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Pre-operative prediction of extracapsular extension of prostate cancer: first external validation of the PRECE model on an independent dataset

  • Urology - Original Paper
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Abstract

Introduction

The PRECE is a model predicting the risk of extracapsular extension (ECE) of prostate cancer: it has been developed on more than 6000 patients who underwent robotic radical prostatectomy (RARP) at the Global Robotic Institute, FL, USA. Up to now, it is the single tool predicting either the side and the amount of ECE. The model has a free user-friendly interface and is made up from simple and available covariates, namely age, PSA, cT, GS and percent of positive core, the latter topographically distributed within the prostate gland. Despite the successful performance at internal validation, the model is still lacking an external validation (EV). The aim of the paper is to externally validate the PRECE model on an Italian cohort of patients elected to RARP.

Methods

269 prostatic lobes from 141 patients represented the validation dataset. The EV was performed with the receiver operating characteristics (ROC) curves and calibration, to address the ability of PRECE to discriminate between patients with or without ECE.

Results

Overall, an ECE was found in 91 out of the 269 prostatic lobes (34%). Twenty-five patients out of pT3 had a bilateral ECE. The ROC curve showed an AUC of 0.80 (95% CI 0.74–0.85). Sensitivity and specificity were 77% and 69%, respectively. The model showed an acceptable calibration with tendency towards overestimation.

Conclusions

From the current EV, the PRECE displays a good predictive performance to discriminate between cases with and without ECE; despite preliminary, outcomes may support the generalizability of the model in dataset other than the development one.

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Authors and Affiliations

  1. ASST Santi Paolo e Carlo, Milan, Italy

    Maria Chiara Sighinolfi, Simone Assumma, Tommaso Calcagnile, Stefano Terzoni & Bernardo Rocco

  2. Azienda Ospedaliero Universitaria di Modena, Modena, Italy

    Simone Assumma, Alessandra Cassani, Luca Sarchi, Tommaso Calcagnile & Salvatore Micali

  3. Data Methods and Systems Statistical Laboratory, University of Brescia, Brescia, Italy

    Marco Sandri

  4. Global Robotics Institute, Florida, USA

    Jonathan Noel, M. Covas Moschovas, Bhat Seetharam & Vipul Patel

  5. ASST Lariana, Menaggio, Italy

    Giorgio Bozzini

  6. University of Milan, Milan, Italy

    Bernardo Rocco

Authors
  1. Maria Chiara Sighinolfi
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  2. Simone Assumma
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Contributions

SMC: project development and manuscript writing. AS: data collection. CA: data collection. SL: data collection. CT: data collection. SM: data analysis. MS: manuscript editing. TS: manuscript editing. NJ: manuscript editing. CMM: manuscript editing. SB: manuscript editing. PV: project development. RB: project development and manuscript editing.

Corresponding author

Correspondence to Maria Chiara Sighinolfi.

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The authors disclose any potential conflict of interest.

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Registry and the Registration No. of the study/trial: N/A.

Ethical approval

The retrospective assessment of factors predicting prostate cancer aggressiveness (including radiological, pathological and laboratories variables) was approved by the local Ethic Committee (982/2018/OSS/AOUMO).

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N/A.

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Animal study: N/A.

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Sighinolfi, M.C., Assumma, S., Cassani, A. et al. Pre-operative prediction of extracapsular extension of prostate cancer: first external validation of the PRECE model on an independent dataset. Int Urol Nephrol 55, 93–97 (2023). https://doi.org/10.1007/s11255-022-03365-4

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