PSA density improves the rate of prostate cancer detection in Chinese men with a PSA between 2.5-10.0 ng ml (-1) and 10.1-20.0 ng ml (-1) : a multicenter study

Clinical and Radiological Factors for Predicting Clinically Significant Prostate Cancer in Biopsy-Naive Patients With PI-RADS 3 Lesions

OBJECTIVE

This study intends to examine the anticipatory power of clinical and radiological parameters in detecting clinically significant prostate cancer in patients demonstrating Prostate Imaging Reporting and Data System 3 lesions.

METHODS

This was a retrospective study. The study included participation from 453 patients at the First Affiliated Hospital of Soochow University, sampled between September 2017 through August 2022. Each patient underwent a routine 12-core prostate biopsy followed by a 2 to 5 core fusion-targeted biopsy. We utilized both univariate and multivariate logistic regression analyses to identify the parameters that have a correlation with clinically significant prostate cancer. The predictive ability of these parameters was assessed using the receiver operating characteristic curve, leading to the creation of a nomogram.

RESULTS

Clinically significant prostate cancer was detected in 68 out of 453 patients with Prostate Imaging Reporting and Data System 3 lesions (15.01%). Among Prostate Imaging Reporting and Data System 3a and 3b patients, 4.78% (3.09% of the total) and 33.75% (11.92% of the total), respectively, had clinically significant prostate cancer. Systematic biopsy improved prostate cancer and clinically significant prostate cancer detection rates by 7.72% and 3.09%, respectively, compared to targeted biopsy. Without systematic biopsy, there would be an undetected rate of 15% for prostate cancer and 8.13% for clinically significant prostate cancer in Prostate Imaging Reporting and Data System 3b patients. Several clinical parameters, including age, prostate-specific antigen density, lesion volume, apparent diffusion coefficient, and digital rectal examination, were statistically significant in the logistic regression analysis for clinically significant prostate cancer. The individual diagnostic accuracies of these parameters for clinically significant prostate cancer were 0.648, 0.645, 0.75, 0.763, and 0.7, respectively, but their combined accuracy improved to 0.866. A well-fit nomogram based on the identified risk factors was constructed (χ2 = 10.254, P = .248).

CONCLUSION

The combination of age, prostate-specific antigen density, lesion volume, apparent diffusion coefficient, and digital rectal examination presented a higher diagnostic value for clinically significant prostate cancer than any single parameter in patients with Prostate Imaging Reporting and Data System 3 lesions. Systematic biopsy proved crucial for biopsy-naive patients with Prostate Imaging Reporting and Data System 3 lesions and should not be omitted.

Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4-20 ng/mL

Excessive prostate biopsy is a common problem for clinicians. Although some hematological and bi-parametric magnetic resonance imaging (bpMRI) parameters might help increase the rate of positive prostate biopsies, there is a lack of studies on whether their combination can further improve clinical detection efficiency. We retrospectively enrolled 394 patients with PSA levels of 4-20 ng/mL who underwent prebiopsy bpMRI during 2010-2021. Based on bpMRI and hematological indicators, six models and a nomogram were constructed to predict the outcomes of biopsy. Furthermore, we constructed and evaluated a risk scoring model based on the nomogram. Age, prostate-specific antigen (PSA) density (PSAD), systemic immune-inflammation index, cystatin C level, and the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 score were significant predictors of prostate cancer (PCa) on multivariable logistic regression analyses (P < 0.05) and the five parameters were used to construct the XYFY nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram was 0.916. Based on the nomogram, a risk scoring model (XYFY risk model) was constructed and then we divided the patients into low-(XYFY score: < 95), medium-(XYFY score: 95-150), and, high-risk (XYFY score: > 150) groups. The predictive values for diagnosis of PCa and clinically-significant PCa among the three risk groups were 3.0%(6/201), 41.8%(51/122), 91.5%(65/71); 0.5%(1/201), 19.7%(24/122), 60.6%(43/71), respectively. In conclusion, in this study, we used hematological and bpMRI parameters to establish and internally validate a XYFY risk scoring model for predicting the biopsy outcomes for patients with PSA levels of 4-20 ng/mL and this risk model would support clinical decision-making and reduce excessive biopsies.

Diagnostic value of combining PI-RADS v2.1 with PSAD in clinically significant prostate cancer

PURPOSE

To investigate the diagnostic value of the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) for clinically significant prostate cancer (CsPCa). We also aimed to combine PI-RADS v2.1 with prostate-specific antigen (PSA) derivatives to improve the predictive value of CsPCa.

METHODS

We retrospectively collected relevant data who underwent standard MRI examinations of the prostate and subjected to a prostate biopsy at Shenzhen People's hospital from November 2014 to November 2019. Included 125 cases of CsPCa and 383 cases of non-CsPCa. All cases were scored using the PI-RADS v2.1. The clinical data collected included age, PSA, free PSA/total PSA, prostate volume and PSA density (PSAD). A univariate analysis was performed to identify statistically significant indicators. Logistic regression was used to analyze the predictive value of the multi-parameter combination on CsPCa.

