Nomograms for predicting survival and recurrence in patients with adenoid cystic carcinoma. An international collaborative study

Abstract Background Due to the rarity of adenoid cystic carcinoma (ACC), information on outcome is based upon small retrospective case series. The aim of our study was to create a large multiinstitutional international dataset of patients with ACC in order to design predictive nomograms for outcome....

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:European journal of cancer (1990) 2015-12, Vol.51 (18), p.2768-2776
Hauptverfasser: Ganly, Ian, Amit, Moran, Kou, Lei, Palmer, Frank L, Migliacci, Jocelyn, Katabi, Nora, Yu, Changhong, Kattan, Michael W, Binenbaum, Yoav, Sharma, Kanika, Naomi, Ramer, Abib, Agbetoba, Miles, Brett, Yang, Xinjie, Lei, Delin, Bjoerndal, Kristine, Godballe, Christian, Mücke, Thomas, Wolff, Klaus-Dietrich, Fliss, Dan, Eckardt, André M, Chiara, Copelli, Sesenna, Enrico, Ali, Safina, Czerwonka, Lukas, Goldstein, David P, Gil, Ziv, Patel, Snehal G
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 2776
container_issue 18
container_start_page 2768
container_title European journal of cancer (1990)
container_volume 51
creator Ganly, Ian
Amit, Moran
Kou, Lei
Palmer, Frank L
Migliacci, Jocelyn
Katabi, Nora
Yu, Changhong
Kattan, Michael W
Binenbaum, Yoav
Sharma, Kanika
Naomi, Ramer
Abib, Agbetoba
Miles, Brett
Yang, Xinjie
Lei, Delin
Bjoerndal, Kristine
Godballe, Christian
Mücke, Thomas
Wolff, Klaus-Dietrich
Fliss, Dan
Eckardt, André M
Chiara, Copelli
Sesenna, Enrico
Ali, Safina
Czerwonka, Lukas
Goldstein, David P
Gil, Ziv
Patel, Snehal G
description Abstract Background Due to the rarity of adenoid cystic carcinoma (ACC), information on outcome is based upon small retrospective case series. The aim of our study was to create a large multiinstitutional international dataset of patients with ACC in order to design predictive nomograms for outcome. Methods ACC patients managed at 10 international centers were identified. Patient, tumor, and treatment characteristics were recorded and an international collaborative dataset created. Multivariable competing risk models were then built to predict the 10 year recurrence free probability (RFP), distant recurrence free probability (DRFP), overall survival (OS) and cancer specific mortality (CSM). All predictors of interest were added in the starting full models before selection, including age, gender, tumor site, clinical T stage, perineural invasion, margin status, pathologic N-status, and M-status. Stepdown method was used in model selection to choose predictive variables. An external dataset of 99 patients from 2 other institutions was used to validate the nomograms. Findings Of 438 ACC patients, 27.2% (119/438) died from ACC and 38.8% (170/438) died of other causes. Median follow-up was 56 months (range 1–306). The nomogram for OS had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N-status and M-status) with a concordance index (CI) of 0.71. The nomogram for CSM had the same variables, except margin status, with a concordance index (CI) of 0.70. The nomogram for RFP had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N status and perineural invasion) (CI 0.66). The nomogram for DRFP had 6 variables (gender, clinical T stage, tumor site, pathologic N-status, perineural invasion and margin status) (CI 0.64). Concordance index for the external validation set were 0.76, 0.72, 0.67 and 0.70 respectively. Interpretation Using an international collaborative database we have created the first nomograms which estimate outcome in individual patients with ACC. These predictive nomograms will facilitate patient counseling in terms of prognosis and subsequent clinical follow-up. They will also identify high risk patients who may benefit from clinical trials on new targeted therapies for patients with ACC. Funding None.
