Value of Information Analysis of Multiparameter Tests for Chemotherapy in Early Breast Cancer: The OPTIMA Prelim Trial
Precision medicine is heralded as offering more effective treatments to smaller targeted patient populations. In breast cancer, adjuvant chemotherapy is standard for patients considered as high-risk after surgery. Molecular tests may identify patients who can safely avoid chemotherapy. To use econom...
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| Veröffentlicht in: | Value in health 2017-12, Vol.20 (10), p.1311-1318 |
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| creator | Hall, Peter S. Smith, Alison Hulme, Claire Vargas-Palacios, Armando Makris, Andreas Hughes-Davies, Luke Dunn, Janet A. Bartlett, John M.S. Cameron, David A. Marshall, Andrea Campbell, Amy Macpherson, Iain R. Dan Rea Francis, Adele Earl, Helena Morgan, Adrienne Stein, Robert C. McCabe, Christopher |
| description | Precision medicine is heralded as offering more effective treatments to smaller targeted patient populations. In breast cancer, adjuvant chemotherapy is standard for patients considered as high-risk after surgery. Molecular tests may identify patients who can safely avoid chemotherapy.
To use economic analysis before a large-scale clinical trial of molecular testing to confirm the value of the trial and help prioritize between candidate tests as randomized comparators.
Women with surgically treated breast cancer (estrogen receptor–positive and lymph node–positive or tumor size ≥30 mm) were randomized to standard care (chemotherapy for all) or test-directed care using Oncotype DX™. Additional testing was undertaken using alternative tests: MammaPrintTM, PAM-50 (ProsignaTM), MammaTyperTM, IHC4, and IHC4-AQUA™ (NexCourse Breast™). A probabilistic decision model assessed the cost-effectiveness of all tests from a UK perspective. Value of information analysis determined the most efficient publicly funded ongoing trial design in the United Kingdom.
There was an 86% probability of molecular testing being cost-effective, with most tests producing cost savings (range −£1892 to £195) and quality-adjusted life-year gains (range 0.17–0.20). There were only small differences in costs and quality-adjusted life-years between tests. Uncertainty was driven by long-term outcomes. Value of information demonstrated value of further research into all tests, with Prosigna currently being the highest priority for further research.
Molecular tests are likely to be cost-effective, but an optimal test is yet to be identified. Health economics modeling to inform the design of a randomized controlled trial looking at diagnostic technology has been demonstrated to be feasible as a method for improving research efficiency. |
| doi_str_mv | 10.1016/j.jval.2017.04.021 |
| format | Article |
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To use economic analysis before a large-scale clinical trial of molecular testing to confirm the value of the trial and help prioritize between candidate tests as randomized comparators.
Women with surgically treated breast cancer (estrogen receptor–positive and lymph node–positive or tumor size ≥30 mm) were randomized to standard care (chemotherapy for all) or test-directed care using Oncotype DX™. Additional testing was undertaken using alternative tests: MammaPrintTM, PAM-50 (ProsignaTM), MammaTyperTM, IHC4, and IHC4-AQUA™ (NexCourse Breast™). A probabilistic decision model assessed the cost-effectiveness of all tests from a UK perspective. Value of information analysis determined the most efficient publicly funded ongoing trial design in the United Kingdom.
There was an 86% probability of molecular testing being cost-effective, with most tests producing cost savings (range −£1892 to £195) and quality-adjusted life-year gains (range 0.17–0.20). There were only small differences in costs and quality-adjusted life-years between tests. Uncertainty was driven by long-term outcomes. Value of information demonstrated value of further research into all tests, with Prosigna currently being the highest priority for further research.
