Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • News & Views
  • Published:

KIDNEY CANCER

Predicting cancer outcomes after resection of high-risk RCC

Prognostic models are crucial for optimal management of patients with renal cell carcinoma (RCC) after surgery. Multiple clinico-pathological models to predict cancer outcomes in these patients exist and seem to have reached their performance ceiling. Future research needs to identify new prognostic markers and to consider when and how prognostic models for RCC are implemented into practice.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

References

  1. Kratzer, T. B. et al. Progress against cancer mortality 50 years after passage of the National Cancer Act. JAMA Oncol. https://doi.org/10.1001/jamaoncol.2021.5668 (2021).

    Article  Google Scholar 

  2. Marconi, L. et al. Prevalence, disease-free, and overall survival of contemporary patients with renal cell carcinoma eligible for adjuvant checkpoint inhibitor trials. Clin. Genitourin. Cancer 19, e92–e99 (2021).

    Article  Google Scholar 

  3. Klatte, T., Rossi, S. H. & Stewart, G. D. Prognostic factors and prognostic models for renal cell carcinoma: a literature review. World J. Urol. 36, 1943–1952 (2018).

    Article  Google Scholar 

  4. Usher-Smith, J. A. et al. Risk models for recurrence and survival after kidney cancer: a systematic review. BJU Int. https://doi.org/10.1111/bju.15673 (2021).

    Article  PubMed  Google Scholar 

  5. Correa, A. F. et al. Predicting disease recurrence, early progression, and overall survival following surgical resection for high-risk localized and locally advanced renal cell carcinoma. Eur. Urol. 80, 20–31 (2021).

    Article  Google Scholar 

  6. Correa, A. F. et al. Predicting renal cancer recurrence: defining limitations of existing prognostic models with prospective trial-based validation. J. Clin. Oncol. 37, 2062–2071 (2019).

    Article  CAS  Google Scholar 

  7. Khene, Z.-E. et al. External validation of the ASSURE model for predicting oncological outcomes after resection of high-risk renal cell carcinoma (RESCUE Study: UroCCR 88). Eur. Urol. Open Sci. 33, 89–93 (2021).

    Article  Google Scholar 

  8. Thompson, R. H. et al. Dynamic outcome prediction in patients with clear cell renal cell carcinoma treated with radical nephrectomy: the D-SSIGN score. J. Urol. 177, 477–480 (2007).

    Article  Google Scholar 

  9. Vasudev, N. S. et al. UK multicenter prospective evaluation of the Leibovich score in localized renal cell carcinoma: performance has altered over time. Urology 136, 162–168 (2020).

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Grant D. Stewart.

Ethics declarations

Competing interests

G.D.S. declares educational grants from Pfizer, AstraZeneca and Intuitive Surgical; consultancy fees from Pfizer, Merck, EUSA Pharma and CMR Surgical; travel expenses from Pfizer; and speaker fees from Pfizer. J.A.U.-S. declares no competing interests.

Additional information

Related links

Predict Prostate: https://prostate.predict.nhs.uk/

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Usher-Smith, J.A., Stewart, G.D. Predicting cancer outcomes after resection of high-risk RCC. Nat Rev Urol 19, 257–258 (2022). https://doi.org/10.1038/s41585-022-00568-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41585-022-00568-3

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer