Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study

In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients wit...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:PloS one 2014-04, Vol.9 (4), p.e93755-e93755
Hauptverfasser: Miao, Hui, Hartman, Mikael, Bhoo-Pathy, Nirmala, Lee, Soo-Chin, Taib, Nur Aishah, Tan, Ern-Yu, Chan, Patrick, Moons, Karel G M, Wong, Hoong-Seam, Goh, Jeremy, Rahim, Siti Mastura, Yip, Cheng-Har, Verkooijen, Helena M
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page e93755
container_issue 4
container_start_page e93755
container_title PloS one
container_volume 9
creator Miao, Hui
Hartman, Mikael
Bhoo-Pathy, Nirmala
Lee, Soo-Chin
Taib, Nur Aishah
Tan, Ern-Yu
Chan, Patrick
Moons, Karel G M
Wong, Hoong-Seam
Goh, Jeremy
Rahim, Siti Mastura
Yip, Cheng-Har
Verkooijen, Helena M
description In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53) to 0.63 (95% CI, 0.60-0.66). The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.
doi_str_mv 10.1371/journal.pone.0093755
format Article
fullrecord <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_1512317438</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A375583012</galeid><doaj_id>oai_doaj_org_article_b673920df8cd4f6eb85e1d80f42a0361</doaj_id><sourcerecordid>A375583012</sourcerecordid><originalsourceid>FETCH-LOGICAL-c730t-a7b46dd995867c02b7caf5e2eae30967cafa1f93df125c252cd6a9b3d0b5818c3</originalsourceid><addsrcrecordid>eNqNk9tu1DAQhiMEomXhDRBYQkJwsYsPcQ5cIFUVh5UqFXG6tRx7suuS2Fs72bJvj7ObVhvUC5SLTCbf_ycznkmS5wQvCMvJuyvXeyubxcZZWGBcspzzB8kpKRmdZxSzh0fxSfIkhCuMOSuy7HFyQtOs5FlJTxP71YM2qjN2hULvt2YrG-RqpAFZt3WohU6GTnZGocpDDJGSVoFHxqKzYKRFN64F-x6FXeig3YMetgZukLQaRTejY9JZFLpe754mj2rZBHg23mfJz08ff5x_mV9cfl6en13MVc5wN5d5lWZalyUvslxhWuVK1hwoSGC4zIYnSeqS6ZpQriinSmeyrJjGFS9IodgseXnw3TQuiLFVQRBOKCN5yopILA-EdvJKbLxppd8JJ43YJ5xfCeljNQ2IKstZSbGuC6XTOoOq4EB0geuUSswyEr3mB69wA5u-mriNqd8xAsEp5SSP_Ifx7_qqBa3Adl42E9n0jTVrsXJbwcqc8byMBm9GA--uewidaE1Q0DTSguv3dTKcFsOBz5JX_6D3d2OkVjIWbGzt4nfVYCrOhsEqGI7sLFncQ8VLQ2tUnMPaxPxE8HYiiEwHf7qV7EMQy-_f_p-9_DVlXx-xa5BNtw6u6YdBC1MwPYDKuxA81HdNJlgMa3TbDTGskRjXKMpeHB_Qneh2b9hfuJQZxA</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1512317438</pqid></control><display><type>article</type><title>Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>SWEPUB Freely available online</source><source>Public Library of Science (PLoS)</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Miao, Hui ; Hartman, Mikael ; Bhoo-Pathy, Nirmala ; Lee, Soo-Chin ; Taib, Nur Aishah ; Tan, Ern-Yu ; Chan, Patrick ; Moons, Karel G M ; Wong, Hoong-Seam ; Goh, Jeremy ; Rahim, Siti Mastura ; Yip, Cheng-Har ; Verkooijen, Helena M</creator><contributor>Aziz, Syed A.</contributor><creatorcontrib>Miao, Hui ; Hartman, Mikael ; Bhoo-Pathy, Nirmala ; Lee, Soo-Chin ; Taib, Nur Aishah ; Tan, Ern-Yu ; Chan, Patrick ; Moons, Karel G M ; Wong, Hoong-Seam ; Goh, Jeremy ; Rahim, Siti Mastura ; Yip, Cheng-Har ; Verkooijen, Helena M ; Aziz, Syed A.</creatorcontrib><description>In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53) to 0.63 (95% CI, 0.60-0.66). The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0093755</identifier><identifier>PMID: 24695692</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Asian Continental Ancestry Group ; Brain ; Brain cancer ; Breast cancer ; Breast Neoplasms - mortality ; Breast Neoplasms - pathology ; Cancer ; Cancer patients ; Cancer therapies ; Care and treatment ; Chemotherapy ; Decision making ; Epidemiology ; Estrogens ; Ethnicity ; Female ; Health aspects ; Health sciences ; Hospitals ; Humans ; Identification methods ; Malaysia ; Mathematical models ; Medical diagnosis ; Medical prognosis ; Medicine ; Medicine and Health Sciences ; Metastases ; Metastasis ; Neoplasm Metastasis - pathology ; Oligonucleotides ; Oncology, Experimental ; Patient outcomes ; Patients ; Prediction models ; Primary care ; Prognosis ; Public health ; Risk groups ; Singapore ; Statistical analysis ; Studies ; Surgery ; Survival ; Systematic review ; Womens health</subject><ispartof>PloS one, 2014-04, Vol.9 (4), p.e93755-e93755</ispartof><rights>COPYRIGHT 2014 Public Library of Science</rights><rights>2014 Miao et al. 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. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2014 Miao et al 2014 Miao et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c730t-a7b46dd995867c02b7caf5e2eae30967cafa1f93df125c252cd6a9b3d0b5818c3</citedby><cites>FETCH-LOGICAL-c730t-a7b46dd995867c02b7caf5e2eae30967cafa1f93df125c252cd6a9b3d0b5818c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973579/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973579/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,550,723,776,780,860,881,2095,2914,23846,27903,27904,53769,53771,79346,79347</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24695692$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttp://kipublications.ki.se/Default.aspx?queryparsed=id:128706502$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><contributor>Aziz, Syed A.</contributor><creatorcontrib>Miao, Hui</creatorcontrib><creatorcontrib>Hartman, Mikael</creatorcontrib><creatorcontrib>Bhoo-Pathy, Nirmala</creatorcontrib><creatorcontrib>Lee, Soo-Chin</creatorcontrib><creatorcontrib>Taib, Nur Aishah</creatorcontrib><creatorcontrib>Tan, Ern-Yu</creatorcontrib><creatorcontrib>Chan, Patrick</creatorcontrib><creatorcontrib>Moons, Karel G M</creatorcontrib><creatorcontrib>Wong, Hoong-Seam</creatorcontrib><creatorcontrib>Goh, Jeremy</creatorcontrib><creatorcontrib>Rahim, Siti Mastura</creatorcontrib><creatorcontrib>Yip, Cheng-Har</creatorcontrib><creatorcontrib>Verkooijen, Helena M</creatorcontrib><title>Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53) to 0.63 (95% CI, 0.60-0.66). The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.</description><subject>Analysis</subject><subject>Asian Continental Ancestry Group</subject><subject>Brain</subject><subject>Brain cancer</subject><subject>Breast cancer</subject><subject>Breast Neoplasms - mortality</subject><subject>Breast Neoplasms - pathology</subject><subject>Cancer</subject><subject>Cancer patients</subject><subject>Cancer therapies</subject><subject>Care and treatment</subject><subject>Chemotherapy</subject><subject>Decision making</subject><subject>Epidemiology</subject><subject>Estrogens</subject><subject>Ethnicity</subject><subject>Female</subject><subject>Health aspects</subject><subject>Health sciences</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Identification methods</subject><subject>Malaysia</subject><subject>Mathematical models</subject><subject>Medical diagnosis</subject><subject>Medical prognosis</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>Metastases</subject><subject>Metastasis</subject><subject>Neoplasm Metastasis - pathology</subject><subject>Oligonucleotides</subject><subject>Oncology, Experimental</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>Prediction models</subject><subject>Primary care</subject><subject>Prognosis</subject><subject>Public health</subject><subject>Risk