RESULTS

Except age, the difference in all of indicators between the CsPCa group and non-CsPCa group was statistically significant. The PI-RADS score and PSAD value had the highest diagnostic value. Logistic regression analysis revealed that the PI-RADS score and PSAD value were independent predictors of CsPCa, with a regression model AUC of 0.935. CsPCa detection rates were low when the PI-RADS score ≤ 2 or the PI-RADS score = 3 and the PSAD value ≤ 0.33 ng/ml/ml.

CONCLUSION

Combining the PI-RADS score and PSAD value improved the predictive performance of CsPCa. Patients with a PI-RADS score ≤ 2 or a PI-RADS score = 3 and a PSAD value ≤ 0.33 ng/ml/ml can avoid an unnecessary biopsy.

Clinical application of free/total PSA ratio in the diagnosis of prostate cancer in men over 50 years of age with total PSA levels of 2.0-25.0 ng ml-1 in Western China

The goal of this study was to investigate the clinical application of free/total prostate-specific antigen (F/T PSA) ratio, considering the new broad serum total PSA (T-PSA) “gray zone” of 2.0–25.0 ng ml⁻¹ in differential diagnosis of prostate cancer (PCa) and benign prostate diseases (BPD) in men over 50 years in Western China. A total of 1655 patients were included, 528 with PCa and 1127 with BPD. Serum T-PSA, free PSA (F-PSA), and F/T PSA ratio were analyzed. Receiver operating characteristic curves were used to assess the efficiency of PSA and F/T PSA ratio. There were 47.4% of cancer patients with T-PSA of 2.0–25.0 ng ml⁻¹. When T-PSA was 2.0–4.0 ng ml⁻¹, 4.0–10.0 ng ml⁻¹, and 10.0–25.0 ng ml⁻¹, the area under the curve (AUC) of F/T PSA ratio was 0.749, 0.769, and 0.761, respectively. The best AUC of F/T PSA ratio was 0.811 when T-PSA was 2.0–25.0 ng ml⁻¹, with a specificity of 0.732, a sensitivity of 0.788, and an optimal cutoff value of 15.5%. The AUC of F/T PSA ratio in different age groups (50–59 years, 60–69 years, 70–79 years, and ≥80 years) was 0.767, 0.806, 0.815, and 0.833, respectively, and the best sensitivity (0.857) and specificity (0.802) were observed in patients over 80 years. The T-PSA trend was in accordance with the Gleason score, tumor node metastasis (TNM) stage, and American Joint Committee on Cancer prognosis group. Therefore, the F/T PSA ratio can facilitate the differential diagnosis of PCa and BPD in the broad T-PSA “gray zone”. Serum T-PSA can be a Gleason score and prognostic indicator.

Peripheral zone PSA density: a predominant variable to improve prostate cancer detection efficiency in men with PSA higher than 4 ng ml-1

To improve the diagnostic efficiency of prostate cancer (PCa) and reduce unnecessary biopsies, we defined and analyzed the diagnostic efficiency of peripheral zone prostate-specific antigen (PSA) density (PZ-PSAD). Patients who underwent systematic 12-core prostate biopsies in Shanghai General Hospital (Shanghai, China) between January 2012 and January 2018 were retrospectively identified (n = 529). Another group of patients with benign prostatic hyperplasia (n = 100) were randomly preselected to obtain the PSA density of the non-PCa cohort (N-PSAD). Prostate volumes and transition zone volumes were measured using multiparameter magnetic resonance imaging (mpMRI) and were combined with PSA and N-PSAD to obtain the PZ-PSAD from a specific algorithm. Receiver operating characteristic (ROC) curve analysis was used to assess the PCa detection efficiency in patients stratified by PSA level, and the area under the ROC curve (AUC) of PZ-PSAD was higher than that of PSA, PSA density (PSAD), and transition zone PSA density (TZ-PSAD). PZ-PSAD could amend the diagnosis for more than half of the patients with inaccurate transrectal ultrasonography (TRUS) and mpMRI results. When TRUS and mpMRI findings were ambiguous to predict PCa (PIRADS score ≤3), PZ-PSAD could increase the positive rate of biopsy from 21.7% to 54.7%, and help 63.8% (150/235) of patients avoid unnecessary prostate biopsy. In patients whose PSA was 4.0–10.0 ng ml⁻¹, 10.1–20.0 ng ml⁻¹, and >20.0 ng ml⁻¹, the ideal PZ-PSAD cut-off value for predicting clinically significant PCa was 0.019 ng ml⁻², 0.297 ng ml⁻², and 1.180 ng ml⁻², respectively (sensitivity >90%). Compared with PSA, PSAD, and TZ-PSAD, the efficiency of PZ-PSAD for predicting PCa is the highest, leading to fewer missed diagnoses and unnecessary biopsies.

