PSA Density Research Articles

Validation of a prognostic blood-based sphingolipid panel for men with localized prostate cancer followed on active surveillance

BackgroundWe previously reported that increases in circulating sphingolipids are associated with elevated risk of biopsy Gleason grade group (GG) upgrading in men on Active Surveillance (AS) for prostate cancer. Here, we aimed to validate these findings and establish a blood-based sphingolipid biomarker panel for identifying men on AS who are at high-risk of biopsy GG upgrading.MethodsMen diagnosed with low- or intermediate-risk prostate cancer in one of two AS cohorts (CANARY PASS and MDACC) were followed for GG upgrading after diagnostic and confirmatory biopsy. The PASS cohort consisted of 544 patients whereas the MDACC Cohort consisted of 697 patients. The number of patients with GG upgrading during course of study follow-up in the PASS and MDACC cohorts were 98 (17.7%) and 133 (19.1%), respectively. Plasmas collected prior to confirmatory biopsy were used for mass spectrometry-based quantitation of 87 unique sphingolipid species. A neural network layer based on 21 sphingolipids was developed in the CANARY PASS cohort for predicting biopsy GG upgrading. Tertile-based thresholds for low-, intermediate-, and high-risk strata were subsequently developed for the sphingolipid panel as well as a model that combined the sphingolipid panel with PSA density and rate of core positivity on diagnostic biopsy. The resultant models and risk thresholds for GG upgrading were validated in the MDACC cohort. Performance was assessed using Cox proportional hazard models, C-index, AUC, and cumulative incidence curves.ResultsThe sphingolipid panel had a HR (per unit standard deviation increase) of 1.36 (95% CI: 1.07–1.70) and 1.35 (95% CI: 1.11–1.64) for predicting GG biopsy upgrading in the PASS and MDACC cohort, respectively. The model that combined the sphingolipid panel with PSA density and rate of core positivity achieved a HR of 1.63 (95% CI: 1.33-2.00) and 1.44 (1.25–1.66), respectively. Tertile-based thresholds, established in the PASS cohort, were applied to the independent MDACC cohort. Compared to the low-risk group, MDACC patients in the high-risk strata had a GG biopsy upgrade HR of 3.65 (95% CI: 2.21–6.02), capturing 50% of the patients that had biopsy upgrading during study follow-up.ConclusionsThe sphingolipid panel is independently associated with GG biopsy upgrading among men in two independent AS cohorts who have previously undergone diagnostic and confirmatory biopsy. The sphingolipid panel, together with clinical factors, provides a potential means for risk stratification to better guide clinical management of men on AS.

Prognostic role of prostate specific antigen kinetics in primary high volume metastatic hormonal sensitive prostate cancer treated with novel hormonal therapy agents

The prognostic value of prostate-specific antigen (PSA) kinetics in primary high-volume metastatic hormone-sensitive prostate cancer (mHSPC) patients treated with novel hormonal therapy agents is still unclear. Here, we retrospectively reviewed the data of 102 patients with primary high-volume mHSPC who received novel hormonal therapy agents. The median follow-up was 32.25 ± 14.51 months and the median nadir PSA (nPSA) was 0.20 (0.06, 11.71) ng/mL after treatment. The mean time to nPSA was 10.82 ± 7.27 months and 55 patients (53.9%) had a PSA-density (PSA-D) ≤ 0.08 at 3-months. Univariate and multivariate Cox regression analyses showed that the absence of visceral metastases, nPSA ≤ 0.2 and PSA-D ≤ 0.08 were independent prognostic factors for better PFS and OS (all P < 0.05). Moreover, patients with nPSA ≤ 0.2 and PSA-D ≤ 0.08 had the best PFS and OS, and the combination of the nPSA and PSA-D had a better predictive accuracy for PFS and OS than nPSA and PSA-D alone. Thus, Visceral metastases, nPSA and PSA-D were independent prognostic factors for primary high-volume mHSPC patients treated with novel hormonal therapy agents. Patients with lower nPSA and PSA-D had a best survival outcome, and the combination of nPSA and PSA-D had a better effect on prognosis predicting.

