Estimating asymptomatic duration in cancer: The aids connection

Ruth Etzioni, Yu Shen

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Many chronic diseases, including AIDS and cancer, do not manifest themselves clinically until some time after their inception. In studies of disease natural history, the duration of the asymptomatic period is of interest - in AIDS, to predict the epidemic's course, and in cancer, to develop efficient screening strategies. This article provides a bridge between the two fields with respect to estimation of the asymptomatic period. By adapting AIDS methodology to cancer, the article identifies a non-parametric method for estimating the duration of the asymptomatic period in cancer. The method is similar to one developed by Louis et al. and is designed to apply to data from a cohort of individuals, screened periodically. After reviewing the similarities and differences between the AIDS and cancer contexts, we develop an EM algorithm that, at convergence, yields a maximum or saddle point of the likelihood. We investigate the performance of the algorithm by means of a simulation study, explore the effect of adding a smoothing step to the estimation procedure, and adapt the method for use with a data set in which disease prevalence is low. We apply the method to data from the HIP breast cancer screening trial.

Original languageEnglish (US)
Pages (from-to)627-644
Number of pages18
JournalStatistics in Medicine
Volume16
Issue number6
DOIs
StatePublished - Mar 30 1997
Externally publishedYes

Fingerprint

Cancer
Acquired Immunodeficiency Syndrome
Neoplasms
Screening
Chronic Disease
Nonparametric Methods
EM Algorithm
Saddlepoint
Natural History
Breast Cancer
Early Detection of Cancer
Smoothing
Likelihood
Simulation Study
Breast Neoplasms
Predict
Methodology

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

Cite this

Estimating asymptomatic duration in cancer : The aids connection. / Etzioni, Ruth; Shen, Yu.

In: Statistics in Medicine, Vol. 16, No. 6, 30.03.1997, p. 627-644.

Research output: Contribution to journalArticle

Etzioni, Ruth ; Shen, Yu. / Estimating asymptomatic duration in cancer : The aids connection. In: Statistics in Medicine. 1997 ; Vol. 16, No. 6. pp. 627-644.
@article{5216d6cacae349a4b84989baeb478b5c,
title = "Estimating asymptomatic duration in cancer: The aids connection",
abstract = "Many chronic diseases, including AIDS and cancer, do not manifest themselves clinically until some time after their inception. In studies of disease natural history, the duration of the asymptomatic period is of interest - in AIDS, to predict the epidemic's course, and in cancer, to develop efficient screening strategies. This article provides a bridge between the two fields with respect to estimation of the asymptomatic period. By adapting AIDS methodology to cancer, the article identifies a non-parametric method for estimating the duration of the asymptomatic period in cancer. The method is similar to one developed by Louis et al. and is designed to apply to data from a cohort of individuals, screened periodically. After reviewing the similarities and differences between the AIDS and cancer contexts, we develop an EM algorithm that, at convergence, yields a maximum or saddle point of the likelihood. We investigate the performance of the algorithm by means of a simulation study, explore the effect of adding a smoothing step to the estimation procedure, and adapt the method for use with a data set in which disease prevalence is low. We apply the method to data from the HIP breast cancer screening trial.",
author = "Ruth Etzioni and Yu Shen",
year = "1997",
month = "3",
day = "30",
doi = "10.1002/(SICI)1097-0258(19970330)16:6<627::AID-SIM438>3.0.CO;2-7",
language = "English (US)",
volume = "16",
pages = "627--644",
journal = "Statistics in Medicine",
issn = "0277-6715",
publisher = "John Wiley and Sons Ltd",
number = "6",

}

TY - JOUR

T1 - Estimating asymptomatic duration in cancer

T2 - The aids connection

AU - Etzioni, Ruth

AU - Shen, Yu

PY - 1997/3/30

Y1 - 1997/3/30

N2 - Many chronic diseases, including AIDS and cancer, do not manifest themselves clinically until some time after their inception. In studies of disease natural history, the duration of the asymptomatic period is of interest - in AIDS, to predict the epidemic's course, and in cancer, to develop efficient screening strategies. This article provides a bridge between the two fields with respect to estimation of the asymptomatic period. By adapting AIDS methodology to cancer, the article identifies a non-parametric method for estimating the duration of the asymptomatic period in cancer. The method is similar to one developed by Louis et al. and is designed to apply to data from a cohort of individuals, screened periodically. After reviewing the similarities and differences between the AIDS and cancer contexts, we develop an EM algorithm that, at convergence, yields a maximum or saddle point of the likelihood. We investigate the performance of the algorithm by means of a simulation study, explore the effect of adding a smoothing step to the estimation procedure, and adapt the method for use with a data set in which disease prevalence is low. We apply the method to data from the HIP breast cancer screening trial.

AB - Many chronic diseases, including AIDS and cancer, do not manifest themselves clinically until some time after their inception. In studies of disease natural history, the duration of the asymptomatic period is of interest - in AIDS, to predict the epidemic's course, and in cancer, to develop efficient screening strategies. This article provides a bridge between the two fields with respect to estimation of the asymptomatic period. By adapting AIDS methodology to cancer, the article identifies a non-parametric method for estimating the duration of the asymptomatic period in cancer. The method is similar to one developed by Louis et al. and is designed to apply to data from a cohort of individuals, screened periodically. After reviewing the similarities and differences between the AIDS and cancer contexts, we develop an EM algorithm that, at convergence, yields a maximum or saddle point of the likelihood. We investigate the performance of the algorithm by means of a simulation study, explore the effect of adding a smoothing step to the estimation procedure, and adapt the method for use with a data set in which disease prevalence is low. We apply the method to data from the HIP breast cancer screening trial.

UR - http://www.scopus.com/inward/record.url?scp=0030933664&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0030933664&partnerID=8YFLogxK

U2 - 10.1002/(SICI)1097-0258(19970330)16:6<627::AID-SIM438>3.0.CO;2-7

DO - 10.1002/(SICI)1097-0258(19970330)16:6<627::AID-SIM438>3.0.CO;2-7

M3 - Article

C2 - 9131752

AN - SCOPUS:0030933664

VL - 16

SP - 627

EP - 644

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 0277-6715

IS - 6

ER -