PSA density in the diagnosis of prostate cancer in the Chinese population: results from the Chinese Prostate Cancer Consortium

We performed this study to investigate the diagnostic performance of prostate-specific antigen density (PSAD) in a multicenter cohort of the Chinese Prostate Cancer Consortium. Outpatients with prostate-specific antigen (PSA) levels ≥4.0 ng ml⁻¹ regardless of digital rectal examination (DRE) results or PSA levels <4.0 ng ml⁻¹ and abnormal DRE results were included from 18 large referral hospitals in China. The diagnostic performance of PSAD and the sensitivity and specificity for the diagnosis of prostate cancer (PCa) and high-grade prostate cancer (HGPCa) at different cutoff values were evaluated. A total of 5220 patients were included in the study, and 2014 (38.6%) of them were diagnosed with PCa. In patients with PSA levels ranging from 4.0 to 10.0 ng ml⁻¹, PSAD was associated with PCa and HGPCa in both univariate (odds ratio [OR] = 45.15, P < 0.0001 and OR = 25.38, P < 0.0001, respectively) and multivariate analyses (OR = 52.55, P < 0.0001 and OR = 26.05, P < 0.0001, respectively). The areas under the receiver operating characteristic curves (AUCs) of PSAD in predicting PCa and HGPCa were 0.627 and 0.630, respectively. With the PSAD cutoff of 0.10 ng ml⁻², we obtained a sensitivity of 88.7% for PCa, and nearly all (89.9%) HGPCa cases could be detected and biopsies could be avoided in 20.2% of the patients (359/1776 cases). Among these patients who avoided biopsies, only 30 cases had HGPCa. We recommend 0.10 ng ml⁻² as the proper cutoff value of PSAD, which will obtain a sensitivity of nearly 90% for both PCa and HGPCa. The results of this study should be validated in prospective, population-based multicenter studies.

Comparison of diagnostic efficacy between transrectal and transperineal prostate biopsy: A propensity score-matched study

This study compared the diagnostic efficacy of transrectal ultrasound (TRUS)-guided prostate biopsy (TRBx) and transperineal prostate biopsy (TPBx) in patients with suspected prostate cancer (PCa). We enrolled 2962 men who underwent transrectal (n = 1216) or transperineal (n = 1746) systematic 12-core prostate biopsy. Clinical data including age, prostate-specific antigen (PSA) level, and prostate volume (PV) were recorded. To minimize confounding, we performed propensity score-matching analysis. We measured and compared PCa detection rates between TRBx and TPBx, which were stratified by clinical characteristics and Gleason scores. The effects of clinical characteristics on PCa detection rate were assessed by logistic regression. For all patients, TPBx detected a higher proportion of clinically significant PCa (P < 0.001). Logistic regression analyses illustrated that PV had a smaller impact on PCa detection rate of TPBx compared with TRBx. Propensity score-matching analysis showed that the detection rates in TRBx were higher than those in TPBx for patients aged >- 80 years (80.4% vs 56.5%, P = 0.004) and with PSA level 20.1-100.0 ng ml^-1 (80.8% vs 69.1%, P = 0.040). In conclusion, TPBx was associated with a higher detection rate of clinically significant PCa than TRBx was; however, because of the high detection rate at certain ages and PSA levels, biopsy approaches should be optimized according to patents' clinical characteristics.

Using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with PSA in the gray zone

The gold standard for prostate cancer (PCa) diagnosis is prostate biopsy. However, it remines controversial as an invasive mean for patients with PSA levels in the gray zone (4–10 ng/mL). This study aimed to develop strategy to reduce the unnecessary prostate biopsy. We retrospectively identified 235 patients with serum total PSA testing in the gray zone before prostate biopsy between 2014 and 2018. Age, PSA derivates, prostate volume and multiparametric magnetic imaging (mpMRI) examination were assessed as predictors for PCa and clinically significant PCa with Gleason score ≥ 7 (CSPCa). Univariate analysis showed that prostate volume, PSAD, and mpMRI examination were significant predictors of PCa and CSPCa (P < 0.05). The differences of diagnostic accuracy between mpMRI examination (AUC = 0.69) and other clinical parameters in diagnostic accuracy for PCa were not statistically significant. However, mpMRI examination (AUC = 0.79) outperformed prostate volume and PSAD in diagnosis of CSPCa. The multivariate models (AUC = 0.79 and 0.84 for PCa and CSPCa) performed significantly better than mpMRI examination for detection of PCa (P = 0.003) and CSPCa (P = 0.036) among patients with PSA level in the gray zone. At the same level of sensitivity as the mpMRI examination to diagnose PCa, applying the multivariate models could reduce the number of biopsies by 5% compared with mpMRI examination. Overall, our results supported the view that the multivariate model could reduce unnecessary biopsies without compromising the ability to diagnose PCa and CSPCa. Further prospective validation is required.

