Journal of Epidemiology and Global Health

Volume 3, Issue 3, September 2013, Pages 157 - 163

Bayesian lead time estimation for the Johns Hopkins Lung Project data

Authors
Hyejeong Jang1, h0jang01@louisville.edu, Seongho Kim2, s0kim023@louisville.edu, Dongfeng Wu*, dongfeng.wu@louisville.edu
Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, KY 40202, United States
1

Tel.: +1 502 852 8078.

2

Tel.: +1 502 852 3525.

*Corresponding author. Tel.: +1 502 852 1888; fax: +1 502 852 3294.
Corresponding Author
Received 13 February 2013, Revised 8 May 2013, Accepted 10 May 2013, Available Online 14 June 2013.
DOI
10.1016/j.jegh.2013.05.001How to use a DOI?
Keywords
Lead time; Lifetime distribution; X-ray screening; Lung cancer
Abstract

Problem statement: Lung cancer screening using X-rays has been controversial for many years. A major concern is whether lung cancer screening really brings any survival benefits, which depends on effective treatment after early detection. The problem was analyzed from a different point of view and estimates were presented of the projected lead time for participants in a lung cancer screening program using the Johns Hopkins Lung Project (JHLP) data.

Method: The newly developed method of lead time estimation was applied where the lifetime T was treated as a random variable rather than a fixed value, resulting in the number of future screenings for a given individual is a random variable. Using the actuarial life table available from the United States Social Security Administration, the lifetime distribution was first obtained, then the lead time distribution was projected using the JHLP data.

Results: The data analysis with the JHLP data shows that, for a male heavy smoker with initial screening ages at 50, 60, and 70, the probability of no-early-detection with semiannual screens will be 32.16%, 32.45%, and 33.17%, respectively; while the mean lead time is 1.36, 1.33 and 1.23 years. The probability of no-early-detection increases monotonically when the screening interval increases, and it increases slightly as the initial age increases for the same screening interval. The mean lead time and its standard error decrease when the screening interval increases for all age groups, and both decrease when initial age increases with the same screening interval.

Conclusion: The overall mean lead time estimated with a random lifetime T is slightly less than that with a fixed value of T. This result is hoped to be of benefit to improve current screening programs.

Copyright
© 2013 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd.
Open Access
Open access under CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/

Download article (PDF)
View full text (HTML)

Journal
Journal of Epidemiology and Global Health
Volume-Issue
3 - 3
Pages
157 - 163
Publication Date
2013/06/14
ISSN (Online)
2210-6014
ISSN (Print)
2210-6006
DOI
10.1016/j.jegh.2013.05.001How to use a DOI?
Copyright
© 2013 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd.
Open Access
Open access under CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/

Cite this article

TY  - JOUR
AU  - Hyejeong Jang
AU  - Seongho Kim
AU  - Dongfeng Wu
PY  - 2013
DA  - 2013/06/14
TI  - Bayesian lead time estimation for the Johns Hopkins Lung Project data
JO  - Journal of Epidemiology and Global Health
SP  - 157
EP  - 163
VL  - 3
IS  - 3
SN  - 2210-6014
UR  - https://doi.org/10.1016/j.jegh.2013.05.001
DO  - 10.1016/j.jegh.2013.05.001
ID  - Jang2013
ER  -