Prostate Health Index and Multiparametric MRI: Partners in Crime Fighting Overdiagnosis and Overtreatment in Prostate Cancer

Impact of Australian federal funding on referral patterns of diagnostic multi-parametric MRI of the prostate

BACKGROUND

Reliable imaging techniques to assist in the diagnosis of prostate cancer (PCa) were not available until the advent of multiparametric magnetic resonance imaging (mpMRI), which has been shown to improve the detection and characterization of prostate lesions. In 2018, the Australian Medicare Benefits Schedule (MBS) extended its coverage to include mpMRI for PCa diagnosis and surveillance.

METHODS

This retrospective cohort study evaluated the impact of the MBS item expansion on mpMRI referral patterns, sources, yields and patient demographics at a Victorian center. Referrals for prostate mpMRI were analysed over a 30-month period before and after a 54-month period following the MBS update. All indications were considered, without exclusion criteria. Baseline continuous variables (age, PSA, PSA density, prostate volume, PIRADS score) were summarized using medians and interquartile ranges. Categorical variables were expressed as numbers and proportions. Statistical analyses included Mann-Whitney U-tests and T-tests for continuous variables, preceded by a Shapiro-Wilk normality test. GraphPad Prism 6 (San Diego, California, USA) facilitated data analysis.

RESULTS

Following the MBS update, there was a yearly average increase of 13.8% in mpMRI referrals, notably with a 125% surge in urologist referrals. The proportion of diagnostic scans rose from 42% pre-update to 70% post-update. These results highlight enhanced referral pathways and specific clinical applications of mpMRI after the MBS expansion.

CONCLUSIONS

In conclusion, federal funding led to a notable rise in mpMRI utilization. Continued monitoring and analysis of the role of mpMRI in PCa diagnostic algorithms are imperative to optimize its benefits and enhance clinical outcomes.

Development and validation of multivariable biopsy-free nomograms to predict clinically significant prostate cancer in patients with prostate-specific antigen levels ≥20 ng/mL

Background

Elevated prostate-specific antigen (PSA) levels often lead to prostate biopsies, which can result in overdiagnosis and complications, thereby increasing preoperative anxiety. This study aimed to develop and validate a novel biopsy-free diagnostic nomogram for accurate detection of clinically significant prostate cancer (csPCa) in patients with PSA levels ≥20 ng/mL.

Methods

The cohort of this retrospective analysis included patients with PSA levels ≥20 ng/mL who underwent evaluation including clinical variables, Prostate Imaging-Reporting and Data System (PI-RADS), prostate health index (PHI), and prostate-specific membrane antigen positron emission tomography-computed tomography (PSMA PET/CT). Nomogram performance was evaluated using the concordance index, calibration plot, decision curve analysis, and the area under the receiver operating characteristic curve (AUC).

Results

Of 684 patients, 478 and 206 were randomly assigned to the diagnostic and validation cohorts, respectively. Multivariable predictors of csPCa included age, PSA density, PI-RADS, location of suspicious lesion, %PSA variation ratio, and acute urinary retention. The foundational nomogram achieved AUCs of 0.930 and 0.911 for the training and validation sets, respectively. By integrating both PHI and PSMA maximum standardized uptake value (SUVmax), the diagnostic accuracy of the advanced nomogram improved significantly, with AUCs of 0.951 and 0.935 for the training and validation sets, respectively. Limitations included the lack of external validation and potential selection bias.

Conclusions

The biopsy-free nomogram presents a promising approach for accurate diagnosis of csPCa in patients with PSA levels ≥20 ng/mL. This non-invasive method can reduce unnecessary biopsies and enhance patient care by identifying those necessitating further evaluation and treatment.

Refining clinically relevant cut-offs of prostate specific antigen density for risk stratification in patients with PI-RADS 3 lesions

BACKGROUND

Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, identified through multiparametric magnetic resonance imaging (mpMRI), present a clinical challenge due to their equivocal nature in predicting clinically significant prostate cancer (csPCa). Aim of the study is to improve risk stratification of patients with PI-RADS 3 lesions and candidates for prostate biopsy.

METHODS

A cohort of 4841 consecutive patients who underwent MRI and subsequent MRI-targeted and systematic biopsies between January 2016 and April 2023 were retrospectively identified from independent prospectively maintained database. Only patients who have PI-RADS 3 lesions were included in the final analysis. A multivariable logistic regression analysis was performed to identify covariables associated with csPCa defined as International Society of Urological Pathology (ISUP) grade group ≥2. Performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and net benefit. Significant predictors were then selected for further exploration using a Chi-squared Automatic Interaction Detection (CHAID) analysis.

RESULTS

Overall, 790 patients had PI-RADS 3 lesions and 151 (19%) had csPCa. Significant associations were observed for age (OR: 1.1 [1.0-1.1]; p = 0.01) and PSA density (OR: 1643 [2717-41,997]; p < 0.01). The CHAID analysis identified PSAd as the sole significant factor influencing the decision tree. Cut-offs for PSAd were 0.13 ng/ml/cc (csPCa detection rate of 1% vs. 18%) for the two-nodes model and 0.09 ng/ml/cc and 0.16 ng/ml/cc for the three-nodes model (csPCa detection rate of 0.5% vs. 2% vs. 17%).

CONCLUSIONS

For individuals with PI-RADS 3 lesions on prostate mpMRI and a PSAd below 0.13, especially below 0.09, prostate biopsy can be omitted, in order to avoid unnecessary biopsy and overdiagnosis of non-csPCa.

Pathologic characteristics and management strategies for two categories of prostate cancer patients with low prostate-specific antigen undergoing radical prostatectomy

Background

Prostate cancer (PCa) with low levels of prostate-specific antigen (PSA) (0-4 ng/mL) includes PCa detected through biopsy and incidental PCa (IPC) in patients with previous prostate surgeries. The study was conducted to compare these two groups of patients undergoing radical prostatectomy (RP), aiming to assess pathological characteristics and suggest strategies for predicting and managing low PSA PCa.

Methods

A retrospective analysis was performed on two categories of low PSA PCa patients. Baseline characteristics, PSA density (PSAD), preoperative multiparametric magnetic resonance imaging (mpMRI) for RP, preoperative and postoperative pathological data, and biochemical recurrence (BCR) were evaluated.

Results

Fifty patients were analyzed. There were 80% of tumors being clinically significant and in early-stage, indicating a favorable prognosis for most low PSA PCa patients, and the use of preoperative androgen deprivation therapy (ADT) treatment may be beneficial for a small subset of patients with advanced tumors. Patients with low PSA and IPC history had lower PSA levels, PSAD, and prostate volume, however, BCR rates did not significantly differ between low PSA patients with and without IPC history. mpMRI and PSAD demonstrated potential in predicting PCa in low PSA cases.

Conclusions

Predicting low PSA PCa remains challenging, but mpMRI and PSAD could be valuable predictors. Both low PSA groups showed a likelihood of clinical significance, with favorable pathological features. Early diagnosis and treatment are crucial, especially for aggressive IPC PCa tumors. Reevaluating PSA thresholds is vital to avoid missed or misdiagnosed low PSA cases.

