Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study

Background Guidelines recommend shared decision-making (SDM) around mammography screening for women ≥ 75 years old. Objective To use microsimulation modeling to estimate the lifetime benefits and harms of screening women aged 75, 80, and 85 years based on their individual risk factors (family histor...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of general internal medicine : JGIM 2024-02, Vol.39 (3), p.428-439
Hauptverfasser: Jayasekera, Jinani, Stein, Sarah, Wilson, Oliver W. A., Wojcik, Kaitlyn M., Kamil, Dalya, Røssell, Eeva-Liisa, Abraham, Linn A., O’Meara, Ellen S., Schoenborn, Nancy Li, Schechter, Clyde B., Mandelblatt, Jeanne S., Schonberg, Mara A., Stout, Natasha K.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 439
container_issue 3
container_start_page 428
container_title Journal of general internal medicine : JGIM
container_volume 39
creator Jayasekera, Jinani
Stein, Sarah
Wilson, Oliver W. A.
Wojcik, Kaitlyn M.
Kamil, Dalya
Røssell, Eeva-Liisa
Abraham, Linn A.
O’Meara, Ellen S.
Schoenborn, Nancy Li
Schechter, Clyde B.
Mandelblatt, Jeanne S.
Schonberg, Mara A.
Stout, Natasha K.
description Background Guidelines recommend shared decision-making (SDM) around mammography screening for women ≥ 75 years old. Objective To use microsimulation modeling to estimate the lifetime benefits and harms of screening women aged 75, 80, and 85 years based on their individual risk factors (family history, breast density, prior biopsy) and comorbidity level to support SDM in clinical practice. Design, Setting, and Participants We adapted two established Cancer Intervention and Surveillance Modeling Network (CISNET) models to evaluate the remaining lifetime benefits and harms of screening U.S. women born in 1940, at decision ages 75, 80, and 85 years considering their individual risk factors and comorbidity levels. Results were summarized for average- and higher-risk women (defined as having breast cancer family history, heterogeneously dense breasts, and no prior biopsy, 5% of the population). Main Outcomes and Measures Remaining lifetime breast cancers detected, deaths (breast cancer/other causes), false positives, and overdiagnoses for average- and higher-risk women by age and comorbidity level for screening (one or five screens) vs. no screening per 1000 women. Results Compared to stopping, one additional screen at 75 years old resulted in six and eight more breast cancers detected (10% overdiagnoses), one and two fewer breast cancer deaths, and 52 and 59 false positives per 1000 average- and higher-risk women without comorbidities, respectively. Five additional screens over 10 years led to 23 and 31 additional breast cancer cases (29–31% overdiagnoses), four and 15 breast cancer deaths avoided, and 238 and 268 false positives per 1000 average- and higher-risk screened women without comorbidities, respectively. Screening women at older ages (80 and 85 years old) and high comorbidity levels led to fewer breast cancer deaths and a higher percentage of overdiagnoses. Conclusions Simulation models show that continuing screening in women ≥ 75 years old results in fewer breast cancer deaths but more false positive tests and overdiagnoses. Together, clinicians and 75 + women may use model output to weigh the benefits and harms of continued screening.
doi_str_mv 10.1007/s11606-023-08518-4
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2894722464</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2931867013</sourcerecordid><originalsourceid>FETCH-LOGICAL-c375t-5eeb79078b611be33ea62d3aa5ad836dc2a28d9f6f12d12a42a80342d3a2a2dd3</originalsourceid><addsrcrecordid>eNp9kb9uFDEQhy1ERC6BF6BAlmiQog3-t2svHQRCIiWiOBClNbeevWxY24e9W5xoaHlNniQ-LoBEQWGN5PnmszU_Qp5ydsoZ0y8z5w1rKiZkxUzNTaUekAWvRV1x1eqHZMGMUZXRUh2So5xvGeNSCPOIHErDOFO1WZBvbzBgP0yZQnD0ApLPNPb0GryP6wSbmy1ddgkxDGFNh0B1_fP7j5NyPkePgU6RXoY-Jk-XN5DQ0bfYDXmIofLwpYy8okCXg59HmMolvY4Ox51pOc1u-5gc9DBmfHJfj8mn83cfzy6qqw_vL89eX1Wd1PVU1Ygr3TJtVg3nK5QSoRFOAtTgjGxcJ0AY1_ZNz4XjApQAw6TaIaXjnDwmL_beTYpfZ8yT9UPucBwhYJyzFaZVWgjVqII-_we9jXMK5XdWtJKbRpcdFkrsqS7FnBP2dpMGD2lrObO7aOw-Gluisb-isTv1s3v1vPLo_oz8zqIAcg_k0gprTH_f_o_2DtXfmsw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2931867013</pqid></control><display><type>article</type><title>Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study</title><source>MEDLINE</source><source>SpringerNature Journals</source><creator>Jayasekera, Jinani ; Stein, Sarah ; Wilson, Oliver W. A. ; Wojcik, Kaitlyn M. ; Kamil, Dalya ; Røssell, Eeva-Liisa ; Abraham, Linn A. ; O’Meara, Ellen S. ; Schoenborn, Nancy Li ; Schechter, Clyde B. ; Mandelblatt, Jeanne S. ; Schonberg, Mara A. ; Stout, Natasha K.