Optimizing Time to Treatment to Achieve Durable Biochemical Disease Control after Surgery in Prostate Cancer: A Multi-Institutional Cohort Study
The impact of treatment delays on prostate cancer-specific outcomes remains ill-defined. This study investigates the effect of time to treatment on biochemical disease control after prostatectomy. This retrospective study includes 1,807 patients who received a prostatectomy as a primary treatment at...
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Veröffentlicht in: | Cancer epidemiology, biomarkers & prevention biomarkers & prevention, 2019-03, Vol.28 (3), p.570-577 |
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creator | Awasthi, Shivanshu Gerke, Travis Park, Jong Y Asamoah, Francis A Williams, Vonetta L Fink, Angelina K Balkrishnan, Rajesh Lee, David I Malkowicz, S Bruce Lal, Priti Dhillon, Jasreman Pow-Sang, Julio M Rebbeck, Timothy R Yamoah, Kosj |
description | The impact of treatment delays on prostate cancer-specific outcomes remains ill-defined. This study investigates the effect of time to treatment on biochemical disease control after prostatectomy.
This retrospective study includes 1,807 patients who received a prostatectomy as a primary treatment at two large tertiary referral centers from 1987 to 2015. Multivariate cox model with restricted cubic spline was used to identify optimal time to receive treatment and estimate the risk of biochemical recurrence.
Median follow-up time of the study was 46 (interquartile range, 18-86) months. Time to treatment was subcategorized based on multivariate cubic spline cox model. In multivariate spline model, adjusted for all the pertinent pretreatment variables, inflection point in the risk of biochemical recurrence was observed around 3 months, which further increased after 6 months. Based on spline model, time to treatment was then divided into 0 to 3 months (61.5%), >3 to 6 months (31.1%), and 6 months (7.4%). In the adjusted cox model, initial delays up to 6 months did not adversely affect the outcome; however, time to treatment >6 months had significantly higher risk of biochemical recurrence (HR, 1.84; 95% confidence interval, 1.30-2.60;
< 0.01).
The initial delays up to 6 months in prostate cancer primary treatment may be sustainable without adversely affecting the outcome. However, significant delays beyond 6 months can unfavorably affect biochemical disease control.
Time to treatment can aid clinicians in the decision-making of prostate cancer treatment recommendation and educate patients against unintentional treatment delays. |
doi_str_mv | 10.1158/1055-9965.EPI-18-0812 |
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This retrospective study includes 1,807 patients who received a prostatectomy as a primary treatment at two large tertiary referral centers from 1987 to 2015. Multivariate cox model with restricted cubic spline was used to identify optimal time to receive treatment and estimate the risk of biochemical recurrence.
Median follow-up time of the study was 46 (interquartile range, 18-86) months. Time to treatment was subcategorized based on multivariate cubic spline cox model. In multivariate spline model, adjusted for all the pertinent pretreatment variables, inflection point in the risk of biochemical recurrence was observed around 3 months, which further increased after 6 months. Based on spline model, time to treatment was then divided into 0 to 3 months (61.5%), >3 to 6 months (31.1%), and 6 months (7.4%). In the adjusted cox model, initial delays up to 6 months did not adversely affect the outcome; however, time to treatment >6 months had significantly higher risk of biochemical recurrence (HR, 1.84; 95% confidence interval, 1.30-2.60;
< 0.01).
The initial delays up to 6 months in prostate cancer primary treatment may be sustainable without adversely affecting the outcome. However, significant delays beyond 6 months can unfavorably affect biochemical disease control.
Time to treatment can aid clinicians in the decision-making of prostate cancer treatment recommendation and educate patients against unintentional treatment delays.</description><identifier>ISSN: 1055-9965</identifier><identifier>EISSN: 1538-7755</identifier><identifier>DOI: 10.1158/1055-9965.EPI-18-0812</identifier><identifier>PMID: 30413401</identifier><language>eng</language><publisher>United States</publisher><subject>Aged ; Follow-Up Studies ; Humans ; Male ; Middle Aged ; Neoplasm Recurrence, Local - pathology ; Neoplasm Recurrence, Local - surgery ; Prognosis ; Prostatectomy - standards ; Prostatic Neoplasms - pathology ; Prostatic Neoplasms - surgery ; Retrospective Studies ; Survival Rate ; Time-to-Treatment - standards</subject><ispartof>Cancer epidemiology, biomarkers & prevention, 2019-03, Vol.28 (3), p.570-577</ispartof><rights>2018 American Association for Cancer Research.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c463t-6df27d19914fe9a79e6d7bbae6a9bcbaff38a21747c10e3469b2e66a2544885a3</citedby><cites>FETCH-LOGICAL-c463t-6df27d19914fe9a79e6d7bbae6a9bcbaff38a21747c10e3469b2e66a2544885a3</cites><orcidid>0000-0001-9055-3538</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,3342,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30413401$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Awasthi, Shivanshu</creatorcontrib><creatorcontrib>Gerke, Travis</creatorcontrib><creatorcontrib>Park, Jong Y</creatorcontrib><creatorcontrib>Asamoah, Francis A</creatorcontrib><creatorcontrib>Williams, Vonetta L</creatorcontrib><creatorcontrib>Fink, Angelina K</creatorcontrib><creatorcontrib>Balkrishnan, Rajesh</creatorcontrib><creatorcontrib>Lee, David I</creatorcontrib><creatorcontrib>Malkowicz, S Bruce</creatorcontrib><creatorcontrib>Lal, Priti</creatorcontrib><creatorcontrib>Dhillon, Jasreman</creatorcontrib><creatorcontrib>Pow-Sang, Julio M</creatorcontrib><creatorcontrib>Rebbeck, Timothy R</creatorcontrib><creatorcontrib>Yamoah, Kosj</creatorcontrib><title>Optimizing Time to Treatment to Achieve Durable Biochemical Disease Control after Surgery in Prostate Cancer: A Multi-Institutional Cohort Study</title><title>Cancer epidemiology, biomarkers & prevention</title><addtitle>Cancer Epidemiol Biomarkers Prev</addtitle><description>The impact of treatment delays on prostate cancer-specific outcomes remains ill-defined. This study investigates the effect of time to treatment on biochemical disease control after prostatectomy.
