Predicting disease progression after nephrectomy for localized renal cell carcinoma: The utility of prognostic models and molecular biomarkers

Paul L. Crispen, Stephen A. Boorjian, Christine M. Lohse, Bradley C. Leibovich, Eugene D. Kwon

Research output: Contribution to journalReview article

61 Scopus citations

Abstract

Disease progression after nephrectomy for pathologically localized renal cell carcinoma (RCC) is associated with a significant mortality rate, given the limited efficacy of available treatment regimens for metastatic disease. As such, several adjuvant trials have been designed to treat patients at particularly high risk for postsurgical RCC progression. Several different prognostic models designed to identify patients at high risk of disease progression are available. Although these available predictive models provide a reasonable assessment of patients' risks of disease progression, the accuracy of these models may further be improved via the incorporation of molecular prognostic biomarkers. Although numerous candidate molecules have been described, few have been specifically assessed for the association with disease progression after nephrectomy. IMP-3, CXCR3, p53, Survivin, cIAP1, B7-H1, and B7-H4 have all been associated with disease progression after nephrectomy. The incorporation of 1 or several of these biomarkers may increase the accuracy of currently available prognostic models and thereby facilitate the appropriate use of adjuvant therapies aimed at preventing future disease progression. As such, the authors review the current prognostic tools for predicting disease progression for localized RCC, and detail studies to date that have evaluated various biomarkers in this setting.

Original languageEnglish (US)
Pages (from-to)450-460
Number of pages11
JournalCancer
Volume113
Issue number3
DOIs
StatePublished - Aug 1 2008

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Keywords

  • Adjuvant trials
  • Disease progression
  • Molecular biomarkers
  • Prognosis
  • Renal cell carcinoma

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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