</creator><creatorcontrib>Jayasekera, Jinani ; Stein, Sarah ; Wilson, Oliver W. A. ; Wojcik, Kaitlyn M. ; Kamil, Dalya ; Røssell, Eeva-Liisa ; Abraham, Linn A. ; O’Meara, Ellen S. ; Schoenborn, Nancy Li ; Schechter, Clyde B. ; Mandelblatt, Jeanne S. ; Schonberg, Mara A. ; Stout, Natasha K.</creatorcontrib><description>Background Guidelines recommend shared decision-making (SDM) around mammography screening for women ≥ 75 years old. Objective To use microsimulation modeling to estimate the lifetime benefits and harms of screening women aged 75, 80, and 85 years based on their individual risk factors (family history, breast density, prior biopsy) and comorbidity level to support SDM in clinical practice. Design, Setting, and Participants We adapted two established Cancer Intervention and Surveillance Modeling Network (CISNET) models to evaluate the remaining lifetime benefits and harms of screening U.S. women born in 1940, at decision ages 75, 80, and 85 years considering their individual risk factors and comorbidity levels. Results were summarized for average- and higher-risk women (defined as having breast cancer family history, heterogeneously dense breasts, and no prior biopsy, 5% of the population). Main Outcomes and Measures Remaining lifetime breast cancers detected, deaths (breast cancer/other causes), false positives, and overdiagnoses for average- and higher-risk women by age and comorbidity level for screening (one or five screens) vs. no screening per 1000 women. Results Compared to stopping, one additional screen at 75 years old resulted in six and eight more breast cancers detected (10% overdiagnoses), one and two fewer breast cancer deaths, and 52 and 59 false positives per 1000 average- and higher-risk women without comorbidities, respectively. Five additional screens over 10 years led to 23 and 31 additional breast cancer cases (29–31% overdiagnoses), four and 15 breast cancer deaths avoided, and 238 and 268 false positives per 1000 average- and higher-risk screened women without comorbidities, respectively. Screening women at older ages (80 and 85 years old) and high comorbidity levels led to fewer breast cancer deaths and a higher percentage of overdiagnoses. Conclusions Simulation models show that continuing screening in women ≥ 75 years old results in fewer breast cancer deaths but more false positive tests and overdiagnoses. Together, clinicians and 75 + women may use model output to weigh the benefits and harms of continued screening.</description><identifier>ISSN: 0884-8734</identifier><identifier>ISSN: 1525-1497</identifier><identifier>EISSN: 1525-1497</identifier><identifier>DOI: 10.1007/s11606-023-08518-4</identifier><identifier>PMID: 38010458</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Aged ; Aged, 80 and over ; Biopsy ; Breast ; Breast cancer ; Breast Density ; Breast Neoplasms - diagnostic imaging ; Breast Neoplasms - epidemiology ; Clinical decision making ; Comorbidity ; Computer Simulation ; Decision making ; Early Detection of Cancer - adverse effects ; Early Detection of Cancer - methods ; Family medical history ; Fatalities ; Female ; Genetics ; Humans ; Internal Medicine ; Mammography ; Mammography - adverse effects ; Mammography - methods ; Mass Screening - adverse effects ; Mass Screening - methods ; Medicine ; Medicine &amp; Public Health ; Modelling ; Original Research ; Risk factors ; Service life assessment ; Simulation models</subject><ispartof>Journal of general internal medicine : JGIM, 2024-02, Vol.39 (3), p.428-439</ispartof><rights>This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023</rights><rights>2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.