Molecular tests are likely to be cost-effective, but an optimal test is yet to be identified. Health economics modeling to inform the design of a randomized controlled trial looking at diagnostic technology has been demonstrated to be feasible as a method for improving research efficiency.</description><identifier>ISSN: 1098-3015</identifier><identifier>EISSN: 1524-4733</identifier><identifier>DOI: 10.1016/j.jval.2017.04.021</identifier><identifier>PMID: 29241890</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adult ; Aged ; Antineoplastic Combined Chemotherapy Protocols - administration & dosage ; Antineoplastic Combined Chemotherapy Protocols - economics ; Breast cancer ; Breast Neoplasms - diagnosis ; Breast Neoplasms - economics ; Breast Neoplasms - therapy ; Candidates ; Chemotherapy ; Chemotherapy, Adjuvant ; Clinical research ; Clinical trials ; Cost analysis ; Cost control ; Cost Savings ; Cost-Benefit Analysis ; Data analysis ; Decision Support Techniques ; Economic analysis ; efficient research design ; Estrogens ; Evidence-based medicine ; Female ; Health care expenditures ; Health economics ; High risk ; Humans ; Lymph nodes ; Middle Aged ; Models, Economic ; Molecular Diagnostic Techniques - methods ; personalized medicine ; Precision medicine ; Precision Medicine - methods ; Quality-Adjusted Life Years ; Savings ; Surgery ; Technology ; Uncertainty ; United Kingdom ; Value ; value of information analysis ; Women</subject><ispartof>Value in health, 2017-12, Vol.20 (10), p.1311-1318</ispartof><rights>2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR)</rights><rights>Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Science Ltd. Dec 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c428t-3e08e038e7c08c307542bc465bbd1d249d8940b51cde977b54e00c0a3a7e0af33</citedby><cites>FETCH-LOGICAL-c428t-3e08e038e7c08c307542bc465bbd1d249d8940b51cde977b54e00c0a3a7e0af33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S109830151730236X$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,30976,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29241890$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hall, Peter S.</creatorcontrib><creatorcontrib>Smith, Alison</creatorcontrib><creatorcontrib>Hulme, Claire</creatorcontrib><creatorcontrib>Vargas-Palacios, Armando</creatorcontrib><creatorcontrib>Makris, Andreas</creatorcontrib><creatorcontrib>Hughes-Davies, Luke</creatorcontrib><creatorcontrib>Dunn, Janet A.</creatorcontrib><creatorcontrib>Bartlett, John M.S.</creatorcontrib><creatorcontrib>Cameron, David A.</creatorcontrib><creatorcontrib>Marshall, Andrea</creatorcontrib><creatorcontrib>Campbell, Amy</creatorcontrib><creatorcontrib>Macpherson, Iain R.</creatorcontrib><creatorcontrib>Dan Rea</creatorcontrib><creatorcontrib>Francis, Adele</creatorcontrib><creatorcontrib>Earl, Helena</creatorcontrib><creatorcontrib>Morgan, Adrienne</creatorcontrib><creatorcontrib>Stein, Robert C.</creatorcontrib><creatorcontrib>McCabe, Christopher</creatorcontrib><creatorcontrib>on behalf of the OPTIMA Trial Management Group</creatorcontrib><creatorcontrib>OPTIMA Trial Management Group</creatorcontrib><title>Value of Information Analysis of Multiparameter Tests for Chemotherapy in Early Breast Cancer: The OPTIMA Prelim Trial</title><title>Value in health</title><addtitle>Value Health</addtitle><description>Precision medicine is heralded as offering more effective treatments to smaller targeted patient populations. In breast cancer, adjuvant chemotherapy is standard for patients considered as high-risk after surgery. Molecular tests may identify patients who can safely avoid chemotherapy.
To use economic analysis before a large-scale clinical trial of molecular testing to confirm the value of the trial and help prioritize between candidate tests as randomized comparators.
Women with surgically treated breast cancer (estrogen receptor–positive and lymph node–positive or tumor size ≥30 mm) were randomized to standard care (chemotherapy for all) or test-directed care using Oncotype DX™. Additional testing was undertaken using alternative tests: MammaPrintTM, PAM-50 (ProsignaTM), MammaTyperTM, IHC4, and IHC4-AQUA™ (NexCourse Breast™). A probabilistic decision model assessed the cost-effectiveness of all tests from a UK perspective. Value of information analysis determined the most efficient publicly funded ongoing trial design in the United Kingdom.
