Predicting cancer outcomes after resection of high-risk RCC
Author:
Publisher
Springer Science and Business Media LLC
Subject
Urology
Link
https://www.nature.com/articles/s41585-022-00568-3.pdf
Reference9 articles.
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).
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).
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).
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).
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).
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1. Predicting recurrence and survival in patients with non-metastatic renal-cell carcinoma after nephrectomy: a prospective population-based study with multicenter validation;International Journal of Surgery;2023-11-27
2. Application of Machine Learning Models to Predict Recurrence After Surgical Resection of Nonmetastatic Renal Cell Carcinoma;European Urology Oncology;2022-08
3. The multispeciality approach to the management of localised kidney cancer;The Lancet;2022-08
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