Risk of mortality of node-negative, ER/PR/HER2 breast cancer subtypes in T1, T2, and T3 tumors
Purpose The purpose of this study was to assess differences in breast cancer-specific mortality within tumors of the same size when breast cancer was defined using the three tumor markers estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Methods...
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| Veröffentlicht in: | Breast cancer research and treatment 2017-10, Vol.165 (3), p.743-750 |
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| creator | Parise, Carol A. Caggiano, Vincent |
| description | Purpose
The purpose of this study was to assess differences in breast cancer-specific mortality within tumors of the same size when breast cancer was defined using the three tumor markers estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2).
Methods
We identified 104,499 cases of node-negative primary female invasive breast cancer from the California Cancer Registry. Tumor size was categorized as T1a, T1b, T1c, T2, and T3. Breast cancer was defined using ER, PR, and HER2. Kaplan–Meier Survival analysis was conducted and Cox Regression was used to compute the adjusted risk of mortality for the ER+/PR+/HER2+, ER−/PR−/HER2− (TNBC), and ER−/PR−/HER2+ (HER2-overexpressing) subtypes when compared with the ER+/PR+/HER2−. Separate models were computed for each tumor size.
Results
Unadjusted survival analysis showed that for all tumor sizes, the ER+/PR+ subtypes regardless of HER status have better breast cancer-specific survival than ER−/PR− subtypes. Subtype was not an important factor for risk of mortality for T1a tumors. The ER+/PR+/HER2+ subtype was only a risk for mortality in T1b tumors that were unadjusted for treatment. For all other tumor sizes, the ER+/PR+/HER2+ had the same mortality as the ER+/PR+/HER2− subtype regardless of adjustment for treatment. The HER2-overexpressing subtype had a higher risk of mortality than the ER+/PR+/HER2− subtype except for T1b tumors that were adjusted for treatment. For all tumor sizes, the TNBC had higher hazard ratios than all other subtypes.
Conclusions
T1a tumors have the same risk of mortality regardless of ER/PR/HER2 subtype, and ER and PR negativity plays a stronger role in survival than HER2 positivity for tumors of all size. |
| doi_str_mv | 10.1007/s10549-017-4383-5 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1917665287</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1939198288</sourcerecordid><originalsourceid>FETCH-LOGICAL-c372t-71c197cb5fc72e154defb0c7d1e8154a0c1fe89a4fa803946cf0abaaca7d88b93</originalsourceid><addsrcrecordid>eNp1kFFLIzEQx4N4nFXvA_giAV98aK6ZZHeTPEqpVhDuKL1XQzY7W1bb3ZrsCv32l1IVEXwahvnNf4YfIRfAfwPnahKB55lhHBTLpJYsPyIjyJVkSoA6JiMOhWKF5sUJOY3xiXNuFDc_yYnQhTaykCPyuGjiM-1quulC79ZNv9s3bVcha3Hl-uYVx3S2mPxdTOazhaBlQBd76l3rMdA4lP1ui5E2LV3CmC7FmLq2oktJ-yElxnPyo3briL_e6hn5dztbTufs4c_d_fTmgXmpRM8UeDDKl3ntlUDIswrrkntVAerUOe6hRm1cVjvNpckKX3NXOuedqrQujTwj14fcbeheBoy93TTR43rtWuyGaMGAKopcaJXQqy_oUzeENn2XKGnAaKF1ouBA-dDFGLC229BsXNhZ4HYv3x7k2yTf7uXbPO1cviUP5Qarj4132wkQByCmUbvC8On0t6n_AYlBjPs</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1939198288</pqid></control><display><type>article</type><title>Risk of mortality of node-negative, ER/PR/HER2 breast cancer subtypes in T1, T2, and T3 tumors</title><source>MEDLINE</source><source>SpringerLink Journals - AutoHoldings</source><creator>Parise, Carol A. ; Caggiano, Vincent</creator><creatorcontrib>Parise, Carol A. ; Caggiano, Vincent</creatorcontrib><description>Purpose
The purpose of this study was to assess differences in breast cancer-specific mortality within tumors of the same size when breast cancer was defined using the three tumor markers estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2).
