Predicting the Onset of Hepatitis B Virus–Related Acute-on-Chronic Liver Failure

The ability to parse tumors into subsets based on biomarker expression has many clinical applications; however, there is no global way to visualize the best cut-points for creating such divisions. We have developed a graphical method, the X-tile plot that illustrates the presence of substantial tumor subpopulations and shows the robustness of the relationship between a biomarker and outcome by construction of a two dimensional projection of every possible subpopulation. We validate X-tile plots by examining the expression of several established prognostic markers (human epidermal growth factor receptor-2, estrogen receptor, p53 expression, patient age, tumor size, and node number) in cohorts of breast cancer patients and show how X-tile plots of each marker predict population subsets rooted in the known biology of their expression.

The performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the receiver operating characteristic [ROC] curve), and goodness-of-fit statistics for calibration.Several new measures have recently been proposed that can be seen as refinements of discrimination measures, including variants of the c statistic for survival, reclassification tables, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Moreover, decision-analytic measures have been proposed, including decision curves to plot the net benefit achieved by making decisions based on model predictions.We aimed to define the role of these relatively novel approaches in the evaluation of the performance of prediction models. For illustration, we present a case study of predicting the presence of residual tumor versus benign tissue in patients with testicular cancer (n = 544 for model development, n = 273 for external validation).We suggest that reporting discrimination and calibration will always be important for a prediction model. Decision-analytic measures should be reported if the predictive model is to be used for clinical decisions. Other measures of performance may be warranted in specific applications, such as reclassification metrics to gain insight into the value of adding a novel predictor to an established model.

Patients with cirrhosis hospitalized for an acute decompensation (AD) and organ failure are at risk for imminent death and considered to have acute-on-chronic liver failure (ACLF). However, there are no established diagnostic criteria for ACLF, so little is known about its development and progression. We aimed to identify diagnostic criteria of ACLF and describe the development of this syndrome in European patients with AD. We collected data from 1343 hospitalized patients with cirrhosis and AD from February to September 2011 at 29 liver units in 8 European countries. We used the organ failure and mortality data to define ACLF grades, assess mortality, and identify differences between ACLF and AD. We established diagnostic criteria for ACLF based on analyses of patients with organ failure (defined by the chronic liver failure-sequential organ failure assessment [CLIF-SOFA] score) and high 28-day mortality rate (>15%). Of the patients assessed, 303 had ACLF when the study began, 112 developed ACLF, and 928 did not have ACLF. The 28-day mortality rate among patients who had ACLF when the study began was 33.9%, among those who developed ACLF was 29.7%, and among those who did not have ACLF was 1.9%. Patients with ACLF were younger and more frequently alcoholic, had more associated bacterial infections, and had higher numbers of leukocytes and higher plasma levels of C-reactive protein than patients without ACLF (P < .001). Higher CLIF-SOFA scores and leukocyte counts were independent predictors of mortality in patients with ACLF. In patients without a prior history of AD, ACLF was unexpectedly characterized by higher numbers of organ failures, leukocyte count, and mortality compared with ACLF in patients with a prior history of AD. We analyzed data from patients with cirrhosis and AD to establish diagnostic criteria for ACLF and showed that it is distinct from AD, based not only on the presence of organ failure(s) and high mortality rate but also on age, precipitating events, and systemic inflammation. ACLF mortality is associated with loss of organ function and high leukocyte counts. ACLF is especially severe in patients with no prior history of AD. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.