The accuracy of pathological data for the prediction of insignificant prostate cancer

Introduction The widespread screening programs prompted a decrease in prostate cancer stage at diagnosis, and active surveillance is an option for patients who may harbor clinically insignificant prostate cancer (IPC). Pathologists include the possibility of an IPC in their reports based on the Gleason score and tumor volume. This study determined the accuracy of pathological data in the identification of IPC in radical prostatectomy (RP) specimens. Materials and Methods Of 592 radical prostatectomy specimens examined in our laboratory from 2001 to 2010, 20 patients harbored IPC and exhibited biopsy findings suggestive of IPC. These biopsy features served as the criteria to define patients with potentially insignificant tumor in this population. The results of the prostate biopsies and surgical specimens of the 592 patients were compared. Results The twenty patients who had IPC in both biopsy and RP were considered real positive cases. All patients were divided into groups based on their diagnoses following RP: true positives (n = 20), false positives (n = 149), true negatives (n = 421), false negatives (n = 2). The accuracy of the pathological data alone for the prediction of IPC was 91.4%, the sensitivity was 91% and the specificity was 74%. Conclusion The identification of IPC using pathological data exclusively is accurate, and pathologists should suggest this in their reports to aid surgeons, urologists and radiotherapists to decide the best treatment for their patients.

Saved in:
Bibliographic Details
Main Authors: Katz,Betina, Srougi,Miguel, Camara-Lopes,Luiz H., Antunes,Alberto A., Nesrallah,Luciano, Nesrallah,Adriano, Dall'Oglio,Marcos, Leite,Katia R. M.
Format: Digital revista
Language:English
Published: Sociedade Brasileira de Urologia 2012
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1677-55382012000600760
Tags: Add Tag
No Tags, Be the first to tag this record!
id oai:scielo:S1677-55382012000600760
record_format ojs
spelling oai:scielo:S1677-553820120006007602013-04-05The accuracy of pathological data for the prediction of insignificant prostate cancerKatz,BetinaSrougi,MiguelCamara-Lopes,Luiz H.Antunes,Alberto A.Nesrallah,LucianoNesrallah,AdrianoDall'Oglio,MarcosLeite,Katia R. M. Prostate cancer Prostate Gleason score Diagnosis Introduction The widespread screening programs prompted a decrease in prostate cancer stage at diagnosis, and active surveillance is an option for patients who may harbor clinically insignificant prostate cancer (IPC). Pathologists include the possibility of an IPC in their reports based on the Gleason score and tumor volume. This study determined the accuracy of pathological data in the identification of IPC in radical prostatectomy (RP) specimens. Materials and Methods Of 592 radical prostatectomy specimens examined in our laboratory from 2001 to 2010, 20 patients harbored IPC and exhibited biopsy findings suggestive of IPC. These biopsy features served as the criteria to define patients with potentially insignificant tumor in this population. The results of the prostate biopsies and surgical specimens of the 592 patients were compared. Results The twenty patients who had IPC in both biopsy and RP were considered real positive cases. All patients were divided into groups based on their diagnoses following RP: true positives (n = 20), false positives (n = 149), true negatives (n = 421), false negatives (n = 2). The accuracy of the pathological data alone for the prediction of IPC was 91.4%, the sensitivity was 91% and the specificity was 74%. Conclusion The identification of IPC using pathological data exclusively is accurate, and pathologists should suggest this in their reports to aid surgeons, urologists and radiotherapists to decide the best treatment for their patients. info:eu-repo/semantics/openAccessSociedade Brasileira de UrologiaInternational braz j urol v.38 n.6 20122012-12-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1677-55382012000600760en10.1590/1677-553820133806760
institution SCIELO
collection OJS
country Brasil
countrycode BR
component Revista
access En linea
databasecode rev-scielo-br
tag revista
region America del Sur
libraryname SciELO
language English
format Digital
author Katz,Betina
Srougi,Miguel
Camara-Lopes,Luiz H.
Antunes,Alberto A.
Nesrallah,Luciano
Nesrallah,Adriano
Dall'Oglio,Marcos
Leite,Katia R. M.
spellingShingle Katz,Betina
Srougi,Miguel
Camara-Lopes,Luiz H.
Antunes,Alberto A.
Nesrallah,Luciano
Nesrallah,Adriano
Dall'Oglio,Marcos
Leite,Katia R. M.
The accuracy of pathological data for the prediction of insignificant prostate cancer
author_facet Katz,Betina
Srougi,Miguel
Camara-Lopes,Luiz H.
Antunes,Alberto A.
Nesrallah,Luciano
Nesrallah,Adriano
Dall'Oglio,Marcos
Leite,Katia R. M.
author_sort Katz,Betina
title The accuracy of pathological data for the prediction of insignificant prostate cancer
title_short The accuracy of pathological data for the prediction of insignificant prostate cancer
title_full The accuracy of pathological data for the prediction of insignificant prostate cancer
title_fullStr The accuracy of pathological data for the prediction of insignificant prostate cancer
title_full_unstemmed The accuracy of pathological data for the prediction of insignificant prostate cancer
title_sort accuracy of pathological data for the prediction of insignificant prostate cancer
description Introduction The widespread screening programs prompted a decrease in prostate cancer stage at diagnosis, and active surveillance is an option for patients who may harbor clinically insignificant prostate cancer (IPC). Pathologists include the possibility of an IPC in their reports based on the Gleason score and tumor volume. This study determined the accuracy of pathological data in the identification of IPC in radical prostatectomy (RP) specimens. Materials and Methods Of 592 radical prostatectomy specimens examined in our laboratory from 2001 to 2010, 20 patients harbored IPC and exhibited biopsy findings suggestive of IPC. These biopsy features served as the criteria to define patients with potentially insignificant tumor in this population. The results of the prostate biopsies and surgical specimens of the 592 patients were compared. Results The twenty patients who had IPC in both biopsy and RP were considered real positive cases. All patients were divided into groups based on their diagnoses following RP: true positives (n = 20), false positives (n = 149), true negatives (n = 421), false negatives (n = 2). The accuracy of the pathological data alone for the prediction of IPC was 91.4%, the sensitivity was 91% and the specificity was 74%. Conclusion The identification of IPC using pathological data exclusively is accurate, and pathologists should suggest this in their reports to aid surgeons, urologists and radiotherapists to decide the best treatment for their patients.
publisher Sociedade Brasileira de Urologia
publishDate 2012
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1677-55382012000600760
work_keys_str_mv AT katzbetina theaccuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT srougimiguel theaccuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT camaralopesluizh theaccuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT antunesalbertoa theaccuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT nesrallahluciano theaccuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT nesrallahadriano theaccuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT dallogliomarcos theaccuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT leitekatiarm theaccuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT katzbetina accuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT srougimiguel accuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT camaralopesluizh accuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT antunesalbertoa accuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT nesrallahluciano accuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT nesrallahadriano accuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT dallogliomarcos accuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
AT leitekatiarm accuracyofpathologicaldataforthepredictionofinsignificantprostatecancer
_version_ 1756428125486448640