This retrospective study includes 1,807 patients who received a prostatectomy as a primary treatment at two large tertiary referral centers from 1987 to 2015. Multivariate cox model with restricted cubic spline was used to identify optimal time to receive treatment and estimate the risk of biochemical recurrence.
Median follow-up time of the study was 46 (interquartile range, 18-86) months. Time to treatment was subcategorized based on multivariate cubic spline cox model. In multivariate spline model, adjusted for all the pertinent pretreatment variables, inflection point in the risk of biochemical recurrence was observed around 3 months, which further increased after 6 months. Based on spline model, time to treatment was then divided into 0 to 3 months (61.5%), >3 to 6 months (31.1%), and 6 months (7.4%). In the adjusted cox model, initial delays up to 6 months did not adversely affect the outcome; however, time to treatment >6 months had significantly higher risk of biochemical recurrence (HR, 1.84; 95% confidence interval, 1.30-2.60;
< 0.01).
The initial delays up to 6 months in prostate cancer primary treatment may be sustainable without adversely affecting the outcome. However, significant delays beyond 6 months can unfavorably affect biochemical disease control.
Time to treatment can aid clinicians in the decision-making of prostate cancer treatment recommendation and educate patients against unintentional treatment delays.</description><subject>Aged</subject><subject>Follow-Up Studies</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Neoplasm Recurrence, Local - pathology</subject><subject>Neoplasm Recurrence, Local - surgery</subject><subject>Prognosis</subject><subject>Prostatectomy - standards</subject><subject>Prostatic Neoplasms - pathology</subject><subject>Prostatic Neoplasms - surgery</subject><subject>Retrospective Studies</subject><subject>Survival Rate</subject><subject>Time-to-Treatment - standards</subject><issn>1055-9965</issn><issn>1538-7755</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVUdtKxDAQDaJ4_wQlP1BN2qZNfBDWXS8LioLrc5im091I2yxpKqxf4Sfb4gV9mhnmnDPMOYSccHbGuZDnnAkRKZWJs-unecRlxCSPt8g-F4mM8lyI7aH_weyRg657ZYzlSohdspewlCcp4_vk43EdbGPfbbukC9sgDY4uPEJosA3jMDEri29IZ72HokZ6ZZ1ZYWMN1HRmO4QO6dS1wbuaQhXQ0-feL9FvqG3pk3ddgDAgoDXoL-iEPvR1sNG87YINfbCuHXSmbuV8oM-hLzdHZKeCusPj73pIXm6uF9O76P7xdj6d3EcmzZIQZWUV5yVXiqcVKsgVZmVeFIAZqMIUUFWJhJjnaW44wyTNVBFjlkEs0lRKAckhufzSXfdFg6UZ3vVQ67W3DfiNdmD1_01rV3rp3rTkjCmlBgHxJWCGJzuP1S-XMz1GpEf79Wi_HiLSXOoxooF3-vfwL-snk-QTlbSRdA</recordid><startdate>20190301</startdate><enddate>20190301</enddate><creator>Awasthi, Shivanshu</creator><creator>Gerke, Travis</creator><creator>Park, Jong Y</creator><creator>Asamoah, Francis A</creator><creator>Williams, Vonetta L</creator><creator>Fink, Angelina K</creator><creator>Balkrishnan, Rajesh</creator><creator>Lee, David I</creator><creator>Malkowicz, S Bruce</creator><creator>Lal, Priti</creator><creator>Dhillon, Jasreman</creator><creator>Pow-Sang, Julio M</creator><creator>Rebbeck, Timothy R</creator><creator>Yamoah, Kosj</creator><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>5PM</scope><orcidid>https://orcid.org/0000-0001-9055-3538</orcidid></search><sort><creationdate>20190301</creationdate><title>Optimizing Time to Treatment to Achieve Durable Biochemical Disease Control after Surgery in Prostate Cancer: A Multi-Institutional Cohort Study</title><author>Awasthi, Shivanshu ; Gerke, Travis ; Park, Jong Y ; Asamoah, Francis A ; Williams, Vonetta L ; Fink, Angelina K ; Balkrishnan, Rajesh ; Lee, David I ; Malkowicz, S Bruce ; Lal, Priti ; Dhillon, Jasreman ; Pow-Sang, Julio M ; Rebbeck, Timothy R ; Yamoah, Kosj</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c463t-6df27d19914fe9a79e6d7bbae6a9bcbaff38a21747c10e3469b2e66a2544885a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Aged</topic><topic>Follow-Up Studies</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Neoplasm Recurrence, Local - pathology</topic><topic>Neoplasm Recurrence, Local - surgery</topic><topic>Prognosis</topic><topic>Prostatectomy - standards</topic><topic>Prostatic Neoplasms - pathology</topic><topic>Prostatic Neoplasms - surgery</topic><topic>Retrospective