Methods
We identified 104,499 cases of node-negative primary female invasive breast cancer from the California Cancer Registry. Tumor size was categorized as T1a, T1b, T1c, T2, and T3. Breast cancer was defined using ER, PR, and HER2. Kaplan–Meier Survival analysis was conducted and Cox Regression was used to compute the adjusted risk of mortality for the ER+/PR+/HER2+, ER−/PR−/HER2− (TNBC), and ER−/PR−/HER2+ (HER2-overexpressing) subtypes when compared with the ER+/PR+/HER2−. Separate models were computed for each tumor size.
Results
Unadjusted survival analysis showed that for all tumor sizes, the ER+/PR+ subtypes regardless of HER status have better breast cancer-specific survival than ER−/PR− subtypes. Subtype was not an important factor for risk of mortality for T1a tumors. The ER+/PR+/HER2+ subtype was only a risk for mortality in T1b tumors that were unadjusted for treatment. For all other tumor sizes, the ER+/PR+/HER2+ had the same mortality as the ER+/PR+/HER2− subtype regardless of adjustment for treatment. The HER2-overexpressing subtype had a higher risk of mortality than the ER+/PR+/HER2− subtype except for T1b tumors that were adjusted for treatment. For all tumor sizes, the TNBC had higher hazard ratios than all other subtypes.
Conclusions
T1a tumors have the same risk of mortality regardless of ER/PR/HER2 subtype, and ER and PR negativity plays a stronger role in survival than HER2 positivity for tumors of all size.</description><identifier>ISSN: 0167-6806</identifier><identifier>EISSN: 1573-7217</identifier><identifier>DOI: 10.1007/s10549-017-4383-5</identifier><identifier>PMID: 28689363</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Adult ; Aged ; Biomarkers, Tumor ; Breast cancer ; Breast Neoplasms - diagnosis ; Breast Neoplasms - epidemiology ; Breast Neoplasms - mortality ; Breast Neoplasms - therapy ; Cancer research ; Epidemiology ; Epidermal growth factor ; ErbB-2 protein ; Estrogen receptors ; Estrogens ; Female ; Follow-Up Studies ; Health risk assessment ; Humans ; Invasiveness ; Kaplan-Meier Estimate ; Medicine ; Medicine & Public Health ; Middle Aged ; Mortality ; Neoplasm Grading ; Neoplasm Staging ; Oncology ; Population Surveillance ; Progesterone ; Proportional Hazards Models ; Receptor, ErbB-2 ; Receptors, Estrogen ; Receptors, Progesterone ; Survival ; Survival analysis ; Tumor markers ; Tumors</subject><ispartof>Breast cancer research and treatment, 2017-10, Vol.165 (3), p.743-750</ispartof><rights>Springer Science+Business Media, LLC 2017</rights><rights>Breast Cancer Research and Treatment is a copyright of Springer, 2017.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c372t-71c197cb5fc72e154defb0c7d1e8154a0c1fe89a4fa803946cf0abaaca7d88b93</citedby><cites>FETCH-LOGICAL-c372t-71c197cb5fc72e154defb0c7d1e8154a0c1fe89a4fa803946cf0abaaca7d88b93</cites><orcidid>0000-0002-3098-6160</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/s10549-017-4383-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10549-017-4383-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28689363$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Parise, Carol A.</creatorcontrib><creatorcontrib>Caggiano, Vincent</creatorcontrib><title>Risk of mortality of node-negative, ER/PR/HER2 breast cancer subtypes in T1, T2, and T3 tumors</title><title>Breast cancer research and treatment</title><addtitle>Breast Cancer Res Treat</addtitle><addtitle>Breast Cancer Res Treat</addtitle><description>Purpose
The purpose of this study was to assess differences in breast cancer-specific mortality within tumors of the same size when breast cancer was defined using the three tumor markers estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2).
Methods
We identified 104,499 cases of node-negative primary female invasive breast cancer from the California Cancer Registry. Tumor size was categorized as T1a, T1b, T1c, T2, and T3. Breast cancer was defined using ER, PR, and HER2. Kaplan–Meier Survival analysis was conducted and Cox Regression was used to compute the adjusted risk of mortality for the ER+/PR+/HER2+, ER−/PR−/HER2− (TNBC), and ER−/PR−/HER2+ (HER2-overexpressing) subtypes when compared with the ER+/PR+/HER2−. Separate models were computed for each tumor size.
