MP44-01 A PROGNOSTIC MODEL FOR OVERALL SURVIVAL IN PATIENTS WITH METASTATIC CLEAR CELL RENAL CARCINOMA: RESULTS FROM CALGB 90206 (ALLIANCE)

Abstract

You have accessJournal of UrologyKidney Cancer: Evaluation and Staging II1 Apr 2015MP44-01 A PROGNOSTIC MODEL FOR OVERALL SURVIVAL IN PATIENTS WITH METASTATIC CLEAR CELL RENAL CARCINOMA: RESULTS FROM CALGB 90206 (ALLIANCE) Hyung Kim, Susan Halabi, Ping Li, Greg Mayhew, Jeff Simko, Andrew Nixon, Eric Small, Brian Rini, Michael Morris, Mary-Ellen Taplin, and Daniel George Hyung KimHyung Kim More articles by this author , Susan HalabiSusan Halabi More articles by this author , Ping LiPing Li More articles by this author , Greg MayhewGreg Mayhew More articles by this author , Jeff SimkoJeff Simko More articles by this author , Andrew NixonAndrew Nixon More articles by this author , Eric SmallEric Small More articles by this author , Brian RiniBrian Rini More articles by this author , Michael MorrisMichael Morris More articles by this author , Mary-Ellen TaplinMary-Ellen Taplin More articles by this author , and Daniel GeorgeDaniel George More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.1543AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Prognosis associated with renal cell carcinoma (RCC) can vary widely. Gene expressions in clear cell RCC were used to develop a multi-marker prognostic model of overall survival (OS). METHODS This study used pretreatment nephrectomy specimens collected as part of CALGB 90206, which was a phase III registration trial that showed no OS benefit for patients with clear cell, metastatic or unresectable RCC initially treated with the combination of interferon-α (INF) and bevacizumab vs INF alone. H&E slides of tumors were centrally reviewed and formalin-fixed, paraffin-embedded tumors were macrodissected prior to RNA extraction. Candidate prognostic genes were identified from a literature search. Expression levels were determined using the OpenArray® high-throughput, microfluidics platform for TaqMan® RT-qPCR. Gene expressions were normalized using 6 previously validated reference genes, which were measured in quadruplicate. The samples were randomly divided at 2:1 ratio into training (n=221) and testing (n=103) sets. In the parent clinical trial, randomization was stratified by the number of adverse clinical risk factors (ACRF, Motzer et al, JCO, 20:289-296, 2002). The proportional hazards model was used to identify genes predicting OS. Using the training set, the model with the highest time dependent area under the curve (AUC) was locked. The estimated coefficients from the training set were used to compute a risk score (RS) for each patient in the testing set. RESULTS Patient characteristics were similar between cases with and without expression profiles. In the training set, multiple model testing with 424 candidate genes identified a prognostic signature containing 8 genes plus ACRF. In the test set, this model had an AUC of 0.723 and was predictive of OS (p<0.001) with median OS= 33.5 (95% CI 20.3-51.9) and 14.9 months (95% CI 12.4-26.3) in the low and high risk groups, respectively. The AUC for a prognostic model containing only the 8 genes was 0.688. The AUC for the ACRF alone was 0.611. Additional primary RCCs from patients with metastatic RCC (n=12) were sampled in multiple sites and standard deviations of gene expressions within a tumor were used as a measure of heterogeneity. All 8 genes in the final prognostic model had minimal heterogeneity. CONCLUSIONS A molecular prognostic signature based on 8 genes was developed using tissue from a phase III trial and predicts OS in patients with metastatic clear cell RCC. This model should be considered for external validation and qualification for use with nonmetastatic RCC. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e526 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Hyung Kim More articles by this author Susan Halabi More articles by this author Ping Li More articles by this author Greg Mayhew More articles by this author Jeff Simko More articles by this author Andrew Nixon More articles by this author Eric Small More articles by this author Brian Rini More articles by this author Michael Morris More articles by this author Mary-Ellen Taplin More articles by this author Daniel George More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...