doi_str_mv 10.1016/j.ejca.2015.09.004
format Article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4988233</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0959804915008497</els_id><sourcerecordid>1738479167</sourcerecordid><originalsourceid>FETCH-LOGICAL-c510t-51fafa983cfa6678d74c8c2e86fdeb3e27eb274ecaec0807d14b9338217cf6913</originalsourceid><addsrcrecordid>eNp9kk9v1DAQxSMEotvCF-CAfOSyYZx_tiVUqaqgIFVwAM6WdzzZeknsxU4W7Y2PjqMtFXDgZFl-73lmflMULziUHHj3elfSDk1ZAW9LUCVA86hYcSnUGmRbPS5WoFq1ltCos-I8pR0ACNnA0-Ks6jrINrEqfn4MY9hGMybWh8j2kazDyfktS3M8uIMZmPGWRcI5RvJIzHm2N5MjPyX2w013zFjywVmGxzQ5ZGgiOh9GU7Irn9UTRZ_1wecoDMNgNiHm-4FYmmZ7fFY86c2Q6Pn9eVF8fff2y_X79e2nmw_XV7drbDlM65b3pjdK1tibrhPSigYlViS73tKmpkrQphINoSEECcLyZqPqWlZcYN8pXl8Ul6fc_bwZyWKuP5pB76MbTTzqYJz--8W7O70NB90oKau6zgGv7gNi-D5TmvToElJuyFOYk-ailo1QvBNZWp2kGENKkfqHbzjoBZ3e6QWdXtBpUDqjy6aXfxb4YPnNKgvenASUx3RwFHVCtyCxLuOZtA3u__mX_9hxcN6hGb7RkdIuzJnTkPvQqdKgPy_Ls-wObwFko0T9C8n9xEY</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1738479167</pqid></control><display><type>article</type><title>Nomograms for predicting survival and recurrence in patients with adenoid cystic carcinoma. An international collaborative study</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals Complete</source><creator>Ganly, Ian ; Amit, Moran ; Kou, Lei ; Palmer, Frank L ; Migliacci, Jocelyn ; Katabi, Nora ; Yu, Changhong ; Kattan, Michael W ; Binenbaum, Yoav ; Sharma, Kanika ; Naomi, Ramer ; Abib, Agbetoba ; Miles, Brett ; Yang, Xinjie ; Lei, Delin ; Bjoerndal, Kristine ; Godballe, Christian ; Mücke, Thomas ; Wolff, Klaus-Dietrich ; Fliss, Dan ; Eckardt, André M ; Chiara, Copelli ; Sesenna, Enrico ; Ali, Safina ; Czerwonka, Lukas ; Goldstein, David P ; Gil, Ziv ; Patel, Snehal G</creator><creatorcontrib>Ganly, Ian ; Amit, Moran ; Kou, Lei ; Palmer, Frank L ; Migliacci, Jocelyn ; Katabi, Nora ; Yu, Changhong ; Kattan, Michael W ; Binenbaum, Yoav ; Sharma, Kanika ; Naomi, Ramer ; Abib, Agbetoba ; Miles, Brett ; Yang, Xinjie ; Lei, Delin ; Bjoerndal, Kristine ; Godballe, Christian ; Mücke, Thomas ; Wolff, Klaus-Dietrich ; Fliss, Dan ; Eckardt, André M ; Chiara, Copelli ; Sesenna, Enrico ; Ali, Safina ; Czerwonka, Lukas ; Goldstein, David P ; Gil, Ziv ; Patel, Snehal G</creatorcontrib><description>Abstract Background Due to the rarity of adenoid cystic carcinoma (ACC), information on outcome is based upon small retrospective case series. The aim of our study was to create a large multiinstitutional international dataset of patients with ACC in order to design predictive nomograms for outcome. Methods ACC patients managed at 10 international centers were identified. Patient, tumor, and treatment characteristics were recorded and an international collaborative dataset created. Multivariable competing risk models were then built to predict the 10 year recurrence free probability (RFP), distant recurrence free probability (DRFP), overall survival (OS) and cancer specific mortality (CSM). All predictors of interest were added in the starting full models before selection, including age, gender, tumor site, clinical T stage, perineural invasion, margin status, pathologic N-status, and M-status. Stepdown method was used in model selection to choose predictive variables. An external dataset of 99 patients from 2 other institutions was used to validate the nomograms. Findings Of 438 ACC patients, 27.2% (119/438) died from ACC and 38.8% (170/438) died of other causes. Median follow-up was 56 months (range 1–306). The nomogram for OS had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N-status and M-status) with a concordance index (CI) of 0.71. The nomogram for CSM had the same