ABSTRACT: BACKGROUND: Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. METHODS: We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiv...
Abstract Background Decision curve analysis is a novel method for evaluating diagnostic tests, predi...
Objectives: Receiver operating characteristic (ROC) curves show how well a risk prediction model dis...
OBJECTIVES: Receiver operating characteristic (ROC) curves show how well a risk prediction model dis...
Multivariable regression models are widely used in medical literature for the purpose of diagnosis o...
Multivariable regression models are widely used in medical literature for the purpose of diagnosis o...
BACKGROUND: Prediction models are essential to the development of prediction rules that guide decisi...
BACKGROUND Decision curve analysis can be used to determine whether a personalized model for trea...
<p>Decision curve analysis of the Full Model (dashed line black line) and Reduced Model (blue solid ...
Background: Decision curve analysis is a method to evaluate prediction models and diagnostic tests t...
BACKGROUND: A number of recent papers have proposed methods to calculate confidence intervals and p ...
Decision curve analysis can be used to determine whether a personalized model for treatment benefit ...
Many decisions in medicine involve trade-offs, such as between diagnosing patients with disease vers...
Background. Diagnostic and prognostic models are typi-cally evaluated with measures of accuracy that...
Many decisions in medicine involve trade-offs, such as between diagnosing patients with disease vers...
textabstractMany decisions in medicine involve trade-offs, such as between diagnosing patients with ...
Abstract Background Decision curve analysis is a novel method for evaluating diagnostic tests, predi...
Objectives: Receiver operating characteristic (ROC) curves show how well a risk prediction model dis...
OBJECTIVES: Receiver operating characteristic (ROC) curves show how well a risk prediction model dis...
Multivariable regression models are widely used in medical literature for the purpose of diagnosis o...
Multivariable regression models are widely used in medical literature for the purpose of diagnosis o...
BACKGROUND: Prediction models are essential to the development of prediction rules that guide decisi...
BACKGROUND Decision curve analysis can be used to determine whether a personalized model for trea...
<p>Decision curve analysis of the Full Model (dashed line black line) and Reduced Model (blue solid ...
Background: Decision curve analysis is a method to evaluate prediction models and diagnostic tests t...
BACKGROUND: A number of recent papers have proposed methods to calculate confidence intervals and p ...
Decision curve analysis can be used to determine whether a personalized model for treatment benefit ...
Many decisions in medicine involve trade-offs, such as between diagnosing patients with disease vers...
Background. Diagnostic and prognostic models are typi-cally evaluated with measures of accuracy that...
Many decisions in medicine involve trade-offs, such as between diagnosing patients with disease vers...
textabstractMany decisions in medicine involve trade-offs, such as between diagnosing patients with ...
Abstract Background Decision curve analysis is a novel method for evaluating diagnostic tests, predi...
Objectives: Receiver operating characteristic (ROC) curves show how well a risk prediction model dis...
OBJECTIVES: Receiver operating characteristic (ROC) curves show how well a risk prediction model dis...