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

急性移植物抗宿主病接受泼尼松治疗 14 天后临床表现和血浆生物标志物的预测价值

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作者:George B McDonald, Laura Tabellini, Barry E Storer, Paul J Martin, Richard L Lawler, Steven L Rosinski, H Gary Schoch, John A Hansen

Abstract

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.

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