variables, except margin status, with a concordance index (CI) of 0.70. The nomogram for RFP had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N status and perineural invasion) (CI 0.66). The nomogram for DRFP had 6 variables (gender, clinical T stage, tumor site, pathologic N-status, perineural invasion and margin status) (CI 0.64). Concordance index for the external validation set were 0.76, 0.72, 0.67 and 0.70 respectively. Interpretation Using an international collaborative database we have created the first nomograms which estimate outcome in individual patients with ACC. These predictive nomograms will facilitate patient counseling in terms of prognosis and subsequent clinical follow-up. They will also identify high risk patients who may benefit from clinical trials on new targeted therapies for patients with ACC. Funding None.</description><identifier>ISSN: 0959-8049</identifier><identifier>EISSN: 1879-0852</identifier><identifier>DOI: 10.1016/j.ejca.2015.09.004</identifier><identifier>PMID: 26602017</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Adenoid cystic cancer ; Adolescent ; Adult ; Age Factors ; Aged ; Aged, 80 and over ; Carcinoma, Adenoid Cystic - mortality ; Carcinoma, Adenoid Cystic - pathology ; Carcinoma, Adenoid Cystic - therapy ; Cooperative Behavior ; Decision Support Techniques ; Disease Progression ; Disease-Free Survival ; Female ; Hematology, Oncology and Palliative Medicine ; Humans ; International Cooperation ; Male ; Middle Aged ; Multivariate Analysis ; Neoplasm Invasiveness ; Neoplasm Recurrence, Local ; Neoplasm Staging ; Nomogram ; Nomograms ; Patient Selection ; Predictive Value of Tests ; Reproducibility of Results ; Retrospective Studies ; Risk Assessment ; Risk Factors ; Sex Factors ; Time Factors ; Treatment Outcome ; Young Adult</subject><ispartof>European journal of cancer (1990), 2015-12, Vol.51 (18), p.2768-2776</ispartof><rights>Elsevier Ltd</rights><rights>2015 Elsevier Ltd</rights><rights>Copyright © 2015 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c510t-51fafa983cfa6678d74c8c2e86fdeb3e27eb274ecaec0807d14b9338217cf6913</citedby><cites>FETCH-LOGICAL-c510t-51fafa983cfa6678d74c8c2e86fdeb3e27eb274ecaec0807d14b9338217cf6913</cites><orcidid>0000-0003-4893-3099 ; 0000-0001-6883-4982 ; 0000-0003-3949-344X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ejca.2015.09.004$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,780,784,885,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26602017$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ganly, Ian</creatorcontrib><creatorcontrib>Amit, Moran</creatorcontrib><creatorcontrib>Kou, Lei</creatorcontrib><creatorcontrib>Palmer, Frank L</creatorcontrib><creatorcontrib>Migliacci, Jocelyn</creatorcontrib><creatorcontrib>Katabi, Nora</creatorcontrib><creatorcontrib>Yu, Changhong</creatorcontrib><creatorcontrib>Kattan, Michael W</creatorcontrib><creatorcontrib>Binenbaum, Yoav</creatorcontrib><creatorcontrib>Sharma, Kanika</creatorcontrib><creatorcontrib>Naomi, Ramer</creatorcontrib><creatorcontrib>Abib, Agbetoba</creatorcontrib><creatorcontrib>Miles, Brett</creatorcontrib><creatorcontrib>Yang, Xinjie</creatorcontrib><creatorcontrib>Lei, Delin</creatorcontrib><creatorcontrib>Bjoerndal, Kristine</creatorcontrib><creatorcontrib>Godballe, Christian</creatorcontrib><creatorcontrib>Mücke, Thomas</creatorcontrib><creatorcontrib>Wolff, Klaus-Dietrich</creatorcontrib><creatorcontrib>Fliss, Dan</creatorcontrib><creatorcontrib>Eckardt, André M</creatorcontrib><creatorcontrib>Chiara, Copelli</creatorcontrib><creatorcontrib>Sesenna, Enrico</creatorcontrib><creatorcontrib>Ali, Safina</creatorcontrib><creatorcontrib>Czerwonka, Lukas</creatorcontrib><creatorcontrib>Goldstein, David