There was an 86% probability of molecular testing being cost-effective, with most tests producing cost savings (range −£1892 to £195) and quality-adjusted life-year gains (range 0.17–0.20). There were only small differences in costs and quality-adjusted life-years between tests. Uncertainty was driven by long-term outcomes. Value of information demonstrated value of further research into all tests, with Prosigna currently being the highest priority for further research.
Molecular tests are likely to be cost-effective, but an optimal test is yet to be identified. Health economics modeling to inform the design of a randomized controlled trial looking at diagnostic technology has been demonstrated to be feasible as a method for improving research efficiency.</description><subject>Adult</subject><subject>Aged</subject><subject>Antineoplastic Combined Chemotherapy Protocols - administration & dosage</subject><subject>Antineoplastic Combined Chemotherapy Protocols - economics</subject><subject>Breast cancer</subject><subject>Breast Neoplasms - diagnosis</subject><subject>Breast Neoplasms - economics</subject><subject>Breast Neoplasms - therapy</subject><subject>Candidates</subject><subject>Chemotherapy</subject><subject>Chemotherapy, Adjuvant</subject><subject>Clinical research</subject><subject>Clinical trials</subject><subject>Cost analysis</subject><subject>Cost control</subject><subject>Cost Savings</subject><subject>Cost-Benefit Analysis</subject><subject>Data analysis</subject><subject>Decision Support Techniques</subject><subject>Economic analysis</subject><subject>efficient research design</subject><subject>Estrogens</subject><subject>Evidence-based medicine</subject><subject>Female</subject><subject>Health care expenditures</subject><subject>Health economics</subject><subject>High risk</subject><subject>Humans</subject><subject>Lymph nodes</subject><subject>Middle Aged</subject><subject>Models, Economic</subject><subject>Molecular Diagnostic Techniques - methods</subject><subject>personalized medicine</subject><subject>Precision medicine</subject><subject>Precision Medicine - methods</subject><subject>Quality-Adjusted Life Years</subject><subject>Savings</subject><subject>Surgery</subject><subject>Technology</subject><subject>Uncertainty</subject><subject>United Kingdom</subject><subject>Value</subject><subject>value of information analysis</subject><subject>Women</subject><issn>1098-3015</issn><issn>1524-4733</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>7QJ</sourceid><recordid>eNp9kU2P0zAURS0EYobCH2CBLLFhk_D8kTpBbEo1A5VmNLMIbC3HeVFdOUmxk0r99zjqMAsWrGxZ515Z9xDynkHOgK0_H_LDyficA1M5yBw4e0GuWcFlJpUQL9MdqjITwIor8ibGAwCsBS9ekyteccnKCq7J6ZfxM9Kxo7uhG0NvJjcOdDMYf44uLu_3s5_c0QTT44SB1hinSBNKt3vsx2mPwRzP1A30xgR_pt8CmjjRrRkshi-03iN9eKx39xv6GNC7ntbBGf-WvOqMj_ju6VyRn7c39fZHdvfwfbfd3GVW8nLKBEKJIEpUFkorQBWSN1aui6ZpWctl1ZaVhKZgtsVKqaaQCGDBCKMQTCfEiny69B7D-HtOX9e9ixa9NwOOc9QspZSqlFzQj_-gh3EOaYioOZRSykombEX4hbJhjDFgp4_B9SacNQO9WNEHvVjRixUNUicrKfThqXpuemyfI381JODrBcC0xclh0NE6TAu2LqCddDu6__X_AR5FnRQ</recordid><startdate>201712</startdate><enddate>201712</enddate><creator>Hall, Peter S.</creator><creator>Smith, Alison</creator><creator>Hulme, Claire</creator><creator>Vargas-Palacios, Armando</creator><creator>Makris, Andreas</creator><creator>Hughes-Davies, Luke</creator><creator>Dunn, Janet A.</creator><creator>Bartlett, John M.S.</creator><creator>Cameron, David A.</creator><creator>Marshall, Andrea</creator><creator>Campbell, Amy</creator><creator>Macpherson, Iain R.</creator><creator>Dan Rea</creator><creator>Francis, Adele</creator><creator>Earl, Helena</creator><creator>Morgan, Adrienne</creator><creator>Stein, Robert C.</creator><creator>McCabe, Christopher</creator><general>Elsevier Inc</general><general>Elsevier Science Ltd</general><scope>6I.