Optimal survival time-related cut-point with censored data.

نویسندگان

  • Xinhua Liu
  • Zhezhen Jin
چکیده

In biomedical research and practice, continuous biomarkers are often used for diagnosis and prognosis, with a cut-point being established on the measurement to aid binary classification. When survival time is examined for the purposes of disease prognostication and is found to be related to the baseline measure of a biomarker, employing a single cut-point on the biomarker may not be very informative. Using survival time-dependent sensitivity and specificity, we extend a concordance probability-based objective function to select survival time-related cut-points. To estimate the objective function with censored survival data, we adopt a non-parametric procedure for time-dependent receiver operational characteristics curves, which uses nearest neighbor estimation techniques. In a simulation study, the proposed method, when used to select a cut-point to optimally predict survival at a given time within a specified range, yields satisfactory results. We apply the procedure to estimate survival time-dependent cut-point on the prognostic biomarker of serum bilirubin among patients with primary biliary cirrhosis.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Optimal cut-point definition in biomarkers: the case of censored failure time outcome

BACKGROUND Cut-point finding is a crucial step for clinical decision making when dealing with diagnostic (or prognostic) biomarkers. The extension of ROC-based cut-point finding methods to the case of censored failure time outcome is of interest when we are in the presence of a biomarker, measured at baseline, used to identify whether there will be the development, or not, of some disease condi...

متن کامل

Spatial Modeling of Censored Survival Data

An important issue in survival data analysis is the identification of risk factors. Some of these factors are identifiable and explainable by presence of some covariates in the Cox proportional hazard model, while the others are unidentifiable or even immeasurable. Spatial correlation of censored survival data is one of these sources that are rarely considered in the literatures. In this paper,...

متن کامل

Monitoring the censored lognormal reliability data in a three-stage process using AFT model

Improving the product reliability is the main concern in both manufacturing and service processes which is obtained by monitoring the reliability-related quality characteristics. Nowadays, products or services are the result of processes with dependent stages referred to as multistage processes. In these processes, the quality characteristic in each stage is affected by the quality characterist...

متن کامل

Design and Analysis of Step Stress Accelerated Life Tests for Censored Data}

Life testing often is consuming a very long time for testing. Therefore, the engineers and statisticians are looking for some approaches to reduce the running time. There is a recommended method for reducing the time of failure, such that the stress level of the test units will increase, and then they will fail earlier than normal operating conditions. These approaches are called accelerated li...

متن کامل

Bayesian Estimation of Reliability of the Electronic Components Using Censored Data from Weibull Distribution: Different Prior Distributions

The Weibull distribution has been widely used in survival and engineering reliability analysis. In life testing experiments is fairly common practice to terminate the experiment before all the items have failed, that means the data are censored. Thus, the main objective of this paper is to estimate the reliability function of the Weibull distribution with uncensored and censored data by using B...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Statistics in medicine

دوره 34 3  شماره 

صفحات  -

تاریخ انتشار 2015