Pooled Analysis of C-Reactive Protein Levels and Mortality in Prostate Cancer Patients

Publication Date

2015

Journal Title

Clin Genitourin Cancer

Abstract

This was a pooled analysis of studies on C-reactive protein (CRP) and prostate cancer mortality. Two hundred thirty-five patients were included. CRP was significantly associated with mortality; the best predictor cutoff was CRP < 12 mg/L. CRP is a routine assay that could be tested at diagnosis to improve prognostication of prostate cancer patients. Introduction: Previous studies have reported that higher C-reactive protein (CRP) levels are significantly associated with worse outcome in prostate cancer patients. The size of each individual study was not large enough to allow sufficient statistical power to draw conclusions. We conducted a pooled analysis of individual data of published studies to evaluate the association between increased CRP level and risk of death in prostate cancer, and to find the best CRP cutoff that could predict mortality. Materials and Methods: Original research studies on prostate cancer survival and CRP levels were identified (n = 6). Corresponding authors were contacted and invited to share individual data. Two data sets were received (235 patients). The combined hazard ratio (HR) was calculated and adjusted for age, prostate-specific antigen, hemoglobin, and alkaline phosphatase. The best cutoff of CRP was explored using X-title software version 3.6.1. Results: High CRP level was statistically significantly associated with mortality (meta-HR, 1.83 [95% confidence interval (CI), 1.51-2.21]), without evidence of heterogeneity among studies. At pooled analysis, adjusted pooled HR for CRP < 5 versus > 5 mg/L was 1.44 (95% CI, 1.02-20.4). The best CRP cutoff was 12 mg/ L: the adjusted HRpooled for CRP < 12 versus >= 12 mg/L was 1.53 (95% CI, 1.01-2.32). Conclusion: Increased CRP levels are associated with overall survival in prostate cancer patients. Because CRP is an affordable and readily available assay, it might hold promise in improving prognostication and potentially to predict the activity of specific therapeutic agents.

Volume Number

13

Issue Number

4

Pages

E217-E221

Document Type

Article

EPub Date

2015/03/05

Status

Faculty

Facility

School of Medicine

Primary Department

Occupational Medicine, Epidemiology and Prevention

PMID

25735198

DOI

10.1016/j.clgc.2015.01.011

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