The prostate-gland asymmetry affects the 3- and 12-month continence recovery after RARP in patients with small prostate glands: a single center study

To test the impact of the prostate-gland asymmetry on continence rates, namely 3- and 12-month continence recovery, in prostate cancer (PCa) patients who underwent robot-assisted radical prostatectomy (RARP). Within our institutional database, RARP patients with complete preoperative MRI features and 12 months follow-up were enrolled (2021-2023). The population has been stratified according to the presence or absence of prostate-gland asymmetry (defined as the presence of median lobe or side lobe dominance). Multivariable logistic regression models (LRMs) predicting the continence rate at 3 and 12 months after RARP were fitted in the overall population. Subsequently, the LRMs were repeated in two subgroup analyses based on prostate size (≤ 40 vs > 40 ml). Overall, 248 consecutive RARP patients were included in the analyses. The rate of continence at 3 and 12 months was 69 and 72%, respectively. After multivariable LRM the bladder neck sparing approach (OR 3.15, 95% CI 1.68-6.09, p value < 0.001) and BMI (OR 0.90, 95% CI 0.82-0.97, p = 0.006) were independent predictors of recovery continence at 3 months. The prostate-gland asymmetry independently predicted lower continence rates at 3 (OR 0.33, 95% CI 0.13-0.83, p = 0.02) and 12 months (OR 0.31, 95% CI 0.10-0.90, p = 0.03) in patients with prostate size ≤ 40 ml. The presence of prostate lobe asymmetry negatively affected the recovery of 3- and 12-months continence in prostate glands ≤ 40 mL. These observations should be considered in the preoperative planning and counseling of RARP patients.

Tumor upgrading among very favorable intermediate-risk prostate cancer patients treated with robot-assisted radical prostatectomy: how can it impact the clinical course?

PURPOSE

We sought to investigate predictors of unfavorable tumor upgrading in very favorable intermediate-risk (IR) prostate cancer (PCa) patients treated with robot-assisted radical prostatectomy, in addition to evaluate how it may affect the risk of disease progression.

METHODS

A very favorable subset of IR PCa patients presenting with prostate-specific antigen (PSA) < 10 ng/mL, percentage of biopsy positive cores (BPC) < 50%, and either International Society of Urological Pathology (ISUP) grade group 1 and clinical stage T2b or ISUP grade group 2 and clinical stage T1c-2b was identified. Unfavorable pathology at radical prostatectomy was defined as the presence of ISUP grade group > 2 (unfavorable tumor upgrading), extracapsular extension (ECE), and seminal vesicle invasion (SVI). Disease progression was defined as the event of biochemical recurrence and/or local recurrence and/or distant metastases. Associations were evaluated by Cox regression and logistic regression analyses.

RESULTS

Overall, 210 patients were identified between January 2013 and October 2020. Unfavorable tumor upgrading was detected in 71 (33.8%) cases, and adverse tumor stage, including ECE or SVI in 18 (8.6%) and 11 (5.2%) patients, respectively. Median (interquartile range) follow-up was 38.5 (16-61) months. PCa progression occurred in 24 (11.4%) patients. Very favorable IR PCa patients with unfavorable tumor upgrading at final pathology showed a persistent risk of disease progression, which hold significance after adjustment for all factors (Hazard Ratio [HR]: 5.95, 95% Confidence Interval [CI]: 1.97-17.92, p = 0.002) of which PSA was an independent predictor (HR: 1.52, 95% CI 1.12-2.08, p = 0.008). Moreover, these subjects were more likely to belong to the biopsy ISUP grade group 2.

CONCLUSIONS

Very favorable IR PCa patients hiding unfavorable tumor upgrading were more likely to experience disease progression. Unfavorable tumor upgrading involved about one-third of cases and was less likely to occur in patients presenting with biopsy ISUP grade group 1. Tumor misclassification is an issue to discuss, when counseling this subset of patients for active surveillance because of the risk of delayed active treatment.

Advances in multiparametric magnetic resonance imaging combined with biomarkers for the diagnosis of high-grade prostate cancer

Clinical decisions based on the test results for prostate-specific antigen often result in overdiagnosis and overtreatment. Multiparametric magnetic resonance imaging (mpMRI) can be used to identify high-grade prostate cancer (HGPCa; Gleason score ≥3 + 4); however, certain limitations remain such as inter-reader variability and false negatives. The combination of mpMRI and prostate cancer (PCa) biomarkers (prostate-specific antigen density, Proclarix, TMPRSS2:ERG gene fusion, Michigan prostate score, ExoDX prostate intelliscore, four kallikrein score, select molecular diagnosis, prostate health index, and prostate health index density) demonstrates high accuracy in the diagnosis of HGPCa, ensuring that patients avoid unnecessary prostate biopsies with a low leakage rate. This manuscript describes the characteristics and diagnostic performance of each biomarker alone and in combination with mpMRI, with the intension to provide a basis for decision-making in the diagnosis and treatment of HGPCa. Additionally, we explored the applicability of the combination protocol to the Asian population.

Evaluation of HNF1B, KLK3, ELAC2, TMPRSS2-ERG, and CTNNB1 polymorphisms associated with prostate cancer in samples of patients from HUPE-UERJ

PURPOSE

Prostate cancer (PCa) is the leading cause of death among men in 48 countries. Genetic alterations play a significant role in PCa carcinogenesis. For the hypothesis of this research, five unique polymorphisms (SNP) were investigated in different genes that showed to be associated in different ways with PCa: rs4430796, rs2735839, rs4792311, rs12329760, and rs28931588, respectively for the genes HNF1B, KLK3, ELAC2, TMPRSS2-ERG, and CTNNB1.

PATIENTS AND METHODS

Blood samples from 426 subjects were evaluated: 290 controls (161 females and 129 males) and 136 PCa patients. SNP were determined by real-time polymerase chain reaction. TaqMan SNP genotyping assay. In the control samples, the SNPs were defined in association with the self-reported ethnicity, and in 218 control samples with markers with ancestry indicators. The genes were in Hardy-Weinberg equilibrium. One hundred and seventy control samples were matched by ethnicity for comparison with the PCa samples.

RESULTS

The G allele at rs28931588 was monomorphic in both patients and controls studied. Significant differences were observed in allelic and genotypic frequencies between the control and Pca samples in rs2735839 (KLK3; p = 0.002 and χ2  = 8.73 and p = 0.01, respectively), by the global frequency and in the dominant model rs2735839_GG (odds ratio [OR] = 0.51, p = 0.02). AA and GA genotypes at rs4792311 (ELAC2) were more frequent in patients with Gleason 7(4 + 3), 8, and 9 (n = 37%-59.7%) compared to patients with Gleason 6 and 7(3 + 4) (n = 26%-40.0%) conferring a protective effect on the GG genotype (OR = 0.45, p = 0.02). The same genotype showed an OR = 2.71 (p = 0.01) for patients with low severity. The HNF1B-KLK3-ELAC2-TMPRSS2-ERG haplotypes: GAAT, AAAT, GAGT, and AAGT were more frequent in patients with Pca with OR ranging from 4.65 to 2.48.

CONCLUSIONS

Higher frequencies of risk alleles were confirmed in the SNPs, KLK3 rs2735839_A, ELAC2 rs4792311_A, and TMPRSS2 rs12329760_T in patients with Pca. Rs2735839_A was associated with risk of Pca and rs4792311_A with severity and Gleason score of 7(4 + 3) or greater. There is a need for careful observation of rs2735839 and rs4792311 in association with the prostatic biopsy due to the increased risk of Pca.

How to avoid prostate biopsy in men with Prostate Image-Reporting and Data System 3 lesion? Development and external validation of new biopsy indication using prostate health index density

Background

To develop a customized prostate biopsy indication using prostate health index density (PHID) combined with multiparametric magnetic resonance imaging (mpMRI) and assess the reliability of the PHID cutoff value in external populations.

Methods

A total of 521 cognitive MRI/ultrasonography fusion prostate biopsies and biomarker tests for prostate-specific antigen (PSA), free PSA, and PHI were performed after mpMRI. The predictive value for clinically significant prostate cancer (csPCa; Gleason score≥7) of PSA derivatives was examined using the ROC curve. We developed a new biopsy indication utilizing a PHID cutoff based on the Prostate Image-Reporting and Data System (PI-RADS) score, which was externally validated.

