Journal
BLOOD
Volume 108, Issue 2, Pages 749-755Publisher
AMER SOC HEMATOLOGY
DOI: 10.1182/blood-2006-01-0254
Keywords
-
Categories
Funding
- NCI NIH HHS [CA 18029, CA 15704] Funding Source: Medline
Ask authors/readers for more resources
Algorithms for grading acute graft-versus-host disease (GVHD) are inaccurate in assessing mortality risk. We developed a method to predict mortality by using data from 386 patients with acute GVHD. From the onset of GVHD to day 100, GVHD manifestations were scored for the skin, liver, and upper and lower gastrointestinal tract, and data were recorded for immunosuppressive treatment, performance, and fever. Logistic regression models predicting nonrelapse mortality (NRM) at day 200 were developed with data from 193 randomly selected patients and then validated in the remaining 193 patients. Clinical parameters were grouped to optimize predictive accuracy measured as the area under a receiver-operator characteristic (ROC) curve. The optimal model included the total serum billrubin concentration, oral intake, need for treatment with prednisone, and performance score. When the overall burden of GVHD was measured by using average Acute GVHD Activity Index (aGVHDAI) scores for each patient in training and validation data sets, areas under ROC curves were 0.87 and 0.85, respectively. Contour lines were generated to reflect the predicted NRM at day 200 as a function of current aGVHDAI scores. These results demonstrate that clinical manifestations of GVHD severity can be used to accurately predict the risk of NRM in real time.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available