P</creatorcontrib><creatorcontrib>Gil, Ziv</creatorcontrib><creatorcontrib>Patel, Snehal G</creatorcontrib><title>Nomograms for predicting survival and recurrence in patients with adenoid cystic carcinoma. An international collaborative study</title><title>European journal of cancer (1990)</title><addtitle>Eur J Cancer</addtitle><description>Abstract Background Due to the rarity of adenoid cystic carcinoma (ACC), information on outcome is based upon small retrospective case series. The aim of our study was to create a large multiinstitutional international dataset of patients with ACC in order to design predictive nomograms for outcome. Methods ACC patients managed at 10 international centers were identified. Patient, tumor, and treatment characteristics were recorded and an international collaborative dataset created. Multivariable competing risk models were then built to predict the 10 year recurrence free probability (RFP), distant recurrence free probability (DRFP), overall survival (OS) and cancer specific mortality (CSM). All predictors of interest were added in the starting full models before selection, including age, gender, tumor site, clinical T stage, perineural invasion, margin status, pathologic N-status, and M-status. Stepdown method was used in model selection to choose predictive variables. An external dataset of 99 patients from 2 other institutions was used to validate the nomograms. Findings Of 438 ACC patients, 27.2% (119/438) died from ACC and 38.8% (170/438) died of other causes. Median follow-up was 56 months (range 1–306). The nomogram for OS had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N-status and M-status) with a concordance index (CI) of 0.71. The nomogram for CSM had the same variables, except margin status, with a concordance index (CI) of 0.70. The nomogram for RFP had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N status and perineural invasion) (CI 0.66). The nomogram for DRFP had 6 variables (gender, clinical T stage, tumor site, pathologic N-status, perineural invasion and margin status) (CI 0.64). Concordance index for the external validation set were 0.76, 0.72, 0.67 and 0.70 respectively. Interpretation Using an international collaborative database we have created the first nomograms which estimate outcome in individual patients with ACC. These predictive nomograms will facilitate patient counseling in terms of prognosis and subsequent clinical follow-up. They will also identify high risk patients who may benefit from clinical trials on new targeted therapies for patients with ACC. Funding None.</description><subject>Adenoid cystic cancer</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Age Factors</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Carcinoma, Adenoid Cystic - mortality</subject><subject>Carcinoma, Adenoid Cystic - pathology</subject><subject>Carcinoma, Adenoid Cystic - therapy</subject><subject>Cooperative Behavior</subject><subject>Decision Support Techniques</subject><subject>Disease Progression</subject><subject>Disease-Free Survival</subject><subject>Female</subject><subject>Hematology, Oncology and Palliative Medicine</subject><subject>Humans</subject><subject>International Cooperation</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Multivariate Analysis</subject><subject>Neoplasm Invasiveness</subject><subject>Neoplasm Recurrence, Local</subject><subject>Neoplasm Staging</subject><subject>Nomogram</subject><subject>Nomograms</subject><subject>Patient Selection</subject><subject>Predictive Value of Tests</subject><subject>Reproducibility of