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External validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular extension in prostate cancer

INTRODUCTION: Recently developed algorithm for prediction of side-specific extracapsular extension (ECE) of prostate cancer required validation before being recommended to use. The algorithm assumed that ECE on a particular side was not likely with same side maximum tumor diameter (MTD) <15 mm AN...

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Autores principales: Zapała, Piotr, Kozikowski, Mieszko, Dybowski, Bartosz, Zapała, Łukasz, Dobruch, Jakub, Radziszewski, Piotr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Polish Urological Association 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552930/
https://www.ncbi.nlm.nih.gov/pubmed/34729221
http://dx.doi.org/10.5173/ceju.2021.0128.R2
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author Zapała, Piotr
Kozikowski, Mieszko
Dybowski, Bartosz
Zapała, Łukasz
Dobruch, Jakub
Radziszewski, Piotr
author_facet Zapała, Piotr
Kozikowski, Mieszko
Dybowski, Bartosz
Zapała, Łukasz
Dobruch, Jakub
Radziszewski, Piotr
author_sort Zapała, Piotr
collection PubMed
description INTRODUCTION: Recently developed algorithm for prediction of side-specific extracapsular extension (ECE) of prostate cancer required validation before being recommended to use. The algorithm assumed that ECE on a particular side was not likely with same side maximum tumor diameter (MTD) <15 mm AND cancerous tissue in ipsilateral biopsy <15% AND PSA <20 ng/mL (both sides condition). The aim of the study was to validate this predictive tool in patients from another department. MATERIAL AND METHODS: Data of 154 consecutive patients (308 prostatic lateral lobes) were used for validation. Predictive factors chosen in the development set of patients were assessed together with other preoperative parameters using logistic regression to check for their significance. Sensitivity, specificity, negative and positive predictive values were calculated for bootstrapped risk-stratified validation dataset. RESULTS: Validation cohort did not differ significantly from development cohort regarding PSA, PSA density, Gleason score (GS), MTD, age, ECE and seminal vesicle invasion rate. In bootstrapped data set (n = 200 random sampling) algorithm revealed 70.2% sensitivity (95% confidence interval (CI) 58.8–83.0%), 49.9% specificity (95%CI: 42.0–57.7%), 83.9% negative predictive value (NPV; 95%CI: 76.1–91.4%) and 31.1% positive predictive value (PPV; 95%CI: 19.6–39.7%). When limiting analysis to high-risk patients (Gleason score >7) the algorithm improved its performance: sensitivity 91%, specificity 47%, PPV 53%, NPV 89%. CONCLUSIONS: Analyzed algorithm is useful for identifying prostate lobes without ECE and deciding on ipsilateral nerve-sparing technique during radical prostatectomy, especially in patients with GS >7. Due to significant number of false positives in case of: MTD ≥15 mm OR cancer in biopsy ≥15% OR PSA ≥20 ng/mL additional evaluation is necessary to aid decision-making.
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spelling pubmed-85529302021-11-01 External validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular extension in prostate cancer Zapała, Piotr Kozikowski, Mieszko Dybowski, Bartosz Zapała, Łukasz Dobruch, Jakub Radziszewski, Piotr Cent European J Urol Original Paper INTRODUCTION: Recently developed algorithm for prediction of side-specific extracapsular extension (ECE) of prostate cancer required validation before being recommended to use. The algorithm assumed that ECE on a particular side was not likely with same side maximum tumor diameter (MTD) <15 mm AND cancerous tissue in ipsilateral biopsy <15% AND PSA <20 ng/mL (both sides condition). The aim of the study was to validate this predictive tool in patients from another department. MATERIAL AND METHODS: Data of 154 consecutive patients (308 prostatic lateral lobes) were used for validation. Predictive factors chosen in the development set of patients were assessed together with other preoperative parameters using logistic regression to check for their significance. Sensitivity, specificity, negative and positive predictive values were calculated for bootstrapped risk-stratified validation dataset. RESULTS: Validation cohort did not differ significantly from development cohort regarding PSA, PSA density, Gleason score (GS), MTD, age, ECE and seminal vesicle invasion rate. In bootstrapped data set (n = 200 random sampling) algorithm revealed 70.2% sensitivity (95% confidence interval (CI) 58.8–83.0%), 49.9% specificity (95%CI: 42.0–57.7%), 83.9% negative predictive value (NPV; 95%CI: 76.1–91.4%) and 31.1% positive predictive value (PPV; 95%CI: 19.6–39.7%). When limiting analysis to high-risk patients (Gleason score >7) the algorithm improved its performance: sensitivity 91%, specificity 47%, PPV 53%, NPV 89%. CONCLUSIONS: Analyzed algorithm is useful for identifying prostate lobes without ECE and deciding on ipsilateral nerve-sparing technique during radical prostatectomy, especially in patients with GS >7. Due to significant number of false positives in case of: MTD ≥15 mm OR cancer in biopsy ≥15% OR PSA ≥20 ng/mL additional evaluation is necessary to aid decision-making. Polish Urological Association 2021-09-18 2021 /pmc/articles/PMC8552930/ /pubmed/34729221 http://dx.doi.org/10.5173/ceju.2021.0128.R2 Text en Copyright by Polish Urological Association https://creativecommons.org/licenses/by-nc-sa/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License, allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material, provided the original work is properly cited and states its license.
spellingShingle Original Paper
Zapała, Piotr
Kozikowski, Mieszko
Dybowski, Bartosz
Zapała, Łukasz
Dobruch, Jakub
Radziszewski, Piotr
External validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular extension in prostate cancer
title External validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular extension in prostate cancer
title_full External validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular extension in prostate cancer
title_fullStr External validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular extension in prostate cancer
title_full_unstemmed External validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular extension in prostate cancer
title_short External validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular extension in prostate cancer
title_sort external validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular extension in prostate cancer
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552930/
https://www.ncbi.nlm.nih.gov/pubmed/34729221
http://dx.doi.org/10.5173/ceju.2021.0128.R2
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