Abstract
The choice of biopsy method is critical in diagnosing prostate cancer (PCa). This retrospective cohort study compared systematic biopsy (SB) or cognitive fusion-targeted biopsy combined with SB (CB) in detecting PCa and clinically significant prostate cancer (csPCa). Data from 2572 men who underwent either SB or CB in Fudan University Shanghai Cancer Center (Shanghai, China) between January 2019 and December 2023 were analyzed. Propensity score matching (PSM) was used to balance baseline characteristics, and detection rates were compared before and after PSM. Subgroup analyses based on prostate-specific antigen (PSA) levels and Prostate Imaging-Reporting and Data System (PI-RADS) scores were performed. Primary and secondary outcomes were the detection rates of PCa and csPCa, respectively. Of 2572 men, 1778 were included in the PSM analysis. Before PSM, CB had higher detection rates for both PCa (62.9% vs 52.4%, odds ratio [OR]: 1.54, P < 0.001) and csPCa (54.9% vs 43.3%, OR: 1.60, P < 0.001) compared to SB. After PSM, CB remained superior in detecting PCa (63.1% vs 47.9%, OR: 1.86, P < 0.001) and csPCa (55.0% vs 38.2%, OR: 1.98, P < 0.001). In patients with PSA 4–12 ng ml−1 (>4 ng ml-1 and ≤12 ng ml-1, which is also applicable to the following text), CB detected more PCa (59.8% vs 40.7%, OR: 2.17, P < 0.001) and csPCa (48.1% vs 27.7%, OR: 2.42, P < 0.001). CB also showed superior csPCa detection in those with PI-RADS 3 lesions (32.1% vs 18.0%, OR: 2.15, P = 0.038). Overall, CB significantly improves PCa and csPCa detection, especially in patients with PSA 4–12 ng ml−1 or PI-RADS 3 lesions.
Keywords: cognitive fusion-targeted biopsy, combined biopsy, detection efficacy, prostate cancer, systematic biopsy
INTRODUCTION
Prostate cancer (PCa) has been an important disease threatening the health of males. According to data published by the Global Cancer Observatory (GLOBOCAN) in 2022,1 PCa is the second most frequent cancer and the fifth leading cause of cancer death among men worldwide, with 1.47 million (14.2%) new cases and 367 000 (7.3%) deaths per year. The national cancer burden data released by the National Cancer Center of China during the same period of 20222 revealed that PCa remains the 6th most common cancer with an age-standardized rate (world) of 18.61 per 100 000 and the 7th leading cause of cancer-related death with an age-standardized rate (world) of 6.59 per 100 000 in Chinese men population. From 2000 to 2018, the age-standardized incidence rates and age-standardized mortality rates of PCa continued to rise with an average annual percentage change of 7.0% and 4.1%, respectively. The burden of disease continued to increase.
Pathological findings from prostate biopsy are the gold standard for diagnosing PCa. Nevertheless, different biopsy methods significantly impact the risk of misclassification and cancer upstaging or downstaging after radical prostatectomy. Currently, transrectal or transperineal ultrasound-guided systematic biopsy is the most commonly used methods in clinical practice. With advancements in magnetic resonance imaging (MRI), newer techniques such as multiparametric MRI (mpMRI)-guided targeted biopsy, with or without systematic biopsy, allow physicians to focus on suspicious regions of interest (ROIs) rather than performing nontargeted, fixed-site biopsies. Due to its accessibility and effectiveness, targeted biopsy has now become widely adopted in clinical practice. Some randomized controlled trials (RCTs) suggest that it improves the detection efficacy of both PCa3 and clinically significant prostate cancer (csPCa)4 compared to systematic biopsy. However, other studies report the contrary conclusions that similar detection rates are observed between targeted and systematic biopsy.5 The superiority of targeted biopsy, its potential combination with systematic biopsy, and its application to specific subgroups or universally have yet to reach a consensus.