Results</subject><subject>Retrospective Studies</subject><subject>Risk Assessment</subject><subject>Risk Factors</subject><subject>Sex Factors</subject><subject>Time Factors</subject><subject>Treatment Outcome</subject><subject>Young Adult</subject><issn>0959-8049</issn><issn>1879-0852</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kk9v1DAQxSMEotvCF-CAfOSyYZx_tiVUqaqgIFVwAM6WdzzZeknsxU4W7Y2PjqMtFXDgZFl-73lmflMULziUHHj3elfSDk1ZAW9LUCVA86hYcSnUGmRbPS5WoFq1ltCos-I8pR0ACNnA0-Ks6jrINrEqfn4MY9hGMybWh8j2kazDyfktS3M8uIMZmPGWRcI5RvJIzHm2N5MjPyX2w013zFjywVmGxzQ5ZGgiOh9GU7Irn9UTRZ_1wecoDMNgNiHm-4FYmmZ7fFY86c2Q6Pn9eVF8fff2y_X79e2nmw_XV7drbDlM65b3pjdK1tibrhPSigYlViS73tKmpkrQphINoSEECcLyZqPqWlZcYN8pXl8Ul6fc_bwZyWKuP5pB76MbTTzqYJz--8W7O70NB90oKau6zgGv7gNi-D5TmvToElJuyFOYk-ailo1QvBNZWp2kGENKkfqHbzjoBZ3e6QWdXtBpUDqjy6aXfxb4YPnNKgvenASUx3RwFHVCtyCxLuOZtA3u__mX_9hxcN6hGb7RkdIuzJnTkPvQqdKgPy_Ls-wObwFko0T9C8n9xEY</recordid><startdate>20151201</startdate><enddate>20151201</enddate><creator>Ganly, Ian</creator><creator>Amit, Moran</creator><creator>Kou, Lei</creator><creator>Palmer, Frank L</creator><creator>Migliacci, Jocelyn</creator><creator>Katabi, Nora</creator><creator>Yu, Changhong</creator><creator>Kattan, Michael W</creator><creator>Binenbaum, Yoav</creator><creator>Sharma, Kanika</creator><creator>Naomi, Ramer</creator><creator>Abib, Agbetoba</creator><creator>Miles, Brett</creator><creator>Yang, Xinjie</creator><creator>Lei, Delin</creator><creator>Bjoerndal, Kristine</creator><creator>Godballe, Christian</creator><creator>Mücke, Thomas</creator><creator>Wolff, Klaus-Dietrich</creator><creator>Fliss, Dan</creator><creator>Eckardt, André M</creator><creator>Chiara, Copelli</creator><creator>Sesenna, Enrico</creator><creator>Ali, Safina</creator><creator>Czerwonka, Lukas</creator><creator>Goldstein, David P</creator><creator>Gil, Ziv</creator><creator>Patel, Snehal G</creator><general>Elsevier Ltd</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>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-4893-3099</orcidid><orcidid>https://orcid.org/0000-0001-6883-4982</orcidid><orcidid>https://orcid.org/0000-0003-3949-344X</orcidid></search><sort><creationdate>20151201</creationdate><title>Nomograms for predicting survival and recurrence in patients with adenoid cystic carcinoma. An international collaborative study</title><author>Ganly, Ian ; Amit, Moran ; Kou, Lei ; Palmer, Frank L ; Migliacci, Jocelyn ; Katabi, Nora ; Yu, Changhong ; Kattan, Michael W ; Binenbaum, Yoav ; Sharma, Kanika ; Naomi, Ramer ; Abib, Agbetoba ; Miles, Brett ; Yang, Xinjie ; Lei, Delin ; Bjoerndal, Kristine ; Godballe, Christian ; Mücke, Thomas ; Wolff, Klaus-Dietrich ; Fliss, Dan ; Eckardt, André M ; Chiara, Copelli ; Sesenna, Enrico ; Ali, Safina ; Czerwonka, Lukas ; Goldstein, David P ; Gil, Ziv ; Patel, Snehal G</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c510t-51fafa983cfa6678d74c8c2e86fdeb3e27eb274ecaec0807d14b9338217cf6913</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adenoid cystic cancer</topic><topic>Adolescent</topic><topic>Adult</topic><topic>Age Factors</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Carcinoma, Adenoid Cystic - mortality</topic><topic>Carcinoma, Adenoid Cystic - pathology</topic><topic>Carcinoma, Adenoid Cystic - therapy</topic><topic>Cooperative Behavior</topic><topic>Decision Support Techniques</topic><topic>Disease Progression</topic><topic>Disease-Free Survival</topic><topic>Female</topic><topic>Hematology, Oncology and Palliative Medicine</topic><topic>Humans</topic><topic>International Cooperation</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Multivariate