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External validation of nomograms including MRI features for the prediction of side-specific extraprostatic extension

Abstract

Background

Prediction of side-specific extraprostatic extension (EPE) is crucial in selecting patients for nerve-sparing radical prostatectomy (RP). Multiple nomograms, which include magnetic resonance imaging (MRI) information, are available predict side-specific EPE. It is crucial that the accuracy of these nomograms is assessed with external validation to ensure they can be used in clinical practice to support medical decision-making.

Methods

Data of prostate cancer (PCa) patients that underwent robot-assisted RP (RARP) from 2017 to 2021 at four European tertiary referral centers were collected retrospectively. Four previously developed nomograms for the prediction of side-specific EPE were identified and externally validated. Discrimination (area under the curve [AUC]), calibration and net benefit of four nomograms were assessed. To assess the strongest predictor among the MRI features included in all nomograms, we evaluated their association with side-specific EPE using multivariate regression analysis and Akaike Information Criterion (AIC).

Results

This study involved 773 patients with a total of 1546 prostate lobes. EPE was found in 338 (22%) lobes. The AUCs of the models predicting EPE ranged from 72.2% (95% CI 69.1–72.3%) (Wibmer) to 75.5% (95% CI 72.5–78.5%) (Nyarangi-Dix). The nomogram with the highest AUC varied across the cohorts. The Soeterik, Nyarangi-Dix, and Martini nomograms demonstrated fair to good calibration for clinically most relevant thresholds between 5 and 30%. In contrast, the Wibmer nomogram showed substantial overestimation of EPE risk for thresholds above 25%. The Nyarangi-Dix nomogram demonstrated a higher net benefit for risk thresholds between 20 and 30% when compared to the other three nomograms. Of all MRI features, the European Society of Urogenital Radiology score and tumor capsule contact length showed the highest AUCs and lowest AIC.

Conclusion

The Nyarangi-Dix, Martini and Soeterik nomograms resulted in accurate EPE prediction and are therefore suitable to support medical decision-making.

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Fig. 1: Calibration slope for all four models.
Fig. 2: Decision–curve analysis for the four models.

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Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Authors and Affiliations

Authors

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Contributions

Conception and design: TFWS. Acquistion of data: JGH, EJRJvan derH, PR, FZ, CK, SS, FDM, GN, GLB, FS, NvonO, NP, PATB, LW, HHEvM, RCNvandenB, GG, TFWS. Statistical analysis: JGH. Analysis and interpretation of data: JGH. Drafting of the manuscript: TFWS, JGH. Critical revision of the manuscript for important intellectual content: JGH, EJRJvanderH, PR, FZ, CK, SS, FDM, GN, GLB, FS, NvonO, NP, PATB, LW, JPAVB, HHEvanM, RCNvandenB, GG, TFWS. Supervision: TFWSoeterik.

Corresponding author

Correspondence to T. F. W. Soeterik.

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The authors declare no competing interests.

Ethics

The Medical research Ethics Committee United (METC-U) registered the study protocol under W18.055 and concluded that the study protocol was not subjected to the Human Subject Act. The METC-U concluded that informed consent was not needed.

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Heetman, J.G., van der Hoeven, E.J.R.J., Rajwa, P. et al. External validation of nomograms including MRI features for the prediction of side-specific extraprostatic extension. Prostate Cancer Prostatic Dis (2023). https://doi.org/10.1038/s41391-023-00738-3

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  • DOI: https://doi.org/10.1038/s41391-023-00738-3

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