Current comparisons between systematic biopsy and cognitive fusion-targeted biopsy largely rely on RCTs, which provide strong internal validity but often lack external applicability. Moreover, the stringent inclusion criteria of RCTs are often not feasible in routine clinical practice, leading to study cohorts that inadequately represent the actual patient population, including treatment variability and demographic diversity. To address this, we utilized a large continuous retrospective cohort from real world and applied propensity score matching (PSM) to evaluate whether combined cognitive fusion-targeted biopsy with systematic biopsy offers advantages over systematic biopsy alone. Furthermore, we aimed to identify the baseline characteristics that predict which patients may benefit most from specific biopsy techniques, providing clinicians with evidence-based guidance for personalized biopsy selection.6
PARTICIPANTS AND METHODS
Study population
From January 2019 to December 2023, we retrospectively recruited 2874 men who underwent either transperineal ultrasound-guided systematic biopsy (SB) or cognitive fusion-targeted biopsy combined with SB (CB) at Fudan University Shanghai Cancer Center (FUSCC), Shanghai, China. Biopsy candidates must fulfill at least one of the following indications: (1) serum prostate-specific antigen (PSA) >4 ng ml−1 or (2) abnormal digital rectal examination (DRE). Three hundred and two patients were excluded due to prior treatment (n = 44), missing PSA data (n = 47), PSA levels exceeding 100 ng ml−1 (n = 206), or active surveillance (n = 5), resulting in 2572 participants being included in the final analysis. All patients enrolled underwent at least one PSA test prior to biopsy. Clinical and pathological data were collected from medical charts and electronic records. The institutional research review board at FUSCC approved the experimental protocols in accordance with the Declaration of Helsinki version 2013 (Approval No. 050432-4-2307E), and all patients provided written informed consent.
Region of interests in combined biopsy
All patients undergoing CB received prebiopsy mpMRI in accordance with the European Society of Urogenital Radiology (ESUR) guidelines.7 mpMRI was performed on a 3.0-T MRI scanner (Magnetom Skyra; Siemens Healthineers, Erlangen, Germany) using four sequences: triplanar T2-weighted, dynamic contrast-enhanced, diffusion-weighted imaging, and MR spectroscopy, following established protocols. All the lesions were graded by three experienced radiologists using Prostate Imaging-Reporting and Data System (PI-RADS) version 2.1 criteria.8 We documented the PI-RADS scores for each lesion per patient.
Biopsy protocol and histopathology
SB involved transperineal ultrasound-guided sampling of 12 fixed cores bilaterally from the apex to the base, striving to target the posterior and lateral regions of the peripheral zone. The 12 cores included: one from each lateral corner of the prostate, two from the peripheral zone, two from the central zone, and one from the transition zone on each side. Including transition zone cores has been demonstrated to enhance the detection of PCa.9 The SB in CB follows the same protocol as standalone systematic biopsy. For targeted biopsy, cognitive fusion was employed, with the urologists localizing the lesion based on mpMRI results and performing transperineal sampling of the ROIs under ultrasound guidance. Only one biopsy core was sampled from each ROI. All biopsies were performed by four urologists (FNW, GWL, HX, and ZH) with over 10 years of experience. Specimens were evaluated by genitourinary pathologists with over 10 years of experience in PCa pathology, in accordance with the International Society of Urological Pathology (Isup) guidelines.10 CsPCa was defined as Isup Grade Group ≥ 2.11 The primary endpoint was the detection rate of PCa, while the secondary endpoint was the detection rate of csPCa.
Statistical analyses
Continuous variables were reported as median with interquartile range (IQR) and categorical variables as frequency and percentages. The Mann–Whitney U test analyzed continuous variables, while Fisher’s exact tests were used for binary variables. Univariate and multivariate logistic regression analyses were conducted to identify the predictors of PCa and csPCa detection rates. PSM was applied to control for bias, and the detection rates of PCa and csPCa were compared between CB and SB. Receiver operating characteristic (ROC) curves were used to determine PSA cut-off point. Statistical significance was defined as two-sided P < 0.05. Analyses were conducted using R software version 4.2.2 (The R Foundation, Boston, MA, USA).
