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Fiori C, Checcucci E, Stura I, Amparore D, De Cillis S, Piana A, Granato S, Volpi G, Sica M, Piramide F, Verri P, Manfredi M, De Luca S, Autorino R, Migliaretti G, Porpiglia F. Development of a novel nomogram to identify the candidate to extended pelvic lymph node dissection in patients who underwent mpMRI and target biopsy only. Prostate Cancer Prostatic Dis 2022:10.1038/s41391-022-00565-y. [PMID: 35750851 DOI: 10.1038/s41391-022-00565-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/16/2022] [Accepted: 06/10/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Nowadays a tool able to predict the risk of lymph-node invasion (LNI) in patients underwent target biopsy (TB) only before radical prostatectomy (RP) is still lacking. Our aim is to develop a model based on mp-MRI and target biopsy (TB) alone able to predict the risk of LNI. METHODS We retrospectively extracted data of patients with preoperative positive mp-MRI and TB only who underwent RARP with ePLND from April 2014 to March 2020. A logistic regression model was performed to evaluate the impact of pre- and intra-operative factors on the risk of LNI. Model discrimination was assessed using an area under (AUC) the ROC curve. A nomogram, and its calibration plot, to predict the risk of LNI were generated based on the logistic model. A validation of the model was done using a similar cohort. RESULTS 461 patients were included, of which 52 (11.27) had LNI. After logistic regression analysis and multivariable model DRE, PI-RADS, seminal vesicle invasion, PSA and worst GS at I and II target lesions were significant predictors of LNI. The AUC was 0.74 [0.67-0.81] 95% CI. The calibration plot shows that our model is very close to the ideal one which is in the 95% CI. After the creation of a visual nomogram, the cut-off to discriminate between the risk or not of LNI was set with Youden index at 60 points that correspond to a risk of LNI of 7%. The model applied on a similar cohort shown a LH+ of 2.58 [2.17-2.98] 95% CI. CONCLUSIONS Our nomogram for patients undergoing MRI-TB only takes into account clinical stage, SVI at MRI, biopsy Gleason pattern and PSA and it is able to identify patients with risk of LNI when a score higher than 7% is achieved.
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Affiliation(s)
- Cristian Fiori
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Enrico Checcucci
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy. .,Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy.
| | - Ilaria Stura
- Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Turin, Italy
| | - Daniele Amparore
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Sabrina De Cillis
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Alberto Piana
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Stefano Granato
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Gabriele Volpi
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Michele Sica
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Federico Piramide
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Paolo Verri
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Matteo Manfredi
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | - Stefano De Luca
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
| | | | - Giuseppe Migliaretti
- Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Turin, Italy
| | - Francesco Porpiglia
- Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy
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