Critical Appraisal of Leibovich 2018 and GRANT Models for Prediction of Cancer-Specific Survival in Non-Metastatic Chromophobe Renal Cell Carcinoma

Author:

Piccinelli Mattia Luca123ORCID,Morra Simone14,Tappero Stefano156ORCID,Cano Garcia Cristina17ORCID,Barletta Francesco18,Incesu Reha-Baris19,Scheipner Lukas110,Baudo Andrea111,Tian Zhe1,Luzzago Stefano23,Mistretta Francesco Alessandro23ORCID,Ferro Matteo2ORCID,Saad Fred1ORCID,Shariat Shahrokh F.12131415,Carmignani Luca1116,Ahyai Sascha10,Tilki Derya91718ORCID,Briganti Alberto8,Chun Felix K. H.7,Terrone Carlo56,Longo Nicola4,de Cobelli Ottavio23,Musi Gennaro23,Karakiewicz Pierre I.1

Affiliation:

1. Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montréal Health Center, Montréal, QC H2X 0A9, Canada

2. Department of Urology, IEO European Institute of Oncology, IRCCS, 20141 Milan, Italy

3. Department of Oncology and Haemato-Oncology, Università degli Studi di Milano, 20122 Milan, Italy

4. Department of Neurosciences, Science of Reproduction and Odontostomatology, University of Naples Federico II, 80131 Naples, Italy

5. Department of Urology, IRCCS Policlinico San Martino, 16132 Genova, Italy

6. Department of Surgical and Diagnostic Integrated Sciences (DISC), University of Genova, 16148 Genova, Italy

7. Department of Urology, University Hospital Frankfurt, Goethe University Frankfurt am Main, 39120 Frankfurt am Main, Germany

8. Division of Experimental Oncology, Unit of Urology, URI Urological Research Institute, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy

9. Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, 20246 Hamburg, Germany

10. Department of Urology, Medical University of Graz, 8036 Graz, Austria

11. Department of Urology, IRCCS Policlinico San Donato, 20097 Milan, Italy

12. Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, 1090 Vienna, Austria

13. Department of Urology, Weill Cornell Medical College, New York, NY 10065, USA

14. Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA

15. Hourani Center of Applied Scientific Research, Al-Ahliyya Amman University, Amman 19328, Jordan

16. Department of Urology, IRCCS Ospedale Galeazzi-Sant’Ambrogio, 20157 Milan, Italy

17. Department of Urology, University Hospital Hamburg-Eppendorf, 20246 Hamburg, Germany

18. Department of Urology, Koc University Hospital, 34010 Istanbul, Turkey

Abstract

Within the Surveillance, Epidemiology, and End Results database (2000–2019), we identified 5522 unilateral surgically treated non-metastatic chromophobe kidney cancer (chRCC) patients. This population was randomly divided into development vs. external validation cohorts. In the development cohort, the original Leibovich 2018 and GRANT categories were applied to predict 5- and 10-year cancer-specific survival (CSS). Subsequently, a novel multivariable nomogram was developed. Accuracy, calibration and decision curve analyses (DCA) tested the Cox regression-based nomogram as well as the Leibovich 2018 and GRANT risk categories in the external validation cohort. The accuracy of the Leibovich 2018 and GRANT models was 0.65 and 0.64 at ten years, respectively. The novel prognostic nomogram had an accuracy of 0.78 at ten years. All models exhibited good calibration. In DCA, Leibovich 2018 outperformed the novel nomogram within selected ranges of threshold probabilities at ten years. Conversely, the novel nomogram outperformed Leibovich 2018 for other values of threshold probabilities. In summary, Leibovich 2018 and GRANT risk categories exhibited borderline low accuracy in predicting CSS in North American non-metastatic chRCC patients. Conversely, the novel nomogram exhibited higher accuracy. However, in DCA, all examined models exhibited limitations within specific threshold probability intervals. In consequence, all three examined models provide individual predictions that might be suboptimal and be affected by limitations determined by the natural history of chRCC, where few deaths occur within ten years from surgery. Further investigations regarding established and novel predictors of CSS and relying on large sample sizes with longer follow-up are needed to better stratify CSS in chRCC.

Publisher

MDPI AG

Subject

Cancer Research,Oncology

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