Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case–control study
Background This study investigates whether quantitative breast density (BD) serves as an imaging biomarker for more intensive breast cancer screening by predicting interval, and node-positive cancers. Methods This case–control study of 1204 women aged 47–73 includes 599 cancer cases (302 screen-dete...
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| Veröffentlicht in: | British journal of cancer 2021-09, Vol.125 (6), p.884-892 |
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| creator | Burnside, Elizabeth S. Warren, Lucy M. Myles, Jonathan Wilkinson, Louise S. Wallis, Matthew G. Patel, Mishal Smith, Robert A. Young, Kenneth C. Massat, Nathalie J. Duffy, Stephen W. |
| description | Background
This study investigates whether quantitative breast density (BD) serves as an imaging biomarker for more intensive breast cancer screening by predicting interval, and node-positive cancers.
Methods
This case–control study of 1204 women aged 47–73 includes 599 cancer cases (302 screen-detected, 297 interval; 239 node-positive, 360 node-negative) and 605 controls. Automated BD software calculated fibroglandular volume (FGV), volumetric breast density (VBD) and density grade (DG). A radiologist assessed BD using a visual analogue scale (VAS) from 0 to 100. Logistic regression and area under the receiver operating characteristic curves (AUC) determined whether BD could predict mode of detection (screen-detected or interval); node-negative cancers; node-positive cancers, and all cancers vs. controls.
Results
FGV, VBD, VAS, and DG all discriminated interval cancers (all
p
|
| doi_str_mv | 10.1038/s41416-021-01466-y |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8438060</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2545607781</sourcerecordid><originalsourceid>FETCH-LOGICAL-c474t-5c6c35ad1d411139baf1b67e21afc7e6f4f976148783b109ffaa154f50a721543</originalsourceid><addsrcrecordid>eNp9kc2OFCEUhYnROG3rC7gwJG7clAJFFVUuTCYT_5JJjImuCUVdWibVUHKpTmrnOxhf0CeRtsfxZyEbIPc75144hDzk7ClndfcMJZe8rZjgFeOybav1FtnwphYV74S6TTaMMVWxXrAzcg_xqlx71qm75Kwuuk70akO-vV9MyD6b7A9AhwQGMx0hoM8rNcFMK3qkOdI5wehtpj5kSAczleJIQxyhmmOBj2prgoWEBaHzknDxmUZH_X5O8QAjRZsAgg-74hVztHHC59QUFcL3L19tDDnFiWJexvU-uePMhPDget-Sj69efrh4U12-e_324vyyslLJXDW2tXVjRj5KznndD8bxoVUguHFWQeuk61XLZae6euCsd84Y3kjXMKNEOdRb8uLkOy_DHkYLZQYz6Tn5vUmrjsbrvyvBf9K7eNCdrDvWsmLw5Nogxc8LYNZ7jxamyQSIC2rRyKZlSnW8oI__Qa_iksoPHyklmBJ1WVsiTpRNETGBuxmGM31MXZ9S1yV1_TN1vRbRoz-fcSP5FXMB6hOApRR2kH73_o_tD6aZvjk</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2572072333</pqid></control><display><type>article</type><title>Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case–control study</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><creator>Burnside, Elizabeth S. ; Warren, Lucy M. ; Myles, Jonathan ; Wilkinson, Louise S. ; Wallis, Matthew G. ; Patel, Mishal ; Smith, Robert A. ; Young, Kenneth C. ; Massat, Nathalie J. ; Duffy, Stephen W.</creator><creatorcontrib>Burnside, Elizabeth S. ; Warren, Lucy M. ; Myles, Jonathan ; Wilkinson, Louise S. ; Wallis, Matthew G. ; Patel, Mishal ; Smith, Robert A. ; Young, Kenneth C. ; Massat, Nathalie J. ; Duffy, Stephen W.</creatorcontrib><description>Background
This study investigates whether quantitative breast density (BD) serves as an imaging biomarker for more intensive breast cancer screening by predicting interval, and node-positive cancers.
