首页> 外文期刊>Anticancer Research: International Journal of Cancer Research and Treatment >Serum sialic acid and prostate-specific antigen in differential diagnosis of benign prostate hyperplasia and prostate cancer.
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Serum sialic acid and prostate-specific antigen in differential diagnosis of benign prostate hyperplasia and prostate cancer.

机译:血清唾液酸和前列腺特异性抗原在良性前列腺增生和前列腺癌的鉴别诊断中。

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摘要

In order to improve the diagnostic accuracy of the serum total and free prostate-specific antigen (PSA) in differential diagnosis between benign prostate hyperplasia (BPH) and prostate cancer, the serum total sialic acid (TSA) was measured and logistic regression (LR) models were built. Significantly higher serum PSA (p<0.001) concentrations were observed in patients with prostate cancer compared to control subjects, but no statistically significant differences were found in serum TSA concentrations between these groups. Serum PSA reliably discriminated patients with prostate cancer from control subjects, the area under the ROC curve (AUC) being 0.991 (0.010). When serum PSA was in the gray zone, from 4 to 10 microg/l, the diagnostic accuracy of PSA in discriminating patients with prostate cancer from BPH patients was very poor, AUC being 0.563 (0.132). However, using the same set of patients the LR model combining serum PSA, free to total PSA ratio and TSA values, as well as digital rectal examination results, had good diagnostic accuracy in discriminating the prostate cancer patients from patients with BPH, the area under the ROC curve being 0.895 (0.054). The present data suggest that the logistic regression model combining laboratory measurements and results of the clinical examination may be a useful adjunct in the differential diagnosis of benign and malignant prostate disease.
机译:为了提高血清总和游离前列腺特异性抗原(PSA)在良性前列腺增生(BPH)和前列腺癌之间的鉴别诊断中的诊断准确性,测量了血清总唾液酸(TSA)和逻辑回归(LR)模型已建立。与对照组相比,前列腺癌患者的血清PSA浓度显着较高(p <0.001),但两组之间的血清TSA浓度无统计学差异。血清PSA能够可靠地区分对照对象的前列腺癌患者,ROC曲线下面积(AUC)为0.991(0.010)。当血清PSA处于灰色区域(从4到10微克/升)时,PSA在区分前列腺癌和BPH患者中的诊断准确性非常差,AUC为0.563(0.132)。然而,使用同一组患者,结合血清PSA,游离总PSA比值和TSA值以及直肠指检结果的LR模型,在区分前列腺癌患者与BPH患者, ROC曲线为0.895(0.054)。目前的数据表明,将实验室测量结果和临床检查结果相结合的逻辑回归模型可能是鉴别良性和恶性前列腺疾病的有用辅助方法。

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