Results
Unadjusted survival analysis showed that for all tumor sizes, the ER+/PR+ subtypes regardless of HER status have better breast cancer-specific survival than ER−/PR− subtypes. Subtype was not an important factor for risk of mortality for T1a tumors. The ER+/PR+/HER2+ subtype was only a risk for mortality in T1b tumors that were unadjusted for treatment. For all other tumor sizes, the ER+/PR+/HER2+ had the same mortality as the ER+/PR+/HER2− subtype regardless of adjustment for treatment. The HER2-overexpressing subtype had a higher risk of mortality than the ER+/PR+/HER2− subtype except for T1b tumors that were adjusted for treatment. For all tumor sizes, the TNBC had higher hazard ratios than all other subtypes.
Conclusions
T1a tumors have the same risk of mortality regardless of ER/PR/HER2 subtype, and ER and PR negativity plays a stronger role in survival than HER2 positivity for tumors of all size.</description><subject>Adult</subject><subject>Aged</subject><subject>Biomarkers, Tumor</subject><subject>Breast cancer</subject><subject>Breast Neoplasms - diagnosis</subject><subject>Breast Neoplasms - epidemiology</subject><subject>Breast Neoplasms - mortality</subject><subject>Breast Neoplasms - therapy</subject><subject>Cancer research</subject><subject>Epidemiology</subject><subject>Epidermal growth factor</subject><subject>ErbB-2 protein</subject><subject>Estrogen receptors</subject><subject>Estrogens</subject><subject>Female</subject><subject>Follow-Up Studies</subject><subject>Health risk assessment</subject><subject>Humans</subject><subject>Invasiveness</subject><subject>Kaplan-Meier Estimate</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Neoplasm Grading</subject><subject>Neoplasm Staging</subject><subject>Oncology</subject><subject>Population Surveillance</subject><subject>Progesterone</subject><subject>Proportional Hazards Models</subject><subject>Receptor, ErbB-2</subject><subject>Receptors, Estrogen</subject><subject>Receptors, Progesterone</subject><subject>Survival</subject><subject>Survival analysis</subject><subject>Tumor markers</subject><subject>Tumors</subject><issn>0167-6806</issn><issn>1573-7217</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1kFFLIzEQx4N4nFXvA_giAV98aK6ZZHeTPEqpVhDuKL1XQzY7W1bb3ZrsCv32l1IVEXwahvnNf4YfIRfAfwPnahKB55lhHBTLpJYsPyIjyJVkSoA6JiMOhWKF5sUJOY3xiXNuFDc_yYnQhTaykCPyuGjiM-1quulC79ZNv9s3bVcha3Hl-uYVx3S2mPxdTOazhaBlQBd76l3rMdA4lP1ui5E2LV3CmC7FmLq2oktJ-yElxnPyo3briL_e6hn5dztbTufs4c_d_fTmgXmpRM8UeDDKl3ntlUDIswrrkntVAerUOe6hRm1cVjvNpckKX3NXOuedqrQujTwj14fcbeheBoy93TTR43rtWuyGaMGAKopcaJXQqy_oUzeENn2XKGnAaKF1ouBA-dDFGLC229BsXNhZ4HYv3x7k2yTf7uXbPO1cviUP5Qarj4132wkQByCmUbvC8On0t6n_AYlBjPs</recordid><startdate>20171001</startdate><enddate>20171001</enddate><creator>Parise, Carol A.</creator><creator>Caggiano, Vincent</creator><general>Springer US</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>3V.</scope><scope>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>K9-</scope><scope>K9.</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-3098-6160</orcidid></search><sort><creationdate>20171001</creationdate><title>Risk of mortality of node-negative, ER/PR/HER2 breast cancer subtypes in T1, T2, and T3 tumors</title><author>Parise, Carol A. ; Caggiano, Vincent</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c372t-71c197cb5fc72e154defb0c7d1e8154a0c1fe89a4fa803946cf0abaaca7d88b93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Biomarkers, Tumor</topic><topic>Breast cancer</topic><topic>Breast Neoplasms - diagnosis</topic><topic>Breast Neoplasms - epidemiology</topic><topic>Breast Neoplasms - mortality</topic><topic>Breast Neoplasms - therapy</topic><topic>Cancer research</topic><topic>Epidemiology</topic><topic>Epidermal growth factor</topic><topic>ErbB-2 protein</topic><topic>Estrogen receptors</topic><topic>Estrogens</topic><topic>Female</topic><topic>Follow-Up Studies</topic><topic>Health risk assessment</topic><topic>Humans</topic><topic>Invasiveness</topic><topic>Kaplan-Meier Estimate</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Neoplasm Grading</topic><topic>Neoplasm Staging</topic><topic>Oncology</topic><topic>Population Surveillance</topic><topic>Progesterone</topic><topic>Proportional Hazards Models</topic><topic>Receptor, ErbB-2</topic><topic>Receptors, Estrogen</topic><topic>Receptors, Progesterone</topic><topic>Survival</topic><topic>Survival analysis</topic><topic>Tumor markers</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Parise, Carol A.