Development and validation of a nomogram model for predicting acute urinary retention after transrectal prostate biopsy

Introduction

Since its application by Hodge et al., transrectal prostate biopsy (TRPB) has become the most popular method for diagnosing prostate cancer (1). The common complications of TRPB include fever (1.4%), sepsis (0.09%), rectal bleeding (5.9%), and voiding dysfunction (1.9%), with an overall incidence that is relatively low (2,3). Infectious complications, especially sepsis, are notably frequent and can be life-threatening (4). A European randomized trial reported that infection was the primary reason for hospital admission following TRPB, accounting for 81% of such cases (4). In recent years, transperineal prostate biopsy has been conducted to effectively reduce the occurrence of infectious complications and rectal bleeding (5). However, compared with the transrectal approach, the transperineal approach has several obvious shortcomings, including a longer operation time, increased procedural discomfort and higher financial costs, and increased risk of acute urine retention (AUR) (6). Several studies have reported that transperineal mapping biopsy (TPMB) has a higher rate of AUR compared to TRPB. According to Skouteris et al., the rate can be as high as 17.7%, compared to approximately 4% for TRPB (7). Owing to the above factors, TRPB is still the most widely used biopsy method and is recommended by the American Urology Association (8).

Voiding impairment after biopsy was first reported by Zisman et al. (9). Following a prostate biopsy, patients may experience an increase in the severity of lower urinary tract symptoms (LUTS), potentially leading to AUR. Previous studies have suggested that its incidence can reach 50%, of which the incidence of AUR is approximately 0.4–2.5% (9,10). For AUR, only a short-term indwelling urinary catheter is sufficient to achieve satisfactory results, whereas the treatment of infectious complications or rectal bleeding can be more complex and invasive. Recent studies have suggested that a large prostate volume and a high International Prostate Symptom Score (IPSS) are risk factors for biopsy-related AUR (11,12). At present, the definitions of AUR are largely based on empirical observations and are open to broad interpretation, whereas AUR is largely defined through the volume of post-void residual urine volumes (PVR) (13). However, there is currently a lack of research on which threshold value defines a significant PVR that requires timely catheterization after prostate biopsy.

Therefore, this study aimed to define the optimal PVR at which catheterization should be recommended for biopsy patients with potential AUR and to establish a nomogram model to predict the occurrence of AUR after TRPB, which may provide valuable guidance for preoperative consultation and improve patient experience. We present this article in accordance with the TRIPOD reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-24-399/rc).

Methods

Patient enrollment, inclusion and exclusion criteria

We retrospectively reviewed consecutive patients who underwent TRPB at The Third Affiliated Hospital of Sun Yat-sen University between January 2019 and November 2023. A total of 403 patients were screened for eligibility, of whom 333 were included in the study, whereas 70 were excluded based on the exclusion criteria. The included patients were then randomly divided into a development cohort (n=233) and a validation cohort (n=100) in a 7:3 ratio. The enrollment process is illustrated in Figure 1.

Figure 1 Flowchart illustrating the selection and grouping procedures. PVR, post-void residual urine volume.

The inclusion criteria for patients were as follows: (I) first prostate biopsy; (II) having undergone magnetic resonance imaging (MRI) before biopsy; and (III) comprehensive records of the biopsies, pathology findings, and laboratory test results were available. The exclusion criteria were as follows: (I) repeated prostate biopsy; (II) a history of chronic urinary retention or indwelling catheters before the biopsy procedure; and (III) pre-biopsy PVR greater than 50 mL.

Data collection

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Medical Ethics Board of The Third Affiliated Hospital of Sun Yat-sen University (No. II2024-156-02) and individual consent for this retrospective analysis was waived. All the clinical and pathological variables of the enrolled patients, including age, body mass index (BMI), medical history (hypertension, diabetes, hypercholesterolemia, triglyceridemia), biopsy results, total prostate-specific antigen (tPSA) levels, and results of routine urine tests, were documented. Moreover, IPSS and quality of life (QoL) were recorded for the AUR patients before the procedure and on day 7 following the biopsy. For all the patients who underwent AUR, the catheter was removed 3 days after biopsy, and the outcomes were recorded. In addition to the above parameters, all prostatic anatomical parameters were obtained from MRI images, such as the prostatic urethral length (PUL), prostatic urethral angle (PUA), intravesical prostatic protrusion (IPP), total prostatic volume (TPV), transitional zone volume (TZV), transition zone index (TZI), and peripheral zone thickness (PZT), were also collected according to previous reports (14-16).

