Criteria for Risk Stratification of Vulvar and Vaginal Smooth Muscle Tumors: An Evaluation of 71 Cases Comparing Proposed Classification Systems
Accurate risk stratification of smooth muscle tumors (SMTs) is essential for appropriate patient management. Yet, the rarity of SMTs of the vagina and vulva makes development of a prognostically meaningful classification system challenging. While 2 classification methods for vulvar SMTs and 1 for va...
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Veröffentlicht in: | The American journal of surgical pathology 2018-01, Vol.42 (1), p.84-94 |
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creator | Sayeed, Sadia Xing, Deyin Jenkins, Sarah M Weisman, Paul S Buehler, Darya Warmke, Laura Uram-Tuculescu, Cora Bakkum-Gamez, Jamie N Howitt, Brooke E Cortese, Cherise Park, Kay J Schoolmeester, J Kenneth |
description | Accurate risk stratification of smooth muscle tumors (SMTs) is essential for appropriate patient management. Yet, the rarity of SMTs of the vagina and vulva makes development of a prognostically meaningful classification system challenging. While 2 classification methods for vulvar SMTs and 1 for vaginal SMTs have been proposed, it is our experience that many pathologists tend to apply criteria for uterine SMTs when evaluating vulvovaginal tumors. We retrospectively reviewed a large cohort of vulvovaginal SMTs with clinical follow-up and evaluated which method most accurately classified tumors according to patient outcome. A total of 71 tumors, 53 vaginal (75%) and 18 vulvar (25%), from 71 patients were identified. All tumors were centrally examined for degree of cytologic atypia, morphology (spindled, epithelioid, myxoid), mitotic index per 10 high power fields, atypical mitotic figures, tumor cell necrosis, ischemic necrosis, tumor interface (circumscribed or infiltrative) and margin status. Clinical features were recorded for each patient. Follow-up was available for 63 patients (89%), and ranged from 1 to 234 months (median64 mo). While site-specific and uterine criteria showed equally excellent sensitivity in classifying smooth muscle neoplasms as leiomyosarcoma according to patient outcome, uterine criteria showed improved specificity relatively to site-specific methods in classifying tumors as nonsarcoma according to patient outcome. We recommend that uterine SMT criteria and nomenclature be adopted for evaluation and classification of vulvovaginal SMTs. |
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Yet, the rarity of SMTs of the vagina and vulva makes development of a prognostically meaningful classification system challenging. While 2 classification methods for vulvar SMTs and 1 for vaginal SMTs have been proposed, it is our experience that many pathologists tend to apply criteria for uterine SMTs when evaluating vulvovaginal tumors. We retrospectively reviewed a large cohort of vulvovaginal SMTs with clinical follow-up and evaluated which method most accurately classified tumors according to patient outcome. A total of 71 tumors, 53 vaginal (75%) and 18 vulvar (25%), from 71 patients were identified. All tumors were centrally examined for degree of cytologic atypia, morphology (spindled, epithelioid, myxoid), mitotic index per 10 high power fields, atypical mitotic figures, tumor cell necrosis, ischemic necrosis, tumor interface (circumscribed or infiltrative) and margin status. Clinical features were recorded for each patient. Follow-up was available for 63 patients (89%), and ranged from 1 to 234 months (median64 mo). While site-specific and uterine criteria showed equally excellent sensitivity in classifying smooth muscle neoplasms as leiomyosarcoma according to patient outcome, uterine criteria showed improved specificity relatively to site-specific methods in classifying tumors as nonsarcoma according to patient outcome. We recommend that uterine SMT criteria and nomenclature be adopted for evaluation and classification of vulvovaginal SMTs.</description><identifier>ISSN: 0147-5185</identifier><identifier>EISSN: 1532-0979</identifier><identifier>DOI: 10.1097/PAS.0000000000000920</identifier><identifier>PMID: 28786880</identifier><language>eng</language><publisher>United States: Copyright Wolters Kluwer Health, Inc. All rights reserved</publisher><subject>Adolescent ; Adult ; Aged ; Aged, 80 and over ; Female ; Follow-Up Studies ; Humans ; Middle Aged ; Prognosis ; Retrospective Studies ; Risk Assessment ; Smooth Muscle Tumor - classification ; Smooth Muscle Tumor - diagnosis ; Smooth Muscle Tumor - pathology ; Vaginal Neoplasms - classification ; Vaginal Neoplasms - diagnosis ; Vaginal Neoplasms - pathology ; Vulvar Neoplasms - classification ; Vulvar Neoplasms - diagnosis ; Vulvar Neoplasms - pathology ; Young Adult</subject><ispartof>The American journal of surgical pathology, 2018-01, Vol.42 (1), p.84-94</ispartof><rights>Copyright © 2018 Wolters Kluwer Health, Inc. 