groups</subject><subject>Singapore</subject><subject>Statistical analysis</subject><subject>Studies</subject><subject>Surgery</subject><subject>Survival</subject><subject>Systematic review</subject><subject>Womens health</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>D8T</sourceid><sourceid>DOA</sourceid><recordid>eNqNk9tu1DAQhiMEomXhDRBYQkJwsYsPcQ5cIFUVh5UqFXG6tRx7suuS2Fs72bJvj7ObVhvUC5SLTCbf_ycznkmS5wQvCMvJuyvXeyubxcZZWGBcspzzB8kpKRmdZxSzh0fxSfIkhCuMOSuy7HFyQtOs5FlJTxP71YM2qjN2hULvt2YrG-RqpAFZt3WohU6GTnZGocpDDJGSVoFHxqKzYKRFN64F-x6FXeig3YMetgZukLQaRTejY9JZFLpe754mj2rZBHg23mfJz08ff5x_mV9cfl6en13MVc5wN5d5lWZalyUvslxhWuVK1hwoSGC4zIYnSeqS6ZpQriinSmeyrJjGFS9IodgseXnw3TQuiLFVQRBOKCN5yopILA-EdvJKbLxppd8JJ43YJ5xfCeljNQ2IKstZSbGuC6XTOoOq4EB0geuUSswyEr3mB69wA5u-mriNqd8xAsEp5SSP_Ifx7_qqBa3Adl42E9n0jTVrsXJbwcqc8byMBm9GA--uewidaE1Q0DTSguv3dTKcFsOBz5JX_6D3d2OkVjIWbGzt4nfVYCrOhsEqGI7sLFncQ8VLQ2tUnMPaxPxE8HYiiEwHf7qV7EMQy-_f_p-9_DVlXx-xa5BNtw6u6YdBC1MwPYDKuxA81HdNJlgMa3TbDTGskRjXKMpeHB_Qneh2b9hfuJQZxA</recordid><startdate>20140401</startdate><enddate>20140401</enddate><creator>Miao, Hui</creator><creator>Hartman, Mikael</creator><creator>Bhoo-Pathy, Nirmala</creator><creator>Lee, Soo-Chin</creator><creator>Taib, Nur Aishah</creator><creator>Tan, Ern-Yu</creator><creator>Chan, Patrick</creator><creator>Moons, Karel G M</creator><creator>Wong, Hoong-Seam</creator><creator>Goh, Jeremy</creator><creator>Rahim, Siti Mastura</creator><creator>Yip, Cheng-Har</creator><creator>Verkooijen, Helena M</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>D8T</scope><scope>ZZAVC</scope><scope>DOA</scope></search><sort><creationdate>20140401</creationdate><title>Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study</title><author>Miao, Hui ; Hartman, Mikael ; Bhoo-Pathy, Nirmala ; Lee, Soo-Chin ; Taib, Nur Aishah ; Tan, Ern-Yu ; Chan, Patrick ; Moons, Karel G M ; Wong, Hoong-Seam ; Goh, Jeremy ; Rahim, Siti Mastura ; Yip, Cheng-Har ; Verkooijen, Helena M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c730t-a7b46dd995867c02b7caf5e2eae30967cafa1f93df125c252cd6a9b3d0b5818c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Analysis</topic><topic>Asian Continental Ancestry Group</topic><topic>Brain</topic><topic>Brain cancer</topic><topic>Breast cancer</topic><topic>Breast Neoplasms - mortality</topic><topic>Breast Neoplasms - pathology</topic><topic>Cancer</topic><topic>Cancer patients</topic><topic>Cancer therapies</topic><topic>Care and treatment</topic><topic>Chemotherapy</topic><topic>Decision making</topic><topic>Epidemiology</topic><topic>Estrogens</topic><topic>Ethnicity</topic><topic>Female</topic><topic>Health aspects</topic><topic>Health sciences</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Identification methods</topic><topic>Malaysia</topic><topic>Mathematical models</topic><topic>Medical diagnosis</topic><topic>Medical prognosis</topic><topic>Medicine</topic><topic>Medicine and Health Sciences</topic><topic>Metastases</topic><topic>Metastasis</topic><topic>Neoplasm Metastasis - pathology</topic><topic>Oligonucleotides</topic><topic>Oncology, Experimental</topic><topic>Patient outcomes</topic><topic>Patients</topic><topic>Prediction models</topic><topic>Primary care</topic><topic>Prognosis</topic><topic>Public health</topic><topic>Risk groups</topic><topic>Singapore</topic><topic>Statistical analysis</topic><topic>Studies</topic><topic>Surgery</topic><topic>Survival</topic><topic>Systematic review</topic><topic>Womens