive Value of Clinical Findings and Plasma Biomarkers after Fourteen Days of Prednisone Treatment for Acute Graft-versus-host Disease

• Published in: Biology of blood and marrow transplantation Vol. 23; no. 8; pp. 1257 - 1263
• Main Authors: McDonald, George B., Tabellini, Laura, Storer, Barry E., Martin, Paul J., Lawler, Richard L., Rosinski, Steven L., Schoch, H. Gary, Hansen, John A.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.08.2017
• Subjects: Acute Disease; Adolescent; Adult; Aged; Aged, 80 and over; Allogeneic; Bilirubin - blood; Biomarker; Biomarkers - blood; Cause of death; Child; Female; Graft vs Host Disease - blood; Graft vs Host Disease - drug therapy; Graft vs Host Disease - mortality; Graft-versus-host disease; Hematopoietic cell transplantation; Hepatitis A Virus Cellular Receptor 2 - blood; Humans; Interleukin-1 Receptor-Like 1 Protein - blood; Male; Marrow transplantation; Middle Aged; Mortality; Outcomes; Positive predictive value; Predictive Value of Tests; Prednisolone - administration & dosage; Receptors, Tumor Necrosis Factor, Type I - blood; Time Factors; Treatment failure; Allogeneic; Graft-versus-host disease; Hematopoietic cell transplantation; Biomarker; Marrow transplantation; Mortality; Treatment failure; Positive predictive value; Cause of death; Outcomes
• ISSN: 1083-8791; 1523-6536
• DOI: 10.1016/j.bbmt.2017.04.029

•For predicting failure after 14 days of graft-versus-host disease treatment, total serum bilirubin and skin graft-versus-host disease stage (area under the curve, .70) was competitive with the biomarker combination of T cell immunoglobulin and mucin domain 3 (TIM3) and interleukin 1 receptor family encoded by the IL1RL1 gene (area under the curve, .73).•For predicting nonrelapse mortality at 1 year, total serum bilirubin (area under the curve, .81) was competitive with the biomarker combination TIM3 and soluble tumor necrosis factor receptor-1 (area under the curve, .85)•Among these graft-versus-host disease–associated deaths, infection was the proximate cause of nonrelapse mortality in essentially all cases•The best predictive models identify only a minority of patients with high-risk graft-versus-host disease; most are falsely predicted to have adverse outcomes We examined the hypothesis that plasma biomarkers and concomitant clinical findings after initial glucocorticoid therapy can accurately predict failure of graft-versus-host-disease (GVHD) treatment and mortality. We analyzed plasma samples and clinical data in 165 patients after 14 days of glucocorticoid therapy and used logistic regression and areas under receiver-operating characteristic curves (AUC) to evaluate associations with treatment failure and nonrelapse mortality (NRM). Initial treatment of GVHD was unsuccessful in 49 patients (30%). For predicting GVHD treatment failure, the best clinical combination (total serum bilirubin and skin GVHD stage: AUC, .70) was competitive with the best biomarker combination (T cell immunoglobulin and mucin domain 3 [TIM3] and [interleukin 1 receptor family encoded by the IL1RL1 gene, ST2]: AUC, .73). The combination of clinical features and biomarker results offered only a slight improvement (AUC, .75). For predicting NRM at 1 year, the best clinical predictor (total serum bilirubin: AUC, .81) was competitive with the best biomarker combination (TIM3 and soluble tumor necrosis factor receptor-1 [sTNFR1]: AUC, .85). The combination offered no improvement (AUC, .85). Infection was the proximate cause of death in virtually all patients. We conclude that after 14 days of glucocorticoid therapy, clinical findings (serum bilirubin, skin GVHD) and plasma biomarkers (TIM3, ST2, sTNFR1) can predict failure of GVHD treatment and NRM. These biomarkers reflect counter-regulatory mechanisms and provide insight into the pathophysiology of GVHD reactions after glucocorticoid treatment. The best predictive models, however, exhibit inadequate positive predictive values for identifying high-risk GVHD cohorts for investigational trials, as only a minority of patients with high-risk GVHD would be identified and most patients would be falsely predicted to have adverse outcomes.