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Yet, the rarity of SMTs of the vagina and vulva makes development of a prognostically meaningful classification system challenging. While 2 classification methods for vulvar SMTs and 1 for vaginal SMTs have been proposed, it is our experience that many pathologists tend to apply criteria for uterine SMTs when evaluating vulvovaginal tumors. We retrospectively reviewed a large cohort of vulvovaginal SMTs with clinical follow-up and evaluated which method most accurately classified tumors according to patient outcome. A total of 71 tumors, 53 vaginal (75%) and 18 vulvar (25%), from 71 patients were identified. All tumors were centrally examined for degree of cytologic atypia, morphology (spindled, epithelioid, myxoid), mitotic index per 10 high power fields, atypical mitotic figures, tumor cell necrosis, ischemic necrosis, tumor interface (circumscribed or infiltrative) and margin status. Clinical features were recorded for each patient. Follow-up was available for 63 patients (89%), and ranged from 1 to 234 months (median64 mo). While site-specific and uterine criteria showed equally excellent sensitivity in classifying smooth muscle neoplasms as leiomyosarcoma according to patient outcome, uterine criteria showed improved specificity relatively to site-specific methods in classifying tumors as nonsarcoma according to patient outcome. We recommend that uterine SMT criteria and nomenclature be adopted for evaluation and classification of vulvovaginal SMTs.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Female</subject><subject>Follow-Up Studies</subject><subject>Humans</subject><subject>Middle Aged</subject><subject>Prognosis</subject><subject>Retrospective Studies</subject><subject>Risk Assessment</subject><subject>Smooth Muscle Tumor - classification</subject><subject>Smooth Muscle Tumor - diagnosis</subject><subject>Smooth Muscle Tumor - pathology</subject><subject>Vaginal Neoplasms - classification</subject><subject>Vaginal Neoplasms - diagnosis</subject><subject>Vaginal Neoplasms - pathology</subject><subject>Vulvar Neoplasms - classification</subject><subject>Vulvar Neoplasms - diagnosis</subject><subject>Vulvar Neoplasms - pathology</subject><subject>Young Adult</subject><issn>0147-5185</issn><issn>1532-0979</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9Uc1u1DAQthCILoU3QMhHLinjOIltDkirqPxIRVRs6dVyEmfX1IkXT7JV36KPXFdblsKBOXgO8_3M-CPkNYMTBkq8O1-uTuBxqRyekAUreZ6luXpKFsAKkZVMlkfkBeJPAJZLlj8nR7kUspISFuS2jm6y0Rnah0i_O7yiqymayfWuTW8Yaejp5ex3JlIzdvTSrN1oPF0NIUwb-nXG1lt6MQ8h4nu6HOnpzvj5wBSM1gYt0joMWxPduKbnMWwD2o7W3iD-8Vnd4GQHfEme9cajffXQj8mPj6cX9efs7NunL_XyLGt5BZCxBioOqsyVFDbd3FadTB-gpLI8r1gnZCNYwytRKJGXBsrWMlb2vYKGd1Bwfkw-7HW3czPYrrVjOtvrbXSDiTc6GKf_noxuo9dhp0vBoahEEnj7IBDDr9nipAeHrfXejDbMqJnKE7Iq4N6r2EPbGBCj7Q82DPR9mDqFqf8NM9HePF7xQPqdXgLIPeA6-BQiXvn52ka9scZPm_9r3wF0QayF</recordid><startdate>201801</startdate><enddate>201801</enddate><creator>Sayeed, Sadia</creator><creator>Xing, Deyin</creator><creator>Jenkins, Sarah M</creator><creator>Weisman, Paul S</creator><creator>Buehler, Darya</creator><creator>Warmke, Laura</creator><creator>Uram-Tuculescu, Cora</creator><creator>Bakkum-Gamez, Jamie N</creator><creator>Howitt, Brooke E</creator><creator>Cortese, Cherise</creator><creator>Park, Kay J</creator><creator>Schoolmeester, J Kenneth</creator><general>Copyright Wolters Kluwer Health, Inc. All rights reserved</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></search><sort><creationdate>201801</creationdate><title>Criteria for Risk Stratification of Vulvar and Vaginal Smooth Muscle Tumors: An Evaluation of 71 Cases Comparing Proposed Classification Systems</title><author>Sayeed, Sadia ; Xing, Deyin ; Jenkins, Sarah M ; Weisman, Paul S ; Buehler, Darya ; Warmke, Laura ; Uram-Tuculescu, Cora ; Bakkum-Gamez, Jamie N ; Howitt, Brooke E ; Cortese, Cherise ; Park, Kay J ; Schoolmeester, J Kenneth</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3600-1b0630952987e153c6d8920989e3261d78b71b36749725a05ce115ff90b3d0433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Female</topic><topic>Follow-Up Studies</topic><topic>Humans</topic><topic>Middle