Your browser doesn't support javascript.
loading
Development of a novel nomogram to identify the candidate to extended pelvic lymph node dissection in patients who underwent mpMRI and target biopsy only.
Fiori, Cristian; Checcucci, Enrico; Stura, Ilaria; Amparore, Daniele; De Cillis, Sabrina; Piana, Alberto; Granato, Stefano; Volpi, Gabriele; Sica, Michele; Piramide, Federico; Verri, Paolo; Manfredi, Matteo; De Luca, Stefano; Autorino, Riccardo; Migliaretti, Giuseppe; Porpiglia, Francesco.
Affiliation
  • Fiori C; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
  • Checcucci E; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy. checcu.e@hotmail.it.
  • Stura I; Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy. checcu.e@hotmail.it.
  • Amparore D; Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Turin, Italy.
  • De Cillis S; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
  • Piana A; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
  • Granato S; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
  • Volpi G; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
  • Sica M; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
  • Piramide F; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
  • Verri P; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
  • Manfredi M; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
  • De Luca S; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
  • Autorino R; Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy.
  • Migliaretti G; Division of Urology, VCU Health, Richmond, VA, USA.
  • Porpiglia F; Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Turin, Italy.
Prostate Cancer Prostatic Dis ; 26(2): 388-394, 2023 06.
Article in En | MEDLINE | ID: mdl-35750851
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Prostatic Neoplasms / Multiparametric Magnetic Resonance Imaging Type of study: Prognostic_studies Limits: Humans / Male Language: En Journal: Prostate Cancer Prostatic Dis Journal subject: ENDOCRINOLOGIA / NEOPLASIAS / UROLOGIA Year: 2023 Document type: Article Affiliation country: Italia

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Prostatic Neoplasms / Multiparametric Magnetic Resonance Imaging Type of study: Prognostic_studies Limits: Humans / Male Language: En Journal: Prostate Cancer Prostatic Dis Journal subject: ENDOCRINOLOGIA / NEOPLASIAS / UROLOGIA Year: 2023 Document type: Article Affiliation country: Italia