Biopsy protocol

TRPB was routinely performed under local anesthesia after cleaning of the bowel via enema. The prostate peripheral nerve block (PPNB) technique was used for prostate anesthesia. The procedures were as follows: using the sagittal view of transrectal ultrasound (TRUS), the junction between the prostate and the seminal vesicle was located on one side. After ensuring no blood return via aspiration, 5 mL of 1% lidocaine was injected into the periprostatic region. The ultrasound should show the gradual separation of the prostate and seminal vesicle from the rectal wall, indicating successful distribution of the local anesthetic. The same procedure was then repeated on the contralateral side to anesthetize the prostate peripheral nerves. Additionally, a bowel cleaning procedure was performed: 1 day before the biopsy, the patient was instructed to follow a low-residue diet. The night before the biopsy and 2 hours prior to the procedure, a cleansing enema was administered. An anal iodine enema was also used before the biopsy.

Systematic 12-core biopsy was performed if MRI or ultrasonography detected suspicious lesions. A Bard biopsy gun (Bard MCl 820; Becton Dickinson, and Co., Franklin Lakes, NJ, USA) and an 18-gauge biopsy needle was used. Beta-lactam antibiotics are administered 1 hour before the biopsy and continued for 2 days post-procedure.

Outcome measurement

The primary outcome measure was the occurrence of AUR. An AUR was defined as a painful inability to void with a PVR greater than 200 mL. PVR was measured by bedside ultrasound every 2 hours after voluntary urination in biopsy patients. All patients were treated with tamsulosin (0.4 mg daily) beginning the day before the biopsy procedure for 14 days. For patients with AUR, the urinary catheter was removed after 3 days of indwelling. The secondary outcome assessment was successful removal of the catheter. Clinical success was defined as the absence of acute urinary retention recurrence.

Statistical analysis

All the data were analyzed via SPSS 23.0 statistical software (IBM Corp., Armonk, NY, USA) and R software (v. 4.1.3; R Foundation for Statistical Computing, Vienna, Austria). The clinical features of patients with PVR and patients without PVR were compared via t-tests, Chi-squared tests, or Mann-Whitney U tests, as appropriate. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for PVR. Eventually, risk factors selected by multivariate analysis were used to establish a nomogram prediction model. A P value <0.05 was considered statistically significant.

To assess the discrimination and calibration of the nomogram, the area under the curve (AUC) and calibration plots (bootstrap method, 1,000 repetitions) and the Hosmer-Lemeshow test (P>0.05 indicates good agreement) were generated. Decision curve analysis (DCA) and clinical impact curve (CIC) were used to determine the clinical value of this nomogram.

Results

Baseline characteristics

A total of 333 patients were included in this study, with a median age of 69 (range, 21–92) years. In this study, 66 out of 333 patients (19.8%) required urinary catheters due to difficulty urinating, with a PVR greater than 200 mL, following prostate biopsy. A total of 66 patients were subsequently divided into 3 groups according to PVR: 200–300, 301–500, and >500 mL. We then compared the IPSS, QoL, and success rate of urinary catheter removal before the procedure and on post-biopsy day 7 among the 3 groups. No difference was found in the baseline characteristics among the 3 groups (P=0.96 and P=0.61, respectively). Compared with those in the PVR (200–300 mL) group, the IPSS and QoL on post-biopsy day 7 were significantly greater in the other 2 groups (P=0.01 and P=0.002, respectively). Moreover, the success rate of urinary catheter removal decreased significantly with increasing PVR among patients with an indwelling urinary catheter (P=0.02). All of the above results are shown in Table 1.