Aged</topic><topic>Prognosis</topic><topic>Retrospective Studies</topic><topic>Risk Assessment</topic><topic>Smooth Muscle Tumor - classification</topic><topic>Smooth Muscle Tumor - diagnosis</topic><topic>Smooth Muscle Tumor - pathology</topic><topic>Vaginal Neoplasms - classification</topic><topic>Vaginal Neoplasms - diagnosis</topic><topic>Vaginal Neoplasms - pathology</topic><topic>Vulvar Neoplasms - classification</topic><topic>Vulvar Neoplasms - diagnosis</topic><topic>Vulvar Neoplasms - pathology</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sayeed, Sadia</creatorcontrib><creatorcontrib>Xing, Deyin</creatorcontrib><creatorcontrib>Jenkins, Sarah M</creatorcontrib><creatorcontrib>Weisman, Paul S</creatorcontrib><creatorcontrib>Buehler, Darya</creatorcontrib><creatorcontrib>Warmke, Laura</creatorcontrib><creatorcontrib>Uram-Tuculescu, Cora</creatorcontrib><creatorcontrib>Bakkum-Gamez, Jamie N</creatorcontrib><creatorcontrib>Howitt, Brooke E</creatorcontrib><creatorcontrib>Cortese, Cherise</creatorcontrib><creatorcontrib>Park, Kay J</creatorcontrib><creatorcontrib>Schoolmeester, J Kenneth</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>The American journal of surgical pathology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sayeed, Sadia</au><au>Xing, Deyin</au><au>Jenkins, Sarah M</au><au>Weisman, Paul S</au><au>Buehler, Darya</au><au>Warmke, Laura</au><au>Uram-Tuculescu, Cora</au><au>Bakkum-Gamez, Jamie N</au><au>Howitt, Brooke E</au><au>Cortese, Cherise</au><au>Park, Kay J</au><au>Schoolmeester, J Kenneth</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Criteria for Risk Stratification of Vulvar and Vaginal Smooth Muscle Tumors: An Evaluation of 71 Cases Comparing Proposed Classification Systems</atitle><jtitle>The American journal of surgical pathology</jtitle><addtitle>Am J Surg Pathol</addtitle><date>2018-01</date><risdate>2018</risdate><volume>42</volume><issue>1</issue><spage>84</spage><epage>94</epage><pages>84-94</pages><issn>0147-5185</issn><eissn>1532-0979</eissn><abstract>Accurate risk stratification of smooth muscle tumors (SMTs) is essential for appropriate patient management. Yet, the rarity of SMTs of the vagina and vulva makes development of a prognostically meaningful classification system challenging. While 2 classification methods for vulvar SMTs and 1 for vaginal SMTs have been proposed, it is our experience that many pathologists tend to apply criteria for uterine SMTs when evaluating vulvovaginal tumors. We retrospectively reviewed a large cohort of vulvovaginal SMTs with clinical follow-up and evaluated which method most accurately classified tumors according to patient outcome. A total of 71 tumors, 53 vaginal (75%) and 18 vulvar (25%), from 71 patients were identified. All tumors were centrally examined for degree of cytologic atypia, morphology (spindled, epithelioid, myxoid), mitotic index per 10 high power fields, atypical mitotic figures, tumor cell necrosis, ischemic necrosis, tumor interface (circumscribed or infiltrative) and margin status. Clinical features were recorded for each patient. Follow-up was available for 63 patients (89%), and ranged from 1 to 234 months (median64 mo). While site-specific and uterine criteria showed equally excellent sensitivity in classifying smooth muscle neoplasms as leiomyosarcoma according to patient outcome, uterine criteria showed improved specificity relatively to site-specific methods in classifying tumors as nonsarcoma according to patient outcome. We recommend that uterine SMT criteria and nomenclature be adopted for evaluation and classification of vulvovaginal SMTs.</abstract><cop>United States</cop><pub>Copyright Wolters Kluwer Health, Inc. All rights reserved</pub><pmid>28786880</pmid><doi>10.1097/PAS.0000000000000920</doi><tpages>11</tpages></addata></record> |
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subjects | Adolescent Adult Aged Aged, 80 and over Female Follow-Up Studies Humans Middle Aged Prognosis Retrospective Studies Risk Assessment Smooth Muscle Tumor - classification Smooth Muscle Tumor - diagnosis Smooth Muscle Tumor - pathology Vaginal Neoplasms - classification Vaginal Neoplasms - diagnosis Vaginal Neoplasms - pathology Vulvar Neoplasms - classification Vulvar Neoplasms - diagnosis Vulvar Neoplasms - pathology Young Adult |
title | Criteria for Risk Stratification of Vulvar and Vaginal Smooth Muscle Tumors: An Evaluation of 71 Cases Comparing Proposed Classification Systems |
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