</scope><scope>AAFTH</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>7QJ</scope><scope>7X8</scope></search><sort><creationdate>201712</creationdate><title>Value of Information Analysis of Multiparameter Tests for Chemotherapy in Early Breast Cancer: The OPTIMA Prelim Trial</title><author>Hall, Peter S. ; Smith, Alison ; Hulme, Claire ; Vargas-Palacios, Armando ; Makris, Andreas ; Hughes-Davies, Luke ; Dunn, Janet A. ; Bartlett, John M.S. ; Cameron, David A. ; Marshall, Andrea ; Campbell, Amy ; Macpherson, Iain R. ; Dan Rea ; Francis, Adele ; Earl, Helena ; Morgan, Adrienne ; Stein, Robert C. ; McCabe, Christopher</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c428t-3e08e038e7c08c307542bc465bbd1d249d8940b51cde977b54e00c0a3a7e0af33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Antineoplastic Combined Chemotherapy Protocols - administration & dosage</topic><topic>Antineoplastic Combined Chemotherapy Protocols - economics</topic><topic>Breast cancer</topic><topic>Breast Neoplasms - diagnosis</topic><topic>Breast Neoplasms - economics</topic><topic>Breast Neoplasms - therapy</topic><topic>Candidates</topic><topic>Chemotherapy</topic><topic>Chemotherapy, Adjuvant</topic><topic>Clinical research</topic><topic>Clinical trials</topic><topic>Cost analysis</topic><topic>Cost control</topic><topic>Cost Savings</topic><topic>Cost-Benefit Analysis</topic><topic>Data analysis</topic><topic>Decision Support Techniques</topic><topic>Economic analysis</topic><topic>efficient research design</topic><topic>Estrogens</topic><topic>Evidence-based medicine</topic><topic>Female</topic><topic>Health care expenditures</topic><topic>Health economics</topic><topic>High risk</topic><topic>Humans</topic><topic>Lymph nodes</topic><topic>Middle Aged</topic><topic>Models, Economic</topic><topic>Molecular Diagnostic Techniques - methods</topic><topic>personalized medicine</topic><topic>Precision medicine</topic><topic>Precision Medicine - methods</topic><topic>Quality-Adjusted Life Years</topic><topic>Savings</topic><topic>Surgery</topic><topic>Technology</topic><topic>Uncertainty</topic><topic>United Kingdom</topic><topic>Value</topic><topic>value of information analysis</topic><topic>Women</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hall, Peter S.</creatorcontrib><creatorcontrib>Smith, Alison</creatorcontrib><creatorcontrib>Hulme, Claire</creatorcontrib><creatorcontrib>Vargas-Palacios, Armando</creatorcontrib><creatorcontrib>Makris, Andreas</creatorcontrib><creatorcontrib>Hughes-Davies, Luke</creatorcontrib><creatorcontrib>Dunn, Janet A.</creatorcontrib><creatorcontrib>Bartlett, John M.S.</creatorcontrib><creatorcontrib>Cameron, David A.</creatorcontrib><creatorcontrib>Marshall, Andrea</creatorcontrib><creatorcontrib>Campbell, Amy</creatorcontrib><creatorcontrib>Macpherson, Iain R.</creatorcontrib><creatorcontrib>Dan Rea</creatorcontrib><creatorcontrib>Francis, Adele</creatorcontrib><creatorcontrib>Earl, Helena</creatorcontrib><creatorcontrib>Morgan, Adrienne</creatorcontrib><creatorcontrib>Stein, Robert C.</creatorcontrib><creatorcontrib>McCabe, Christopher</creatorcontrib><creatorcontrib>on behalf of the OPTIMA Trial Management Group</creatorcontrib><creatorcontrib>OPTIMA Trial Management Group</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>MEDLINE - Academic</collection><jtitle>Value in health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hall, Peter S.</au><au>Smith, Alison</au><au>Hulme, Claire</au><au>Vargas-Palacios, Armando</au><au>Makris, Andreas</au><au>Hughes-Davies, Luke</au><au>Dunn, Janet A.</au><au>Bartlett, John M.S.</au><au>Cameron, David A.</au><au>Marshall, Andrea</au><au>Campbell, Amy</au><au>Macpherson, Iain R.</au><au>Dan Rea</au><au>Francis, Adele</au><au>Earl, Helena</au><au>Morgan, Adrienne</au><au>Stein, Robert C.