PURPOSE: To analyse the performance of iXip in the prediction of prostate cancer (PCa) and high-grade PCa. METHODS: A consecutive series of men undergoing MRI/FUSION prostate biopsies were enrolled in one centre. Indications for prostate biopsy included abnormal prostate-specific antigen (PSA) levels (PSA > 4 ng/ml) and/or abnormal digital rectal examination (DRE) and/or abnormal MRI. All patients underwent the evaluation of serum PSA-IgM concentration and the iXip ratio was calculated. Accuracy iXip for the prediction of PCa was evaluated using multivariable binary regression analysis and receiver operator characteristics (ROC) curves. RESULTS: Overall 160 patients with a median age of 65 (62/73) years were enrolled. Overall, 42% patients were diagnosed with PCa and 75% of them had high-grade cancer (Epstein ≥ 3). Patients with PCa were older and presented higher PSA levels, higher PIRADS scores and lower prostate volumes (PVs). On ROC analysis iXip presented an area under the curve (AUC) of 0.57 in the prediction of PCa and of 0.54 for the prediction of high-grade PCa. CONCLUSIONS: In our experience, immune PSA complexes are not predictors of PCa. iXip analysis should not be included in the diagnostic pathway of patients at increased risk of PCa.
PURPOSE: To analyse the performance of iXip in the prediction of prostate cancer (PCa) and high-grade PCa. METHODS: A consecutive series of men undergoing MRI/FUSION prostate biopsies were enrolled in one centre. Indications for prostate biopsy included abnormal prostate-specific antigen (PSA) levels (PSA > 4 ng/ml) and/or abnormal digital rectal examination (DRE) and/or abnormal MRI. All patients underwent the evaluation of serum PSA-IgM concentration and the iXip ratio was calculated. Accuracy iXip for the prediction of PCa was evaluated using multivariable binary regression analysis and receiver operator characteristics (ROC) curves. RESULTS: Overall 160 patients with a median age of 65 (62/73) years were enrolled. Overall, 42% patients were diagnosed with PCa and 75% of them had high-grade cancer (Epstein ≥ 3). Patients with PCa were older and presented higher PSA levels, higher PIRADS scores and lower prostate volumes (PVs). On ROC analysis iXip presented an area under the curve (AUC) of 0.57 in the prediction of PCa and of 0.54 for the prediction of high-grade PCa. CONCLUSIONS: In our experience, immune PSA complexes are not predictors of PCa. iXip analysis should not be included in the diagnostic pathway of patients at increased risk of PCa.
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Keywords:
Prostate cancer; biomarkers; high grade; iXip; immune-complex