A novel algorithm to improve pathologic stage prediction of clinically organ‐confined muscle‐invasive bladder cancer
BACKGROUND: An algorithm was created to predict pathologic stage in patients with clinically organ‐confined muscle‐invasive bladder cancer. METHODS: The sample consisted of 133 consecutive patients scheduled to undergo cystectomy. To develop a tool to predict nonorgan‐confined disease before surgery...
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Veröffentlicht in: | Cancer 2009-04, Vol.115 (7), p.1459-1464 |
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creator | Margel, David Harel, Amir Yossepowitch, Ofer Baniel, Jack |
description | BACKGROUND:
An algorithm was created to predict pathologic stage in patients with clinically organ‐confined muscle‐invasive bladder cancer.
METHODS:
The sample consisted of 133 consecutive patients scheduled to undergo cystectomy. To develop a tool to predict nonorgan‐confined disease before surgery, principal component analysis (PCA) was applied. Patients were stratified into a training set (n = 89) and a validation set (n = 44), and 7 parameters were evaluated: levels of carcinoembryonic antigen, cancer antigen (CA) 125, and carbohydrate antigen (CA) 19‐9; clinical stage; presence of hydronephrosis; presence of carcinoma in situ; and initial tumor size >3 cm. PCA was applied to the training set to determine the weight of each parameter. A PCA score was generated for each patient in the set, and a cutoff defining nonorgan‐confined disease was established. The accuracy of the cutoff was quantified by the area under the receiver operator characteristics curve (AUC). The model was then applied to the validation set without recalculation; the AUC and the positive and negative predictive values of the validation set were calculated.
RESULTS:
On pathologic evaluation, 71 patients (53%) were found to have organ‐confined tumors and 62 patients (47%) had extravesical disease. The AUC was 0.85 in the training group (95% confidence interval [95% CI], 0.71‐0.97) and 0.84 in the validation group (95% CI, 0.75‐0.93). The positive and negative predictive values in the validation group were 88% (95% CI, 71%‐96%) and 94% (95% CI, 71%‐99%), respectively.
CONCLUSIONS:
The newly devised, internally validated, algorithm was 85% accurate in predicting nonorgan‐confined bladder disease before cystectomy. Further external validation in a large cohort was recommended as still necessary. Cancer 2009. © 2009 American Cancer Society.
In the current study, a unique algorithm was developed to assist in predicting nonorgan‐confined disease in patients with muscle‐invasive urothelial carcinoma. The newly devised formula was 85% accurate, and the findings were internally validated. |
doi_str_mv | 10.1002/cncr.24138 |
format | Article |
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An algorithm was created to predict pathologic stage in patients with clinically organ‐confined muscle‐invasive bladder cancer.
METHODS:
The sample consisted of 133 consecutive patients scheduled to undergo cystectomy. To develop a tool to predict nonorgan‐confined disease before surgery, principal component analysis (PCA) was applied. Patients were stratified into a training set (n = 89) and a validation set (n = 44), and 7 parameters were evaluated: levels of carcinoembryonic antigen, cancer antigen (CA) 125, and carbohydrate antigen (CA) 19‐9; clinical stage; presence of hydronephrosis; presence of carcinoma in situ; and initial tumor size >3 cm. PCA was applied to the training set to determine the weight of each parameter. A PCA score was generated for each patient in the set, and a cutoff defining nonorgan‐confined disease was established. The accuracy of the cutoff was quantified by the area under the receiver operator characteristics curve (AUC). The model was then applied to the validation set without recalculation; the AUC and the positive and negative predictive values of the validation set were calculated.
RESULTS:
On pathologic evaluation, 71 patients (53%) were found to have organ‐confined tumors and 62 patients (47%) had extravesical disease. The AUC was 0.85 in the training group (95% confidence interval [95% CI], 0.71‐0.97) and 0.84 in the validation group (95% CI, 0.75‐0.93). The positive and negative predictive values in the validation group were 88% (95% CI, 71%‐96%) and 94% (95% CI, 71%‐99%), respectively.
