2004
DOI: 10.1200/jco.2004.09.104
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Use of the University of California Los Angeles Integrated Staging System to Predict Survival in Renal Cell Carcinoma: An International Multicenter Study

Abstract: This study defines the general applicability of the UISS for predicting survival in patients with RCC. The UISS is an accurate predictor of survival for patients with localized RCC applicable to external databases. Although the UISS may be useful for patients with metastatic RCC, it may be less accurate in this subset of patients due to the heterogeneity of patients and treatments.

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Cited by 362 publications
(182 citation statements)
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“…Despite validation, none of the proposed models or nomograms is 100% accurate, with C-indices ranging from 74% to 82.2% for assessment of recurrence and from 68% to 89% for assessment of cancer-specific mortality [76]. A commonly used model is the UISS integrated staging system using TNM stage, Eastern Cooperative Oncology Group PS, and nuclear grade [46,77]. The SSIGN score adds necrosis and tumour size and has been modified by Leibovich [44,45].…”
Section: Local Therapy Of Metastases In Rccmentioning
confidence: 99%
“…Despite validation, none of the proposed models or nomograms is 100% accurate, with C-indices ranging from 74% to 82.2% for assessment of recurrence and from 68% to 89% for assessment of cancer-specific mortality [76]. A commonly used model is the UISS integrated staging system using TNM stage, Eastern Cooperative Oncology Group PS, and nuclear grade [46,77]. The SSIGN score adds necrosis and tumour size and has been modified by Leibovich [44,45].…”
Section: Local Therapy Of Metastases In Rccmentioning
confidence: 99%
“…However, the prognostic information provided by RCC subtype is lost when stratified to tumour stage (LE 3) [43]. For localised RCC, several risk scores and nomograms can be used, including the Stage, Size, Grade, and Necrosis Score (SSIGN) [44], a modified version of the SSIGN score (Leibovich score) [45], the University of California Los Angeles Integrated Staging System (UISS) [46], and Karakiewicz's nomogram (LE 3) [47]; Section 3.7 provides further details. Clinical factors include patient PS, localised symptoms, cachexia, anaemia, elevated neutrophil and platelet counts, and other laboratory parameters, and are predominantly used in prognostic risk models in mRCC (LE 3) [48,49].…”
Section: Prognostic Factorsmentioning
confidence: 99%
“…Post-operative predictive models including the MSKCC post-operative prognostic nomogram, the Mayo clinic SSIGN score and UCLA UISS score were created using clinical stage, tumor histology, pathologic tumor size, pathologic stage and grade, pathologic necrosis, ECOG performance score and symptomatic presentation to predict the freedom from disease recurrence or overall survival after definitive therapy. [8][9][10][11][12][13] Since the various post-operative predictive tools are based on pathologic variables, their utility in the pre-operative setting is limited. A pre-operative tool that predicts the likelihood of metastatic disease following definitive surgical therapy would be useful to risk-stratify patients prior to surgery.…”
Section: Introductionmentioning
confidence: 99%