Predictors of Prostate Cancer at Fusion Biopsy: The Role of Positive Family History, Hypertension, Diabetes, and Body Mass Index.

BACKGROUND: PSA density and an elevated PI-RADS score are among the strongest predictors of prostate cancer (PCa) in a fusion biopsy. Positive family history, hypertension, diabetes, and obesity have also been associated with the risk of developing PCa. We aim to identify predictors of the prostate cancer detection rate (CDR) in a series of patients undergoing a fusion biopsy. METHODS: We retrospectively evaluated 736 consecutive patients who underwent an elastic fusion biopsy from 2020 to 2022. Targeted biopsies (2-4 cores per MRI target) were followed by systematic mapping (10-12 cores). Clinically significant PCa (csPCa) was defined as ISUP score ≥ 2. Uni- and multi-variable logistic regression analyses were performed to identify predictors of CDR among age, body mass index (BMI), hypertension, diabetes, positive family history, PSA, a positive digital rectal examination (DRE), PSA density ≥ 0.15, previous negative biopsy status, PI-RADS score, and size of MRI lesion. RESULTS: The median patients' age was 71 years, and median PSA was 6.6 ng/mL. A total of 20% of patients had a positive digital rectal examination. Suspicious lesions in mpMRI were scored as 3, 4, and 5 in 14.9%, 55.0%, and 17.5% of cases, respectively. The CDR was 63.2% for all cancers and 58.7% for csPCa. Only age (OR 1.04, p < 0.001), a positive DRE (OR 1.75, p = 0.04), PSA density (OR 2.68, p < 0.001), and elevated PI-RADS score (OR 4.02, p = 0.003) were significant predictors of the CDR in the multivariable analysis for overall PCa. The same associations were found for csPCa. The size of an MRI lesion was associated with the CDR only in uni-variable analysis (OR 1.07, p < 0.001). BMI, hypertension, diabetes, and a positive family history were not predictors of PCa. CONCLUSIONS: In a series of patients selected for a fusion biopsy, positive family history, hypertension, diabetes, or BMI are not predictors of PCa detection. PSA-density and PI-RADS score are confirmed to be strong predictors of the CDR.

Accuracy of elastic fusion biopsy: Comparing prostate cancer detection between targeted and systematic biopsy.

INTRODUCTION: When performing targeted biopsy (TBx), the need to add systematic biopsies (SBx) is often debated. Aim of the study is to evaluate the added value of SBx in addition to TBx in terms of prostate cancer (PCa) detection rates (CDR), and to test the concordance between multiparametric magnetic resonance imaging (mpMRI) findings and fusion biopsy results in terms of cancer location. METHODS: We performed a retrospective, multicentric study that gathered data on 1992 consecutive patients who underwent elastic fusion biopsy between 2011 and 2020. A standardized approach was used, with TBx (2-4 cores per target) followed by SBx (12-14 cores). We assessed CDR of TBx, of SBx, and TBx+SBx for all cancers and clinically significant PCa (csPCa), defined as ISUP score ≥2. CDR was evaluated according to radiological and clinical parameters, with a particular focus on PI-RADS 3 lesions. In a subgroup of 1254 patients we tested the discordance between mpMRI findings and fusion biopsy results in terms of cancer location. Uni- and multivariable logistic regression analyses were performed to identify predictors of CDR. RESULTS: CDR of TBx+SBx was 63.0% for all cancers and 38.8% of csPCa. Per-patient analysis showed that SBx in addition to TBx improved CDR by 4.5% for all cancers and 3.4% for csPCa. Patients with lesions scored as PI-RADS 3, 4, and 5 were diagnosed with PCa in 27.9%, 72.8%, and 92.3%, and csPCa in 10.7%, 43.6%, and 69.3%, respectively. When positive, PI-RADS 3 lesions were ISUP grade 1 in 61.1% of cases. Per-lesion analysis showed that discordance between mpMRI and biopsy was found in 56.6% of cases, with 710 patients having positive SBx outside mpMRI targets, of which 414 (58.0%) were clinically significant. PSA density ≥0.15 was a strong predictor of CDR. CONCLUSIONS: The addition of systematic mapping to TBx contributes to a minority of per-patient diagnoses but detects a high number of PCa foci outside mpMRI targets, increasing biopsy accuracy for the assessment of cancer burden within the prostate. High PSA-density significantly increases the risk of PCa, both in the whole cohort and in PI-RADS 3 cases.

Two Novel Ceramide-Like Molecules and miR-5100 Levels as Biomarkers Improve Prediction of Prostate Cancer in Gray-Zone PSA.

Reliable liquid biopsy-based tools able to accurately discriminate prostate cancer (PCa) from benign prostatic hyperplasia (BPH), when PSA is within the "gray zone" (PSA 4-10), are still urgent. We analyzed plasma samples from a cohort of 102 consecutively recruited patients with PSA levels between 4 and 16 ng/ml, using the SANIST-Cloud Ion Mobility Metabolomic Mass Spectrometry platform, combined with the analysis of a panel of circulating microRNAs (miR). By coupling CIMS ion mobility technology with SANIST, we were able to reveal three new structures among the most differentially expressed metabolites in PCa vs. BPH. In particular, two were classified as polyunsaturated ceramide ester-like and one as polysaturated glycerol ester-like. Penalized logistic regression was applied to build a model to predict PCa, using six circulating miR, seven circulating metabolites, and demographic/clinical variables, as covariates. Four circulating metabolites, miR-5100, and age were selected by the model, and the corresponding prediction score gave an AUC of 0.76 (C.I. = 0.66-0.85). At a specified cut-off, no high-risk tumor was misclassified, and 22 out of 53 BPH were correctly identified, reducing by 40% the false positives of PSA. We developed and applied a novel, minimally invasive, liquid biopsy-based powerful tool to characterize novel metabolites and identified new potential non-invasive biomarkers to better predict PCa, when PSA is uninformative as a tool for precision medicine in genitourinary cancers.