CONCLUSIONS:
The newly devised, internally validated, algorithm was 85% accurate in predicting nonorgan‐confined bladder disease before cystectomy. Further external validation in a large cohort was recommended as still necessary. Cancer 2009. © 2009 American Cancer Society.
In the current study, a unique algorithm was developed to assist in predicting nonorgan‐confined disease in patients with muscle‐invasive urothelial carcinoma. The newly devised formula was 85% accurate, and the findings were internally validated.</description><identifier>ISSN: 0008-543X</identifier><identifier>EISSN: 1097-0142</identifier><identifier>DOI: 10.1002/cncr.24138</identifier><identifier>PMID: 19152435</identifier><identifier>CODEN: CANCAR</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Algorithms ; Biological and medical sciences ; CA 125 ; CA 19‐9 ; CA-125 Antigen - analysis ; CA-19-9 Antigen - analysis ; carcinoembryonic antigen ; Carcinoembryonic Antigen - analysis ; Female ; Humans ; Male ; mathematical prediction model ; Medical sciences ; Middle Aged ; Neoplasm Invasiveness - pathology ; Neoplasm Staging - methods ; Nephrology. Urinary tract diseases ; Prognosis ; Reproducibility of Results ; tumor markers ; Tumors ; Tumors of the urinary system ; Urinary Bladder Neoplasms - pathology ; Urinary tract. Prostate gland ; urothelial carcinoma</subject><ispartof>Cancer, 2009-04, Vol.115 (7), p.1459-1464</ispartof><rights>Copyright © 2009 American Cancer Society</rights><rights>2009 INIST-CNRS</rights><rights>(c) 2009 American Cancer Society</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4248-36d9425c4f4f0e79fce74578493e97a023c1f867d95a9ec0bdd2cb58e95586aa3</citedby><cites>FETCH-LOGICAL-c4248-36d9425c4f4f0e79fce74578493e97a023c1f867d95a9ec0bdd2cb58e95586aa3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fcncr.24138$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fcncr.24138$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,1427,27903,27904,45553,45554,46388,46812</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=21257211$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19152435$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Margel, David</creatorcontrib><creatorcontrib>Harel, Amir</creatorcontrib><creatorcontrib>Yossepowitch, Ofer</creatorcontrib><creatorcontrib>Baniel, Jack</creatorcontrib><title>A novel algorithm to improve pathologic stage prediction of clinically organ‐confined muscle‐invasive bladder cancer</title><title>Cancer</title><addtitle>Cancer</addtitle><description>BACKGROUND:
An algorithm was created to predict pathologic stage in patients with clinically organ‐confined muscle‐invasive bladder cancer.
METHODS:
The sample consisted of 133 consecutive patients scheduled to undergo cystectomy. To develop a tool to predict nonorgan‐confined disease before surgery, principal component analysis (PCA) was applied. Patients were stratified into a training set (n = 89) and a validation set (n = 44), and 7 parameters were evaluated: levels of carcinoembryonic antigen, cancer antigen (CA) 125, and carbohydrate antigen (CA) 19‐9; clinical stage; presence of hydronephrosis; presence of carcinoma in situ; and initial tumor size >3 cm. PCA was applied to the training set to determine the weight of each parameter. A PCA score was generated for each patient in the set, and a cutoff defining nonorgan‐confined disease was established. The accuracy of the cutoff was quantified by the area under the receiver operator characteristics curve (AUC). The model was then applied to the validation set without recalculation; the AUC and the positive and negative predictive values of the validation set were calculated.
RESULTS:
On pathologic evaluation, 71 patients (53%) were found to have organ‐confined tumors and 62 patients (47%) had extravesical disease. The AUC was 0.85 in the training group (95% confidence interval [95% CI], 0.71‐0.97) and 0.84 in the validation group (95% CI, 0.75‐0.93). The positive and negative predictive values in the validation group were 88% (95% CI, 71%‐96%) and 94% (95% CI, 71%‐99%), respectively.