Predicting cancer detection rates from multiparametric prostate MRI

Introduction: Although the Prostate Imaging-Reporting and Data System (PI-RADS) categorization represents the standard method for assessing the risk of prostate cancer using prostate magnetic resonance imaging (MRI), there exists wide variation in cancer detection rates (CDRs) in real-world practice. We therefore evaluated the association of clinical and radiographic features with CDRs and developed a predictive model to improve clinical management. Methods: We identified men aged 18–89 years with elevated prostate-specific antigen (PSA) or on active surveillance for prostate cancer who underwent MRI-ultrasound (US) fusion biopsy or in-bore MRI-targeted biopsy. The associations of features with the per-lesion CDR (Gleason 6–10) and clinically significant (cs) CDR (Gleason 7–10) were examined using logistic regression, and results were operationalized into a predictive model. Results: Targeted biopsy was performed for 347 lesions in 281 patients. Overall, the CDR was 49.0% and the csCDR was 28.0%. On multivariable analysis, increasing PI-RADS category, no prior prostate biopsies, smaller prostate size, and increasing PSA density were independently associated with higher CDR, while 0–1 prior prostate biopsies, and a solitary PI-RADS 3–5 lesion were associated with higher csCDR. A predictive model provided a greater net benefit than a strategy of performing biopsy in all PI-RADS 3–5 lesions across a wide range of threshold probabilities. Conclusions: Several clinical and radiographic features are independently associated with the risk of prostate cancer in men undergoing MRI-targeted biopsy. A predictive model based on these features can improve clinical decisions regarding biopsy compared to the conventional strategy of performing biopsy for all PI-RADS 3–5 lesions.

Detecting Clinically Significant Prostate Cancer in PI-RADS 3 Lesions Using T2w-Derived Radiomics Feature Maps in 3T Prostate MRI

Prostate Imaging Reporting and Data System version 2.1 (PI-RADS) category 3 lesions are a challenge in the clinical workflow. A better detection of the infrequently occurring clinically significant prostate cancer (csPCa) in PI-RADS 3 lesions is an important objective. The purpose of this study was to evaluate if feature maps calculated from T2-weighted (T2w) 3 Tesla (3T) MRI can help detect csPCa in PI-RADS category 3 lesions. In-house biparametric 3T prostate MRI examinations acquired between January 2019 and June 2023 because of elevated prostate-specific antigen (PSA) levels were retrospectively screened. Inclusion criteria were a PI-RADS 3 lesion and available results of an ultrasound-guided targeted and systematic biopsy. Exclusion criteria were a simultaneous PI-RADS category 4 or 5 lesion and hip replacement. Target lesions with the International Society of Urological Pathology (ISUP) grade group 1 were rated clinically insignificant PCa (ciPCa) and ≥2 csPCa. This resulted in 52 patients being included in the final analysis, of whom 11 (21.1%), 8 (15.4%), and 33 (63.5%) patients had csPCa, ciPCa, and no PCa, respectively, with the latter two groups being combined as non-csPCa. Eight of the csPCas were located in the peripheral zone (PZ) and three in the transition zone (TZ). In the non-csPCa group, 29 were located in the PZ and 12 in the TZ. Target lesions were marked with volumes of interest (VOIs) on axial T2w images. Axial T2w images were then converted to 93 feature maps. VOIs were copied into the maps, and feature quantity was retrieved directly. Features were tested for significant differences with the Mann–Whitney U-test. Univariate models for single feature performance and bivariate models implementing PSA density (PSAD) were calculated. Ten map-derived features differed significantly between the csPCa and non-csPCa groups (AUCs: 0.70–0.84). The diagnostic performance for TZ lesions (AUC: 0.83–1.00) was superior to PZ lesions (AUC: 0.74–0.85). In the bivariate models, performance in the PZ improved with AUCs &gt;0.90 throughout. Parametric feature maps alone and as bivariate models with PSAD can (?) noninvasively identify csPCa in PI-RADS 3 lesions and could serve as a quantitative tool reducing ambiguity in PI-RADS 3 lesions.