Results

The combination of PHID and mpMRI (AUC = 0.884) demonstrated the highest predictive ability for csPCa, although PHID (AUC = 0.843) and PI-RADS (AUC = 0.806) individually also showed a high diagnostic value. When a PHID cutoff of 0.75 was used in men with PI-RADS 3 lesions, the negative predictive value of csPCa was 100%, and approximately half of the biopsies could be safely avoided.

Conclusion

Compared to PHID or PI-RADS scores alone, the combination of PHID and PI-RADS scores increased the accuracy of csPCa detection and the number of cases in which biopsy could be avoided. In men with PI-RADS 3 lesions, the optimal PHID cutoff ≥0.75 can prevent half of the unnecessary biopsies without missing csPCa. In men with PI-RADS 4-5 lesions, biopsies are warranted regardless of PHID values because csPCa could be accompanied by low PHID.

Validation of Epstein criteria and development of a nomogram for active surveillance in a contemporary Chinese population

PURPOSE

To evaluate the Epstein criteria for insignificant prostate cancer (CaP) prediction in a contemporary Chinese population, and to develop a risk model with combined clinical and systematic biopsy and targeted biopsy parameters for active surveillance.

METHODS

A total of 249 CaP patients with biopsy Gleason score (GS) of 6 were included. One hundred and one patients were eligible for insignificant CaP on final pathology (GS ≤6 and organ-confined). Diagnostic tests were used to validate the ability of the 2 Epstein criteria. Univariate and multivariate regression analyses were performed to identify predictors of insignificant CaP for the development of predictive models. Receiver operating characteristics analysis was used to select the best model, followed by risk nomogram construction and internal validation.

RESULTS

There were 47 patients met EC1 and 61 met EC2, with pathological upgrading rates of 36% and 41%, respectively, and 70% (71/101) and 64% (65/101) were missed, with areas under the curve of 0.591 and 0.594, respectively. Four prediction models were developed using regression analysis, and model 2 incorporating age, prostate-specific antigen density, maximum percentage of core involvement at systematic biopsy, and percentage of positive cores at targeted biopsy showed the best diagnostic value (area under the curve = 0.731, sensitivity 62.4%, specificity 77.0%) and was used to construct the nomogram. Calibration curves and decision curve analysis demonstrated favorable calibration (mean absolute error 0.048) and clinical benefits of the novel nomogram.

CONCLUSION

The Epstein criteria need to be revised by incorporating targeted biopsy parameters to improve diagnostic performance, and a novel nomogram was developed with better prediction of insignificant CaP.

Beyond blood biomarkers: the role of SelectMDX in clinically significant prostate cancer identification

INTRODUCTION

New potential biomarkers to pre-intervention identification of a clinically significant prostate cancer (csPCa) will prevent overdiagnosis and overtreatment and limit quality of life impairment of PCa patients.

AREAS COVERED

We have developed a comprehensive review focusing our research on the increasing knowledge of the role of SelectMDX® in csPCa detection. Areas identified as clinically relevant are the ability of SelectMDX® to predict csPCa in active surveillance setting, its predictive ability when combined with multiparametric MRI and the role of SelectMDX® in the landscape of urinary biomarkers.

EXPERT OPINION

Several PCa biomarkers have been developed either alone or in combination with clinical variables to improve csPCa detection. SelectMDX® score includes genomic markers, age, PSA, prostate volume, and digital rectal examination. Several studies have shown consistency in the ability to improve detection of csPCa, avoidance of unnecessary prostate biopsies, helpful in decision-making for clinical benefit of PCa patients with future well designed, and impactful studies.

Relationship between Proclarix and the Aggressiveness of Prostate Cancer

INTRODUCTION

Proclarix is a CE-marked test that provides the risk of clinically significant prostate cancer (csPCa), ranging from 0% to 100%, based on the serum measurement of Thrombospondin-1, cathepsin D, prostate-specific antigen (PSA), and percentage of free PSA in addition to age. We hypothesize that Proclarix could be correlated with PCa aggressiveness. We analyzed the association of this new biomarker with four surrogates of aggressiveness: grade group (GG) in the biopsy, clinical stage, risk of biochemical recurrence after primary treatment of localized PCa, and pathology in the surgical specimen.

MATERIAL AND METHODS

This is a retrospective study from 606 men with suspicion of PCa [PSA of ≥ 3.0 ng/mL and/or abnormal digital rectal examination (DRE)], in whom Proclarix was assessed (0-100%). The GG was defined by the International Society of Urological Pathology categories. The TNM was used for clinical staging (cT based on DRE, whereas cN and cM were established with computed tomography and 99-technetium bone scintigraphy). The risk of biochemical recurrence of localized PCa after primary treatment was defined by combining PSA, GG, and cT. Finally, an unfavorable pathology in a surgical specimen was defined as GG > 2 or pT ≥ 3.

RESULTS

The median age of the cohort was 67 years old, with a median PSA of 7 ng/mL and a rate of abnormal DRE of 23.3%. CsPCa was detected in 254 men (41.9%), with a median Proclarix of 60.1% compared with 37.3% obtained in patients with insignificant PCa and 20.7% in men without PCa. Among patients with GG > 3, Proclarix was significantly higher (58.2%) than in those with GG of 3 or lower (33.1%, p < 0.001). Men with localized tumors exhibited a Proclarix median of 37.3% compared with those with advanced disease (60.1%, p < 0.001). Proclarix levels among 197 patients with low and intermediate risk of biochemical recurrence were 24.9% and 35.0%, respectively, significantly lower compared with patients with high-risk disease (58.7%, p < 0.001). Unfavorable pathology was observed in 35 patients out of the 79 who underwent radical prostatectomy, with a Proclarix median of 35.7% compared with 23.7% obtained in patients with favorable pathology (p = 0.013). Proclarix and magnetic resonance imaging were independent predictors of the four surrogates of aggressiveness analyzed.

CONCLUSION

There is a correlation between Proclarix and the aggressiveness of PCa.

Optimal PSA density threshold and predictive factors for the detection of clinically significant prostate cancer in patient with a PI-RADS 3 lesion on MRI

INTRODUCTION

While Prostate Imaging Reporting and Data System (PI-RADS) 4 and 5 lesions usually justify prostate biopsy (PBx), the management of a PI-RADS 3 lesion can be discussed. The aim of our study was to determine the optimal prostate-specific antigen density (PSAD) threshold and predictive factors of clinically significant prostate cancer (csPCa) in patients with a PI-RADS 3 lesion on MRI.

PATIENTS AND METHODS

Using our prospectively maintained database, we conducted a monocentric retrospective study, including all patients with a clinical suspicious of prostate cancer (PCa), all of them had a PI-RADS 3 lesion on the mpMRI prior to PBx. Patients under active surveillance or displaying suspicious digital rectal examination were excluded. Clinically significant (csPCa) was defined as PCa with any ISUP grade group ≥ 2 (Gleason ≥ 3 + 4).

RESULTS

We included 158 patients. The detection rate of csPCa was 22.2%. In case of PSAD ≤ 0.15 ng/ml/cm³, PBx would be omitted in 71.5% (113/158) of men at the cost of missing 15.0% (17/113) of csPCa. With a threshold of 0.15 ng/ml/cm³, the sensitivity and the specificity were 0.51 and 0.78 respectively. The positive predictive value was 0.40 and the negative predictive value was 0.85. According to multivariate analysis, age (OR = 1.10, CI95% 1.03-1.19, P = 0.007), and PSAD ≥ 0.15 ng/ml/cm³ (OR = 3.59, CI95% 1.41-9.47, P = 0.008) were independent predictive factors of csPCa. Previous negative PBx was negatively associated with csPCa (OR = 0.24, CI 95% 0.07-0.66, P = 0.01).