At a ratio of 7:3, the cohort was randomly divided into a development cohort (n=233) and a validation cohort (n=100). We found that hypercholesterolemia, PUL, PUA, TPV, TZV, and TZI were significantly associated with AUR (P=0.001, P<0.001, respectively). In the development cohort, we observed a longer PUL, greater PUA, TPV, TZV, and TZI in the AUR group than in the non-AUR group (P<0.001). Moreover, there was a significantly increased prevalence of hypercholesteremia (P=0.04) in the AUR group. In the validation cohort, the differences between the groups of variables were consistent with those in the development cohort (Table 2). The characteristics of all patients are presented in Table 2.

Logistic regression analysis of clinical features

Logistic regression analysis was performed to identify the independent risk factors for predicting AUR in the development cohort. Univariate analysis confirmed that hypercholesteremia, PUL, PUA, TPV, TZV, and TZI were independent risk factors for AUR (P=0.03, P<0.001, respectively) (Table 3). Furthermore, multivariate analysis (forward and stepwise) revealed only 3 independent risk factors, namely, PUL [odds ratio (OR) =1.086, 95% confidence interval (CI): 1.023–1.158, P<0.001], PUA (OR =1.056, 95% CI: 1.028–1.088, P<0.001), and hypercholesteremia (OR =3.013, 95% CI: 1.317–7.020, P=0.01) (Table 4).

Development of the prediction nomogram

We established a nomogram model to predict the presence of AUR after TRPB according to the results of multivariate analysis (Figure 2). To evaluate the performance of the model in the development cohort, a receiver operating characteristic (ROC) curve was drawn, and the AUC was calculated to be 0.834 (95% CI: 0.772–0.896), whereas the concordance index (C-index) was 0.823. As shown in Figure 3A, we observed that the AUC of the complex model was greater than the AUCs of the 3 other individual risk factors. Similarly, better performance of the complex model was shown in the validation cohort, as the AUC increased to 0.895 (95% CI: 0.831–0.958), and the C-index was 0.878, as shown in Figure 3B. Furthermore, as depicted in Figure 3C,3D, the calibration curve showed great agreement between the predictions made by the nomogram and the actual observations in the development and validation cohorts. Additionally, these findings were verified by the Hosmer-Lemeshow test (P=0.69 and P=0.70, respectively).

Figure 2 Nomogram for predicting the likelihood of AUR occurrence in prostate biopsy patients. AUR, acute urinary retention.

Figure 3 Assessment of the discrimination and calibration of the nomogram. ROC curves comparing the complex model with individual feature models in the development cohort (A) and validation cohort (B). Calibration curves depicting the performance of the complex model in the development cohort (C) and validation cohort (D). Decision curves of the complex model and individual feature models for predicting AUR occurrence in prostate biopsy patients (E). CIC analysis was used to assess the model (F). ROC, receiver operating characteristic; AUR, acute urinary retention; CIC, clinical impact curve; AUC, area under curve; CI, confidence interval.

Clinical use

DCA was performed to test the clinical utility of the nomogram. As shown in Figure 3E, the complex model achieved an optimal overall net benefit when the threshold probability ranged from 0.1 to 0.88, suggesting that receiving early intervention is beneficial. A CIC was used to further assess the predictive utility and practical relevance of the nomogram. As depicted in Figure 3F, the complex model demonstrated superior net benefits across a broad spectrum of threshold probabilities. Both DCA and CIC evaluations revealed that the nomograms incorporating hypercholesterolemia, PUL, and PUA exhibited substantial predictive efficacy.

Discussion

In published reports, TRPB has been suggested to cause objective voiding impairment, with some patients even experiencing urinary retention after the procedure (17). However, a clear threshold for PVR, which determines the placement of a catheter, has not yet been established. In the present study, we proposed that a 200 mL PVR may be a cutoff point for catheterization in patients. Furthermore, nomograms are a type of mathematical device or model that is widely used to help doctors make decisions in different clinical settings, especially in predicting complications or patient prognosis. Here, we established a nomogram based on individual patient data to predict the occurrence of AUR to aid in the early detection and timely treatment of this complication.