</rights><rights>This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-5eeb79078b611be33ea62d3aa5ad836dc2a28d9f6f12d12a42a80342d3a2a2dd3</citedby><cites>FETCH-LOGICAL-c375t-5eeb79078b611be33ea62d3aa5ad836dc2a28d9f6f12d12a42a80342d3a2a2dd3</cites><orcidid>0000-0001-9212-7225</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11606-023-08518-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11606-023-08518-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,781,785,27928,27929,41492,42561,51323</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38010458$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jayasekera, Jinani</creatorcontrib><creatorcontrib>Stein, Sarah</creatorcontrib><creatorcontrib>Wilson, Oliver W. A.</creatorcontrib><creatorcontrib>Wojcik, Kaitlyn M.</creatorcontrib><creatorcontrib>Kamil, Dalya</creatorcontrib><creatorcontrib>Røssell, Eeva-Liisa</creatorcontrib><creatorcontrib>Abraham, Linn A.</creatorcontrib><creatorcontrib>O’Meara, Ellen S.</creatorcontrib><creatorcontrib>Schoenborn, Nancy Li</creatorcontrib><creatorcontrib>Schechter, Clyde B.</creatorcontrib><creatorcontrib>Mandelblatt, Jeanne S.</creatorcontrib><creatorcontrib>Schonberg, Mara A.</creatorcontrib><creatorcontrib>Stout, Natasha K.</creatorcontrib><title>Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study</title><title>Journal of general internal medicine : JGIM</title><addtitle>J GEN INTERN MED</addtitle><addtitle>J Gen Intern Med</addtitle><description>Background Guidelines recommend shared decision-making (SDM) around mammography screening for women ≥ 75 years old. Objective To use microsimulation modeling to estimate the lifetime benefits and harms of screening women aged 75, 80, and 85 years based on their individual risk factors (family history, breast density, prior biopsy) and comorbidity level to support SDM in clinical practice. Design, Setting, and Participants We adapted two established Cancer Intervention and Surveillance Modeling Network (CISNET) models to evaluate the remaining lifetime benefits and harms of screening U.S. women born in 1940, at decision ages 75, 80, and 85 years considering their individual risk factors and comorbidity levels. Results were summarized for average- and higher-risk women (defined as having breast cancer family history, heterogeneously dense breasts, and no prior biopsy, 5% of the population). Main Outcomes and Measures Remaining lifetime breast cancers detected, deaths (breast cancer/other causes), false positives, and overdiagnoses for average- and higher-risk women by age and comorbidity level for screening (one or five screens) vs. no screening per 1000 women. Results Compared to stopping, one additional screen at 75 years old resulted in six and eight more breast cancers detected (10% overdiagnoses), one and two fewer breast cancer deaths, and 52 and 59 false positives per 1000 average- and higher-risk women without comorbidities, respectively. Five additional screens over 10 years led to 23 and 31 additional breast cancer cases (29–31% overdiagnoses), four and 15 breast cancer deaths avoided, and 238 and 268 false positives per 1000 average- and higher-risk screened women without comorbidities, respectively. Screening women at older ages (80 and 85 years old) and high comorbidity levels led to fewer breast cancer deaths and a higher percentage of overdiagnoses. Conclusions Simulation models show that continuing screening in women ≥ 75 years old results in fewer breast cancer deaths but more false positive tests and overdiagnoses. Together, clinicians and 75 + women may use model output to weigh the benefits and harms of continued screening.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Biopsy</subject><subject>Breast</subject><subject>Breast cancer</subject><subject>Breast Density</subject><subject>Breast Neoplasms - diagnostic imaging</subject><subject>Breast Neoplasms - epidemiology</subject><subject>Clinical decision making</subject><subject>Comorbidity</subject><subject>Computer Simulation</subject><subject>Decision making</subject><subject>Early Detection of Cancer - adverse effects</subject><subject>Early Detection of Cancer - methods</subject><subject>Family medical history</subject><subject>Fatalities</subject><subject>Female</subject><subject>Genetics</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Mammography</subject><subject>Mammography - adverse effects</subject><subject>Mammography - methods</subject><subject>Mass Screening - adverse effects</subject><subject>Mass Screening - methods</subject><subject>Medicine</subject><subject>Medicine &amp; Public