CONCLUSION

Our result suggests that the optimal PSAD threshold was 0.15 ng/ml/cm³. However, in this case omitting PBx in 71.5% of cases would be at the cost of missing 15.0% of csPCa. PSAD should not be used alone, other predictive factors as age and PBx history should also be considered in the discussion with the patient, to avoid PBx while missing few csPCa.

The Association of Prostate Cancer and Urinary Tract Infections: A New Perspective of Prostate Cancer Pathogenesis

Background and objectives: Microbiota of the urinary tract may be associated with urinary tract malignancy, including prostate cancer. Materials and Methods: We retrospectively collected patients with newly diagnosed prostate cancer and subjects without prostate cancer from the National Health Insurance Research Database (NHIRD) in Taiwan between 1 January 2000 and 31 December 2016. A total of 5510 subjects were recruited and followed until the diagnosis of a primary outcome (urinary tract infection, pyelonephritis, cystitis, and prostatitis). Results: We found that the patients with prostate cancer had a significantly higher risk of urinary tract infections than those without prostate cancer. The adjusted hazard ratios for pyelonephritis, prostatitis, and cystitis were 2.30 (95% CI = 1.36–3.88), 2.04 (95% CI = 1.03–4.05), and 4.02 (95 % CI = 2.11–7.66), respectively. We clearly identified the sites of infection and associated comorbidities in the prostate cancer patients with urinary tract infections. In addition, we found that the patients receiving radiotherapy and androgen deprivation therapy had a lower risk of urinary tract infections than the patients in corresponding control groups. Conclusions: Our study suggests that an abnormal urine microbiome could potentially contribute to the development of prostate cancer through inflammation and immune dysregulation. Furthermore, an imbalanced microbiome may facilitate bacterial overgrowth in urine, leading to urinary tract infections. These findings have important implications for the diagnosis and treatment of prostate cancer. Further research is needed to better understand the role of the urine microbiome in prostate cancer pathogenesis and to identify potential microbiome-targeted therapies for the prevention and treatment of prostate cancer.

Vitamin D, a Regulator of Androgen Levels, Is Not Correlated to PSA Serum Levels in a Cohort of the Middle Italy Region Participating to a Prostate Cancer Screening Campaign

Prostate cancer (PCa) is the most common non-cutaneous malignancy in men worldwide, and it represents the fifth leading cause of death. It has long been recognized that dietary habits can impact prostate health and improve the benefits of traditional medical care. The activity of novel agents on prostate health is routinely assessed by measuring changes in serum prostate-specific antigen (PSA) levels. Recent studies hypothesized that vitamin D supplementation reduces circulating androgen levels and PSA secretion, inhibits cell growth of the hormone-sensitive PCa cell lines, counteracts neoangiogenesis and improves apoptosis. However, the results are conflicting and inconsistent. Furthermore, the use of vitamin D in PCa treatments has not achieved consistently positive results to date. In order to assess the existence of a correlation between the PSA and 25(OH)vitamin D levels as widely hypothesized in the literature, we analyzed the serum PSA and 25(OH)vitamin D concentration on a cohort of one hundred patients joining a PCa screening campaign. Additionally, we performed medical and pharmacological anamnesis and analyzed lifestyle, as sport practice and eating habits, by administering a questionnaire on family history. Although several studies suggested a protective role of vitamin D in PCa onset prevention and progression, our preliminary results revealed a clear absence of correlation between the serum vitamin D and PSA concentration levels, suggesting that vitamin D has no impact on PCa risk. Further investigations enrolling a huge number of patients are needed with particular attention to vitamin D supplementation, calcium intake, solar radiation that influences vitamin D metabolism and other potential indicators of health to confirm the absence of correlation observed in our study.

A Neural Network Model Combining [-2]proPSA, freePSA, Total PSA, Cathepsin D, and Thrombospondin-1 Showed Increased Accuracy in the Identification of Clinically Significant Prostate Cancer

BACKGROUND

The Prostate Health Index (PHI) and Proclarix (PCLX) have been proposed as blood-based tests for prostate cancer (PCa). In this study, we evaluated the feasibility of an artificial neural network (ANN)-based approach to develop a combinatorial model including PHI and PCLX biomarkers to recognize clinically significant PCa (csPCa) at initial diagnosis.

METHODS

To this aim, we prospectively enrolled 344 men from two different centres. All patients underwent radical prostatectomy (RP). All men had a prostate-specific antigen (PSA) between 2 and 10 ng/mL. We used an artificial neural network to develop models that can identify csPCa efficiently. As inputs, the model uses [-2]proPSA, freePSA, total PSA, cathepsin D, thrombospondin, and age.

RESULTS

The output of the model is an estimate of the presence of a low or high Gleason score PCa defined at RP. After training on a dataset of up to 220 samples and optimization of the variables, the model achieved values as high as 78% for sensitivity and 62% for specificity for all-cancer detection compared with those of PHI and PCLX alone. For csPCa detection, the model showed 66% (95% CI 66-68%) for sensitivity and 68% (95% CI 66-68%) for specificity. These values were significantly different compared with those of PHI (p < 0.0001 and 0.0001, respectively) and PCLX (p = 0.0003 and 0.0006, respectively) alone.

CONCLUSIONS

Our preliminary study suggests that combining PHI and PCLX biomarkers may help to estimate, with higher accuracy, the presence of csPCa at initial diagnosis, allowing a personalized treatment approach. Further studies training the model on larger datasets are strongly encouraged to support the efficiency of this approach.

Biomarkers of Aggressive Prostate Cancer at Diagnosis

In the United States, prostate cancer (CaP) remains the second leading cause of cancer deaths in men. CaP is predominantly indolent at diagnosis, with a small fraction (25-30%) representing an aggressive subtype (Gleason score 7-10) that is prone to metastatic progression. This fact, coupled with the criticism surrounding the role of prostate specific antigen in prostate cancer screening, demonstrates the current need for a biomarker(s) that can identify clinically significant CaP and avoid unnecessary biopsy procedures and psychological implications of being diagnosed with low-risk prostate cancer. Although several diagnostic biomarkers are available to clinicians, very few comparative trials have been performed to assess the clinical effectiveness of these biomarkers. It is of note, however, that a majority of these clinical trials have been over-represented by men of Caucasian origin, despite the fact that African American men have a 1.7 times higher incidence and 2.1 times higher rate of mortality from prostate cancer. Biomarkers for CaP diagnosis based on the tissue of origin include urine-based gene expression assays (PCA3, Select MDx, ExoDx Prostate IntelliScore, Mi-Prostate Score, PCA3-PCGEM1 gene panel), blood-based protein biomarkers (4K, PHI), and tissue-based DNA biomarker (Confirm MDx). Another potential direction that has emerged to aid in the CaP diagnosis include multi-parametric magnetic resonance imaging (mpMRI) and bi-parametric magnetic resonance imaging (bpMRI), which in conjunction with clinically validated biomarkers may provide a better approach to predict clinically significant CaP at diagnosis. In this review, we discuss some of the adjunctive biomarker tests along with newer imaging modalities that are currently available to help clinicians decide which patients are at risk of having high-grade CaP on prostate biopsy with the emphasis on clinical utility of the tests across African American (AA) and Caucasian (CA) men.