RESULTS
Cohort
A total of 2572 participants were included in the study and categorized into two groups based on the biopsy method: SB (n = 2124, 82.6%) and CB (n = 448, 17.4%). The clinicopathological characteristics of the cohort before PSM are summarized in Table 1. The age and PSA levels between the two cohorts exhibited significant statistical differences (P = 0.006 and P = 0.007, respectively). The primary and secondary outcomes, as well as Isup grade group, are also recorded in Table 1.
Table 1.
Demographic and clinical characteristics of the patients before propensity score matching
| Characteristic | Overall (n=2572; 100.0%) | SB (n=2124; 82.6%) | CB (n=448; 17.4%) | P |
|---|---|---|---|---|
| Age (year), median (IQR) | 68 (62–73) | 68 (62–73) | 67 (62–71) | 0.006a |
| Total PSA (ng ml−1), median (IQR) | 10.40 (6.71–18.00) | 10.61 (6.84–18.60) | 9.80 (6.29–16.13) | 0.007a |
| Biopsy result, n (%) | <0.001b | |||
| Positive | 1395 (54.2) | 1113 (52.4) | 282 (62.9) | |
| Negative | 1177 (45.8) | 1011 (47.6) | 166 (37.1) | |
| Total cores, median (IQR) | 12 (12–12) | 12 (12–12) | 13 (13–13) | <0.001a |
| Targeted biopsy cores, n (%) | <0.001c | |||
| 0 | 2124 (82.6) | 2124 (100.0) | 0 (0) | |
| 1 | 344 (13.4) | 0 (0) | 344 (76.8) | |
| 2 | 87 (3.4) | 0 (0) | 87 (19.4) | |
| 3 | 16 (0.6) | 0 (0) | 16 (3.6) | |
| 4 | 1 (<0.1) | 0 (0) | 1 (0.2) | |
| ISUP, n (%) | 0.135c | |||
| 1 | 227 (16.3) | 191 (17.2) | 36 (12.8) | |
| 2 | 263 (18.9) | 211 (19.0) | 52 (18.4) | |
| 3 | 228 (16.3) | 173 (15.5) | 55 (19.5) | |
| 4 | 359 (25.7) | 276 (24.8) | 83 (29.4) | |
| 5 | 315 (22.6) | 259 (23.3) | 56 (19.9) | |
| Rare types of PCad | 3 (0.2) | 3 (0.3) | 0 (0) |
aWilcoxon rank sum test; bPearson’s Chi-squared test; cFisher’s exact test; drare types of PCa refer to PCa that are not suitable for Gleason score, including embryonal rhabdomyosarcoma, adenocarcinoma of the urethral epithelium, and spindle cell rhabdomyosarcoma, but not ductal adenocarcinoma and intraductal carcinoma. IQR: interquartile range; PSA: prostate-specific antigen; ISUP: International Society of Urological Pathology; PCa: prostate cancer; SB: systematic biopsy; CB: combined biopsy
The stratified analysis based on PSA and PI-RADS scores before PSM
Previous studies have indicated that12,13 patients with PSA ≤4 ng ml−1 do not have an indication for biopsy; meanwhile, patients with PSA > 20 ng ml−1 are at a high risk for PCa. Patients with PSA levels between 4 ng ml−1 and 20 ng ml−1 have a moderate risk of PCa, and the likelihood of PCa or csPCa remains ambiguous. ROC curve analysis identified 12 ng ml−1 as an optimal PSA cut-off within the 4–20 ng ml−1 range for distinguishing PCa and csPCa. This cut-off enhances risk stratification in moderate-risk patients, aiding in the optimization of biopsy strategies. Accordingly, 4 ng ml−1, 12 ng ml−1, and 20 ng ml−1 were selected as PSA stratification points (Supplementary Figure 1 (124.7KB, tif) ).