Health</subject><subject>Modelling</subject><subject>Original Research</subject><subject>Risk factors</subject><subject>Service life assessment</subject><subject>Simulation models</subject><issn>0884-8734</issn><issn>1525-1497</issn><issn>1525-1497</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kb9uFDEQhy1ERC6BF6BAlmiQog3-t2svHQRCIiWiOBClNbeevWxY24e9W5xoaHlNniQ-LoBEQWGN5PnmszU_Qp5ydsoZ0y8z5w1rKiZkxUzNTaUekAWvRV1x1eqHZMGMUZXRUh2So5xvGeNSCPOIHErDOFO1WZBvbzBgP0yZQnD0ApLPNPb0GryP6wSbmy1ddgkxDGFNh0B1_fP7j5NyPkePgU6RXoY-Jk-XN5DQ0bfYDXmIofLwpYy8okCXg59HmMolvY4Ox51pOc1u-5gc9DBmfHJfj8mn83cfzy6qqw_vL89eX1Wd1PVU1Ygr3TJtVg3nK5QSoRFOAtTgjGxcJ0AY1_ZNz4XjApQAw6TaIaXjnDwmL_beTYpfZ8yT9UPucBwhYJyzFaZVWgjVqII-_we9jXMK5XdWtJKbRpcdFkrsqS7FnBP2dpMGD2lrObO7aOw-Gluisb-isTv1s3v1vPLo_oz8zqIAcg_k0gprTH_f_o_2DtXfmsw</recordid><startdate>20240201</startdate><enddate>20240201</enddate><creator>Jayasekera, Jinani</creator><creator>Stein, Sarah</creator><creator>Wilson, Oliver W. A.</creator><creator>Wojcik, Kaitlyn M.</creator><creator>Kamil, Dalya</creator><creator>Røssell, Eeva-Liisa</creator><creator>Abraham, Linn A.</creator><creator>O’Meara, Ellen S.</creator><creator>Schoenborn, Nancy Li</creator><creator>Schechter, Clyde B.</creator><creator>Mandelblatt, Jeanne S.</creator><creator>Schonberg, Mara A.</creator><creator>Stout, Natasha K.</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><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>7QL</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>K9.</scope><scope>M7N</scope><scope>NAPCQ</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9212-7225</orcidid></search><sort><creationdate>20240201</creationdate><title>Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study</title><author>Jayasekera, Jinani ; Stein, Sarah ; Wilson, Oliver W. A. ; Wojcik, Kaitlyn M. ; Kamil, Dalya ; Røssell, Eeva-Liisa ; Abraham, Linn A. ; O’Meara, Ellen S. ; Schoenborn, Nancy Li ; Schechter, Clyde B. ; Mandelblatt, Jeanne S. ; Schonberg, Mara A. ; Stout, Natasha K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-5eeb79078b611be33ea62d3aa5ad836dc2a28d9f6f12d12a42a80342d3a2a2dd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Biopsy</topic><topic>Breast</topic><topic>Breast cancer</topic><topic>Breast Density</topic><topic>Breast Neoplasms - diagnostic imaging</topic><topic>Breast Neoplasms - epidemiology</topic><topic>Clinical decision making</topic><topic>Comorbidity</topic><topic>Computer Simulation</topic><topic>Decision making</topic><topic>Early Detection of Cancer - adverse effects</topic><topic>Early Detection of Cancer - methods</topic><topic>Family medical history</topic><topic>Fatalities</topic><topic>Female</topic><topic>Genetics</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Mammography</topic><topic>Mammography - adverse effects</topic><topic>Mammography - methods</topic><topic>Mass Screening - adverse effects</topic><topic>Mass Screening - methods</topic><topic>Medicine</topic><topic>Medicine &amp; Public Health</topic><topic>Modelling</topic><topic>Original Research</topic><topic>Risk factors</topic><topic>Service life assessment</topic><topic>Simulation models</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jayasekera, Jinani</creatorcontrib><creatorcontrib>Stein, Sarah</creatorcontrib><creatorcontrib>Wilson, Oliver W. A.</creatorcontrib><creatorcontrib>Wojcik, Kaitlyn M.</creatorcontrib><creatorcontrib>Kamil, Dalya</creatorcontrib><creatorcontrib>Røssell, Eeva-Liisa</creatorcontrib><creatorcontrib>Abraham, Linn A.</creatorcontrib><creatorcontrib>O’Meara, Ellen S.</creatorcontrib><creatorcontrib>Schoenborn, Nancy Li</creatorcontrib><creatorcontrib>Schechter, Clyde B.</creatorcontrib><creatorcontrib>Mandelblatt, Jeanne S.</creatorcontrib><creatorcontrib>Schonberg, Mara A.</creatorcontrib><creatorcontrib>Stout, Natasha K.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of general internal medicine : JGIM</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jayasekera, Jinani</au><au>Stein, Sarah</au><au>Wilson, Oliver W. A.</au><au>Wojcik, Kaitlyn M.</au><au>Kamil, Dalya</au><au>Røssell, Eeva-Liisa</au><au>Abraham, Linn A.</au><au>O’Meara, Ellen S.</au><au>Schoenborn, Nancy Li</au><au>Schechter, Clyde B.</au><au>Mandelblatt, Jeanne S.</au><au>Schonberg, Mara A.</au><au>Stout, Natasha K.