Studies</topic><topic>Survival Rate</topic><topic>Time-to-Treatment - standards</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Awasthi, Shivanshu</creatorcontrib><creatorcontrib>Gerke, Travis</creatorcontrib><creatorcontrib>Park, Jong Y</creatorcontrib><creatorcontrib>Asamoah, Francis A</creatorcontrib><creatorcontrib>Williams, Vonetta L</creatorcontrib><creatorcontrib>Fink, Angelina K</creatorcontrib><creatorcontrib>Balkrishnan, Rajesh</creatorcontrib><creatorcontrib>Lee, David I</creatorcontrib><creatorcontrib>Malkowicz, S Bruce</creatorcontrib><creatorcontrib>Lal, Priti</creatorcontrib><creatorcontrib>Dhillon, Jasreman</creatorcontrib><creatorcontrib>Pow-Sang, Julio M</creatorcontrib><creatorcontrib>Rebbeck, Timothy R</creatorcontrib><creatorcontrib>Yamoah, Kosj</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancer epidemiology, biomarkers & prevention</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Awasthi, Shivanshu</au><au>Gerke, Travis</au><au>Park, Jong Y</au><au>Asamoah, Francis A</au><au>Williams, Vonetta L</au><au>Fink, Angelina K</au><au>Balkrishnan, Rajesh</au><au>Lee, David I</au><au>Malkowicz, S Bruce</au><au>Lal, Priti</au><au>Dhillon, Jasreman</au><au>Pow-Sang, Julio M</au><au>Rebbeck, Timothy R</au><au>Yamoah, Kosj</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimizing Time to Treatment to Achieve Durable Biochemical Disease Control after Surgery in Prostate Cancer: A Multi-Institutional Cohort Study</atitle><jtitle>Cancer epidemiology, biomarkers & prevention</jtitle><addtitle>Cancer Epidemiol Biomarkers Prev</addtitle><date>2019-03-01</date><risdate>2019</risdate><volume>28</volume><issue>3</issue><spage>570</spage><epage>577</epage><pages>570-577</pages><issn>1055-9965</issn><eissn>1538-7755</eissn><abstract>The impact of treatment delays on prostate cancer-specific outcomes remains ill-defined. This study investigates the effect of time to treatment on biochemical disease control after prostatectomy.
This retrospective study includes 1,807 patients who received a prostatectomy as a primary treatment at two large tertiary referral centers from 1987 to 2015. Multivariate cox model with restricted cubic spline was used to identify optimal time to receive treatment and estimate the risk of biochemical recurrence.
Median follow-up time of the study was 46 (interquartile range, 18-86) months. Time to treatment was subcategorized based on multivariate cubic spline cox model. In multivariate spline model, adjusted for all the pertinent pretreatment variables, inflection point in the risk of biochemical recurrence was observed around 3 months, which further increased after 6 months. Based on spline model, time to treatment was then divided into 0 to 3 months (61.5%), >3 to 6 months (31.1%), and 6 months (7.4%). In the adjusted cox model, initial delays up to 6 months did not adversely affect the outcome; however, time to treatment >6 months had significantly higher risk of biochemical recurrence (HR, 1.84; 95% confidence interval, 1.30-2.60;
< 0.01).
The initial delays up to 6 months in prostate cancer primary treatment may be sustainable without adversely affecting the outcome. However, significant delays beyond 6 months can unfavorably affect biochemical disease control.
Time to treatment can aid clinicians in the decision-making of prostate cancer treatment recommendation and educate patients against unintentional treatment delays.</abstract><cop>United States</cop><pmid>30413401</pmid><doi>10.1158/1055-9965.EPI-18-0812</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-9055-3538</orcidid><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; American Association for Cancer Research; EZB-FREE-00999 freely available EZB journals |
subjects | Aged Follow-Up Studies Humans Male Middle Aged Neoplasm Recurrence, Local - pathology Neoplasm Recurrence, Local - surgery Prognosis Prostatectomy - standards Prostatic Neoplasms - pathology Prostatic Neoplasms - surgery Retrospective Studies Survival Rate Time-to-Treatment - standards |
title | Optimizing Time to Treatment to Achieve Durable Biochemical Disease Control after Surgery in Prostate Cancer: A Multi-Institutional Cohort Study |
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