Evaluation of PSA-age volume score in predicting prostate cancer in Chinese population

This study was performed to evaluate prostate-specific antigen-age volume (PSA-AV) scores in predicting prostate cancer (PCa) in a Chinese biopsy population. A total of 2355 men who underwent initial prostate biopsy from January 2006 to November 2015 in Huashan Hospital were recruited in the current study. The PSA-AV scores were calculated and assessed together with PSA and PSA density (PSAD) retrospectively. Among 2133 patients included in the analysis, 947 (44.4%) were diagnosed with PCa. The mean age, PSA, and positive rates of digital rectal examination result and transrectal ultrasound result were statistically higher in men diagnosed with PCa (all P < 0.05). The values of area under the receiver operating characteristic curves (AUCs) of PSAD and PSA-AV were 0.864 and 0.851, respectively, in predicting PCa in the entire population, both performed better than PSA (AUC = 0.805; P < 0.05). The superiority of PSAD and PSA-AV was more obvious in subgroup with PSA ranging from 2.0 ng ml^-1 to 20.0 ng ml^-1. A PSA-AV score of 400 had a sensitivity and specificity of 93.7% and 40.0%, respectively. In conclusion, the PSA-AV score performed equally with PSAD and was better than PSA in predicting PCa. This indicated that PSA-AV score could be a useful tool for predicting PCa in Chinese population.

Prostate transitional zone volume-based nomogram for predicting prostate cancer and high progression prostate cancer in a real-world population

PURPOSE

To evaluate and compare the efficacy of prostate volume (PV), transitional zone volume (TZV), and prostate volume index (PVI, the ratio of TZV to peripheral zone volume) in the identification of men at risk of prostate cancer (PCa) and high-progression PCa (HPPCa) at the initial biopsy (IBX) in a real-world population.

METHODS

From Jul 2014 to Aug 2016, data on 1144 patients who had undergone the initial prostate biopsies were prospectively collected and analyzed. Univariate and multivariate logistic regression analyses were performed to identify the independent predictors for PCa and HPPCa. Based on independent predictors, nomogram models were developed and internally validated to assess a man's risk of harboring PCa and HPPCa.

RESULTS

The detection rates of PCa and HPPCa were 43.09% (493/1144) and 39.16% (448/1144), respectively. In the multivariate analyses, age, PSA, TZV, DRE, and TRUS instead of PV or PVI were independent predictors for PCa and HPPCa, percent free PSA was independent predictor for PCa not for HPPCa. Such independent predictors were finally included in the nomogram models. The AUCs of TZV-based nomogram models were 87.0% for PCa and 87.7% for HPPCa, which were higher than that of PSA alone or other predictive models.

CONCLUSIONS

TZV is a better predictive biomarker than PV or PVI for PCa and HPPCa, we recommend adding TZV but not PV or PVI to the nomogram models to improve the predictive accuracy of PCa and HPPCa at IBX.

Performance of the Prostate Health Index in predicting prostate biopsy outcomes among men with a negative digital rectal examination and transrectal ultrasonography

The [-2]proPSA (p2PSA) and its derivatives, the p2PSA-to-free PSA ratio (%p2PSA), and the Prostate Health Index (PHI) have greatly improved discrimination between men with and without prostate cancer (PCa) in prostate biopsies. However, little is known about their performance in cases where a digital rectal examination (DRE) and transrectal ultrasonography (TRUS) are negative. A prospective cohort of 261 consecutive patients in China with negative DRE and TRUS were recruited and underwent prostate biopsies. A serum sample had collected before the biopsy was used to measure various PSA derivatives, including total prostate-specific antigen (tPSA), free PSA, and p2PSA. For each patient, the free-to-total PSA ratio (%fPSA), PSA density (PSAD), p2PSA-to-free PSA ratio (%p2PSA), and PHI were calculated. Discriminative performance was assessed using the area under the receiver operating characteristic curve (AUC) and the biopsy rate at 91% sensitivity. The AUC scores within the entire cohort with respect to age, tPSA, %fPSA, PSAD, p2PSA, %p2PSA, and PHI were 0.598, 0.751, 0.646, 0.789, 0.814, 0.808, and 0.853, respectively. PHI was the best predictor of prostate biopsy results, especially in patients with a tPSA of 10.1-20 ng ml-1 . Compared with other markers, at a sensitivity of 91%, PHI was the most useful for determining which men did not need to undergo biopsy, thereby avoiding unnecessary procedures. The use of PHI could improve the accuracy of PCa detection by predicting prostate biopsy outcomes among men with a negative DRE and TRUS in China.