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study</atitle><jtitle>Journal of general internal medicine : JGIM</jtitle><stitle>J GEN INTERN MED</stitle><addtitle>J Gen Intern Med</addtitle><date>2024-02-01</date><risdate>2024</risdate><volume>39</volume><issue>3</issue><spage>428</spage><epage>439</epage><pages>428-439</pages><issn>0884-8734</issn><issn>1525-1497</issn><eissn>1525-1497</eissn><abstract>Background Guidelines recommend shared decision-making (SDM) around mammography screening for women ≥ 75 years old. Objective To use microsimulation modeling to estimate the lifetime benefits and harms of screening women aged 75, 80, and 85 years based on their individual risk factors (family history, breast density, prior biopsy) and comorbidity level to support SDM in clinical practice. Design, Setting, and Participants We adapted two established Cancer Intervention and Surveillance Modeling Network (CISNET) models to evaluate the remaining lifetime benefits and harms of screening U.S. women born in 1940, at decision ages 75, 80, and 85 years considering their individual risk factors and comorbidity levels. Results were summarized for average- and higher-risk women (defined as having breast cancer family history, heterogeneously dense breasts, and no prior biopsy, 5% of the population). Main Outcomes and Measures Remaining lifetime breast cancers detected, deaths (breast cancer/other causes), false positives, and overdiagnoses for average- and higher-risk women by age and comorbidity level for screening (one or five screens) vs. no screening per 1000 women. Results Compared to stopping, one additional screen at 75 years old resulted in six and eight more breast cancers detected (10% overdiagnoses), one and two fewer breast cancer deaths, and 52 and 59 false positives per 1000 average- and higher-risk women without comorbidities, respectively. Five additional screens over 10 years led to 23 and 31 additional breast cancer cases (29–31% overdiagnoses), four and 15 breast cancer deaths avoided, and 238 and 268 false positives per 1000 average- and higher-risk screened women without comorbidities, respectively. Screening women at older ages (80 and 85 years old) and high comorbidity levels led to fewer breast cancer deaths and a higher percentage of overdiagnoses. Conclusions Simulation models show that continuing screening in women ≥ 75 years old results in fewer breast cancer deaths but more false positive tests and overdiagnoses. Together, clinicians and 75 + women may use model output to weigh the benefits and harms of continued screening.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>38010458</pmid><doi>10.1007/s11606-023-08518-4</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-9212-7225</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0884-8734
ispartof Journal of general internal medicine : JGIM, 2024-02, Vol.39 (3), p.428-439
issn 0884-8734
1525-1497
1525-1497
language eng
recordid cdi_proquest_miscellaneous_2894722464
source MEDLINE; SpringerNature Journals
subjects Aged
Aged, 80 and over
Biopsy
Breast
Breast cancer
Breast Density
Breast Neoplasms - diagnostic imaging
Breast Neoplasms - epidemiology
Clinical decision making
Comorbidity
Computer Simulation
Decision making
Early Detection of Cancer - adverse effects
Early Detection of Cancer - methods
Family medical history
Fatalities
Female
Genetics
Humans
Internal Medicine
Mammography
Mammography - adverse effects
Mammography - methods
Mass Screening - adverse effects
Mass Screening - methods
Medicine
Medicine & Public Health
Modelling
Original Research
Risk factors
Service life assessment
Simulation models
title Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-17T12%3A02%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Benefits%20and%20Harms%20of%20Mammography%20Screening%20in%2075%E2%80%89+%E2%80%89Women%20to%20Inform%20Shared%20Decision-making:%20a%20Simulation%20Modeling%20Study&rft.jtitle=Journal%20of%20general%20internal%20medicine%20:%20JGIM&rft.au=Jayasekera,%20Jinani&rft.date=2024-02-01&rft.volume=39&rft.issue=3&rft.spage=428&rft.epage=439&rft.pages=428-439&rft.issn=0884-8734&rft.eissn=1525-1497&rft_id=info:doi/10.1007/s11606-023-08518-4&rft_dat=%3Cproquest_cross%3E2931867013%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2931867013&rft_id=info:pmid/38010458&rfr_iscdi=true