Literature DB >> 21444679

Tissue biomarkers for prognosis in pancreatic ductal adenocarcinoma: a systematic review and meta-analysis.

Nigel B Jamieson1, C Ross Carter, Colin J McKay, Karin A Oien.   

Abstract

PURPOSE: The management of pancreatic ductal adenocarcinoma (PDAC) continues to present a great challenge particularly with regard to prediction of outcome following pancreaticoduodenectomy. Molecular markers have been extensively investigated by numerous groups with the aim of enhancing prognostication; however, despite hundreds of studies that have sought to assess the potential prognostic value of molecular markers in predicting the clinical course following resection of PDAC, at this time, no molecular marker assay forms part of recommended clinical practice. EXPERIMENTAL
DESIGN: We conducted a systematic review and meta-analysis of the published literature for immunohistochemistry-based biomarkers of PDAC outcome. A dual search strategy was applied to the PubMed database on January 6, 2010, to identify cohort studies that reported associations between immunohistochemical biomarker expression and survival outcomes in PDAC, and conformed to the REMARK (REporting recommendations for tumor MARKer prognostic studies) criteria.
RESULTS: A total of 103 distinct proteins met all inclusion criteria. Promising markers that emerged for the prediction of overall survival included BAX (HR = 0.31, 95% CI: 0.71-0.56), Bcl-2 (HR = 0.41, 95% CI: 0.27-0.63), survivin (HR = 0.46, 95% CI: 0.29-0.73), Ki-67: (HR = 2.42, 95% CI: 1.87-3.14), COX-2 (HR = 1.39, 95% CI: 1.13-1.71), E-cadherin (HR = 1.80, 95% CI: 1.33-2.42), and S100 calcium-binding proteins, in particular S100A2 (HR = 3.23, 95% CI: 1.58-6.62).
CONCLUSIONS: We noted that that there was incomplete adherence to the REMARK guidelines with inadequate methodology reporting as well as failure to perform multivariate analysis. Addressing the persistent incomplete adoption of these criteria may eventually result in the incorporation of molecular marker assessment within PDAC management algorithms. ©2011 AACR.

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Year:  2011        PMID: 21444679     DOI: 10.1158/1078-0432.CCR-10-3284

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


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