Before conducting the stratified analysis, we broadly explored the pathology of each biopsy site in SB and stratified patients by PSA levels, calculating PCa detection rates for each site within the different PSA levels (Figure 1). It can be observed that in the PSA ≤4 ng ml−1 group, the PCa detection rate per biopsy site was around 5%, while it neared 50% in the PSA 20–100 ng ml−1 (>20 ng ml-1 and ≤100 ng ml-1, which is also applicable to the following text) group. It is also observed that the detection rate at each biopsy site nearly doubles between adjacent PSA subgroups. This finding might suggest that the selected cut-off points offer significant stratification efficacy.
Figure 1.
The detection rate of prostate cancer (PCa) at different sites of systematic biopsy across various prostate-specific antigen levels. The percentages inside each donut chart indicate the PCa detection rate at the corresponding biopsy site. (a) Patients with PSA ≤4 ng ml−1. (b) Patients with PSA 4–12 ng ml−1 (>4 ng ml−1 and ≤12 ng ml−1). (c) Patients with PSA 12–20 ng ml−1 (>12 ng ml−1 and ≤20 ng ml−1). (d) Patients with PSA 20–100 ng ml−1 (>20 ng ml−1 and ≤100 ng ml−1). PSA: prostate-specific antigen.
Prior to balancing baseline characteristics between the two groups using PSM analysis, we conducted a preliminary assessment of potential differences in detection efficiency between the two methods in the overall population. The results showed that CB had a higher detection rate of both PCa (62.9% vs 52.4%, odds ratio [OR]: 1.54, 95% confidence interval [CI]: 1.25–1.91, P < 0.001) and csPCa (54.9% vs 43.3%, OR: 1.60, 95% CI: 1.30–1.96, P < 0.001) compared to SB. Subsequently, we performed further stratified analysis.
PSA ≤4 ng ml−1 is deemed normal, and a biopsy is not recommended without additional evidence. However, 76 patients in our cohort with PSA ≤4 ng ml−1 still underwent biopsy, due to abnormal DRE. Nevertheless, among patients with PSA ≤4 ng ml−1, the detection rates of PCa or csPCa by both methods did not show any statistically significant difference (both P > 0.05). For PSA 4–12 ng ml−1 (>4 ng ml-1 and ≤12 ng ml-1, which is also applicable to the following text), CB outperformed SB in detecting PCa (59.6% vs 42.1%, OR: 2.02, 95% CI: 1.55–2.66, P < 0.001) and csPCa (47.9% vs 29.1%, OR: 2.25, 95% CI: 1.71–2.95, P < 0.001). In PSA levels of 12–20 ng ml−1 (>12 ng ml-1 and ≤20 ng ml-1, which is also applicable to the following text) and 20–100 ng ml−1, no statistically significant differences were found between SB and CB for PCa or csPCa detection (all P > 0.05; Figure 2a and 2b).
Figure 2.
Detection rates of PCa and csPCa in different subgroups stratified by PSA and PI-RADS scores before propensity score matching, respectively. Detection rate of (a) PCa and (b) csPCa stratified by PSA before PSM. Detection rates of (c) PCa and (d) csPCa stratified by PI-RADS scores before PSM, limited to patients with central reviewed PI-RADS 3+ scores. *P < 0.05 and ***P < 0.001 indicate statistically significant differences between the two groups. The error bars represent the 95% confidence interval. PSM: propensity score matching; PSA: prostate-specific antigen; PCa: prostate cancer; csPCa: clinically significant prostate cancer; PI-RADS: Prostate Imaging-Reporting and Data System.
