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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

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

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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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Author notes

  1. These authors contributed equally: Cristian Fiori, Enrico Checcucci.

  2. These authors jointly supervised this work: Giuseppe Migliaretti, Francesco Porpiglia.

Authors and Affiliations

  1. Division of Urology, Department Of Oncology, School of Medicine, University of Turin, San Luigi Hospital, Orbassano, Turin, Italy

    Cristian Fiori, Enrico Checcucci, Daniele Amparore, Sabrina De Cillis, Alberto Piana, Stefano Granato, Gabriele Volpi, Michele Sica, Federico Piramide, Paolo Verri, Matteo Manfredi, Stefano De Luca & Francesco Porpiglia

  2. Department of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy

    Enrico Checcucci

  3. Department of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Turin, Italy

    Ilaria Stura & Giuseppe Migliaretti

  4. Division of Urology, VCU Health, Richmond, VA, USA

    Riccardo Autorino

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Contributions

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 26, 388–394 (2023). https://doi.org/10.1038/s41391-022-00565-y

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