A magnetic resonance imaging-based nomogram for predicting clinically significant prostate cancer at radical prostatectomy

Castellani, Daniele; Cecchini, Silvia; Mazzucchelli, Roberta; Soraci, Luca; Rosa, Mirko Di; Fabbietti, Paolo; Palagonia, Erika; Puccio, Francesca; Carnevali, Francesca; Paci, Enrico; Montironi, Rodolfo; Galosi, Andrea Benedetto

doi:10.1016/j.urolonc.2022.04.011

Cited by 3 publications

(7 citation statements)

References 27 publications

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“…The nomogram derived from the current results significantly outperformed serum PSA in diagnostic and prognostic performance, and its predictive accuracies, as indicated by the AUC and CI, which was comparable to various studies 25,29,31 . The calibration curves for our nomogram presented good concordance between the nomogram prediction and the actual observation of the likelihood of csPCa.…”

Section: Discussionsupporting

confidence: 74%

“…Four recent studies that used MRI/PI-RAD scores for the creation of prediction models have reached the same conclusion. [28][29][30][31] According to ROC analysis in all datasets, where it varied from 0.80 to 0.96, Jing et al 28 integrated radiomics signature and PI-RADS to construct a radiomics nomogram with superior discriminatory capacity, predicting csPCa, which surpassed the subjective evaluation alone of PSA. The use of multiparametric-MRI (mpMRI) based nomograms for predicting csPCa showed a slight but significant net benefit in Castellani's DCA compared to those excluding PI-RADS scores, and the AUC for the full model including PI-RADS scores was 0.77.…”

Section: Nomograms Have Been Developed and Validated In Previousmentioning

confidence: 99%

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Development and internal validation of a nomogram predicting significant prostate cancer: Is it clinically applicable in low prevalent prostate cancer countries? A multicenter study

Arafa,

Farhat,

Khan

et al. 2023

The Prostate

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BackgroundAccurately identifying aggressive prostate tumors and studying them as a separate outcome are urgently needed. Nomogram is a predictive tool using an algorithm, it has been widely applied in clinical practice to predict prognosis. We aimed to develop and internally validate a nomogram predicting clinically significant prostate cancer (csPCa).MethodsData were retrieved from the records of the two main hospitals in Riyadh, during the period 2019–2022. Significant variables associated with csPCa cases were used to develop and internally validate a novel nomogram, utilizing the C index, and calibration curves. Decision curve analysis (DCA) was used to assess its clinical utility.ResultsProstate imaging reporting and data system (PI‐RADS), smaller prostate volume, and prostate‐specific antigen (PSA) > 10 ng/mL were significantly associated with the risk csPCa, respectively. The model developed by the nomogram showed an excellent accuracy for csPCa discrimination, as indicated by area under the curve (0.83), and calibration curves. DCA showed that our model was superior and surpassed all other models with a larger net benefit for various threshold probabilities. Based on our model, at a probability threshold of 30%, biopsying patients is the equivalent of a strategy that led to an absolute 5% reduction in the number of biopsies without missing any csPCa.ConclusionThe developed nomogram consisting of PI‐RAD, total PSA, and prostate volume showed a robust predictive capacity for csPCa before prostate biopsy that may be valuable for clinical judgment to prevent needless biopsy. Yet, the small percentage (5%) of yielded unnecessary biopsies that could be saved by using such a model, cast an important question on its merit and clinical applicability.

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Section: Discussionsupporting

confidence: 74%

Section: Nomograms Have Been Developed and Validated In Previousmentioning

confidence: 99%

Development and internal validation of a nomogram predicting significant prostate cancer: Is it clinically applicable in low prevalent prostate cancer countries? A multicenter study

Arafa,

Farhat,

Khan

et al. 2023

The Prostate

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“…We compared the performance of our nomogram with the current available nomograms in the literature. [10][11][12] The area under the ROC was modestly higher than the other tested nomograms. The current nomogram incorporates more clinical variables that are commonly used while counseling patient.…”

Section: Discussionmentioning

confidence: 70%

“…We compared the performance of our nomogram with the current available nomograms in the literature 10–12 . The area under the ROC was modestly higher than the other tested nomograms.…”

Section: Discussionmentioning

confidence: 99%

“…However, they were mostly hampered by the small number of patients, heterogenous patient populations, and others (Table S1). [10][11][12] In this context, we sought to identify clinical variables associated with CS prostate cancer and combine them with PI-RADS v2 scores to construct and validate a nomogram that improves the specificity of PI-RADS score, which provide individualized risk assessment, and improve patient counseling.…”

Section: Introductionmentioning

confidence: 99%

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Development and validation of nomogram to improve the specificity of multiparametric MRI for clinically significant prostate cancer

Shiekh,

Houenstein,

Ramahi

et al. 2023

Int J of Urology

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ObjectiveTo develop and validate a nomogram to improve the specificity of prostate imaging reporting and data system (PI‐RADS) on multiparametric magnetic resonance imaging (MRI) for clinically significant prostate cancer on targeted fusion biopsy.MethodsA retrospective review of patients who underwent fusion biopsy for PI‐RADS 3–5 lesions using UroNav and Artemis systems between 2016 and 2022 was performed. Patients were divided into those with CS disease on fusion biopsy (Gleason grade group ≥2) versus those without. Multivariable analysis was used to identify variables associated with CS disease. A 100‐point nomogram was constructed, and ROC curve was generated.Results1485 lesions (1032 patients) were identified, 510 (34%) were PI‐RADS 3, 586 (40%) were PI‐RADS 4, and 389 (26%) were PI‐RADS 5. Of these, 11% of PI‐RADS 3, 39% of PI‐RADS 4, and 61% of PI‐RADS 5 showed CS disease. CS disease was associated with older age (OR 1.04, 95% CI 1.02–1.06, p < 0.01), previous negative biopsy (OR 0.52, 95% CI 0.36–0.74, p < 0.01), presence of multiple PI‐RADS 3–5 lesions (OR 0.61, 95% CI 0.45–0.83, p < 0.01), peripheral zone location (OR 1.88, 95% CI 1.30–2.70, p < 0.01), PSA density (OR 1.48 per 0.1 unit, 95% CI 1.33–1.64, p < 0.01), PI‐RADS score 4 (OR 3.28, 95% CI 2.21–4.87, p < 0.01), and PI‐RADS score 5 (OR 7.65, 95% CI 4.93–11.85, p < 0.01). Area under ROC curve was 82% for nomogram compared to 75% for PI‐RADS score alone.ConclusionWe report a nomogram that combines PI‐RADS score with other clinical parameters. The nomogram outperforms PI‐RADS score for the detection of CS prostate cancer.

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Which men with non-malignant pathology at magnetic resonance imaging-targeted prostate biopsy and persistent PI-RADS 3-5 lesions should repeat biopsy?

Castellani

Pace²,

Cecchini³

et al. 2022

Urologic Oncology: Seminars and Original Investigations

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A magnetic resonance imaging-based nomogram for predicting clinically significant prostate cancer at radical prostatectomy

Cited by 3 publications

References 27 publications

Development and internal validation of a nomogram predicting significant prostate cancer: Is it clinically applicable in low prevalent prostate cancer countries? A multicenter study

Development and internal validation of a nomogram predicting significant prostate cancer: Is it clinically applicable in low prevalent prostate cancer countries? A multicenter study

Development and validation of nomogram to improve the specificity of multiparametric MRI for clinically significant prostate cancer

Which men with non-malignant pathology at magnetic resonance imaging-targeted prostate biopsy and persistent PI-RADS 3-5 lesions should repeat biopsy?

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