P034 Prostate MRI reduction in biopsy-naïve men with PSA

P034 Prostate MRI reduction in biopsy-naïve men with PSA <7 ng/ml using PSA-Density (PSAD), Digital Rectal Examination (DRE) and age risk stratification

P031 Analysis of the index lesion involvement zone variable in predictive models of prostate cancer: Integrating PSA density and prostate MRI data using PI-RADS classification before biopsy

P031 Analysis of the index lesion involvement zone variable in predictive models of prostate cancer: Integrating PSA density and prostate MRI data using PI-RADS classification before biopsy

Targeted microwave ablation of localised prostate cancer: Initial results of VIOLETTE trial

AbstractObjectiveThe aim of this study was to assess the precision and safety of targeted microwave ablation (TMA) using organ‐based tracking (OBT) fusion, in patients with intermediate risk prostate cancer.Patients and methodWe conducted a prospective, multicentric trial. Eligible patients had a prostate‐specific antigen (PSA) &lt; 20 ng/mL, a magnetic resonance imaging (MRI)‐visible index tumour of Gleason score 3 + 4, with largest axis ≤15 mm and distant of at least 5 mm from the rectum and apex. TMA was performed with microwave needle applicator using OBT fusion, with a transperineal or a transrectal approach. In this interim analysis, we evaluated precision, safety, urinary and sexual outcomes, and PSA density kinetics.ResultsAt this point, 37 patients were treated in five centres. Median (interquartile range) age is 68 (63–72) years. Baseline median prostate volume and PSA are of 45 (34–57) mL and 8 (6.2–10.8) ng/mL, respectively. Median largest tumour axis on T2W MRI is of 11 mm (10–13). Patients were treated under general anaesthesia or conscious IV sedation in an outpatient setting. Anaesthesia had a median duration of 78 (66–90) min. A median number of 3 (2–4) 12‐W ablations of 2 to 5 min were performed per patient. After a median follow‐up of 6 (2.4–10) months, we observed 58 adverse events (AE) in 22 patients. These were of Common Terminology Criteria for Adverse Events (CTCAE) grade 1, 2 and 3 in 43 (74%), 13 (22%) and 2 (4%) cases. Six (15%) patients had an acute urinary retention, five of which considered as severe AE because of rehospitalisation. We did not observe any significant difference in International Prostate Symptom Score (IPSS), Male Sexual Health Questionnaire‐ejaculatory dysfunction (MSHQ‐EjD) and International Index of Erectile Function (IIEF5) from baseline to last follow‐up. Median PSA density evolved from 0.2 (0.1–0.3) at baseline to 0.1 (0.07–0.16) at 12 months.ConclusionsThese preliminary results suggest that TMA using OBT fusion is precise and safe in patients with intermediate risk localised prostate cancer. Further inclusions and follow‐up are needed to assess oncological outcome.

Predictive Value of PSA Density in Pathological Discordance Terms in Patients who Undergo Robotic Surgery for Low-risk Prostate Cancer: An Analytic Cross-sectional Study of a Tertiary Reference Center

Predictive Value of PSA Density in Pathological Discordance Terms in Patients who Undergo Robotic Surgery for Low-risk Prostate Cancer: An Analytic Cross-sectional Study of a Tertiary Reference Center

Reply to "Is the Free-to-Total PSA Ratio Less Important Than PSA Density and PSA Velocity in Patients With Negative MRI Examinations?"

Reply to "Is the Free-to-Total PSA Ratio Less Important Than PSA Density and PSA Velocity in Patients With Negative MRI Examinations?"

Is the Free-to-Total PSA Ratio Less Important Than PSA Density and PSA Velocity in Patients With Negative MRI Examinations?

Is the Free-to-Total PSA Ratio Less Important Than PSA Density and PSA Velocity in Patients With Negative MRI Examinations?

Using a novel PSMA-PET and PSA-based model to enhance the diagnostic accuracy for clinically significant prostate cancer and avoid unnecessary biopsy in men with PI-RADS ≤ 3 MRI.