CONCLUSIONS:
The newly devised, internally validated, algorithm was 85% accurate in predicting nonorgan‐confined bladder disease before cystectomy. Further external validation in a large cohort was recommended as still necessary. Cancer 2009. © 2009 American Cancer Society.
In the current study, a unique algorithm was developed to assist in predicting nonorgan‐confined disease in patients with muscle‐invasive urothelial carcinoma. The newly devised formula was 85% accurate, and the findings were internally validated.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Algorithms</subject><subject>Biological and medical sciences</subject><subject>CA 125</subject><subject>CA 19‐9</subject><subject>CA-125 Antigen - analysis</subject><subject>CA-19-9 Antigen - analysis</subject><subject>carcinoembryonic antigen</subject><subject>Carcinoembryonic Antigen - analysis</subject><subject>Female</subject><subject>Humans</subject><subject>Male</subject><subject>mathematical prediction model</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Neoplasm Invasiveness - pathology</subject><subject>Neoplasm Staging - methods</subject><subject>Nephrology. Urinary tract diseases</subject><subject>Prognosis</subject><subject>Reproducibility of Results</subject><subject>tumor markers</subject><subject>Tumors</subject><subject>Tumors of the urinary system</subject><subject>Urinary Bladder Neoplasms - pathology</subject><subject>Urinary tract. Prostate gland</subject><subject>urothelial carcinoma</subject><issn>0008-543X</issn><issn>1097-0142</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkU1uFDEQhS0EIkNgwwGQN7CI1IntttvtZTQKP1IUpAgkdi1PdXli5LYHuydhdhwhZ-QkOMwIdrAq1dOnV6r3CHnJ2SlnTJxBhHwqJG_7R2TBmdEN41I8JgvGWN8o2X45Is9K-VpXLVT7lBxxw5WQrVqQ7-c0plsM1IZ1yn6-meicqJ82uap0Y-ebFNLaAy2zXVch4-hh9inS5CgEHz3YEHY05bWNP3_cQ4rORxzptC0QsCo-3triq9kq2HHETMFGwPycPHE2FHxxmMfk89uLT8v3zeXHdx-W55cNSCH7pu1GI4UC6aRjqI0D1FLpXpoWjbZMtMBd3-nRKGsQ2GocBaxUj0apvrO2PSZv9r71o29bLPMw-QIYgo2YtmXoNFOKG_ZfUNRQdcdkBU_2IORUSkY3bLKfbN4NnA0PhQwPhQy_C6nwq4PrdjXh-Bc9NFCB1wfAlhqlyzUdX_5wggulBeeV43vuzgfc_ePksLxaXu-P_wKDMqbF</recordid><startdate>20090401</startdate><enddate>20090401</enddate><creator>Margel, David</creator><creator>Harel, Amir</creator><creator>Yossepowitch, Ofer</creator><creator>Baniel, Jack</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><general>Wiley-Blackwell</general><scope>IQODW</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>7U7</scope><scope>C1K</scope><scope>7X8</scope></search><sort><creationdate>20090401</creationdate><title>A novel algorithm to improve pathologic stage prediction of clinically organ‐confined muscle‐invasive bladder cancer</title><author>Margel, David ; Harel, Amir ; Yossepowitch, Ofer ; Baniel, Jack</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4248-36d9425c4f4f0e79fce74578493e97a023c1f867d95a9ec0bdd2cb58e95586aa3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Algorithms</topic><topic>Biological and medical sciences</topic><topic>CA 125</topic><topic>CA 19‐9</topic><topic>CA-125 Antigen - analysis</topic><topic>CA-19-9 Antigen - analysis</topic><topic>carcinoembryonic antigen</topic><topic>Carcinoembryonic Antigen - analysis</topic><topic>Female</topic><topic>Humans</topic><topic>Male</topic><topic>mathematical prediction model</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Neoplasm Invasiveness - pathology</topic><topic>Neoplasm Staging - methods</topic><topic>Nephrology. Urinary tract diseases</topic><topic>Prognosis</topic><topic>Reproducibility of Results</topic><topic>tumor markers</topic><topic>Tumors</topic><topic>Tumors of the urinary system</topic><topic>Urinary Bladder Neoplasms - pathology</topic><topic>Urinary tract. Prostate gland</topic><topic>urothelial