The diagnostic effectiveness of serum sialic acid predicts both qualitative and quantitative prostate cancer in patients with prostate-specific antigen between 4 and 20 ng/mL - Sun, Jingtao; Yan, Lei (Frontiers in Endocrinology, 2023)
Introduction This study aimed to evaluate the predictive value of the serum biochemical index, including alkaline phosphatase (AKP), lactate dehydrogenase (LDH), α-L-fucosidase (AFU), serum sialic acid (SA), and fibrinogen (FIB), for prostate cancer (PCa) and clinically significant prostate cancer (CSPCa) in patients with a prostate-specific antigen (PSA) value between 4 and 20 ng/mL. Patients and methods This study retrospectively examined the clinical data of 408 eligible patients who underwent prostate biopsies in our hospital between March 2015 and July 2022. CSPCa was defined as a “Gleason grade group of≥2”. For analyzing the association between PCa/CSPCa and serum biochemical index, univariable logistic regression and multivariable logistic regression were conducted. Based on the multivariable logistic regression model, we constructed models and compared the area under the curve (AUC). We generated the nomogram, the ROC curve, the DCA curve, and the calibration curve for PCa. Results Overall, we studied 271 patients with PCa (including 155 patients with CSPCa) and 137 non-PCa patients. Patients with PCa were more likely to consume alcohol, have higher total PSA (TPSA) values, and have lower free PSA (FPSA) and free/total PSA (f/T) values. There were higher TPSA values and lower f/T values in the CSPCa group when compared with the non-CSPCa group. The univariate logistic regression analyses did not show significant results. However, AKP, AFU, SA, TPSA, and FPSA all retain significant significance when all factors are included in multifactor logistic regression analysis. This finding suggests that the exposure factor exhibited an independent effect on the outcome after controlling for other factors, including the potential confounding effects that may have been underestimated. Through ROC curves, we found that SA and TPSA levels are more powerful predictors. In contrast, there is a lack of excellent predictive value for PCA and CSPCa using Age, AFU, FIB, and FPSA. Conclusion In our study, serum biochemical index is a potential prediction tool for PCa and CSPCa for patients with PSA values between 4 and 20 ng/mL. Additionally, the new serum biochemical index SA is also useful when diagnosing PCa and CSPCa, as we conclude in our study.