Furthermore, according to PI-RADS version 2.1, the significance of lesions with a PI-RADS score of 3 for csPCa remains ambiguous. Therefore, we seek to determine which biopsy method offers greater benefits for patients with indeterminate imaging findings. We conducted a stratified analysis by PI-RADS on a subset of patients (n = 959) who underwent mpMRI at our institution with PI-RADS 3+ scores assessed through central review (Figure 2c and 2d). The results indicate that there were no statistically significant differences in PCa and csPCa detection rates between SB and CB for patients with PI-RADS scores of 4 or 5 (all P > 0.05). However, for patients with PI-RADS score of 3, CB demonstrated superior detection efficacy of csPCa compared to SB (31.6% vs 17.8%, OR: 2.14, 95% CI: 1.11–4.03, P = 0.028), but without significant difference in PCa detection (P > 0.05; Figure 2c and 2d).
Results of PSM analysis
Univariate and multivariate logistic regression models were used to assess possible baseline risk factors influencing the detection rates of PCa and csPCa. These factors were ultimately included as covariates in the PSM analysis. In univariate analysis, age and PSA were significant risk factors for both PCa and csPCa detection (all P < 0.001). Multivariate analysis confirmed these findings that age and PSA were independent risk factors for both PCa and csPCa detection (all P < 0.001; Supplementary Figure 2 (59.3KB, tif) ). This is consistent with the conclusions of a previous study.14
Before PSM, the two cohorts showed imbalance in age and PSA (P = 0.006 and P = 0.007, respectively). To achieve an appropriate balance of these risk factors, 3:1 nearest-neighbor propensity score matching was performed using age and PSA as covariates, with a caliper of 0.05×s.d. After PSM, 447 pairs (1778 patients) were included. Age and PSA were balanced between groups, with standardized mean differences of −0.055 and 0.021, respectively (Supplementary Table 1 and Supplementary Figure 3 (44.8KB, tif) ). Demographic and clinical characteristics of the patients after PSM are summarized in Table 2.
Supplementary Table 1.
Baseline covariates before and after propensity score matching
| Variables | Before PSM | After PSM | ||||||
|---|---|---|---|---|---|---|---|---|
|
|
|
|||||||
| SB | CB | SMD | Pa | SB | CB | SMD | Pa | |
| Count (n) | 2 124 | 448 | - | - | 1 331 | 447 | - | - |
| Age, mean (s.d.) | 67.47 (8.41) | 66.54 (7.57) | −0.123 | 0.021 | 66.98 (7.78) | 66.60 (7.48) | −0.055 | 0.354 |
| PSA, mean (s.d.) | 18.36 (21.34) | 14.02 (13.62) | −0.319 | <0.001 | 13.55 (12.85) | 14.04 (13.63) | 0.021 | 0.505 |
aWilcoxon rank sum test. PSM: propensity score matching; SMD: standardized mean difference; s.d.: standard deviation; PSA: prostate-specific antigen; SB: systematic biopsy; CB: combined biopsy
Table 2.