Methods
This case–control study of 1204 women aged 47–73 includes 599 cancer cases (302 screen-detected, 297 interval; 239 node-positive, 360 node-negative) and 605 controls. Automated BD software calculated fibroglandular volume (FGV), volumetric breast density (VBD) and density grade (DG). A radiologist assessed BD using a visual analogue scale (VAS) from 0 to 100. Logistic regression and area under the receiver operating characteristic curves (AUC) determined whether BD could predict mode of detection (screen-detected or interval); node-negative cancers; node-positive cancers, and all cancers vs. controls.
Results
FGV, VBD, VAS, and DG all discriminated interval cancers (all
p
< 0.01) from controls. Only FGV-quartile discriminated screen-detected cancers (
p
< 0.01). Based on AUC, FGV discriminated all cancer types better than VBD or VAS. FGV showed a significantly greater discrimination of interval cancers, AUC = 0.65, than of screen-detected cancers, AUC = 0.61 (
p
< 0.01) as did VBD (0.63 and 0.53, respectively,
p
< 0.001).
Conclusion
FGV, VBD, VAS and DG discriminate interval cancers from controls, reflecting some masking risk. Only FGV discriminates screen-detected cancers perhaps adding a unique component of breast cancer risk.</description><identifier>ISSN: 0007-0920</identifier><identifier>ISSN: 1532-1827</identifier><identifier>EISSN: 1532-1827</identifier><identifier>DOI: 10.1038/s41416-021-01466-y</identifier><identifier>PMID: 34168297</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/67/1347 ; 692/499 ; Aged ; Biomedical and Life Sciences ; Biomedicine ; Breast cancer ; Breast Density ; Breast Neoplasms - diagnostic imaging ; Cancer Research ; Cancer screening ; Case-Control Studies ; Drug Resistance ; Early Detection of Cancer ; Epidemiology ; Female ; Humans ; Mammography - methods ; Medical screening ; Middle Aged ; Molecular Medicine ; Oncology ; Randomized Controlled Trials as Topic ; Visual Analog Scale ; Visual discrimination</subject><ispartof>British journal of cancer, 2021-09, Vol.125 (6), p.884-892</ispartof><rights>The Author(s) 2021</rights><rights>2021. The Author(s).</rights><rights>The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-5c6c35ad1d411139baf1b67e21afc7e6f4f976148783b109ffaa154f50a721543</citedby><cites>FETCH-LOGICAL-c474t-5c6c35ad1d411139baf1b67e21afc7e6f4f976148783b109ffaa154f50a721543</cites><orcidid>0000-0003-3344-2238 ; 0000-0002-1095-994X ; 0000-0003-4901-7922 ; 0000-0002-6600-435X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438060/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438060/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,41464,42533,51294,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34168297$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Burnside, Elizabeth S.</creatorcontrib><creatorcontrib>Warren, Lucy M.</creatorcontrib><creatorcontrib>Myles, Jonathan</creatorcontrib><creatorcontrib>Wilkinson, Louise S.</creatorcontrib><creatorcontrib>Wallis, Matthew G.</creatorcontrib><creatorcontrib>Patel, Mishal</creatorcontrib><creatorcontrib>Smith, Robert A.</creatorcontrib><creatorcontrib>Young, Kenneth C.</creatorcontrib><creatorcontrib>Massat, Nathalie J.</creatorcontrib><creatorcontrib>Duffy, Stephen W.</creatorcontrib><title>Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case–control study</title><title>British journal of cancer</title><addtitle>Br J Cancer</addtitle><addtitle>Br J Cancer</addtitle><description>Background
This study investigates whether quantitative breast density (BD) serves as an imaging biomarker for more intensive breast cancer screening by predicting interval, and node-positive cancers.
Methods
This case–control study of 1204 women aged 47–73 includes 599 cancer cases (302 screen-detected, 297 interval; 239 node-positive, 360 node-negative) and 605 controls. Automated BD software calculated fibroglandular volume (FGV), volumetric breast density (VBD) and density grade (DG). A radiologist assessed BD using a visual analogue scale (VAS) from 0 to 100. Logistic regression and area under the receiver operating characteristic curves (AUC) determined whether BD could predict mode of detection (screen-detected or interval); node-negative cancers; node-positive cancers, and all cancers vs. controls.