The diagnostic evaluation of men with suspected prostate cancer (PCa) yet inconclusive MRI (PI-RADS ≤ 3) presents a common clinical challenge. [68Ga]Ga-labelled prostate-specific membrane antigen ([68Ga]Ga-PSMA) positron emission tomography/computed tomography (PET/CT) has shown promise in identifying clinically significant PCa (csPCa). We aim to establish a diagnostic model incorporating PSMA-PET to enhance the diagnostic process of csPCa in PI-RADS ≤ 3 men. This study retrospective included 151 men with clinical suspicion of PCa and PI-RADS ≤ 3 MRI. All men underwent [68Ga]Ga-PSMA PET/CT scans and ultrasound/MRI/PET fusion-guided biopsies. csPCa was defined as Grade Group ≥ 2. PRIMARY-scores from PSMA-PET scans were evaluated. A diagnostic model incorporating PSMA-PET and prostate-specific antigen (PSA)-derived parameters was developed. The discriminative performance and clinical utility were compared with conventional methods. Internal validation was conducted using a fivefold cross-validation with 1000 iterations. In this PI-RADS ≤ 3 cohort, areas-under-the-curve (AUCs) for detecting csPCa were 0.796 (95%CI, 0.738-0.853), 0.851 (95%CI, 0.783-0.918) and 0.806 (95%CI, 0.742-0.870) for PRIMARY-score, SUVmax and routine clinical PSMA-PET assessment, respectively. The diagnostic model comprising PRIMARY-score, SUVmax and serum free PSA/total PSA (fPSA/tPSA) achieved a significantly higher AUC of 0.906 (95%CI, 0.851-0.961) compared to strategies based on PRIMARY-score or SUVmax (P < 0.05) and markedly superior to conventional strategies typically based on PSA density (P < 0.001). The average fivefold cross-validated AUC with 1000 iterations was 0.878 (95%CI, 0.820-0.954). Theoretically, using a threshold of 21.6%, the model could have prevented 78% of unnecessary biopsies while missing only 7.8% of csPCa cases in this cohort. A novel diagnostic model incorporating PSMA-PET derived metrics-PRIMARY-score and SUVmax-along with serum fPSA/tPSA, has been developed and validated. The integrated model may assist clinical decision-making with enhanced diagnostic accuracy over the individual conventional metrics. It has great potential to reduce unnecessary biopsies for men with PI-RADS ≤ 3 MRI results and warrants further prospective and external evaluations.

The efficacy of different biomarkers and endpoints to refine referrals for suspected prostate cancer: the TARGET study (Tiered integrAted tests for eaRly diaGnosis of clinically significant ProstatE Tumours).

The majority of men referred with a raised PSA for suspected prostate cancer will receive unnecessary tertiary investigations including MRI and biopsy. Here, we compared different types of biomarkers to refine tertiary referrals and when different definitions of clinically significant cancer were used. Data and samples from 798 men referred for a raised PSA (≥ 3ng/mL) and investigated through an MRI-guided biopsy pathway were accessed for this study. Bloods were acquired pre-biopsy for liquid biomarkers and germline DNA. Variables explored included PSA + Age (base model), free/total PSA (FTPSA), Prostate Health Index (phi), PSA density (PSAd), polygenic risk score (PRS) and MRI (≥ LIKERT 3). Different diagnostic endpoints for significant cancer (≥ grade group 2 [GG2], ≥ GG3, ≥ Cambridge Prognostic Group 2 [CPG2], ≥ CPG3) were tested. The added value of each biomarker to the base model was evaluated using logisticregression models, AUC and decision curve analysis (DCA) plots. The median age and PSA was 65years and 7.13ng/mL respectively. Depending on definition of clinical significance, ≥ grade group 2 (GG2) was detected in 57.0% (455/798), ≥ GG3 in 27.5% (220/798), ≥ CPG2 in 61.6% (492/798) and ≥ CPG3 in 42.6% (340/798). In the pre-MRI context, the PSA + Age (base model) AUC for prediction of ≥ GG2, ≥ GG3, ≥ CPG2 and ≥ CPG3 was 0.66, 0.68, 0.70 and 0.75 respectively. Adding phi and PSAd to base model improved performance across all diagnostic endpoints but was notably better when the composite CPG prognostic score was used: AUC 0.82, 0.82, 0.83, 0.82 and AUC 0.74, 0.73, 0.79, 0.79 respectively. In contrast, neither FTPSA or PRS scores improved performance especially in detection of ≥ GG3 and ≥ CPG3 disease. Combining biomarkers did not alter results. Models using phi and PSAd post-MRI also improved performances but again benefit varied with diagnostic endpoint. In DCA analysis, models which incorporated PSAd and phi in particular were effective at reducing use of MRI and/or biopsies especially for ≥ CPG3 disease. Incorporating phi or PSAd can refine and tier who is referred for tertiary imaging and/or biopsy after a raisedPSA test. Incremental value however varied depending on the definition of clinical significance and was particularly useful when composite prognostic endpoints are used.