Demographic and clinical characteristics of the patients after propensity score matching
| Characteristic | Overall (n=1778; 100.0%) | SB (n=1331; 74.9%) | CB (n=447; 25.1%) | P |
|---|---|---|---|---|
| Age (year), median (IQR) | 67 (62–72) | 67 (62–72) | 67 (62–71) | 0.262a |
| Total PSA (ng ml−1), median (IQR) | 9.88 (6.48–14.78) | 9.89 (6.56–14.60) | 9.80 (6.30–16.26) | 0.780a |
| Biopsy result, n (%) | <0.001b | |||
| Positive | 920 (51.7) | 638 (47.9) | 282 (63.1) | |
| Negative | 858 (48.3) | 693 (52.1) | 165 (36.9) | |
| Total cores, median (IQR) | 12 (12–13) | 12 (12–12) | 13 (13–13) | <0.001a |
| Targeted biopsy cores, n (%) | <0.001c | |||
| 0 | 1331 (74.9) | 1331 (100.0) | 0 (0) | |
| 1 | 344 (19.3) | 0 (0) | 344 (77.0) | |
| 2 | 86 (4.8) | 0 (0) | 86 (19.2) | |
| 3 | 16 (0.9) | 0 (0) | 16 (3.6) | |
| 4 | 1 (<0.1) | 0 (0) | 1 (0.2) | |
| ISUP, n (%) | 0.045b | |||
| 1 | 164 (17.8) | 128 (20.1) | 36 (12.8) | |
| 2 | 186 (20.2) | 134 (21.0) | 52 (18.4) | |
| 3 | 165 (17.9) | 110 (17.2) | 55 (19.5) | |
| 4 | 238 (25.9) | 155 (24.3) | 83 (29.4) | |
| 5 | 166 (18.0) | 110 (17.2) | 56 (19.9) | |
| Rare types of PCad | 1 (0.1) | 1 (0.2) | 0 (0) |
aWilcoxon rank sum test; bPearson’s Chi-squared test; cFisher’s exact test; drare types of PCa refer to PCa that are not suitable for Gleason score, including embryonal rhabdomyosarcoma, adenocarcinoma of the urethral epithelium, and spindle cell rhabdomyosarcoma, but not ductal adenocarcinoma and intraductal carcinoma. IQR: interquartile range; PSA: prostate-specific antigen; ISUP: International Society of Urological Pathology; PCa: prostate cancer; SB: systematic biopsy; CB: combined biopsy
We conducted a comparative analysis of the detection efficiency between CB and SB within the PSM-adjusted cohort. The results showed that CB detected more PCa (63.1% vs 47.9%, OR: 1.86, 95% CI: 1.49–2.32, P < 0.001) and csPCa (55.0% vs 38.2%, OR: 1.98, 95% CI: 1.59–2.46, P < 0.001) compared to SB. Further stratified analysis of the PSM-matched cohort yielded conclusions that were largely consistent with those obtained prior to PSM as well. Compared to SB, CB showed superior detection rates for both PCa (59.8% vs 40.7%, OR: 2.17, 95% CI: 1.64–2.88, P < 0.001) and csPCa (48.1% vs 27.7%, OR: 2.42, 95% CI: 1.82–3.22, P < 0.001) in patients with PSA 4–12 ng ml−1 (Figure 3a and 3b). Additionally, stratified analysis was performed on all patients with central reviewed PI-RADS 3+ scores (n = 705), which showed that CB demonstrated superior detection rate of csPCa (32.1% vs 18.0%, OR: 2.15, 95% CI: 1.08–4.24, P = 0.038) compared to SB among patients with PI-RADS score of 3, but without statistically significant difference in PCa detection (P > 0.05; Figure 3c and 3d).
Figure 3.
Detection rates of PCa and csPCa in different subgroups stratified by PSA and PI-RADS scores after propensity score matching, respectively. Detection rates of (a) PCa and (b) csPCa stratified by PSA after PSM. Detection rates of (c) PCa and (d) csPCa stratified by PI-RADS scores after PSM, limited to patients with central reviewed PI-RADS 3+ scores. *P < 0.05 and ***P < 0.001 indicate statistically significant differences between the two groups. The error bars represent the 95% confidence interval. PSM: propensity score matching; PSA: prostate-specific antigen; PCa: prostate cancer; csPCa: clinically significant prostate cancer; PI-RADS: Prostate Imaging-Reporting and Data System.
DISCUSSION
This single-center, real-world retrospective study used PSM on a large consecutive patient sample to minimize bias aiming to more precisely assess the diagnostic efficiency of CB versus SB for detecting PCa and csPCa. PSM results showed that CB had superior detection rates for both PCa and csPCa overall, consistent with prior studies.15,16 Further analysis revealed that CB was particularly effective in patients with PSA 4–12 ng ml−1 or PI-RADS 3 lesions, suggesting greater clinical benefit in more precise patient stratification.