carcinoma</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Margel, David</creatorcontrib><creatorcontrib>Harel, Amir</creatorcontrib><creatorcontrib>Yossepowitch, Ofer</creatorcontrib><creatorcontrib>Baniel, Jack</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Toxicology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>MEDLINE - Academic</collection><jtitle>Cancer</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Margel, David</au><au>Harel, Amir</au><au>Yossepowitch, Ofer</au><au>Baniel, Jack</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A novel algorithm to improve pathologic stage prediction of clinically organ‐confined muscle‐invasive bladder cancer</atitle><jtitle>Cancer</jtitle><addtitle>Cancer</addtitle><date>2009-04-01</date><risdate>2009</risdate><volume>115</volume><issue>7</issue><spage>1459</spage><epage>1464</epage><pages>1459-1464</pages><issn>0008-543X</issn><eissn>1097-0142</eissn><coden>CANCAR</coden><abstract>BACKGROUND:
An algorithm was created to predict pathologic stage in patients with clinically organ‐confined muscle‐invasive bladder cancer.
METHODS:
The sample consisted of 133 consecutive patients scheduled to undergo cystectomy. To develop a tool to predict nonorgan‐confined disease before surgery, principal component analysis (PCA) was applied. Patients were stratified into a training set (n = 89) and a validation set (n = 44), and 7 parameters were evaluated: levels of carcinoembryonic antigen, cancer antigen (CA) 125, and carbohydrate antigen (CA) 19‐9; clinical stage; presence of hydronephrosis; presence of carcinoma in situ; and initial tumor size >3 cm. PCA was applied to the training set to determine the weight of each parameter. A PCA score was generated for each patient in the set, and a cutoff defining nonorgan‐confined disease was established. The accuracy of the cutoff was quantified by the area under the receiver operator characteristics curve (AUC). The model was then applied to the validation set without recalculation; the AUC and the positive and negative predictive values of the validation set were calculated.
RESULTS:
On pathologic evaluation, 71 patients (53%) were found to have organ‐confined tumors and 62 patients (47%) had extravesical disease. The AUC was 0.85 in the training group (95% confidence interval [95% CI], 0.71‐0.97) and 0.84 in the validation group (95% CI, 0.75‐0.93). The positive and negative predictive values in the validation group were 88% (95% CI, 71%‐96%) and 94% (95% CI, 71%‐99%), respectively.
CONCLUSIONS:
The newly devised, internally validated, algorithm was 85% accurate in predicting nonorgan‐confined bladder disease before cystectomy. Further external validation in a large cohort was recommended as still necessary. Cancer 2009. © 2009 American Cancer Society.
In the current study, a unique algorithm was developed to assist in predicting nonorgan‐confined disease in patients with muscle‐invasive urothelial carcinoma. The newly devised formula was 85% accurate, and the findings were internally validated.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>19152435</pmid><doi>10.1002/cncr.24138</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adult Aged Aged, 80 and over Algorithms Biological and medical sciences CA 125 CA 19‐9 CA-125 Antigen - analysis CA-19-9 Antigen - analysis carcinoembryonic antigen Carcinoembryonic Antigen - analysis Female Humans Male mathematical prediction model Medical sciences Middle Aged Neoplasm Invasiveness - pathology Neoplasm Staging - methods Nephrology. Urinary tract diseases Prognosis Reproducibility of Results tumor markers Tumors Tumors of the urinary system Urinary Bladder Neoplasms - pathology Urinary tract. Prostate gland urothelial carcinoma |
title | A novel algorithm to improve pathologic stage prediction of clinically organ‐confined muscle‐invasive bladder cancer |
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