Results
FGV, VBD, VAS, and DG all discriminated interval cancers (all
p
< 0.01) from controls. Only FGV-quartile discriminated screen-detected cancers (
p
< 0.01). Based on AUC, FGV discriminated all cancer types better than VBD or VAS. FGV showed a significantly greater discrimination of interval cancers, AUC = 0.65, than of screen-detected cancers, AUC = 0.61 (
p
< 0.01) as did VBD (0.63 and 0.53, respectively,
p
< 0.001).
Conclusion
FGV, VBD, VAS and DG discriminate interval cancers from controls, reflecting some masking risk. Only FGV discriminates screen-detected cancers perhaps adding a unique component of breast cancer risk.</description><subject>631/67/1347</subject><subject>692/499</subject><subject>Aged</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Breast cancer</subject><subject>Breast Density</subject><subject>Breast Neoplasms - diagnostic imaging</subject><subject>Cancer Research</subject><subject>Cancer screening</subject><subject>Case-Control Studies</subject><subject>Drug Resistance</subject><subject>Early Detection of Cancer</subject><subject>Epidemiology</subject><subject>Female</subject><subject>Humans</subject><subject>Mammography - methods</subject><subject>Medical screening</subject><subject>Middle Aged</subject><subject>Molecular Medicine</subject><subject>Oncology</subject><subject>Randomized Controlled Trials as Topic</subject><subject>Visual Analog Scale</subject><subject>Visual discrimination</subject><issn>0007-0920</issn><issn>1532-1827</issn><issn>1532-1827</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp9kc2OFCEUhYnROG3rC7gwJG7clAJFFVUuTCYT_5JJjImuCUVdWibVUHKpTmrnOxhf0CeRtsfxZyEbIPc75144hDzk7ClndfcMJZe8rZjgFeOybav1FtnwphYV74S6TTaMMVWxXrAzcg_xqlx71qm75Kwuuk70akO-vV9MyD6b7A9AhwQGMx0hoM8rNcFMK3qkOdI5wehtpj5kSAczleJIQxyhmmOBj2prgoWEBaHzknDxmUZH_X5O8QAjRZsAgg-74hVztHHC59QUFcL3L19tDDnFiWJexvU-uePMhPDget-Sj69efrh4U12-e_324vyyslLJXDW2tXVjRj5KznndD8bxoVUguHFWQeuk61XLZae6euCsd84Y3kjXMKNEOdRb8uLkOy_DHkYLZQYz6Tn5vUmrjsbrvyvBf9K7eNCdrDvWsmLw5Nogxc8LYNZ7jxamyQSIC2rRyKZlSnW8oI__Qa_iksoPHyklmBJ1WVsiTpRNETGBuxmGM31MXZ9S1yV1_TN1vRbRoz-fcSP5FXMB6hOApRR2kH73_o_tD6aZvjk</recordid><startdate>20210914</startdate><enddate>20210914</enddate><creator>Burnside, Elizabeth S.</creator><creator>Warren, Lucy M.</creator><creator>Myles, Jonathan</creator><creator>Wilkinson, Louise S.</creator><creator>Wallis, Matthew G.</creator><creator>Patel, Mishal</creator><creator>Smith, Robert A.</creator><creator>Young, Kenneth C.</creator><creator>Massat, Nathalie J.</creator><creator>Duffy, Stephen W.</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7TO</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-3344-2238</orcidid><orcidid>https://orcid.org/0000-0002-1095-994X</orcidid><orcidid>https://orcid.org/0000-0003-4901-7922</orcidid><orcidid>https://orcid.org/0000-0002-6600-435X</orcidid></search><sort><creationdate>20210914</creationdate><title>Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case–control study</title><author>Burnside, Elizabeth S. ; Warren, Lucy M. ; Myles, Jonathan ; Wilkinson, Louise S. ; Wallis, Matthew G. ; Patel, Mishal ; Smith, Robert A. ; Young, Kenneth C. ; Massat, Nathalie J. ; Duffy, Stephen W.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-5c6c35ad1d411139baf1b67e21afc7e6f4f976148783b109ffaa154f50a721543</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>631/67/1347</topic><topic>692/499</topic><topic>Aged</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Breast cancer</topic><topic>Breast Density</topic><topic>Breast Neoplasms - diagnostic imaging</topic><topic>Cancer Research</topic><topic>Cancer screening</topic><topic>Case-Control Studies</topic><topic>Drug Resistance</topic><topic>Early Detection of Cancer</topic><topic>Epidemiology</topic><topic>Female</topic><topic>Humans</topic><topic>Mammography - methods</topic><topic>Medical screening</topic><topic>Middle Aged</topic><topic>Molecular Medicine</topic><topic>Oncology</topic><topic>Randomized Controlled Trials as Topic</topic><topic>Visual Analog Scale</topic><topic>Visual discrimination</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Burnside, Elizabeth S.