Predicting cumulative risk of disease onset by redistributing weights

Tianle Chen, Yanyuan Ma, Yuanjia Wang

Research output: Contribution to journalArticle

Abstract

We propose a simple approach predicting the cumulative risk of disease accommodating predictors with time-varying effects and outcomes subject to censoring. We use a nonparametric function for the coefficient of the time-varying effect and handle censoring through self-consistency equations that redistribute the probability mass of censored outcomes to the right. The computational procedure is extremely convenient and can be implemented by standard software. We prove large sample properties of the proposed estimator and evaluate its finite sample performance through simulation studies. We apply the method to estimate the cumulative risk of developing Huntington's disease (HD) from subjects with huntingtin gene mutation using a large collaborative HD study data and illustrate an inverse relationship between the cumulative risk of HD and the length of cytosine-adenine-guanine repeats in the huntingtin gene.

Original languageEnglish (US)
Pages (from-to)2427-2443
Number of pages17
JournalStatistics in Medicine
Volume34
Issue number16
DOIs
StatePublished - Jul 20 2015

Fingerprint

Huntington Disease
Weights and Measures
Censoring
Time-varying
Cytosine
Guanine
Adenine
Gene
Self-consistency
Genes
Software
Predictors
Mutation
Simulation Study
Estimator
Evaluate
Coefficient
Estimate

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Statistics and Probability

Cite this

Chen, Tianle ; Ma, Yanyuan ; Wang, Yuanjia. / Predicting cumulative risk of disease onset by redistributing weights. In: Statistics in Medicine. 2015 ; Vol. 34, No. 16. pp. 2427-2443.
@article{dd3ed1ceb10840c98071c1f77b642649,
title = "Predicting cumulative risk of disease onset by redistributing weights",
abstract = "We propose a simple approach predicting the cumulative risk of disease accommodating predictors with time-varying effects and outcomes subject to censoring. We use a nonparametric function for the coefficient of the time-varying effect and handle censoring through self-consistency equations that redistribute the probability mass of censored outcomes to the right. The computational procedure is extremely convenient and can be implemented by standard software. We prove large sample properties of the proposed estimator and evaluate its finite sample performance through simulation studies. We apply the method to estimate the cumulative risk of developing Huntington's disease (HD) from subjects with huntingtin gene mutation using a large collaborative HD study data and illustrate an inverse relationship between the cumulative risk of HD and the length of cytosine-adenine-guanine repeats in the huntingtin gene.",
author = "Tianle Chen and Yanyuan Ma and Yuanjia Wang",
year = "2015",
month = "7",
day = "20",
doi = "10.1002/sim.6499",
language = "English (US)",
volume = "34",
pages = "2427--2443",
journal = "Statistics in Medicine",
issn = "0277-6715",
publisher = "John Wiley and Sons Ltd",
number = "16",

}

Predicting cumulative risk of disease onset by redistributing weights. / Chen, Tianle; Ma, Yanyuan; Wang, Yuanjia.

In: Statistics in Medicine, Vol. 34, No. 16, 20.07.2015, p. 2427-2443.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Predicting cumulative risk of disease onset by redistributing weights

AU - Chen, Tianle

AU - Ma, Yanyuan

AU - Wang, Yuanjia

PY - 2015/7/20

Y1 - 2015/7/20

N2 - We propose a simple approach predicting the cumulative risk of disease accommodating predictors with time-varying effects and outcomes subject to censoring. We use a nonparametric function for the coefficient of the time-varying effect and handle censoring through self-consistency equations that redistribute the probability mass of censored outcomes to the right. The computational procedure is extremely convenient and can be implemented by standard software. We prove large sample properties of the proposed estimator and evaluate its finite sample performance through simulation studies. We apply the method to estimate the cumulative risk of developing Huntington's disease (HD) from subjects with huntingtin gene mutation using a large collaborative HD study data and illustrate an inverse relationship between the cumulative risk of HD and the length of cytosine-adenine-guanine repeats in the huntingtin gene.

AB - We propose a simple approach predicting the cumulative risk of disease accommodating predictors with time-varying effects and outcomes subject to censoring. We use a nonparametric function for the coefficient of the time-varying effect and handle censoring through self-consistency equations that redistribute the probability mass of censored outcomes to the right. The computational procedure is extremely convenient and can be implemented by standard software. We prove large sample properties of the proposed estimator and evaluate its finite sample performance through simulation studies. We apply the method to estimate the cumulative risk of developing Huntington's disease (HD) from subjects with huntingtin gene mutation using a large collaborative HD study data and illustrate an inverse relationship between the cumulative risk of HD and the length of cytosine-adenine-guanine repeats in the huntingtin gene.

UR - http://www.scopus.com/inward/record.url?scp=84930415542&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84930415542&partnerID=8YFLogxK

U2 - 10.1002/sim.6499

DO - 10.1002/sim.6499

M3 - Article

C2 - 25847392

AN - SCOPUS:84930415542

VL - 34

SP - 2427

EP - 2443

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 0277-6715

IS - 16

ER -