Does Multiparametric Magnetic Resonance of Prostate Outperform Risk Calculators in Predicting Prostate Cancer in Biopsy Naïve Patients?
clinically significant prostate cancer
decision curve analysis
mpMRI
prostate cancer
risk calculator
Journal
Frontiers in oncology
ISSN: 2234-943X
Titre abrégé: Front Oncol
Pays: Switzerland
ID NLM: 101568867
Informations de publication
Date de publication:
2020
2020
Historique:
received:
06
09
2020
accepted:
24
11
2020
entrez:
25
1
2021
pubmed:
26
1
2021
medline:
26
1
2021
Statut:
epublish
Résumé
European Association of Urology (EAU) guidelines recommend using risk-calculators (RCs), imaging or additional biomarkers in asymptomatic men at risk of prostate cancer (PCa). To compare the performance of mpMRI, a RC we recently developed and two commonly used RC not including mpMRI in predicting the risk of PCa, as well as the added value of mpMRI to each RC. Single-center retrospective study evaluating 221 biopsy-naïve patients who underwent prebiopsy mpMRI. Patients' probabilities of any PCa and clinically significant PCa (csPC, defined as Gleason-Score ≥3 + 4) were computed according to mpMRI, European Randomized Study of Screening for Prostate Cancer RC (ERSPC-RC), the Prostate Biopsy Collaborative Group RC (PBCG-RC) and the Foggia Prostate Cancer RC (FPC-RC). Logistic regression, AUC, and Decision curve analysis (DCA) were used to assess the accuracy of tested models. The FPC-RC outperformed mpMRI in diagnosing both any PCa (AUC 0.76 mpMRI was outperformed by the novel FPC-RC and showed similar performances compared to the PBCG and ERSPC RCs in predicting csPCa. The addition of mpMRI findings improved the diagnostic accuracy of each of these calculators.
Sections du résumé
BACKGROUND
BACKGROUND
European Association of Urology (EAU) guidelines recommend using risk-calculators (RCs), imaging or additional biomarkers in asymptomatic men at risk of prostate cancer (PCa).
OBJECTIVES
OBJECTIVE
To compare the performance of mpMRI, a RC we recently developed and two commonly used RC not including mpMRI in predicting the risk of PCa, as well as the added value of mpMRI to each RC.
DESIGN SETTING AND PARTICIPANTS
METHODS
Single-center retrospective study evaluating 221 biopsy-naïve patients who underwent prebiopsy mpMRI.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS
METHODS
Patients' probabilities of any PCa and clinically significant PCa (csPC, defined as Gleason-Score ≥3 + 4) were computed according to mpMRI, European Randomized Study of Screening for Prostate Cancer RC (ERSPC-RC), the Prostate Biopsy Collaborative Group RC (PBCG-RC) and the Foggia Prostate Cancer RC (FPC-RC). Logistic regression, AUC, and Decision curve analysis (DCA) were used to assess the accuracy of tested models.
RESULTS AND LIMITATION
RESULTS
The FPC-RC outperformed mpMRI in diagnosing both any PCa (AUC 0.76
CONCLUSIONS
CONCLUSIONS
mpMRI was outperformed by the novel FPC-RC and showed similar performances compared to the PBCG and ERSPC RCs in predicting csPCa. The addition of mpMRI findings improved the diagnostic accuracy of each of these calculators.
Identifiants
pubmed: 33489907
doi: 10.3389/fonc.2020.603384
pmc: PMC7821426
doi:
Types de publication
Journal Article
Langues
eng
Pagination
603384Informations de copyright
Copyright © 2021 Falagario, Silecchia, Bruno, Di Nauta, Auciello, Sanguedolce, Milillo, Macarini, Selvaggio, Carrieri and Cormio.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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