Improving the Effective Spatial Resolution in 1H-MRSI of the Prostate with Three-Dimensional Overdiscretized Reconstructions

In in vivo ¹H-MRSI of the prostate, small matrix sizes can cause voxel bleeding extending to regions far from a voxel, dispersing a signal of interest outside that voxel and mixing extra-prostatic residual lipid signals into the prostate. To resolve this problem, we developed a three-dimensional overdiscretized reconstruction method. Without increasing the acquisition time from current 3D MRSI acquisition methods, this method is aimed to improve the localization of metabolite signals in the prostate without compromising on SNR. The proposed method consists of a 3D spatial overdiscretization of the MRSI grid, followed by noise decorrelation with small random spectral shifts and weighted spatial averaging to reach a final target spatial resolution. We successfully applied the three-dimensional overdiscretized reconstruction method to 3D prostate ¹H-MRSI data at 3T. Both in phantom and in vivo, the method proved to be superior to conventional weighted sampling with Hamming filtering of k-space. Compared with the latter, the overdiscretized reconstructed data with smaller voxel size showed up to 10% less voxel bleed while maintaining higher SNR by a factor of 1.87 and 1.45 in phantom measurements. For in vivo measurements, within the same acquisition time and without loss of SNR compared with weighted k-space sampling and Hamming filtering, we achieved increased spatial resolution and improved localization in metabolite maps.

Landmarks in the evolution of prostate biopsy

Approaches and techniques used for diagnostic prostate biopsy have undergone considerable evolution over the past few decades: from the original finger-guided techniques to the latest MRI-directed strategies, from aspiration cytology to tissue core sampling, and from transrectal to transperineal approaches. In particular, increased adoption of transperineal biopsy approaches have led to reduced infectious complications and improved antibiotic stewardship. Furthermore, as image fusion has become integral, these novel techniques could be incorporated into prostate biopsy methods in the future, enabling 3D-ultrasonography fusion reconstruction, molecular targeting based on PET imaging and autonomous robotic-assisted biopsy.

Role of inflammatory factors in prediction of Gleason score and its upgrading in localized prostate cancer patients after radical prostatectomy

Purpose

To investigate the role of inflammatory factors including systemic immune-inflammation index (SII) and neutrophil to lymphocyte ratio (NLR) in predicting Gleason Score (GS) and Gleason Score upgrading (GSU) in localized prostate cancer (PCa) after radical prostatectomy (RP).

Methods

The data of 297 patients who underwent prostate biopsy and RP in our center from January 2014 to March 2020 were retrospectively analyzed. Preoperative clinical characteristics including age, values of tPSA, total prostate volume (TPV), f/t PSA ratio, body mass index (BMI), biopsy GS and inflammatory factors including SII, NLR, lymphocyte to monocyte (LMR), neutrophil ratio (NR), platelet to lymphocyte ratio (PLR), lymphocyte ratio (LR), mean platelet volume (MPV) and red cell distribution (RDW) as well as pathological T (pT) stage were collected and compared according to the grades of RP GS (GS ≤ 6 and GS≥7), respectively. ROC curve analysis was used to confirm the discriminative ability of inflammatory factors including SII, NLR and their combination with tPSA for predicting GS and GSU. By using univariate and multivariate logistic regression analysis, the association between significant inflammatory markers and grades of GS were evaluated.

Results

Patients enrolled were divided into low (GS ≤ 6) and high (GS≥7) groups by the grades of GS. The median values of clinical factors were 66.08 ± 6.04 years for age, 36.62 ± 23.15 mL for TPV, 26.16 ± 33.59 ng/mL for tPSA and 0.15 ± 0.25 for f/t PSA ratio, 22.34 ± 3.14 kg/m² for BMI, 15 (5.1%) were pT1, 116 (39.1%) were pT2 and 166 (55.9%) were pT3. According to the student's t test, patients in high GS group had a greater proportion of patients with pT3 (P<0.001), and higher NLR (P=0.04), SII (P=0.037) and tPSA (P=0.015) compared with low GS group, the distribution of age, TPV, f/t PSA ratio, BMI, LMR, NR, PLR, LR, MPV and RDW did not show any significantly statistical differences. The AUC for SII, NLR and tPSA was 0.732 (P=0.007), 0.649 (P=0.045) and 0.711 (P=0.015), with threshold values of 51l.08, 2.3 and 10.31ng/mL, respectively. According to the multivariable logistic regression models, NLR ≥ 2.3 (OR, 2.463; 95% CI, 0.679-10.469, P=0.042), SII ≥ 511.08 (OR, 3.519; 95% CI 0.891-12.488; P=0.003) and tPSA ≥ 10.31 ng/mL (OR, 4.146; 95% CI, 1.12-15.35; P=0.033) were all independent risk factors associated with higher GS. The AUC for combination of SII, NLR with tPSA was 0.758 (P=0.003) and 0.756 (P=0.003), respectively. GSU was observed in a total of 48 patients with GS ≤ 6 (55.17%). Then patients were divided into 2 groups (high and low) according to the threshold value of SII, NLR, tPSA, SII+tPSA and NLR+tPSA, respectively, when the GSU rates were compared with regard to these factors, GSU rate in high level group was significantly higher than that in low level group, P=0.001, 0.044, 0.017, <0.001 and <0.001, respectively.

Conclusion

High SII, NLR and tPSA were associated with higher GS and higher GSU rate. SII was likely to be a more favorable biomarker for it had the largest AUC area compared with tPSA and NLR; the combination of SII or NLR with tPSA had greater values for predicting GS and GSU compared with NLR, SII or tPSA alone, since the AUC area of combination was much higher. SII, NLR were all useful inflammatory biomarkers for predicting GS and detecting GSU among localized PCa patients with biopsy GS ≤ 6.

Aquaporins as Prognostic Biomarker in Prostate Cancer

Prostate cancer is a complex heterogeneous disease that affects millions of males worldwide. Despite rapid advances in molecular biology and innovation in technology, few biomarkers have been forthcoming in prostate cancer. The currently available biomarkers for the prognosis of prostate cancer are inadequate and face challenges, thus having limited clinical utility. To date, there are a number of prognostic and predictive biomarkers identified for prostate cancer but lack specificity and sensitivity to guide clinical decision making. There is still tremendous scope for specific biomarkers to understand the natural history and complex biology of this heterogeneous disease, and to identify early treatment responses. Accumulative studies indicate that aquaporins (AQPs) a family of membrane water channels may serve as a prognostic biomarker for prostate cancer in monitoring disease advancement. In the present review, we discuss the existing prostate cancer biomarkers, their limitations, and aquaporins as a prospective biomarker of prognostic significance in prostate cancer.

Zinc in Prostate Health and Disease: A Mini Review

Introduction-With the high global prevalence of prostate cancer and associated mortalities, it is important to enhance current clinical practices for better prostate cancer outcomes. The current review is towards understanding the value of Zn towards this mission. Method-General information on Zn in biology and multiple aspects of Zn involvement in prostate health and disease were referred to in PubMed. Results-The most influential feature of Zn towards prostate health is its ability to retain sufficient citrate levels for a healthy prostate. Zn deficiencies were recorded in serum, hair, and prostate tissue of men with prostate cancer compared to non-cancer controls. Zn gut absorption, albumin binding, and storage compete with various factors. There are multiple associations of Zn cellular influx and efflux transporters, Zn finger proteins, matrix metalloproteinases, and Zn signaling with prostate cancer outcomes. Such Zn marker variations associated with prostate cancer recorded from biological matrices may improve algorithms for prostate cancer screening, prognosis, and management when coupled with standard clinical practices. Discussion-The influence of Zn in prostatic health and disease is multidimensional, therefore more personalized Zn requirements may be beneficial. Several opportunities exist to utilize and improve understanding of Zn associations with prostate health and disease.

Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI

INTRODUCTION

On prostate biopsy, multiparametric magnetic resonance imaging (mpMRI) and the Prostate Health Index (PHI) have allowed prediction of clinically significant prostate cancer (csPCa).

METHODS

To predict the likelihood of csPCa, we created a nomogram based on a multivariate model that included PHI and mpMRI. We assessed 315 males who were scheduled for prostate biopsies.

RESULTS

We used the Prostate Imaging Reporting and Data System version 2 (PI-RADS V2) to assess mpMRI and optimize PHI testing prior to biopsy. Univariate analysis showed that csPCa may be identified by PHI with a cut-off value of 77.77, PHID with 2.36, and PI-RADS with 3 as the best threshold. Multivariable logistic models for predicting csPCa were developed using PI-RADS, free PSA (fPSA), PHI, and prostate volume. A multivariate model that included PI-RADS, fPSA, PHI, and prostate volume had the best accuracy (AUC: 0.882). Decision curve analysis (DCA), which was carried out to verify the nomogram's clinical applicability, showed an ideal advantage (13.35% higher than the model that include PI-RADS only).

DISCUSSION

In conclusion, the nomogram based on PHI and mpMRI is a valuable tool for predicting csPCa while avoiding unnecessary biopsy as much as possible.

8-Hydroxy-2-Deoxyguanosine and 8-Iso-Prostaglandin F2α: Putative Biomarkers to assess Oxidative Stress Damage Following Robot-Assisted Radical Prostatectomy (RARP)

Objective: Prostate cancer (PCa) is the most common type of cancer. Biomarkers help researchers to understand the mechanisms of disease and refine diagnostic panels. We measured urinary 8-hydroxy-2-deoxyguanosine (8-OHdG) and 8-iso-prostaglandin F2α (8-IsoF2α) to assess oxidative stress damage in PCa patients undergoing robot-assisted radical prostatectomy (RARP). Methods: Forty PCa patients were enrolled in the study. Urine was collected before (T0) and 3 months after the RARP procedure (T1). 8-OHdG and 8-IsoF2α were measured through liquid chromatography-tandem mass spectrometry. Sex- and age-matched healthy subjects served as controls (CTRL). Results: At T0, patients exhibited significantly higher levels of 8-OHdG than CTRL (p = 0.026). At T1, 23/40 patients who completed the 3-month follow-up showed levels of 8-OHdG that were significantly lower than at T0 (p = 0.042), and comparable to those of the CTRL subjects (p = 0.683). At T0, 8-Iso-PGF2α levels were significantly higher in PCa patients than in CTRL subjects (p = 0.0002). At T1, 8-Iso-PGF2α levels were significantly lower than at T0 (p < 0.001) and were comparable to those of CTRL patients (p = 0.087). Conclusions: A liquid chromatography-tandem mass spectrometry method reveals enhanced OHdG and 8-Iso-PGF2α in the urine of PCa patients. RARP normalizes such indices of oxidative stress. Large-sized sample studies and long-term follow-ups are now needed to validate these urinary biomarkers for use in the early prevention and successful treatment of PCa.

PEDAL protocol: a prospective single-arm paired comparison of multiparametric MRI and 18F-DCPFyl PSMA PET/CT to diagnose prostate cancer

INTRODUCTION

Prostate-specific membrane antigen positron emission tomography (PSMA-PET) has emerged as valuable imaging to assessing metastatic disease in prostate malignancy. However, there has been limited studies exploring the utility PSMA-PET as primary imaging assessing for index lesions prior to biopsy. The primary objective of this study is to compare the diagnostic accuracy of 18-fluorine PSMA (18F DCFPyL PSMA) PET scans to multiparametric MRI (mpMRI) to detect primary prostate cancer at prostate biopsy.

METHODS AND ANALYSIS

The PEDAL trial is a multicentre, prospective, single-arm, paired comparison, non-randomised phase III trial in subjects considered for diagnostic prostate biopsy. Subjects who are eligible for a diagnostic mpMRI prostate will undergo additional same-day 18 F DCFPyl PSMA PET/CT of the chest, abdomen and pelvis. Software coregistration of the mpMRI and PSMA-PET/CT images will be performed. The reporting of the mpMRI prostate, PSMA-PET/CT and PSMA PET/MRI coregistration will be performed blinded. The diagnostic accuracy of PSMA PET/CT alone, and in combination with mpMRI, to detect prostate cancer will be assessed. Histopathology at prostate biopsy will be used as the reference standard. Sample size calculations estimate that 240 subjects will need to be recruited to demonstrate 20% superiority of PSMA-PET/CT. The sensitivity, specificity, positive predictive value and negative predictive value of the combination of mpMRI prostate and PSMA PET/CT compared with targeted and systematic prostate biopsy will be evaluated. It is hypothesised that PSMA PET/CT combined with mpMRI prostate will have improved diagnostic accuracy compared with mpMRI prostate alone for detection of prostate cancer in biopsy-naïve men, resulting in a significant impact on patient management.

ETHICS AND DISSEMINATION

This study was approved by the independent Human Research Ethics Committee. Results will be published in peer-reviewed medical journals with eligible investigators will significantly contribute.

TRIAL REGISTRATION NUMBER

ACTRN12620000261910.

The Clinical Utility of Systemic Immune-Inflammation Index Supporting Charlson Comorbidity Index and CAPRA-S Score in Determining Survival after Radical Prostatectomy-A Single Centre Study

The selection of candidates for the curative treatment of PCa requires a careful assessment of life expectancy. Recently, blood-count inflammatory markers have been introduced as prognosticators of oncological and non-oncological outcomes in different settings. This retrospective, monocentric study included 421 patients treated with radical prostatectomy (RP) for nonmetastatic PCa and aimed at determining the utility of a preoperative SII (neutrophil count × platelet count/lymphocyte count) in predicting survival after RP. Patients with high SIIs (≥900) presented significantly shorter survival (p = 0.02) and high SIIs constituted an independent predictor of overall survival [HR 2.54 (95%CI 1.24−5.21); p = 0.01] when adjusted for high (≥6) age-adjusted CCI (ACCI) [HR 2.75 (95%CI 1.27−5.95); p = 0.01] and high (≥6) CAPRA-S [HR 2.65 (95%CI 1.32−5.31); p = 0.006]. Patients with high scores (ACCI and/or CAPRA-S) and high SIIs were at the highest risk of death (p < 0.0001) with approximately a one-year survival loss during the first seven years after surgery. In subgroup of high CAPRA-S (≥6), patients with high ACCIs and high SIIs were at the highest risk of death (p <0.0001). Our study introduces the SII as a straightforward marker of mortality after RP that can be helpful in pre- and postoperative decision-making.

m6A Methylation Regulators Are Predictive Biomarkers for Tumour Metastasis in Prostate Cancer

Simple Summary

Recurrence and metastatic progression always lead to dismal outcomes in prostate cancer (PCa). There is no reliable biomarker for the prediction of recurrence and metastasis other than the Prostate Cancer Antigen (PCA). N6-methyladenosine (m⁶A) is the most common post-transcriptional mRNA modification and is regulated by m⁶A regulators dynamically. Since m⁶A modification is associated with cancer development and outgrowth, we performed a consensus clustering on PCa with regard to the gene expression of all m⁶A regulators. We identified three subtypes of Pca with distinct m⁶A expression patterns and enriched biological pathways. We also established an m⁶A score for metastasis prediction based on our clustering, which is potentially a predictive biomarker for Pca metastasis.

