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26 July 2019 : Clinical Research  

Specific Biomarkers of Prostate Cancer-Associated Ischemic Stroke: A Case-Control Study

Ya Chen1ABCDEF*, Qi-Xiong Qin1B, Chao Qin1E, Dao-Bin Cheng1F, Chun-Xia Huang1C, Yun-Fei Wei2D, Zhi-Jian Liang1AG

DOI: 10.12659/MSM.917970

Med Sci Monit 2019; 25:5536-5542

Abstract

BACKGROUND: Ischemic stroke in cancer patients is associated with poor prognosis. However, the specific biomarkers of cancer-associated ischemic stroke (CaIS) have not been well defined.

MATERIAL AND METHODS: A retrospective study was conducted on PCaIS patients. Clinical data and laboratory and imaging findings were collected. Multivariable logistic regression analysis was used to analyze the independent risk factors for PCaIS. A multiple model combining the independent risk factors of PCaIS was developed using the receiver operating characteristic (ROC) and area under the ROC curve (AUC).

RESULTS: A total of 83 PCaIS patients and 83 prostate cancer (PCa) patients were included. PCaIS patients had higher levels of D-dimer, neutrophil-to-lymphocyte ratio (NLR), and total prostate-specific antigen (T-PSA). In the multivariate analysis, D-dimer [OR=1.001, 95% CI: 1.00,1.00, P=0.002], NLR [OR=1.12, 95% CI: 1.04,1.22, P=0.005], and T-PSA [OR=6.275, 95% CI: 2.57,15.31, P<0.001] were independent risk factors of PCaIS. Additionally, the AUC of the multiple model of PCaIS was 0.815 (95% CI, 0.750-0.869), with sensitivity of 81.71% and specificity of 70.21%.

CONCLUSIONS: Elevated levels of D-dimer and T-PSA and increased NLR are independent risk factors of PCaIS. The multiple model of PCaIS can be a specific biomarker and is a reliable predictor of development of PCaIS.

Keywords: Biological Markers, Prostatic Neoplasms, Stroke, Aged, Aged, 80 and over, Biomarkers, Tumor, Brain Ischemia, Case-Control Studies, Lymphocytes, Middle Aged, Multivariate Analysis, Neutrophils, Prostate-Specific Antigen, ROC Curve, Retrospective Studies, Risk Factors, Sensitivity and Specificity

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750