Analysis</topic><topic>Neoplasm Invasiveness</topic><topic>Neoplasm Recurrence, Local</topic><topic>Neoplasm Staging</topic><topic>Nomogram</topic><topic>Nomograms</topic><topic>Patient Selection</topic><topic>Predictive Value of Tests</topic><topic>Reproducibility of Results</topic><topic>Retrospective Studies</topic><topic>Risk Assessment</topic><topic>Risk Factors</topic><topic>Sex Factors</topic><topic>Time Factors</topic><topic>Treatment Outcome</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ganly, Ian</creatorcontrib><creatorcontrib>Amit, Moran</creatorcontrib><creatorcontrib>Kou, Lei</creatorcontrib><creatorcontrib>Palmer, Frank L</creatorcontrib><creatorcontrib>Migliacci, Jocelyn</creatorcontrib><creatorcontrib>Katabi, Nora</creatorcontrib><creatorcontrib>Yu, Changhong</creatorcontrib><creatorcontrib>Kattan, Michael W</creatorcontrib><creatorcontrib>Binenbaum, Yoav</creatorcontrib><creatorcontrib>Sharma, Kanika</creatorcontrib><creatorcontrib>Naomi, Ramer</creatorcontrib><creatorcontrib>Abib, Agbetoba</creatorcontrib><creatorcontrib>Miles, Brett</creatorcontrib><creatorcontrib>Yang, Xinjie</creatorcontrib><creatorcontrib>Lei, Delin</creatorcontrib><creatorcontrib>Bjoerndal, Kristine</creatorcontrib><creatorcontrib>Godballe, Christian</creatorcontrib><creatorcontrib>Mücke, Thomas</creatorcontrib><creatorcontrib>Wolff, Klaus-Dietrich</creatorcontrib><creatorcontrib>Fliss, Dan</creatorcontrib><creatorcontrib>Eckardt, André M</creatorcontrib><creatorcontrib>Chiara, Copelli</creatorcontrib><creatorcontrib>Sesenna, Enrico</creatorcontrib><creatorcontrib>Ali, Safina</creatorcontrib><creatorcontrib>Czerwonka, Lukas</creatorcontrib><creatorcontrib>Goldstein, David P</creatorcontrib><creatorcontrib>Gil, Ziv</creatorcontrib><creatorcontrib>Patel, Snehal G</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>European journal of cancer (1990)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ganly, Ian</au><au>Amit, Moran</au><au>Kou, Lei</au><au>Palmer, Frank L</au><au>Migliacci, Jocelyn</au><au>Katabi, Nora</au><au>Yu, Changhong</au><au>Kattan, Michael W</au><au>Binenbaum, Yoav</au><au>Sharma, Kanika</au><au>Naomi, Ramer</au><au>Abib, Agbetoba</au><au>Miles, Brett</au><au>Yang, Xinjie</au><au>Lei, Delin</au><au>Bjoerndal, Kristine</au><au>Godballe, Christian</au><au>Mücke, Thomas</au><au>Wolff, Klaus-Dietrich</au><au>Fliss, Dan</au><au>Eckardt, André M</au><au>Chiara, Copelli</au><au>Sesenna, Enrico</au><au>Ali, Safina</au><au>Czerwonka, Lukas</au><au>Goldstein, David P</au><au>Gil, Ziv</au><au>Patel, Snehal G</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Nomograms for predicting survival and recurrence in patients with adenoid cystic carcinoma. An international collaborative study</atitle><jtitle>European journal of cancer (1990)</jtitle><addtitle>Eur J Cancer</addtitle><date>2015-12-01</date><risdate>2015</risdate><volume>51</volume><issue>18</issue><spage>2768</spage><epage>2776</epage><pages>2768-2776</pages><issn>0959-8049</issn><eissn>1879-0852</eissn><abstract>Abstract Background Due to the rarity of adenoid cystic carcinoma (ACC), information on outcome is based upon small retrospective case series. The aim of our study was to create a large multiinstitutional international dataset of patients with ACC in order to design predictive nomograms for outcome. Methods ACC patients managed at 10 international centers were identified. Patient, tumor, and treatment characteristics were recorded and an international collaborative dataset created. Multivariable competing risk models were then built to predict the 10 year recurrence free probability (RFP), distant recurrence free probability (DRFP), overall