Is Confirmatory Biopsy Still Necessary for Active Surveillance of Men With Grade Group 1 Prostate Cancer in the Era of Multiparametric Magnetic Resonance Imaging?

Men diagnosed with prostate cancer (PCa) considering active surveillance (AS) are recommended confirmatory biopsy (CBx). Whether this is necessary in the era of MRI-informed biopsies is questionable. We studied men with Grade Group [GG] 1 PCa at diagnostic biopsy (DBx) considering AS who underwent MRI and CBx (systematic + targeted) within 18 months. Outcomes were grade reclassification to GG ≥ 2, GG ≥ 3, and reclassification to unfavorable intermediate risk disease (UIR). Subset analyses were performed for men with (1) MRI prior to DBx and (2) MRI after DBx. Five hundred twenty-two men had GG1 PCa at DBx. At CBx, 20% reclassified to GG ≥ 2, 12% to UIR, and 5.6% to GG ≥ 3. Of the 306 with positive MRI (PI-RADS > 3), 27% reclassified to GG ≥ 2 and 16% to UIR disease; men with negative MRI experienced these outcomes at rates of 9.2% and 5.5%. There were no differences in reclassification outcomes based on MRI timing (group A vs B), and neither PSA density nor prostate volume added to MRI information. In men with MRI targets, approximately 1/3 of GG > 2 reclassification events were only captured by systematic biopsy core(s). Reclassification rates at CBx were high in men with positive MRI, but < 10% for all reclassification outcomes in men with negative MRI (95% CI 5.8%-14% for GG > 2, 2.9%-10% for UIR, 0.8%-5.3% for GG > 3). Our data support systematic + targeted CBx for men with positive MRI considering AS, while men with GG1 cancer and negative MRI should be able to defer CBx.

The value of adjusted PSAD in prostate cancer detection in the Chinese population.

To investigate the value of adjusted prostate-specific antigen density (PSADadj) in the diagnosis of prostate cancer (PCa). Data from 410 patients who underwent transrectal ultrasound-guided prostate biopsy were retrospectively analyzed in Beijing Tsinghua Changgung Hospital between November 2014 and March 2024. All patients were divided into PCa and benign prostatic hyperplasia (BPH) groups according to pathological results. Multivariate logistic regression analyses were performed to evaluate the odd ratios (ORs) of predictors for PCa occurrence. Receiver operating characteristic curves were plotted, and the area under the curve (AUC) values were used to assess and compare the diagnostic accuracies of total PSA (tPSA), free-to-total (f/t) PSA, free PSA (fPSA), PSAD, and PSADadj (PSAD×weight). There were 166 patients in the PCa group and 244 in the BPH group. Multivariate analyses demonstrated that PSAD was positively correlated with the presence of PCa, with the highest OR value among all PSA-related parameters (OR = 19.075, p<0.001). tPSA, fPSAD, PSAD, and PSADadj had high accuracy in predicting PCa, with AUC values of 0.633, 0.730, 0.778, and 0.780. Of note, PSADadj had the highest AUC with a sensitivity of 63.3% and specificity of 81.6%. Similarly, in patients with a PSA level in the gray zone, the diagnostic accuracy of PSADadj in predicting PCa (AUC, 0.709; 95% CI, 0.616-0.802) remained better than other PSA-related markers. PSADadj has an advantage over other PSA-related markers in detecting PCa and could be used for making biopsy decisions.

Unlocking Precision Enhancing Prostate Cancer Detection and Reducing Unnecessary Biopsies with Combined Prostate-Specific Antigen Density and PI-RADS Score.