</creatorcontrib><creatorcontrib>Warren, Lucy M.</creatorcontrib><creatorcontrib>Myles, Jonathan</creatorcontrib><creatorcontrib>Wilkinson, Louise S.</creatorcontrib><creatorcontrib>Wallis, Matthew G.</creatorcontrib><creatorcontrib>Patel, Mishal</creatorcontrib><creatorcontrib>Smith, Robert A.</creatorcontrib><creatorcontrib>Young, Kenneth C.</creatorcontrib><creatorcontrib>Massat, Nathalie J.</creatorcontrib><creatorcontrib>Duffy, Stephen W.</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>British Nursing Database</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>British journal of cancer</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Burnside, Elizabeth S.</au><au>Warren, Lucy M.</au><au>Myles, Jonathan</au><au>Wilkinson, Louise S.</au><au>Wallis, Matthew G.</au><au>Patel, Mishal</au><au>Smith, Robert A.</au><au>Young, Kenneth C.</au><au>Massat, Nathalie J.</au><au>Duffy, Stephen W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case–control study</atitle><jtitle>British journal of cancer</jtitle><stitle>Br J Cancer</stitle><addtitle>Br J Cancer</addtitle><date>2021-09-14</date><risdate>2021</risdate><volume>125</volume><issue>6</issue><spage>884</spage><epage>892</epage><pages>884-892</pages><issn>0007-0920</issn><issn>1532-1827</issn><eissn>1532-1827</eissn><abstract>Background
This study investigates whether quantitative breast density (BD) serves as an imaging biomarker for more intensive breast cancer screening by predicting interval, and node-positive cancers.
Methods
This case–control study of 1204 women aged 47–73 includes 599 cancer cases (302 screen-detected, 297 interval; 239 node-positive, 360 node-negative) and 605 controls. Automated BD software calculated fibroglandular volume (FGV), volumetric breast density (VBD) and density grade (DG). A radiologist assessed BD using a visual analogue scale (VAS) from 0 to 100. Logistic regression and area under the receiver operating characteristic curves (AUC) determined whether BD could predict mode of detection (screen-detected or interval); node-negative cancers; node-positive cancers, and all cancers vs. controls.
Results
FGV, VBD, VAS, and DG all discriminated interval cancers (all
p
< 0.01) from controls. Only FGV-quartile discriminated screen-detected cancers (
p
< 0.01). Based on AUC, FGV discriminated all cancer types better than VBD or VAS. FGV showed a significantly greater discrimination of interval cancers, AUC = 0.65, than of screen-detected cancers, AUC = 0.61 (
p
< 0.01) as did VBD (0.63 and 0.53, respectively,
p
< 0.001).
Conclusion
FGV, VBD, VAS and DG discriminate interval cancers from controls, reflecting some masking risk. Only FGV discriminates screen-detected cancers perhaps adding a unique component of breast cancer risk.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>34168297</pmid><doi>10.1038/s41416-021-01466-y</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0003-3344-2238</orcidid><orcidid>https://orcid.org/0000-0002-1095-994X</orcidid><orcidid>https://orcid.org/0000-0003-4901-7922</orcidid><orcidid>https://orcid.org/0000-0002-6600-435X</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | British journal of cancer, 2021-09, Vol.125 (6), p.884-892 |
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| source | MEDLINE; Springer Nature - Complete Springer Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central |
| subjects | 631/67/1347 692/499 Aged Biomedical and Life Sciences Biomedicine Breast cancer Breast Density Breast Neoplasms - diagnostic imaging Cancer Research Cancer screening Case-Control Studies Drug Resistance Early Detection of Cancer Epidemiology Female Humans Mammography - methods Medical screening Middle Aged Molecular Medicine Oncology Randomized Controlled Trials as Topic Visual Analog Scale Visual discrimination |
| title | Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case–control study |
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