PSA is the most commonly used tumor marker for diagnosing PCa. In Western populations, PCa detection rates are relatively low when PSA levels are between 4 ng ml−1 and 20 ng ml−1. PSA levels between 4 ng ml−1 and 10 ng ml−1 are often referred to as the “gray zone”,17 where the detection rates are ambiguous. Notably, studies have indicated that the PSA “gray zone” in Asian men may be higher than that in Western populations.18,19 Ethnic differences affect PSA levels and PCa detection rates, which may be due to disparities in lifestyle and dietary patterns among different populations, underscoring disparities in PCa risk and management strategies.20,21,22 We employed ROC curve analysis to determine a more accurate gray zone cutoff within the PSA range of 4–20 ng ml−1. And, our research preliminarily proved that, in patients with PSA levels between 4 ng ml−1 and 12 ng ml−1, CB demonstrated higher detection rates for both PCa and csPCa. Further research will be conducted to validate the applicability and specificity of this gray zone in Asian men. For PI-RADS 3 lesions, where MRI findings are often inconclusive, cancer risk is lower, but csPCa remains a possibility.23 Relying solely on MRI-targeted biopsy may result in missed diagnoses due to unclear imaging, while SB alone may miss csPCa due to its nontargeted nature. Our findings indicate that CB, particularly in PI-RADS 3 lesions, can effectively reduce missed diagnoses and improve csPCa detection rates.
In our study, we employed PSA levels and PI-RADS scores, two widely used clinical parameters, to effectively stratify patients undergoing prostate biopsy. However, the parameters analyzed are not exhaustive. Previous research has explored the influence of additional factors, such as genomics,24 nuclear medicine,25 and various urological functional parameters like bladder outlet obstruction (BOO)26 and postvoid residual urine volume (PVRUV),27 on biopsy outcomes. Future research could incorporate a broader range of clinical parameters to further refine prebiopsy risk stratification and optimize biopsy method selection.
Previous studies have shown that compared to SB, targeted biopsy alone can increase csPCa detection when reducing the detection of clinically insignificant prostate cancer.4,28,29 However, studies conducted around the same period reported opposing conclusions.30,31 Thus, whether MRI-targeted biopsy can fully replace standard SB remains debated. These inconsistencies may arise from differences in cohort sizes, inclusion/exclusion criteria, biopsy protocols, and operator expertise. Although these studies do not provide a unified conclusion, they indicate the potential clinical benefits of targeted biopsy. Nevertheless, current evidence also cautions that it is premature to replace SB with targeted biopsy alone. Combining both methods may offer superior clinical benefits.
Huang et al.32 demonstrated that, in the transperineal biopsy subgroup, CB significantly outperformed SB in the detection of csPCa (24.0% vs 12.6%, OR: 2.19, P = 0.01). Our result is an external validation of their study. Moreover, our findings highlighted the advantage of CB in detecting PCa, particularly in patients with PI-RADS 3.
What’s more, targeted biopsy was performed with 1 core per lesion in our center, which differs from international conventions. Nonetheless, the findings from this retrospective study are quite similar to those reported in many other studies,15,16,32 suggesting that even with fewer targeted biopsy cores, robust detection rates for PCa and csPCa can be achieved. Therefore, whether the number of targeted biopsy cores can be reduced when maintaining high diagnostic accuracy remains a question for future research to explore.
However, several limitations in our study should be noted. First, the retrospective nature of the study resulted in certain missing value of some parameters, such as the unavailability of mpMRI central review for accurate PI-RADS scores for many patients. Second, pathologists are not rigor blinded for biopsy method. Third, the different cores of target biopsy determined by the urologist could influence detection rates. At last, the single-center nature may limit the generalizability of the findings, as results might not be replicable in centers with less experienced surgeons or low-quality equipment. Nonetheless, our center ensures standardized biopsy protocols, high-quality pathology, Isup grading, and PI-RADS reporting for mpMRI, which guarantees the credibility of the conclusion.