</creatorcontrib><creatorcontrib>Caggiano, Vincent</creatorcontrib><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>Oncogenes and Growth Factors 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>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</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>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</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 Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Breast cancer research and treatment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Parise, Carol A.</au><au>Caggiano, Vincent</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Risk of mortality of node-negative, ER/PR/HER2 breast cancer subtypes in T1, T2, and T3 tumors</atitle><jtitle>Breast cancer research and treatment</jtitle><stitle>Breast Cancer Res Treat</stitle><addtitle>Breast Cancer Res Treat</addtitle><date>2017-10-01</date><risdate>2017</risdate><volume>165</volume><issue>3</issue><spage>743</spage><epage>750</epage><pages>743-750</pages><issn>0167-6806</issn><eissn>1573-7217</eissn><abstract>Purpose
The purpose of this study was to assess differences in breast cancer-specific mortality within tumors of the same size when breast cancer was defined using the three tumor markers estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2).
Methods
We identified 104,499 cases of node-negative primary female invasive breast cancer from the California Cancer Registry. Tumor size was categorized as T1a, T1b, T1c, T2, and T3. Breast cancer was defined using ER, PR, and HER2. Kaplan–Meier Survival analysis was conducted and Cox Regression was used to compute the adjusted risk of mortality for the ER+/PR+/HER2+, ER−/PR−/HER2− (TNBC), and ER−/PR−/HER2+ (HER2-overexpressing) subtypes when compared with the ER+/PR+/HER2−. Separate models were computed for each tumor size.
Results
Unadjusted survival analysis showed that for all tumor sizes, the ER+/PR+ subtypes regardless of HER status have better breast cancer-specific survival than ER−/PR− subtypes. Subtype was not an important factor for risk of mortality for T1a tumors. The ER+/PR+/HER2+ subtype was only a risk for mortality in T1b tumors that were unadjusted for treatment. For all other tumor sizes, the ER+/PR+/HER2+ had the same mortality as the ER+/PR+/HER2− subtype regardless of adjustment for treatment. The HER2-overexpressing subtype had a higher risk of mortality than the ER+/PR+/HER2− subtype except for T1b tumors that were adjusted for treatment. For all tumor sizes, the TNBC had higher hazard ratios than all other subtypes.
Conclusions
T1a tumors have the same risk of mortality regardless of ER/PR/HER2 subtype, and ER and PR negativity plays a stronger role in survival than HER2 positivity for tumors of all size.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>28689363</pmid><doi>10.1007/s10549-017-4383-5</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-3098-6160</orcidid></addata></record> |
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| subjects | Adult Aged Biomarkers, Tumor Breast cancer Breast Neoplasms - diagnosis Breast Neoplasms - epidemiology Breast Neoplasms - mortality Breast Neoplasms - therapy Cancer research Epidemiology Epidermal growth factor ErbB-2 protein Estrogen receptors Estrogens Female Follow-Up Studies Health risk assessment Humans Invasiveness Kaplan-Meier Estimate Medicine Medicine & Public Health Middle Aged Mortality Neoplasm Grading Neoplasm Staging Oncology Population Surveillance Progesterone Proportional Hazards Models Receptor, ErbB-2 Receptors, Estrogen Receptors, Progesterone Survival Survival analysis Tumor markers Tumors |
| title | Risk of mortality of node-negative, ER/PR/HER2 breast cancer subtypes in T1, T2, and T3 tumors |
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