Time-dependent ROC curves for censored survival data and a diagnostic marker.

  title={Time-dependent ROC curves for censored survival data and a diagnostic marker.},
  author={Patrick J. Heagerty and Thomas Lumley and Margaret Sullivan Pepe},
  volume={56 2},
ROC curves are a popular method for displaying sensitivity and specificity of a continuous diagnostic marker, X, for a binary disease variable, D. However, many disease outcomes are time dependent, D(t), and ROC curves that vary as a function of time may be more appropriate. A common example of a time-dependent variable is vital status, where D(t) = 1 if a patient has died prior to time t and zero otherwise. We propose summarizing the discrimination potential of a marker X, measured at baseline… Expand
Nonparametric estimation of time-dependent ROC curves conditional on a continuous covariate.
New nonparametric estimators of the cumulative/dynamic time-dependent ROC curve that allow accounting for the possible modifying effect of current or past covariate measures on the discriminatory power of the biomarker are presented. Expand
A Simple Method to Estimate the Time-dependent ROC Curve Under Right Censoring
The time-dependent Receiver Operating Characteristic (ROC) curve is often used to study the diagnostic accuracy of a single continuous biomarker, measured at baseline, on the onset of a diseaseExpand
Smoothed time-dependent receiver operating characteristic curve for right censored survival data.
The results show that the proposed method performs better and appear to be quite robust to bandwidth choice, and the results also reveal the good performances of a proposed nonparametric bootstrap procedure. Expand
Time-dependent diagnostic accuracy analysis with censored outcome and censored predictor
Abstract We consider a unified approach for estimating time-dependent diagnostic accuracy measures, including time-dependent sensitivity, specificity, positive predictive value, negative predictiveExpand
Non-parametric estimation of a time-dependent predictive accuracy curve.
This work proposes a direct, non-parametric method to estimate the time-dependent Area under the curve (AUC) which it refers to as the weighted mean rank (WMR) estimator, and establishes the asymptotic properties of the proposed estimator. Expand
Understanding the predictive value of continuous markers for censored survival data using a likelihood ratio approach
The TD-LR provides a more nuanced understanding of the relationship between continuous markers and the likelihood of events in censored survival data and allows more straightforward communication with a clinical audience through graphical presentation. Expand
A simple method to estimate the time-dependent receiver operating characteristic curve and the area under the curve with right censored data
This work derives a novel, closed-form formula to calculate the area under the time-dependent receiver operating characteristic curve by weighting the censored data by the conditional probability of disease onset prior to the time horizon given the biomarker, the observed time to event, and the censoring indicator. Expand
Time-dependent ROC analysis for censored biomarker data due to limit of detection
The proposed methods are shown to outperform the simple substitution method that has been conventionally adopted for handling censored data by using parameter estimates from the Cox regression model that accommodates censored biomarker measurements. Expand
Estimating a time-dependent concordance index for survival prediction models with covariate dependent censoring.
The existing methodology for applications where the length of the follow-up period depends on the predictor variables is extended and a class of inverse probability of censoring weighted estimators is discussed in which the estimates rely on a working model for the conditional censoring distribution. Expand
Net time-dependent ROC curves: a solution for evaluating the accuracy of a marker to predict disease-related mortality.
This paper proposes a new estimator of time-dependent ROC curves, which includes this concept of net survival, in order to evaluate the capacity of a marker to predict disease-specific mortality, and performs simulations to validate this estimator. Expand


A regression modelling framework for receiver operating characteristic curves in medical diagnostic testing
SUMMARY Receiver operating characteristic curves (ROC's) are used to evaluate diagnostic tests when test results are not binary. They describe the inherent capacity of the test for distinguishingExpand
The two sample problem with censored data
A medical investigator attempting to compare two different treatments for, say, prolongation of life among disease victims, often finds himself in the following situation: at time T, when it isExpand
Smooth non-parametric receiver operating characteristic (ROC) curves for continuous diagnostic tests.
A smooth non-parametric ROC curve derived from kernel density estimates of the two test result distributions is proposed, which is fit well by parametric methods and LABROC4, the other of which is not. Expand
Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine.
Receiver-operating characteristic (ROC) plots provide a pure index of accuracy by demonstrating the limits of a test's ability to discriminate between alternative states of health over the complete spectrum of operating conditions. Expand
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics,Expand
Nonparametric Estimation from Incomplete Observations
Abstract In lifetesting, medical follow-up, and other fields the observation of the time of occurrence of the event of interest (called a death) may be prevented for some of the items of the sampleExpand
Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.
A nonparametric approach to the analysis of areas under correlated ROC curves is presented, by using the theory on generalized U-statistics to generate an estimated covariance matrix. Expand
Receiver operating characteristic (ROC) methodology: the state of the art.
  • J. Hanley
  • Medicine
  • Critical reviews in diagnostic imaging
  • 1989
The nature of the data generated by ROC studies is described, the choices of summary indices of performance (accuracy) are evaluated, and the data-analytic techniques used are outlined, including how to incorporate data from multiple observers and multiple "readings". Expand
Nearest Neighbor Estimation of a Bivariate Distribution Under Random Censoring
We consider the problem of estimating the bivariate distribution of the random vector (X, Y) when Y may be subject to random censoring. The censoring variable C is allowed to depend on X but it isExpand
Maximum likelihood estimation of receiver operating characteristic (ROC) curves from continuously-distributed data.
Two new algorithms for fitting binormal ROC curves to continuously-distributed data are developed: a true ML algorithm (LABROC4) and a quasi-ML algorithm (LabROC5) that requires substantially less computation with large data sets. Expand