Validation of Serum Amyloid alpha as an Independent Biomarker for Progression-Free and Overall Survival in Metastatic Renal Cell Cancer Patients

Joost S. Vermaat, Frank L. Gerritse, Astrid A. van der Veldt, Wijnand M. Roessingh, Tatjana M. Niers, Sjoukje F. Oosting, Stefan Sleijfer, Jeanine M. Roodhart, Jos H. Beijnen, Jan H. Schellens, Jourik A. Gietema, Epie Boven, Dick J. Richel, John B. Haanen, Emile E. Voest

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17 Citations (Scopus)


Background: We recently identified apolipoprotein A2 (ApoA2) and serum amyloid a (SAA) as independent prognosticators in metastatic renal cell carcinoma (mRCC) patients, thereby improving the accuracy of the Memorial-Sloan Kettering Cancer Center (MSKCC) model. Objective: Validate these results prospectively in a separate cohort of mRCC patients treated with tyrosine kinase inhibitors (TKIs). Design, setting, and participants: For training we used 114 interferon-treated mRCC patients (inclusion 2001-2006). For validation we studied 151 TKI-treated mRCC patients (inclusion 2003-2009). Measurements: Using Cox proportional hazards regression analysis, SAA and ApoA2 were associated with progression-free survival (PFS) and overall survival (OS). In 72 TKI-treated patients, SAA levels were analyzed longitudinally as a potential early marker for treatment effect. Results and limitations: Baseline ApoA2 and SAA levels significantly predicted PFS and OS in the training and validation cohorts. Multivariate analysis identified SAA in both separate patient sets as a robust and independent prognosticator for PFS and OS. In contrast to our previous findings, ApoA2 interacted with SAA in the validation cohort and did not contribute to a better predictive accuracy than SAA alone and was therefore excluded from further analysis. According to the tertiles of SAA levels, patients were categorized in three risk groups, demonstrating accurate risk prognostication. SAA as a single biomarker showed equal prognostic accuracy when compared with the multifactorial MSKCC risk mode. Using receiver operating characteristic analysis, SAA levels >71 ng/ml were designated as the optimal cut-off value in the training cohort, which was confirmed for its significant sensitivity and specificity in the validation cohort. Applying SAA >71 ng/ml as an additional risk factor significantly improved the predictive accuracy of the MSKCC model in both independent cohorts. Changes in SAA levels after 6-8 wk of TKI treatment had no value in predicting treatment outcome. Conclusions: SAA but not ApoA2 was shown to be a robust and independent prognosticator for PFS and OS in mRCC patients. When incorporated in the MSKCC model, SAA showed additional prognostic value for patient management. (C) 2012 European Association of Urology. Published by Elsevier B. V. All rights reserved
Original languageEnglish
Pages (from-to)685-695
JournalEuropean Urology
Issue number4
Publication statusPublished - 2012

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