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Related Experiment Videos

External validation of the preoperative risk evaluation for partial nephrectomy (PREP) score.

Jacob O'Hara1, Kennedy Okhawere2, Nicolas A Soputro3

  • 1Department of Urology Hackensack University Medical Center Hackensack New Jersey USA.

BJUI Compass
|July 8, 2026
PubMed
Summary

The preoperative risk evaluation for partial nephrectomy (PREP) score showed poor performance in predicting major complications for robot-assisted partial nephrectomy (RAPN) patients. External validation in a large cohort suggests the PREP score needs coefficient re-estimation for better accuracy.

Keywords:
complicationsmultiportpartial nephrectomyrobotic surgerysingle port

Related Experiment Videos

Area of Science:

  • Urology
  • Surgical Oncology
  • Robotic Surgery

Background:

  • The preoperative risk evaluation for partial nephrectomy (PREP) score was developed to predict major complications after partial nephrectomy.
  • External validation is crucial to assess the generalizability of risk prediction models in diverse patient populations and surgical settings.
  • Robot-assisted partial nephrectomy (RAPN) is increasingly utilized, necessitating validated risk assessment tools specific to this approach.

Purpose of the Study:

  • To externally validate the PREP score's performance in a large, multi-institutional cohort of patients undergoing robot-assisted partial nephrectomy (RAPN).
  • To assess the discrimination and calibration of the PREP score in predicting major complications (Clavien-Dindo grade III-V) within 30 days post-RAPN.
  • To identify specific patient characteristics associated with major complications in the RAPN cohort.

Main Methods:

  • Retrospective analysis of 8,615 patients who underwent RAPN from the United States Kidney Cancer Data Network (US-KIDNET).
  • Evaluation of PREP score's discrimination using the area under the receiver operating characteristic curve (AUC).
  • Assessment of calibration using the Hosmer-Lemeshow (HL) goodness-of-fit test and logistic regression for individual component associations.

Main Results:

  • The PREP score demonstrated poor discrimination (AUC = 0.547) and poor calibration (HL χ² = 150.2, p < 0.001) in the RAPN cohort.
  • Performance was consistent across different robotic platforms and surgical approaches.
  • Coronary artery disease, chronic obstructive pulmonary disease, chronic kidney disease, and obesity were independently associated with increased risk of major complications.

Conclusions:

  • The PREP score, as currently formulated, does not perform well for predicting major complications in a large, multi-institutional cohort undergoing RAPN.
  • Simple recalibration may be insufficient; coefficient re-estimation of the PREP score might be necessary for improved accuracy in robotic surgery settings.
  • Specific comorbidities like CAD, COPD, CKD, and obesity are significant predictors of complications in RAPN patients.