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Is mammography screening beneficial: An individual-based stochastic model for breast cancer incidence and mortality
The benefits of mammography screening have been controversial, with conflicting findings from various studies. We hypothesize that unmeasured heterogeneity in tumor aggressiveness underlies these conflicting results. Based on published data from the Canadian National Breast Screening Study (CNBSS),...
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Published in: | PLoS computational biology 2020-07, Vol.16 (7), p.e1008036-e1008036 |
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description | The benefits of mammography screening have been controversial, with conflicting findings from various studies. We hypothesize that unmeasured heterogeneity in tumor aggressiveness underlies these conflicting results. Based on published data from the Canadian National Breast Screening Study (CNBSS), we develop and parameterize an individual-based mechanistic model for breast cancer incidence and mortality that tracks five stages of breast cancer progression and incorporates the effects of age on breast cancer incidence and all-cause mortality. The model accurately reproduces the reported outcomes of the CNBSS. By varying parameters, we predict that the benefits of mammography depend on the effectiveness of cancer treatment and tumor aggressiveness. In particular, patients with the most rapidly growing or potentially largest tumors have the highest benefit and least harm from the screening, with only a relatively small effect of age. However, the model predicts that confining mammography to populations with a high risk of acquiring breast cancer increases the screening benefit only slightly compared with the full population. |
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In particular, patients with the most rapidly growing or potentially largest tumors have the highest benefit and least harm from the screening, with only a relatively small effect of age. However, the model predicts that confining mammography to populations with a high risk of acquiring breast cancer increases the screening benefit only slightly compared with the full population.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1008036</identifier><identifier>PMID: 32628726</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Age factors ; Biology and Life Sciences ; Breast cancer ; Care and treatment ; Diagnosis ; Evaluation ; Health care ; Health risks ; Heterogeneity ; Mammography ; Medicine and Health Sciences ; Mortality ; Patients ; People and places ; Research and Analysis Methods ; Software ; Stochastic models ; Stochasticity ; Test reliability ; Tumors ; United States ; Womens health</subject><ispartof>PLoS computational biology, 2020-07, Vol.16 (7), p.e1008036-e1008036</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Le, Adler. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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T</creatorcontrib><creatorcontrib>Adler, Frederick R</creatorcontrib><title>Is mammography screening beneficial: An individual-based stochastic model for breast cancer incidence and mortality</title><title>PLoS computational biology</title><description>The benefits of mammography screening have been controversial, with conflicting findings from various studies. We hypothesize that unmeasured heterogeneity in tumor aggressiveness underlies these conflicting results. Based on published data from the Canadian National Breast Screening Study (CNBSS), we develop and parameterize an individual-based mechanistic model for breast cancer incidence and mortality that tracks five stages of breast cancer progression and incorporates the effects of age on breast cancer incidence and all-cause mortality. The model accurately reproduces the reported outcomes of the CNBSS. 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T</au><au>Adler, Frederick R</au><au>Finley, Stacey</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Is mammography screening beneficial: An individual-based stochastic model for breast cancer incidence and mortality</atitle><jtitle>PLoS computational biology</jtitle><date>2020-07-06</date><risdate>2020</risdate><volume>16</volume><issue>7</issue><spage>e1008036</spage><epage>e1008036</epage><pages>e1008036-e1008036</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>The benefits of mammography screening have been controversial, with conflicting findings from various studies. We hypothesize that unmeasured heterogeneity in tumor aggressiveness underlies these conflicting results. Based on published data from the Canadian National Breast Screening Study (CNBSS), we develop and parameterize an individual-based mechanistic model for breast cancer incidence and mortality that tracks five stages of breast cancer progression and incorporates the effects of age on breast cancer incidence and all-cause mortality. The model accurately reproduces the reported outcomes of the CNBSS. By varying parameters, we predict that the benefits of mammography depend on the effectiveness of cancer treatment and tumor aggressiveness. In particular, patients with the most rapidly growing or potentially largest tumors have the highest benefit and least harm from the screening, with only a relatively small effect of age. However, the model predicts that confining mammography to populations with a high risk of acquiring breast cancer increases the screening benefit only slightly compared with the full population.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>32628726</pmid><doi>10.1371/journal.pcbi.1008036</doi><orcidid>https://orcid.org/0000-0002-9022-3157</orcidid><orcidid>https://orcid.org/0000-0002-3106-4045</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Age factors Biology and Life Sciences Breast cancer Care and treatment Diagnosis Evaluation Health care Health risks Heterogeneity Mammography Medicine and Health Sciences Mortality Patients People and places Research and Analysis Methods Software Stochastic models Stochasticity Test reliability Tumors United States Womens health |
title | Is mammography screening beneficial: An individual-based stochastic model for breast cancer incidence and mortality |
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