survival (OS) and cancer specific mortality (CSM). All predictors of interest were added in the starting full models before selection, including age, gender, tumor site, clinical T stage, perineural invasion, margin status, pathologic N-status, and M-status. Stepdown method was used in model selection to choose predictive variables. An external dataset of 99 patients from 2 other institutions was used to validate the nomograms. Findings Of 438 ACC patients, 27.2% (119/438) died from ACC and 38.8% (170/438) died of other causes. Median follow-up was 56 months (range 1–306). The nomogram for OS had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N-status and M-status) with a concordance index (CI) of 0.71. The nomogram for CSM had the same variables, except margin status, with a concordance index (CI) of 0.70. The nomogram for RFP had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N status and perineural invasion) (CI 0.66). The nomogram for DRFP had 6 variables (gender, clinical T stage, tumor site, pathologic N-status, perineural invasion and margin status) (CI 0.64). Concordance index for the external validation set were 0.76, 0.72, 0.67 and 0.70 respectively. Interpretation Using an international collaborative database we have created the first nomograms which estimate outcome in individual patients with ACC. These predictive nomograms will facilitate patient counseling in terms of prognosis and subsequent clinical follow-up. They will also identify high risk patients who may benefit from clinical trials on new targeted therapies for patients with ACC. Funding None.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>26602017</pmid><doi>10.1016/j.ejca.2015.09.004</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0003-4893-3099</orcidid><orcidid>https://orcid.org/0000-0001-6883-4982</orcidid><orcidid>https://orcid.org/0000-0003-3949-344X</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0959-8049
ispartof European journal of cancer (1990), 2015-12, Vol.51 (18), p.2768-2776
issn 0959-8049
1879-0852
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4988233
source MEDLINE; Elsevier ScienceDirect Journals Complete
subjects Adenoid cystic cancer
Adolescent
Adult
Age Factors
Aged
Aged, 80 and over
Carcinoma, Adenoid Cystic - mortality
Carcinoma, Adenoid Cystic - pathology
Carcinoma, Adenoid Cystic - therapy
Cooperative Behavior
Decision Support Techniques
Disease Progression
Disease-Free Survival
Female
Hematology, Oncology and Palliative Medicine
Humans
International Cooperation
Male
Middle Aged
Multivariate Analysis
Neoplasm Invasiveness
Neoplasm Recurrence, Local
Neoplasm Staging
Nomogram
Nomograms
Patient Selection
Predictive Value of Tests
Reproducibility of Results
Retrospective Studies
Risk Assessment
Risk Factors
Sex Factors
Time Factors
Treatment Outcome
Young Adult
title Nomograms for predicting survival and recurrence in patients with adenoid cystic carcinoma. An international collaborative study
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T08%3A13%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Nomograms%20for%20predicting%20survival%20and%20recurrence%20in%20patients%20with%20adenoid%20cystic%20carcinoma.%20An%20international%20collaborative%20study&rft.jtitle=European%20journal%20of%20cancer%20(1990)&rft.au=Ganly,%20Ian&rft.date=2015-12-01&rft.volume=51&rft.issue=18&rft.spage=2768&rft.epage=2776&rft.pages=2768-2776&rft.issn=0959-8049&rft.eissn=1879-0852&rft_id=info:doi/10.1016/j.ejca.2015.09.004&rft_dat=%3Cproquest_pubme%3E1738479167%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1738479167&rft_id=info:pmid/26602017&rft_els_id=S0959804915008497&rfr_iscdi=true