Prostate volume predicts high grade prostate cancer both in digital rectal examination negative (ct1c) and positive (≥ct2) patients

A Prostate-Specific Membrane Antigen PET-Based Approach for Improved Diagnosis of Prostate Cancer in Gleason Grade Group 1: A Multicenter Retrospective Study

The preoperative Gleason grade group (GG) from transrectal ultrasound-guided prostate biopsy is crucial for treatment decisions but may underestimate the postoperative GG and miss clinically significant prostate cancer (csPCa), particularly in patients with biopsy GG1. In such patients, an SUVmax of at least 12 has 100% specificity for detecting csPCa. In patients with an SUVmax of less than 12, we aimed to develop a model to improve the diagnostic accuracy of csPCa. Methods: The study retrospectively included 56 prostate cancer patients with transrectal ultrasound-guided biopsy GG1 and an SUVmax of less than 12 from 2 tertiary hospitals. All [68Ga]Ga-PSMA-HBED-CC PET scans were centrally reviewed in Xijing Hospital. A deep learning model was used to evaluate the overlap of SUVmax (size scale, 3 cm) and the level of Gleason pattern (size scale, 500 μm). A diagnostic model was developed using the PRIMARY score and SUVmax, and its discriminative performance and clinical utility were compared with other methods. The 5-fold cross-validation (repeated 1,000 times) was used for internal validation. Results: In patients with GG1 and an SUVmax of less than 12, significant prostate-specific membrane antigen (PSMA) histochemical score (H-score) H-score overlap occurred among benign gland, Gleason pattern 3, and Gleason pattern 4 lesions, causing SUVmax overlap between csPCa and non-csPCa. The model of 10 × PRIMARY score + 2 × SUVmax exhibited a higher area under the curve (AUC, 0.8359; 95% CI, 0.7233-0.9484) than that found using only the SUVmax (AUC, 0.7353; P = 0.048) or PRIMARY score (AUC, 0.7257; P = 0.009) for the cohort and a higher AUC (0.8364; 95% CI, 0.7114-0.9614) than that found using only the Prostate Imaging Reporting and Data System (PI-RADS) score of 5-4 versus 3-1 (AUC, 0.7036; P = 0.149) and the PI-RADS score of 5-3 versus 2-1 (AUC, 0.6373; P = 0.014) for a subgroup. The model reduced the misdiagnosis of the PI-RADS score of 5-4 versus 3-1 by 78.57% (11/14) and the PI-RADS score of 5-3 versus 2-1 by 77.78% (14/18). The internal validation showed that the mean 5-fold cross-validated AUC was 0.8357 (95% CI, 0.8357-0.8358). Conclusion: We preliminarily suggest that the model of 10 × PRIMARY score + 2 × SUVmax may enhance the diagnostic accuracy of csPCa in patients with biopsy GG1 and an SUVmax of less than 12 by maximizing PSMA information use, reducing the misdiagnosis of the PI-RADS score, and thereby aiding in making appropriate treatment decisions.

Association between prostate size and the incidence of prostate cancer: a meta-analysis and review for urologists and clinicians

PURPOSE

To review the literature regarding any clinically significant association between prostate size and the incidence of prostate cancer (PCa). No previous review or meta-analysis has reported this clinical question.

METHODS

A thorough literature review was performed using PubMed and applying the 'PRISMA' guidelines. Inclusion and exclusion criteria were defined.

RESULTS

A total of 30 articles met the search criteria. Of these 30 articles, 27 reported an inverse correlation between prostate volume (PV) and incidence of biopsy-proven PCa. The remaining three articles provided no clear statistically significant results, and there was no study showing a direct or positive correlation between PV and the incidence of PCa.

CONCLUSION

This review and meta-analysis is the first report summarizing the literature on the clinical question of whether prostate size affects the incidence of PCa. Ninety percent of studies (27/30) show significant evidence supporting the hypothesis that prostate size may be protective of PCa. This review and the outlined discussion should encourage other clinical investigators to explore the relationship between PV and the incidence and aggressiveness of PCa. If future studies should confirm the hypothesis of the dynamic interactions between the different prostatic zones in a growing prostate, it will have relevant clinical implications on the management of BPH and PCa.

Elevated prostate volume index and prostatic chronic inflammation reduce the number of positive cores at first prostate biopsy set: results in 945 consecutive patients

OBJECTIVE

To assess the association between prostate volume index (PVI), and prostatic chronic inflammation (PCI) as predictors of prostate cancer (PCA). PVI is the ratio between the central transition zone volume (CTZV) and the peripheral zone volume (PZV).

