Multicenter External Validation of a Nomogram for Predicting Positive Prostate-specific Membrane Antigen/Positron Emission Tomography Scan in Patients with Prostate Cancer Recurrence.

Biochemical recurrence Positron emission tomography nomogram Prostate cancer Prostate cancer nomogram Prostate-specific membrane antigen Prostate-specific membrane antigen/positron emission tomography

Journal

European urology oncology
ISSN: 2588-9311
Titre abrégé: Eur Urol Oncol
Pays: Netherlands
ID NLM: 101724904

Informations de publication

Date de publication:
02 2023
Historique:
received: 20 09 2021
revised: 14 11 2021
accepted: 03 12 2021
pubmed: 23 12 2021
medline: 11 2 2023
entrez: 22 12 2021
Statut: ppublish

Résumé

A nomogram has recently been developed to predict To perform external validation of the original nomogram in a multicentric setting. A total of 1639 patients who underwent PSMA-PET for prostate-specific antigen (PSA) relapse after radical therapy were retrospectively included from six high-volume PET centers. The external cohort was stratified according to clinical setting categories: group 1: first-time biochemical recurrence (n = 774); group 2: PSA relapse after salvage therapy (n = 499); group-3: biochemical persistence after radical prostatectomy (n = 210); and group-4: advanced-stage PCa before second-line systemic therapies (n = 124). PSMA-PET in recurrent PCa. PSMA-PET detection rate was assessed in the overall population and in each subgroup. A multivariable logistic regression model was produced to evaluate the predictors of a positive scan. The performance characteristics of the model were assessed by quantifying the predictive accuracy (PA) according to model calibration. The Youden's index was used to find the best nomogram's cutoff. Decision curve analysis (DCA) was implemented to quantify the nomogram's clinical net benefit. In the external cohort, the overall detection rate was 53.8% versus 51.2% in the original population. At multivariate analysis, International Society of Urological Pathology grade group, PSA, PSA doubling time, and clinical setting were independent predictors of a positive scan (all p ≤ 0.02). The PA of the nomogram was identical to the original model (82.0%); the model showed an optimal calibration curve. The best nomogram's cutoff was 55%. In the DCA, the nomogram revealed clinical net benefit when the threshold nomogram probabilities were ≥20%. The retrospective design is a major limitation. The original nomogram exhibited excellent characteristics on external validation. The incidence of a false negative scan can be reduced if PSMA-PET is performed when the predicted probability is ≥20%. A nomogram has been developed to predict prostate-specific membrane antigen/positron emission tomography (PSMA-PET) results for recurrent prostate cancer (PCa). The nomogram represents an easy tool in the decision-making process of recurrent PCa.

Sections du résumé

BACKGROUND
A nomogram has recently been developed to predict
OBJECTIVE
To perform external validation of the original nomogram in a multicentric setting.
DESIGN, SETTING, AND PARTICIPANTS
A total of 1639 patients who underwent PSMA-PET for prostate-specific antigen (PSA) relapse after radical therapy were retrospectively included from six high-volume PET centers. The external cohort was stratified according to clinical setting categories: group 1: first-time biochemical recurrence (n = 774); group 2: PSA relapse after salvage therapy (n = 499); group-3: biochemical persistence after radical prostatectomy (n = 210); and group-4: advanced-stage PCa before second-line systemic therapies (n = 124).
INTERVENTION
PSMA-PET in recurrent PCa.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS
PSMA-PET detection rate was assessed in the overall population and in each subgroup. A multivariable logistic regression model was produced to evaluate the predictors of a positive scan. The performance characteristics of the model were assessed by quantifying the predictive accuracy (PA) according to model calibration. The Youden's index was used to find the best nomogram's cutoff. Decision curve analysis (DCA) was implemented to quantify the nomogram's clinical net benefit.
RESULTS AND LIMITATIONS
In the external cohort, the overall detection rate was 53.8% versus 51.2% in the original population. At multivariate analysis, International Society of Urological Pathology grade group, PSA, PSA doubling time, and clinical setting were independent predictors of a positive scan (all p ≤ 0.02). The PA of the nomogram was identical to the original model (82.0%); the model showed an optimal calibration curve. The best nomogram's cutoff was 55%. In the DCA, the nomogram revealed clinical net benefit when the threshold nomogram probabilities were ≥20%. The retrospective design is a major limitation.
CONCLUSIONS
The original nomogram exhibited excellent characteristics on external validation. The incidence of a false negative scan can be reduced if PSMA-PET is performed when the predicted probability is ≥20%.
PATIENT SUMMARY
A nomogram has been developed to predict prostate-specific membrane antigen/positron emission tomography (PSMA-PET) results for recurrent prostate cancer (PCa). The nomogram represents an easy tool in the decision-making process of recurrent PCa.

Identifiants

pubmed: 34933814
pii: S2588-9311(21)00217-0
doi: 10.1016/j.euo.2021.12.002
pii:
doi:

Substances chimiques

Prostate-Specific Antigen EC 3.4.21.77

Types de publication

Multicenter Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

41-48

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2021 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Auteurs

Lorenzo Bianchi (L)

Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy; Università degli studi di Bologna, Bologna, Italy.

Paolo Castellucci (P)

Division of Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.

Andrea Farolfi (A)

Division of Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy. Electronic address: andrea.farolfi6@unibo.it.

Matteo Droghetti (M)

Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.

Carlos Artigas (C)

Department of Nuclear Medicine, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium.

Jose Leite (J)

PET/CT Center, DASA - Diagnósticos da Améric, Rio de Janeiro, Brazil.

Paola Corona (P)

Fundación Centro Diagnóstico Nuclear (FCDN), Buenos Aires, Argentina.

Qaid Ahmed Shagera (QA)

Department of Nuclear Medicine, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium.

Renata Moreira (R)

PET/CT Center, DASA - Diagnósticos da Améric, Rio de Janeiro, Brazil.

Christian González (C)

Fundación Centro Diagnóstico Nuclear (FCDN), Buenos Aires, Argentina.

Marcelo Queiroz (M)

Department of Radiology, Hospital Sírio-Libanês, University of Sao Paulo, Sao Paulo, Brazil.

Felipe de Galiza Barbosa (F)

Department of Radiology, Hospital Sírio-Libanês, University of Sao Paulo, Sao Paulo, Brazil.

Riccardo Schiavina (R)

Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy; Università degli studi di Bologna, Bologna, Italy.

Desiree Deandreis (D)

Nuclear Medicine, Department of Medical Sciences, University of Turin, Turin, Italy.

Stefano Fanti (S)

Division of Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.

Francesco Ceci (F)

Division of Nuclear Medicine and Theranostics, IEO European Institute of Oncology IRCCS, Milan, Italy.

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Classifications MeSH