Abstract

Prostate cancer (PCa) is one of the most common cancers in men. Usually, most PCas at initial diagnosis are localized and hormone-dependent, and grow slowly. Patients with localized PCas have a nearly 100% 5-year survival rate; however, the 5-year survival rate of metastatic or progressive PCa is still dismal. N6-methyladenosine (m⁶A) is the most common post-transcriptional mRNA modification and is dynamically regulated by m⁶A regulators. A few studies have shown that the abnormal expression of m⁶A regulators is significantly associated with cancer progression and immune cell infiltration, but the roles of these regulators in PCa remain unclear. Here, we examined the expression profiles and methylation levels of 21 m⁶A regulators across the Cancer Genome Atlas (TCGA), 495 PCas by consensus clustering, and correlated the expression of m⁶A regulators with PCa progression and immune cell infiltration. Consensus clustering was applied for subtyping Pca samples into clusters based on the expression profiles of m⁶A regulators. Each subtype’s signature genes were obtained by a pairwise differential expression analysis. Featured pathways of m⁶A subtypes were predicted by Gene Ontology. The m⁶A score was developed to predict m⁶A activation. The association of the m⁶A score with patients’ survival, metastasis and immune cell infiltration was also investigated. We identified three distinct clusters in PCa based on the expression profiles of 21 m⁶A regulators by consensus clustering. The differential expression and pathway analyses on the three clusters uncovered the m⁶A regulators involved in metabolic processes and immune responses in PCa. Moreover, we developed an m⁶A score to evaluate the m⁶A regulator activation for PCa. The m⁶A score is significantly associated with Gleason scores and metastasis in PCa. The predictive capacity of the m⁶A score on PCa metastasis was also validated in another independent cohort with an area under the curve of 89.5%. Hence, our study revealed the critical role of m⁶A regulators in PCa progression and the m⁶A score is a promising predictive biomarker for PCa metastasis.

Multiparametric MRI for Staging of Prostate Cancer: A Multicentric Analysis of Predictive Factors to Improve Identification of Extracapsular Extension before Radical Prostatectomy

Simple Summary

In this multicentric study, we tested the accuracy of multiparametric magnetic resonance imaging (mpMRI) in detecting extracapsular extension (ECE) out of the prostate in order to plan surgical sparing of neurovascular bundles in radical prostatectomy. Univariate and multivariate logistic regression analyses were performed to identify other risk factors for ECE. We found that it has a good ability to exclude extracapsular extension but a poor ability to identify it correctly. Risk factors other than mpMRI that predicted ECE were as follows: prostatic specific antigen, digital rectal examination, ratio of positive cores, and biopsy grade group. We suggest that using mpMRI exclusively should not be recommended to decide on surgical approaches.

Abstract

The correct identification of extracapsular extension (ECE) of prostate cancer (PCa) on multiparametric magnetic resonance imaging (mpMRI) is crucial for surgeons in order to plan the nerve-sparing approach in radical prostatectomy. Nerve-sparing strategies allow for better outcomes in preserving erectile function and urinary continence, notwithstanding this can be penalized with worse oncologic results. The aim of this study was to assess the ability of preoperative mpMRI to predict ECE in the final prostatic specimen (PS) and identify other possible preoperative predictive factors of ECE as a secondary end-point. We investigated a database of two high-volume hospitals to identify men who underwent a prostate biopsy with a pre-biopsy mpMRI and a subsequent RP. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of mpMRI in predicting ECE were calculated. A univariate analysis was performed to find the association between image staging and pathological staging. A multivariate logistic regression was performed to investigate other preoperative predictive factors. A total of 1147 patients were selected, and 203 out of the 1147 (17.7%) patients were classified as ECE according to the mpMRI. ECE was reported by pathologists in 279 out of the 1147 PS (24.3%). The PPV was 0.58, the NPV was 0.72, the sensitivity was 0.32, and the specificity was 0.88. The multivariate analysis found that PSA (OR 1.057, C.I. 95%, 1.016–1.100, p = 0.006), digital rectal examination (OR 0.567, C.I. 95%, 0.417–0.770, p = 0.0001), ratio of positive cores (OR 9.687, C.I. 95%, 3.744–25.006, p = 0.0001), and biopsy grade in prostate biopsy (OR 1.394, C.I. 95%, 1.025–1.612, p = 0.0001) were independent factors of ECE. The mpMRI has a great ability to exclude ECE, notwithstanding that low sensitivity is still an important limitation of the technique.

Prostate health index (PHI) as a reliable biomarker for prostate cancer: a systematic review and meta-analysis

OBJECTIVES

Prostate cancer (PCa) represents the second most common solid cancer in men worldwide. In the last decades, the prostate health index (PHI) emerged as a reliable biomarker for detecting PCa and differentiating between non-aggressive and aggressive forms. However, before introducing it in clinical practice, more evidence is required. Thus, we performed a systematic review and meta-analysis for assessing the diagnostic performance of PHI for PCa and for detecting clinically significant PCa (csPCa).

METHODS

Relevant publications were identified by a systematic literature search on PubMed and Web of Science from inception to January 11, 2022.

RESULTS

Sixty studies, including 14,255 individuals, met the inclusion criteria for our meta-analysis. The pooled sensitivity and specificity of PHI for PCa detection was 0.791 (95%CI 0.739-0.834) and 0.625 (95%CI 0.560-0.686), respectively. The pooled sensitivity and specificity of PHI for csPCa detection was 0.874 (95%CI 0.803-0.923) and 0.569 (95%CI 0.458-0.674), respectively. Additionally, the diagnostic odds ratio was 6.302 and 9.206, respectively, for PCa and csPCa detection, suggesting moderate to good effectiveness of PHI as a diagnostic test.

CONCLUSIONS

PHI has a high accuracy for detecting PCa and discriminating between aggressive and non-aggressive PCa. Thus, it could be useful as a biomarker in predicting patients harbouring more aggressive cancer and guiding biopsy decisions.

Machine Learning and Clinical-Radiological Characteristics for the Classification of Prostate Cancer in PI-RADS 3 Lesions

The Prostate Imaging Reporting and Data System (PI-RADS) classification is based on a scale of values from 1 to 5. The value is assigned according to the probability that a finding is a malignant tumor (prostate carcinoma) and is calculated by evaluating the signal behavior in morphological, diffusion, and post-contrastographic sequences. A PI-RADS score of 3 is recognized as the equivocal likelihood of clinically significant prostate cancer, making its diagnosis very challenging. While PI-RADS values of 4 and 5 make biopsy necessary, it is very hard to establish whether to perform a biopsy or not in patients with a PI-RADS score 3. In recent years, machine learning algorithms have been proposed for a wide range of applications in medical fields, thanks to their ability to extract hidden information and to learn from a set of data without previous specific programming. In this paper, we evaluate machine learning approaches in detecting prostate cancer in patients with PI-RADS score 3 lesions via considering clinical-radiological characteristics. A total of 109 patients were included in this study. We collected data on body mass index (BMI), location of suspicious PI-RADS 3 lesions, serum prostate-specific antigen (PSA) level, prostate volume, PSA density, and histopathology results. The implemented classifiers exploit a patient’s clinical and radiological information to generate a probability of malignancy that could help the physicians in diagnostic decisions, including the need for a biopsy.

Modified Prostate Health Index Density Significantly Improves Clinically Significant Prostate Cancer (csPCa) Detection

Background

Early screening of clinically significant prostate cancer (csPCa) may offer opportunities in revolutionizing the survival benefits of this lethal disease. We sought to introduce a modified prostate health index density (mPHI) model using imaging indicators and to compare its diagnostic performance for early detection of occult onset csPCa within the prostate-specific antigen (PSA) gray zone with that of PHI and PHID.

