Abstract
Malignant renal tumors account for 2.5% of the total cancer incidence and 2% of the total cancer mortality in the US.’ Of them, renal cell carcinoma (RCC) is the most common. The estimated 5-year survival for patients with tumors confined to the kidney is 90–95%. Conversely, advanced RCC is associated with poor prognosis.’ Radiotherapy and chemotherapy are not effective and immunotherapy is currently the adjuvant therapy available. Since the natural history of RCC is unpredictable, it is important to define staging systems that may guide the therapeutic approach towards the disease and predict outcomes. Staging systems, at general should efficiently communicate key tumor characteristics, aid clinicians in the appropriate selection of therapeutic options for an individual patient, stratisfy patients’ risk of cancer progression or cancer death, and determine selection criteria for clinical trials. When a consensus regarding an accurate, universal staging system is possible, it allows outcome comparison between different demographic groups and therefore facilitates evaluation of treatment options and clinical research.
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Leibovici, D., Sella, A., Siegel, I.Y., Zisman, A. (2003). New Algorithms for the Staging of Kidney Cancer. In: Figlin, R.A. (eds) Kidney Cancer. Cancer Treatment and Research, vol 116. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0451-1_3
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DOI: https://doi.org/10.1007/978-1-4615-0451-1_3
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