This study is based on real-world data, aligned with daily clinical practice, offering valuable insights into the biopsy method selection for physicians. Additionally, subgroup analysis aids clinicians in personalizing biopsy strategies for individual patients.
In conclusion, our study showed that, compared with SB, CB significantly improves detection rates of PCa and csPCa, particularly in patients with PSA 4–12 ng ml−1, when demonstrating greater efficacy in detecting csPCa in those with PI-RADS 3 lesions.
AUTHOR CONTRIBUTIONS
FNW and BD designed and supervised the research. BRY analyzed the data and wrote the manuscript. HW collected the data and revised the manuscript. YQZ interpreted the data. FNW, GWL, HX, and ZH conducted the biopsy surgery. All authors read and approved the final manuscript.
COMPETING INTERESTS
All authors declare no competing interests.
Receiver operating characteristic (ROC) curves and Youden index analyses for predicting prostate cancer (PCa) and clinically significant prostate cancer (csPCa) using prostate-specific antigen (PSA) level. (a) The ROC curve was used to evaluate the predictive performance of PSA in detecting the rate of PCa. (b) The ROC curve was used to evaluate the predictive performance of PSA in detecting the rate of csPCa. (c) PSA cutoff points and corresponding Youden index for PCa detection rate. (d) PSA cutoff points and corresponding Youden index for csPCa detection rate. AUC: area under the curve. CI: confidence intervals.
Forest plot. Univariate (Univ) and multivariate (Multiv) logistic regression analyses for prostate cancer and clinically significant prostate cancer. PSA: prostate-specific antigen; OR: odds ratios; CI: confidence intervals; PCa: prostate cancer; csPCa: clinically significant prostate cancer.
Love plot. The figure shows the absolute standardized mean differences (SMD) for key covariates (PSA and age) before (red points) and after (blue points) propensity score matching. The dashed line at 0.1 marks the threshold for acceptable balance, showing improved covariate balance postmatching. PSA: prostate-specific antigen.
ACKNOWLEDGMENTS
We thank Prof. Bing-Ni Zhou and Xiao-Hang Liu (Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China) for kindly providing central review of mpMRI in this study. This study was supported financially by the National Nature Science Foundation of China (No. 82373355, No. 82172703, No. 82303856, and No. 82473505), the Discipline Leader Project of Shanghai Municipal Health Commission (No. 2022XD013), and the AoXiang Project of Shanghai Anti-Cancer Association (No. SACA-AX202302).
Supplementary Information is linked to the online version of the paper on the Asian Journal of Andrology website.
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Supplementary Materials
Receiver operating characteristic (ROC) curves and Youden index analyses for predicting prostate cancer (PCa) and clinically significant prostate cancer (csPCa) using prostate-specific antigen (PSA) level. (a) The ROC curve was used to evaluate the predictive performance of PSA in detecting the rate of PCa. (b) The ROC curve was used to evaluate the predictive performance of PSA in detecting the rate of csPCa. (c) PSA cutoff points and corresponding Youden index for PCa detection rate. (d) PSA cutoff points and corresponding Youden index for csPCa detection rate. AUC: area under the curve. CI: confidence intervals.
Forest plot. Univariate (Univ) and multivariate (Multiv) logistic regression analyses for prostate cancer and clinically significant prostate cancer. PSA: prostate-specific antigen; OR: odds ratios; CI: confidence intervals; PCa: prostate cancer; csPCa: clinically significant prostate cancer.
Love plot. The figure shows the absolute standardized mean differences (SMD) for key covariates (PSA and age) before (red points) and after (blue points) propensity score matching. The dashed line at 0.1 marks the threshold for acceptable balance, showing improved covariate balance postmatching. PSA: prostate-specific antigen.