Methods and Participation

Between August 2020 and January 2022, a training cohort of 278 patients (total PSA 4.0-10.0 ng/ml) who were scheduled for a prostate biopsy were prospectively recruited. PHI and PHID were compared with mPHI ( LD TRD × APD × TPV × PHI ) for the diagnosis performance in identifying csPCa. Pathology outcomes from systematic prostate biopsies were considered the gold standard.

Results

This model was tested in a training cohort consisting of 73 csPCa, 14 non-clinically significant prostate cancer(non-csPCa), and 191 benign prostatic hyperplasia (BPH) samples. In the univariate analysis for the PSA gray zone cohort, for overall PCa, the AUC of mPHI (0.856) was higher than PHI (0.774) and PHID (0.835). For csPCa, the AUC of mPHI (0.859) also surpassed PHI (0.787) and PHID (0.825). For detection of csPCa, compared with lower specificities from PHI and PHID, mPHI performed the highest specificity (76.5%), by sparing 60.0% of unnecessary biopsies at the cost of missing 11 cases of csPCa. The mPHI outperformed PHI and PHID for overall PCa detection. In terms of csPCa, mPHI exceeds diagnostic performance with a better net benefit in decision curve analysis (DCA) compared with PHI or PHID.

Conclusions

We have developed a modified PHI density (mPHI) model that can sensitively distinguish early-stage csPCa patients within the PSA gray zone.

Clinical Trial Registration

ClinicalTrials.gov, NCT04251546.

A Model to Detect Significant Prostate Cancer Integrating Urinary Peptide and Extracellular Vesicle RNA Data

There is a clinical need to improve assessment of biopsy-naïve patients for the presence of clinically significant prostate cancer (PCa). In this study, we investigated whether the robust integration of expression data from urinary extracellular vesicle RNA (EV-RNA) with urine proteomic metabolites can accurately predict PCa biopsy outcome. Urine samples collected within the Movember GAP1 Urine Biomarker study (n = 192) were analysed by both mass spectrometry-based urine-proteomics and NanoString gene-expression analysis (167 gene-probes). Cross-validated LASSO penalised regression and Random Forests identified a combination of clinical and urinary biomarkers for predictive modelling of significant disease (Gleason Score (Gs) ≥ 3 + 4). Four predictive models were developed: ‘MassSpec’ (CE-MS proteomics), ‘EV-RNA’, and ‘SoC’ (standard of care) clinical data models, alongside a fully integrated omics-model, deemed ‘ExoSpec’. ExoSpec (incorporating four gene transcripts, six peptides, and two clinical variables) is the best model for predicting Gs ≥ 3 + 4 at initial biopsy (AUC = 0.83, 95% CI: 0.77−0.88) and is superior to a standard of care (SoC) model utilising clinical data alone (AUC = 0.71, p < 0.001, 1000 resamples). As the ExoSpec Risk Score increases, the likelihood of higher-grade PCa on biopsy is significantly greater (OR = 2.8, 95% CI: 2.1−3.7). The decision curve analyses reveals that ExoSpec provides a net benefit over SoC and could reduce unnecessary biopsies by 30%.

Radiomics in prostate cancer: an up-to-date review

Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male population. The diagnosis, the identification of aggressive disease, and the post-treatment follow-up needs a more comprehensive and holistic approach. Radiomics is the extraction and interpretation of images phenotypes in a quantitative manner. Radiomics may give an advantage through advancements in imaging modalities and through the potential power of artificial intelligence techniques by translating those features into clinical outcome prediction. This article gives an overview on the current evidence of methodology and reviews the available literature on radiomics in PCa patients, highlighting its potential for personalized treatment and future applications.

Biomarkers for prostate cancer detection and risk stratification

Although prostate cancer (PCa) is the most commonly diagnosed cancer in men, most patients do not die from the disease. Prostate specific antigen (PSA), the most widely used oncologic biomarker, has revolutionized screening and early detection, resulting in reduced proportion of patients presenting with advanced disease. However, given the inherent limitations of PSA, additional diagnostic and prognostic tools are needed to facilitate early detection and accurate risk stratification of disease. Serum, urine, and tissue-based biomarkers are increasingly being incorporated into the clinical care paradigm, but there is still a limited understanding of how to use them most effectively. In the current article, we review test characteristics and clinical performance data for both serum [4 K score, prostate health index (phi)] and urine [SelectMDx, ExoDx Prostate Intelliscore, MyProstateScore (MPS), and PCa antigen 3 (PCA3)] biomarkers to aid decisions regarding initial or repeat biopsies as well as tissue-based biomarkers (Confirm MDx, Decipher, Oncotype Dx, and Polaris) aimed at risk stratifying patients and identifying those patients most likely to benefit from treatment versus surveillance or monotherapy versus multi-modal therapy.

Health-Related Quality of Life following Cytoreductive Radical Prostatectomy in Patients with De-Novo Oligometastatic Prostate Cancer

Simple Summary

Recent retrospective data indicate a survival benefit of surgical removal of the prostate in patients with oligometastatic prostate cancer as part of a multimodal therapeutic regime. However, the impact of radical prostatectomy (RP) on patient’s health-related quality of life (HRQOL) in this scenario has not been evaluated yet. In a contemporary and well-balanced cohort, we compared the self-assessed HRQOL of patients with oligometastatic prostate cancer with patients with locally confined prostate cancer two years postoperatively. In multivariate analysis, we found no significant difference in postoperative HRQOL and urinary continence recovery in patients with de-novo oligo-metastatic compared to patients with locally confined prostate cancer.

Abstract

(1) Background: local treatment of the primary tumor has become a valid therapeutic option in de-novo oligo-metastatic prostate cancer (PC). However, evidence regarding radical prostatectomy (RP) in this setting is still subpar, and the effect of cytoreductive RP on postoperative health-related quality of life (HRQOL) is still unclear. (2) Methods: for the current study, patients with de-novo oligo-metastatic PC (cM1-oligo), defined as ≤5 bone lesions in the preoperative staging, were included, and matched cohorts using the variables age, body-mass index (BMI), and pT-stage were generated. Patient-reported outcome measures (PROMS) were assessed pre- and postoperatively using the validated EORTC-QLQ-C30, IIEF-5, and ICIQ-SF questionnaires. The primary endpoint for univariate and multivariable analysis was good general HRQOL defined by previously validated cut-off values. (3) Results: in total, 1268 patients (n = 84 (7%) cM1-oligo) underwent RP between 2012 and 2020 at one tertiary care center. A matched cohort of 411 patients (n = 79 with oligo-metastatic bone disease (cM1-oligo) and n = 332 patients without clinical indication of metastatic disease (cM0)) was created. The median follow-up was 25mo. There was no significant difference in good general HRQOL rates between cM1-oligo-patients and cM0-patients before RP (45.6% vs. 55.2%, p = 0.186), and at time of follow-up (44% vs. 56%, p = 0.811). Global health status (GHS) worsened significantly in cM0-patients compared to baseline (−5, p = 0.001), whereas GHS did not change significantly in cM1-oligo-patients (+3.2, p = 0.381). In multivariate analysis stratified for good erectile function (IIEF5 > 18; OR 5.722, 95% CI 1.89–17.36, p = 0.002) and continence recovery (OR 1.671, 95% CI 1.03–2.70, p = 0.036), cM1-oligo was not an independent predictive feature for general HRQOL (OR 0.821, 95% CI 0.44–1.53, p = 0.536). (4) Conclusions: in this large contemporary retrospective analysis, we observed no significant difference in HRQOL in patients with the oligometastatic bone disease after cytoreductive radical prostatectomy, when compared to patients with localized disease at time of surgery.