health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Miao, Hui</creatorcontrib><creatorcontrib>Hartman, Mikael</creatorcontrib><creatorcontrib>Bhoo-Pathy, Nirmala</creatorcontrib><creatorcontrib>Lee, Soo-Chin</creatorcontrib><creatorcontrib>Taib, Nur Aishah</creatorcontrib><creatorcontrib>Tan, Ern-Yu</creatorcontrib><creatorcontrib>Chan, Patrick</creatorcontrib><creatorcontrib>Moons, Karel G M</creatorcontrib><creatorcontrib>Wong, Hoong-Seam</creatorcontrib><creatorcontrib>Goh, Jeremy</creatorcontrib><creatorcontrib>Rahim, Siti Mastura</creatorcontrib><creatorcontrib>Yip, Cheng-Har</creatorcontrib><creatorcontrib>Verkooijen, Helena M</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing &amp; Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health &amp; 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>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology 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>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</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 &amp; Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SwePub Articles full text</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Miao, Hui</au><au>Hartman, Mikael</au><au>Bhoo-Pathy, Nirmala</au><au>Lee, Soo-Chin</au><au>Taib, Nur Aishah</au><au>Tan, Ern-Yu</au><au>Chan, Patrick</au><au>Moons, Karel G M</au><au>Wong, Hoong-Seam</au><au>Goh, Jeremy</au><au>Rahim, Siti Mastura</au><au>Yip, Cheng-Har</au><au>Verkooijen, Helena M</au><au>Aziz, Syed A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2014-04-01</date><risdate>2014</risdate><volume>9</volume><issue>4</issue><spage>e93755</spage><epage>e93755</epage><pages>e93755-e93755</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53) to 0.63 (95% CI, 0.60-0.66). The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24695692</pmid><doi>10.1371/journal.pone.0093755</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1932-6203
ispartof PloS one, 2014-04, Vol.9 (4), p.e93755-e93755
issn 1932-6203
1932-6203
language eng
recordid cdi_plos_journals_1512317438
source MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; SWEPUB Freely available online; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry
subjects Analysis
Asian Continental Ancestry Group
Brain
Brain cancer
Breast cancer
Breast Neoplasms - mortality
Breast Neoplasms - pathology
Cancer
Cancer patients
Cancer therapies
Care and treatment
Chemotherapy
Decision making
Epidemiology
Estrogens
Ethnicity
Female
Health aspects
Health sciences
Hospitals
Humans
Identification methods
Malaysia
Mathematical models
Medical diagnosis
Medical prognosis
Medicine
Medicine and Health Sciences
Metastases
Metastasis
Neoplasm Metastasis - pathology
Oligonucleotides
Oncology, Experimental
Patient outcomes
Patients
Prediction models
Primary care
Prognosis
Public health
Risk groups
Singapore
Statistical analysis
Studies
Surgery
Survival
Systematic review
Womens health
title Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T05%3A24%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Predicting%20survival%20of%20de%20novo%20metastatic%20breast%20cancer%20in%20Asian%20women:%20systematic%20review%20and%20validation%20study&rft.jtitle=PloS%20one&rft.au=Miao,%20Hui&rft.date=2014-04-01&rft.volume=9&rft.issue=4&rft.spage=e93755&rft.epage=e93755&rft.pages=e93755-e93755&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0093755&rft_dat=%3Cgale_plos_%3EA375583012%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1512317438&rft_id=info:pmid/24695692&rft_galeid=A375583012&rft_doaj_id=oai_doaj_org_article_b673920df8cd4f6eb85e1d80f42a0361&rfr_iscdi=true