To determine clinically significant prostate cancer (csPCa) detection rate by combining the prostate-specific antigen density (PSAD) and prostate imaging-reporting and data system (PI-RADS) scores. Descriptive study. Place and Duration of the Study: Department of Urology, University of Health Sciences, Ankara Oncology Training and Research Hospital, from January 2018 to April 2023. Patients who underwent prostate biopsies after multiparametric magnetic resonance imaging (mpMRI) were included in the study. PI-RADS 4 and 5 lesions were considered as MR positive. The cut-off values for PSAD were also determined to evaluate csPCa. csPCa detection rates were evaluated by grouping the patients based on the PSAD and mpMRI findings. PSAD cut-off value of 0.165 ng/mL/mL (sensitivity 80%, specificity 72%) was detected to predict csPCa (AUC = 0.81, 95% CI:0.756-0.866, p<0.001). csPCa detection rate was low (3%) in patients who have low PI-RADS scores (1-3) and a PSAD <0.165 ng/mL/mL. On the other hand, csPCa detection rate was high (50.5%) in patients who have a high PI-RADS score (4-5 lesions) and with a PSAD ≥0.165 ng/mL/mL. csPCa detection rates are low in patients with PI-RADS 1-3 lesions and low PSAD values. Unnecessary biopsy may be avoided in these patients. Gleason score, PI-RADS, Prostate cancer, Prostate-specific antigen, Prostate-specific antigen density.

Navigating the gray zone: Machine learning can differentiate malignancy in PI-RADS 3 lesions

IntroductionThe objective of this study is to predict the probability of prostate cancer in PI-RADS 3 lesions using machine learning methods that incorporate clinical and mpMRI parameters. MethodsThe study included patients who had PI-RADS 3 lesions detected on mpMRI and underwent fusion biopsy between January 2020 and January 2024. Radiological parameters (Apparent diffusion coefficient (ADC), tumour ADC/contralateral ADC ratio, Ktrans value, periprostatic adipose tissue thickness, lesion size, prostate volume) and clinical parameters (age, body mass index, total prostate specific antigen, free PSA, PSA density, systemic inflammatory index, neutrophil-lymphocyte ratio [NLR], platelet lymphocyte ratio, lymphocyte monocyte ratio) were documented. The probability of prostate cancer prediction in PI-RADS 3 lesions was calculated using 6 different machine-learning models, with the input parameters being the aforementioned variables. ResultsOf the 235 participants in the trial, 61 had malignant fusion biopsy pathology and 174 had benign pathology. Among 6 different machine learning algorithms, the random forest model had the highest accuracy (0.86±0.04; 95% CI 0.85–0.87), F1 score (0.91±0.03; 95% CI 0.91–0.92) and AUC value (0.92±0.06; 95% CI 0.88–0.90). In SHAP analysis based on random forest model, tumour ADC, tumour ADC/contralateral ADC ratio and PSA density were the 3 most successful parameters in predicting malignancy. On the other hand, systemic inflammatory index and neutrophil lymphocyte ratio showed higher accuracy in predicting malignancy than total PSA, age, free PSA/total PSA and lesion size in SHAP analysis. ConclusionAmong the machine learning models we developed, especially the random forest model can predict malignancy in PI-RADS 3 lesions and prevent unnecessary biopsy. This model can be used in clinical practice with multicentre studies including more patients.

Determining Long-term Prostate Cancer Outcomes for Active Surveillance Patients Without Early Disease Progression: Implications for Slowing or Stopping Surveillance

Background and objectiveActive surveillance (AS) of prostate cancer (PCa) is the standard of care for low-grade disease, but there is limited guidance on tailoring protocols for stable patients. We investigated long-term outcomes for patients without initial progression and risk factors for upgrade. MethodsMen on AS with Gleason grade group (GG) 1 PCa on three serial biopsies, ≥5 yr without progression, and ≥10 yr of follow-up were included. Outcomes were upgrade (GG ≥2), major upgrade (GG ≥3), progression to treatment, metastasis, PCa-specific survival, and overall survival. Cox proportional hazards regression models were used to estimate the associations between patient characteristics and risk of upgrade. Key findings and limitationsA total of 774 men met the inclusion criteria. At 10, 12, and 15 yr, upgrade-free survival rates were 56%, 45%, and 21%; major upgrade–free survival rates were 88%, 83%, and 61%; treatment-free survival rates were 86%, 83%, and 73%; metastasis-free survival rates were 99%, 99%, and 98%; and overall survival rates were 98%, 96%, and 95%, respectively. PCa-specific survival was 100% at 15 yr. On a multivariable analysis, year of diagnosis, age, body mass index (BMI), and biopsy core positivity were associated with upgrade (all p < 0.01), whereas age and prostate-specific antigen (PSA) density were associated with major upgrade. Conclusions and clinical implicationsPatients without progression for 5 yr on AS had modest rates of upgrade and low rates of metastasis, and mortality at 15 yr of follow-up. Year of diagnosis, older age, increased BMI, and increased biopsy core positivity were associated with upgrade, whereas older age and greater PSA density were associated with an increased risk of major upgrade. A subset of these patients may benefit from deintensification of AS protocols. Patient summaryThere are little reported data or clinical guidelines for patients with prostate cancer (PCa) who are stable for many years on active surveillance (AS). We show, in a large cohort, that PCa patients without progression for 5 yr on AS have modest rates of upgrade and very low rates of metastasis, and mortality rates at 15 yr of follow-up, and that older age, increased body mass index, and increased PCa volume are associated with an increased likelihood of future upgrade. This study supports continued AS in this patient population and deintensification in select patients.

