A method for evaluating breast cancer screening strategies using screen-preventable loss of life.

The objective of this study is to describe how screen-preventable loss of life (screen-PLL) can be used to analyze the distribution of life savings with mammographic screening. The determination of screen-PLL with mammography is possible using a natural history model of breast cancer that simulates...

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Main Authors: Kimbroe J Carter, Frank Castro, Roy N Morcos
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0243113
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spelling doaj-91ce0d98d1be46a6a14b49be7c449de12021-03-04T12:50:37ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-011512e024311310.1371/journal.pone.0243113A method for evaluating breast cancer screening strategies using screen-preventable loss of life.Kimbroe J CarterFrank CastroRoy N MorcosThe objective of this study is to describe how screen-preventable loss of life (screen-PLL) can be used to analyze the distribution of life savings with mammographic screening. The determination of screen-PLL with mammography is possible using a natural history model of breast cancer that simulates clinical and pathologic events of this disease. This investigation uses a Monte Carlo Markov model with data from the Surveillance, Epidemiology, and End Results Program; American Cancer Society; and National Vital Statistics System. Populations of one million women per screening strategy are simulated over a lifetime with mammographic screening based on current guidelines of the American Cancer Society (ACS), United States Preventive Services Task Force (USPSTF), triennial screening from age 50-70, and no screening. Screen-PLL curves are generated and show guideline performance over a lifetime. The screen-PLL curve with no screening is determined by tumor discovery through clinical awareness and has the highest values of screen-PLL. The ACS and USPSTF strategies demonstrate screen-PLL curves favoring the elderly. The curve for triennial screening is more uniform than the ACS or USPSTF curves but could be improved by adding screen(s) at either end of the 50-70 age range. This study introduces the use of screen-PLL as a tool to improve the understanding of screening guidelines and allowing a more balanced allocation of life savings across an aging population. The method presented shows how screen-PLL can be used to analyze and potentially improve breast cancer screening guidelines.https://doi.org/10.1371/journal.pone.0243113
collection DOAJ
language English
format Article
sources DOAJ
author Kimbroe J Carter
Frank Castro
Roy N Morcos
spellingShingle Kimbroe J Carter
Frank Castro
Roy N Morcos
A method for evaluating breast cancer screening strategies using screen-preventable loss of life.
PLoS ONE
author_facet Kimbroe J Carter
Frank Castro
Roy N Morcos
author_sort Kimbroe J Carter
title A method for evaluating breast cancer screening strategies using screen-preventable loss of life.
title_short A method for evaluating breast cancer screening strategies using screen-preventable loss of life.
title_full A method for evaluating breast cancer screening strategies using screen-preventable loss of life.
title_fullStr A method for evaluating breast cancer screening strategies using screen-preventable loss of life.
title_full_unstemmed A method for evaluating breast cancer screening strategies using screen-preventable loss of life.
title_sort method for evaluating breast cancer screening strategies using screen-preventable loss of life.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2020-01-01
description The objective of this study is to describe how screen-preventable loss of life (screen-PLL) can be used to analyze the distribution of life savings with mammographic screening. The determination of screen-PLL with mammography is possible using a natural history model of breast cancer that simulates clinical and pathologic events of this disease. This investigation uses a Monte Carlo Markov model with data from the Surveillance, Epidemiology, and End Results Program; American Cancer Society; and National Vital Statistics System. Populations of one million women per screening strategy are simulated over a lifetime with mammographic screening based on current guidelines of the American Cancer Society (ACS), United States Preventive Services Task Force (USPSTF), triennial screening from age 50-70, and no screening. Screen-PLL curves are generated and show guideline performance over a lifetime. The screen-PLL curve with no screening is determined by tumor discovery through clinical awareness and has the highest values of screen-PLL. The ACS and USPSTF strategies demonstrate screen-PLL curves favoring the elderly. The curve for triennial screening is more uniform than the ACS or USPSTF curves but could be improved by adding screen(s) at either end of the 50-70 age range. This study introduces the use of screen-PLL as a tool to improve the understanding of screening guidelines and allowing a more balanced allocation of life savings across an aging population. The method presented shows how screen-PLL can be used to analyze and potentially improve breast cancer screening guidelines.
url https://doi.org/10.1371/journal.pone.0243113
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