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Development of a novel nomogram to identify the candidate to extended pelvic lymph node dissection in patients who underwent mpMRI and target biopsy only



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.


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.


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.


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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Fig. 1: Evaluation of modelʼs performance.
Fig. 2

Data availability

The data that support the findings of this study are available from the corresponding author, EC, upon reasonable request


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Authors and Affiliations



CF: Conceptualization, Methodology, Review. EC: Data Analysis, Manuscript Writing. IS: Methodology, Statistical Analysis. DA: Manuscript writing, Data Analysis. SDC: Data Collection. AP: Data Collection. SG: Data Collection. GV: Data Collection, Language review. MS: Data Collection. FP: Data Collection. PV: Data Collection, Language review. MM: Review, Supervision. SDL: Supervision. RA: Review. GM: Methodology, Statistical Analysis. FP: Conceptualization, Methodology, Review

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Correspondence to Enrico Checcucci.

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Fiori, C., Checcucci, E., Stura, I. et al. 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).

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