MATERIALS AND METHODS

Parameters evaluated included age, prostate specific antigen (PSA), total prostate volume (TPV), PSA density (PSAD), digital rectal exam (DRE), PVI, PCI and number of positive cores (NPC). All patients underwent baseline 14-core, trans-perineal random biopsies. Associations of parameters with the NPC were investigated by univariate and multivariate linear regression analysis.

RESULTS

Between September 2010 to September 2017, 945 patients were evaluated. PCA was detected in 477 cases (50.7%), PCI in 205 cases (21.7%). PCA patients, compared to negative cases, were older (68.3 vs. 64.4 years) with smaller TPV (36 vs. 48.3mL) and CTZV (19.2 vs. 25.4), higher PSAD (0.24 vs. 0.15ng/mL/mL), further PVI values were lower (0.9 vs. 1.18) and biopsy cores less frequently involved by PCI (9.4% vs. 34.2%). High PVI and the presence of PCI were independent negative predictors of NPC in model I considering PSA and TVP (PVI, regression coefficient, RC -0,6; p=0.002) and PCI (RC -1,4; p<0.0001); and in model II considering PSAD (PVI:RC -0,7; p<0,0001; and PCI: RC -1,5; p<0.0001).

CONCLUSIONS

High PVI and the presence of PCI lowered the mean rate of NPC and is associated with less aggressive tumor biology expressed by low tumor burden. PVI can give prognostic information before planning baseline random biopsies. Confirmatory studies are required.

Biparametric prostate MRI and clinical indicators predict clinically significant prostate cancer in men with "gray zone" PSA levels

PURPOSE

To predict clinically significant prostate cancer (cs-PCa) by combining the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) score based on biparametric magnetic resonance imaging (bp-MRI) and clinical indicators in men with prostate-specific antigen (PSA) levels in the gray zone of 4-10 ng/mL.

METHOD

We retrospectively analyzed 364 patients with elevated PSA levels in the gray zone who had pathologically confirmed disease and had undergone MRI examinations from January 2015 to October 2019; a training group (n = 255) and validation group (n = 109) were randomly established. Multivariate logistic regression analysis of the training group was performed to identify the independent predictors for cs-PCa, thereby establishing a predictive model that was evaluated in the training and validation groups by analyzing the receiver operating characteristic (ROC) curve.

RESULTS

In the training group, the PI-RADS v2 score and prostate volume (PV) were independent predictors of cs-PCa (P < 0.05). The prediction model comprising the PI-RADS v2 score and PV had a larger AUC than the other predictors alone in the training group. The diagnostic sensitivity and specificity of the prediction model were 84.1 % and 83.4 %, respectively. The prediction model was indicated to have better predictive performance in the validation group.

CONCLUSIONS

The prediction model exhibits a satisfactory predictive value for cs-PCa in men with PSA levels in the gray zone. PI-RADS v2 is the strongest univariate predictor for the detection of cs-PCa in men with PSA in the gray zone, but combining this with the PV can provide superior predictive ability.

Contemporary Distribution of High-Grade Prostate Cancer in the Circumstances of Opportunistic Testing

Screening has dramatically changed the distribution of the mean age, stage and grade of prostate cancer (PCa) at diagnosis. However, regional-level data that characterize contemporary PCa patients are limited. The aim of the study was to ascertain main clinical and pathological characteristics of PCa at the present time in the circumstances of opportunistic testing.

High-grade PCa according to age, serum prostate specific antigen (PSA), volume prostate, PSA density (PSAD), digital rectal examination (DRE) number of positive cores biopsies and the average percentage of cancer in biopsy at diagnosis has been retrospectively evaluated in 100 men with biopsyproven PCa, at Clinical Centre Kragujevac, from September 2016 until September 2017. PCa were stratified according to Gleason score (GS) into low/intermediate-grade (GS ≤ 7) and high-grade (GS ≥ 8). To identify the determinants associated with high-grade PCa, we performed univariate and multivariate logistic regression.

The most prevalent PCa were the low/intermediate-grade (65%), followed by high-grade (35%). The mean age of the patients was 71.5 (range: 56–88) years and median PSA was 14.6 (range: 1.4–935) ng/ml. There were significant differences in age, PSA, PSAD, DRE, number of positive biopsy and average percentage of cancer in biopsy between patients with or without high-grade GS. Logistic analysis demonstrated the PSAD and age have strong prognostic value of high-grade PCa.

In conclusion, our study has shown the worrying frequency of high-grade PCa in the circumstances of opportunistic testing. Older men and higher level of PSAD had a much higher probability of high-grade PCa.