Elevating precision: A thorough investigation of multiparametric prostate MRI for prolonged insights into early continence prediction after robot-assisted laparoscopic prostatectomy

BackgroundWhile radical prostatectomy stands out as one of the most effective curative treatments for prostate cancer, it does come with annoying side effects, such as urinary incontinence (UI). We aimed to investigate the predictability of UI using MRI measurements, along with clinical and disease-related variables. MethodsWe included 191 patients who underwent robot-assisted laparoscopic radical prostatectomy between July 2020 and October 2022 in the study. Preoperative MRIs of the patients are re-evaluated by an experienced uroradiologist, and membranous urethral length (MUL), urethra wall thickness, levator ani thickness, outer levator distance, Lee's apex shape, intravesical prostate protrusion length, prostate apex depth, and pubic height measurements were made. Additionally, retrospective data on patients' age, BMI, PSA, PSA density, prostate volume, IPSS, clinical stage, and nerve-sparing status were collected. Patients were categorized into two groups based on continence status in the third postoperative month: continent or incontinent. The definition of UI was accepted as the use of one or more pads per day. ResultsUI was observed in 38.21 % of the patients in the postoperative third month. Among MRI measurements, only MUL showed a significant relationship with UI (p < 0.001). IPSS (p = 0.004) and Clinical Stage (p < 0.001) were also significantly associated with continence status. Logistic regression analysis identified BMI (p = 0.023; CI 0.73–0.97), IPSS (p = 0.002; CI 1.03–1.17), MUL (p = 0.001; CI 0.66–0.90), and Clinical Stage (p < 0.001; CI 1.53–2.71) as significant predictors. In Multivariable Regression analysis, Clinical Stage emerged as the most powerful predictor of UI (p < 0.001). ConclusionsExcept for MUL, MRI measurements may not predict postoperative UI. A combination of IPSS, clinical stage, and MUL effectively informs patients about postoperative outcomes. These findings contribute to enhancing preoperative counseling for patients undergoing radical prostatectomy.

