Comparative Study
Journal Article
Add like
Add dislike
Add to saved papers

Integrated staging systems for conventional renal cell carcinoma: a comparison of two prognostic models.

OBJECTIVE: The objective of the current study was to compare, in a single center experience, the discriminating accuracy of two prognostic models to predict the outcome of patients surgically treated for conventional renal cell carcinoma (RCC).

PATIENTS AND METHODS: We retrospectively evaluated the clinical and pathological data of 100 patients surgically treated for RCC between 1998-2008 at our institution. For each patient, prognostic scores were calculated according to two models: the University of California Los Angeles integrated staging system (UISS) and the Stage, Size, Grade, and Necrosis (SSIGN) developed at the Mayo Clinic. The prognostic predictive ability of models was evaluated using receiver operating characteristic (ROC) curves.

RESULTS: The median follow-up was 62 months (range 12-120). All clinical and pathological features that compound the algorithms were significantly associated with death from RCC in univariate and multivariate setting. The 5-year cancer-specific survival (CSS) according to the SSIGN score were 95% in the '0-2' category, 88% in '3-4', 60% in '5-6', 37% in '7-9' and 0% in the '> or = 10' group (long-rank p value < 0.001); according to the UISS the 5 yr CSS probabilities in non-metastatic patients were 100% in low, 80% in intermediate and 54% in high-risk groups; in metastatic patients, the respectively CSS were 40% in low and 25% in high-risk groups (long-rank p value < 0.001). The area under the ROC curve was 0.815 for the SSIGN score and 0.843 for the UISS (p = 0.632).

CONCLUSION: In our series the SSIGN and UISS discriminated well, without relevant differences. Currently both algorithms represent usefuls clinical tools that allow risk assessment after surgical treatment of RCC. We encourage the uro-oncologist to begin to routinely rely on them in real-life practice.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app