Published June 4, 2026 | Version 1.0.0
Software Open

Analysis code and frozen prediction model: pre-operative prediction of clinically significant ISUP grade upgrading (development and external validation)

Authors/Creators

  • 1. Department of General, Oncological and Laparoscopic Urology, John Paul II Provincial Hospital, Bełchatów, Poland
  • 2. Department of Urology, Brigham and Women's Hospital, Boston, MA, USA
  • 3. Pomeranian Medical University, Szczecin, Poland
  • 4. Department of Urology, Medical University of Gdańsk, Gdańsk, Poland
  • 5. Department of Urology, Institute of Medical Sciences, Faculty of Medicine, Collegium Medicum, Cardinal Stefan Wyszyński University in Warsaw, Warsaw, Poland; Department of Urology and Urological Oncology, Multidisciplinary Hospital in Warsaw-Międzylesie, Warsaw, Poland
  • 6. Department of Biostatistics and Translational Medicine, Medical University of Lodz, Łódź, Poland; Dana-Farber Cancer Institute, Boston, MA, USA
  • 7. Department of Urology, Brigham and Women's Hospital, Boston, MA, USA; Department of Biostatistics and Translational Medicine, Medical University of Lodz, Łódź, Poland; Dana-Farber Cancer Institute, Boston, MA, USA

Description

Analysis code, the frozen pre-operative logistic-regression model (coefficients and PSA restricted-cubic-spline knots), and aggregate result files underlying a study developing and externally validating a model for clinically significant ISUP grade upgrading (radical-prostatectomy ISUP grade group >= 3 among favorable-risk biopsy ISUP grade group 1-2 prostate cancer). The model was developed in a Polish cohort and externally validated in a de-identified United States cohort. No patient-level data are included; individual-participant data are under controlled access. The model is shared for transparency and reproducibility and is not externally established or deployment-ready.

Notes

Corresponding authors: Mateusz Jobczyk and Konrad Stawiski. This deposit contains analysis code, the frozen prediction model, and aggregate results only; individual-participant data are under controlled access (see README.md). The manuscript DOI will be added as a related identifier on publication.

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analysis-code-and-model_v1.0.0.zip

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