Abstract C014: Lower negative predictive value of prostate MRI in Black men

Abstract Introduction: PIRADS scoring with multiparametric-MRI (MRI) has a pooled 90% negative predictive value (NPV) allowing men to defer biopsy while enhancing Gleason Grade group 2-5 (GG2-5) prostate cancer (PCa) detection. PSA density (PSAD) ≥0.15ng/ml/cm3 has been shown to enhance NPV of the prostate MRI in non-Black men. We assessed the performance of the prostate MRI in Black vs. non-Black men by evaluating sensitivity and NPV, and identified a PSAD threshold providing ≥90% NPV in Black men. Methods: We prospectively recruited Black and non-Black men referred to outpatient urology clinics for abnormal PSA or prostate exam in three similar biomarker validation studies from 2017–23 before MRI-informed diagnostic transrectal or transperineal prostate biopsy. We combined this research cohort with a retrospective clinical cohort of clinically similar Black and non-Black men from one academic institution who also underwent prostate MRIs and MRI-informed biopsies for elevated PSA. Trained radiologists used PIRADS version 2.0 or 2.1 for scoring. Results: Following the combination of the research and clinical cohorts, 286 Black men and 965 non-Black men with PSA&amp;lt;15.0ng/ml were included in the analysis. PIRADS ≥3 had an NPV of 77.1% versus 87.6% and a sensitivity of 90.7% vs. 96.3% for GG2-5 PCa in Black versus non-Black men, respectively (both p&amp;lt;0.05). Using PSAD ≥0.09 for Black men with PIRADS 1-2 lesions increased sensitivity to 92.9%. For PIRADS 1-2, GG2-5 PCa frequency was 5.3% higher in Black versus non-Black men with PSAD&amp;lt;0.15, and 11.0% higher in Black versus non-Black men with PSAD≥0.15. For PIRADS=3, GG2-5 PCa frequency was 9.1% higher in Black men with PSAD&amp;lt;0.15 and 27.9% higher for PSAD≥0.15. For PIRADS=4, GG2-5 PCa frequency was 15.9% higher in Black men with PSAD&amp;lt;0.15, and 9.5% higher for PSAD≥0.15. Conclusion: The PIRADS ≥3 threshold has a lower NPV and sensitivity in Black men. A negative prostate MRI requires a PSAD ≥0.09 threshold for safe biopsy deferral in Black men to maintain a sensitivity ≥90%. Citation Format: Sarah Sandlow, Samuel Carbunaru MD, Zequn Sun PhD, Bernice Ofori MPH, Courtney M. P. Hollowell MD, Patricia Vidal MD, Eric Li MD, Edward M. Schaeffer MD, PhD, Peter Gann MD, ScD, Ashley Ross MD, PhD, Shilajit Kundu MD, Adam B. Murphy MD, MBA, MSCI. Lower negative predictive value of prostate MRI in Black men [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C014.

Abstract C180: Not all PIRADS 3s are equal; fusion biopsy outcomes by PIRADS score and ethnicity in a diverse population

Abstract Introduction and Objective: Magnetic resonance imaging (MRI) is increasingly utilized in the diagnosis of prostate cancer (PCa). Although PIRADS 3 lesions have been associated with a lower likelihood of detecting clinically significant prostate cancer (csPCa) at the time of targeted fusion biopsy (FB), existing data on multiethnic populations are sparse. We assessed the pathologic concordance of PIRADS 3 vs 4 or 5 lesions in detection of PCa and csPCa in comparison to PSA density in a diverse population. Methods: A retrospective study of all patients who underwent image-guided FB for PIRADS 3-5 lesions from 2016-2022 was conducted. Demographic, clinical, and pathologic data were extracted from electronic medical records. Mixed-effects logistic regression models were used to examine the association of race/ethnicity and PSA density with risks of overall PCa and csPCa. A stratified analysis by PIRADS score (3 vs 4 or 5) was also carried out to explore the associations between detection rates of PCa and race/ethnicity. Results: A total of 565 men with 997 lesions were analyzed, with average age 63.2 years (SD: 7.5) at the time of biopsy. Of the men, 279 (49.4%) were Non-Hispanic Black (NHB), 112 (19.8%) were Non-Hispanic White, and 174 (30.8%) were Hispanic. 520 (52.16%), 310 (31.09%), and 167 (16.75%) individual MRI lesions were PIRADS 3, 4, and 5, respectively with distributions of PIRADS scores being similar across all race/ethnicities. The overall rates of PCa detection were 44.8% in NHB, 37.6% in Hispanics, and 33.0% in NHW. Compared to NHW, NHB has 2.52 higher odds of detecting overall PCa (95% CI 1.10-5.78; p = 0.03), whereas Hispanic men had an OR = 1.18 (p = 0.72). Interestingly, the increase in PCa detection among NHB was only observed for PIRADs 3 lesions (OR = 4.84 95% CI 1.11-21.2, p = 0.04). NHB men also had 2.1-fold higher odds of detecting csPCa (95% CI 0.92-4.77; p = 0.08) in comparison to NHW with a similar trend mimicking association with PRIADS scores, although results were not statistically significant. Conclusions: We report that NHB men have higher odds of detection rates of overall PCa in FB in comparison to NHW and Hispanic men, albeit only at PIRADS 3 scores. These findings may serve to improve risk stratification and assist with shared decision making when discussing triggers for biopsy. Source of funding: None Citation Format: David G. Hanelin, Andrewe Baca, Priya Dave, Rutul Patel, Ilir Agalliu, Alexander Sankin, Ahmed Aboumohamed, Kara Watts. Not all PIRADS 3s are equal; fusion biopsy outcomes by PIRADS score and ethnicity in a diverse population [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C180.