</au><au>McCabe, Christopher</au><aucorp>on behalf of the OPTIMA Trial Management Group</aucorp><aucorp>OPTIMA Trial Management Group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Value of Information Analysis of Multiparameter Tests for Chemotherapy in Early Breast Cancer: The OPTIMA Prelim Trial</atitle><jtitle>Value in health</jtitle><addtitle>Value Health</addtitle><date>2017-12</date><risdate>2017</risdate><volume>20</volume><issue>10</issue><spage>1311</spage><epage>1318</epage><pages>1311-1318</pages><issn>1098-3015</issn><eissn>1524-4733</eissn><abstract>Precision medicine is heralded as offering more effective treatments to smaller targeted patient populations. In breast cancer, adjuvant chemotherapy is standard for patients considered as high-risk after surgery. Molecular tests may identify patients who can safely avoid chemotherapy.
To use economic analysis before a large-scale clinical trial of molecular testing to confirm the value of the trial and help prioritize between candidate tests as randomized comparators.
Women with surgically treated breast cancer (estrogen receptor–positive and lymph node–positive or tumor size ≥30 mm) were randomized to standard care (chemotherapy for all) or test-directed care using Oncotype DX™. Additional testing was undertaken using alternative tests: MammaPrintTM, PAM-50 (ProsignaTM), MammaTyperTM, IHC4, and IHC4-AQUA™ (NexCourse Breast™). A probabilistic decision model assessed the cost-effectiveness of all tests from a UK perspective. Value of information analysis determined the most efficient publicly funded ongoing trial design in the United Kingdom.
There was an 86% probability of molecular testing being cost-effective, with most tests producing cost savings (range −£1892 to £195) and quality-adjusted life-year gains (range 0.17–0.20). There were only small differences in costs and quality-adjusted life-years between tests. Uncertainty was driven by long-term outcomes. Value of information demonstrated value of further research into all tests, with Prosigna currently being the highest priority for further research.
Molecular tests are likely to be cost-effective, but an optimal test is yet to be identified. Health economics modeling to inform the design of a randomized controlled trial looking at diagnostic technology has been demonstrated to be feasible as a method for improving research efficiency.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>29241890</pmid><doi>10.1016/j.jval.2017.04.021</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Value in health, 2017-12, Vol.20 (10), p.1311-1318 |
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| source | Applied Social Sciences Index & Abstracts (ASSIA); MEDLINE; Elsevier ScienceDirect Journals; EZB-FREE-00999 freely available EZB journals |
| subjects | Adult Aged Antineoplastic Combined Chemotherapy Protocols - administration & dosage Antineoplastic Combined Chemotherapy Protocols - economics Breast cancer Breast Neoplasms - diagnosis Breast Neoplasms - economics Breast Neoplasms - therapy Candidates Chemotherapy Chemotherapy, Adjuvant Clinical research Clinical trials Cost analysis Cost control Cost Savings Cost-Benefit Analysis Data analysis Decision Support Techniques Economic analysis efficient research design Estrogens Evidence-based medicine Female Health care expenditures Health economics High risk Humans Lymph nodes Middle Aged Models, Economic Molecular Diagnostic Techniques - methods personalized medicine Precision medicine Precision Medicine - methods Quality-Adjusted Life Years Savings Surgery Technology Uncertainty United Kingdom Value value of information analysis Women |
| title | Value of Information Analysis of Multiparameter Tests for Chemotherapy in Early Breast Cancer: The OPTIMA Prelim Trial |
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