In recent years, the European Association of Urology (EAU) guidelines have recommended transperineal prostate biopsy. However, TRPB remains widely used due to several advantages, including a low incidence of AUR, which ranges from 0% to 4.4% (18-20). In our study, AUR was detected in 66 patients (19.8%). This is because the diagnosis of AUR can be subjective, whereas the use of PVR for catheter insertion is not consistent. An inability to voluntarily pass urine with a PVR >500 mL is generally considered indicative of AUR (21). However, tissue trauma and swelling after prostate biopsy undoubtedly increase urinary resistance, exacerbating difficulties in urination and the risk of infection. An excess of 200 mL of PVR suggests incomplete emptying, and PVR greater than 200–300 mL is widely believed to be associated with a less favorable response to treatment, increasing the risk of urinary tract infections (UTIs), upper urinary tract dilation, and renal insufficiency (22,23). Therefore, we believe that PVR is the key factor for early diagnosis and timely intervention in patients with AUR. Here, through subgroup analysis of patients with different PVRs, we first identified 200 mL PVR as the intervention threshold on the basis of the significant changes in IPSS, QoL, and successful catheter removal rates between different PVR patients. We hypothesize that the result may be associated with temporary bladder dysfunction caused by bladder overdistention. Additionally, it may be also due to the more pronounced effect of tamsulosin in patients with early intervention for urinary retention, as previous studies have shown that tamsulosin can reduce the incidence of AUR after biopsy (17,24,25). Hence, we took a more proactive approach in diagnosing AUR to safeguard bladder function, especially when patients required intervention following a post-prostate biopsy PVR exceeding 200 mL.

According to the univariate logistic regression analysis, the TZV and TZI were identified as risk factors for AUR. In an early study, TZV and TZI were reported to be significantly associated with LUTS and peak urine flow (25). Similar results were demonstrated by several studies that suggested that relatively larger TPV (>45 mL) and TZV, and higher TZI tend to be more likely to cause AUR (26,27). This may be attributed to more severe prostatic instrumental trauma and prostatic edema/swelling caused by prostate biopsy (10,11). In addition, in early studies, the PUL and PUA were demonstrated to correlate with the severity of LUTS, which are potential risk factors for surgery (10,11,28,29). Our study is the first to report that PUL and PUA can effectively predict the occurrence of AUR. Mechanistically, we hypothesized that prostatic instrumental trauma or edema may further increase the PUL and PUA and subsequently increase the urethral frictional force or bladder outlet resistance to trigger AUR. Additionally, we utilized MRI-measured PUL and PUA data. MRI provides high-resolution, high-contrast images depicting prostate structure, improving measurement accuracy and consistency. In contrast, TRUS images may vary owing to anatomical structures and operator proficiency, leading to uncertainties. Thus, MRI enables more precise PUA and PUL measurements, ultimately enhancing the model’s overall reliability.

Older patients are more likely to develop metabolic syndrome (MetS), which is closely correlated with underlying diseases, such as central obesity, diabetes, hypertension, and dyslipidemia. Recently, evidence has supported the role of MetS parameters in LUTS due to benign prostatic enlargement (BPE) (30). As reported by Lee et al., increased waist circumference is thought to aggravate LUTS (31). In addition, Gacci et al. reported that patients who have greater TPV and TZV always have low serum high-density lipoprotein (HDL) cholesterol levels (32). Our data revealed that hypercholesteremia significantly increased the occurrence of AUR. Therefore, this should be considered a preoperative risk factor when counseling patients prior to prostate biopsy.

Multivariate analysis was further performed in a forward stepwise manner to select risk factors that were strongly associated with AUR (entry criteria P<0.1, retention criteria P<0.05). Of the 6 clinical features, PUL, PUA, and hypercholesteremia were eventually retained and chosen for constructing a nomogram. The final nomograms were composed of 3 clinical features with the highest accuracy and calibration agreement and achieved an AUC of 0.834 in the development cohort and 0.895 in the validation cohort. Furthermore, both DCA and CIC in the current study showed that decision-making based on nomograms to address AUR added more benefit than the treat-all scheme or the treat-none scheme. Hence, the prediction model presents a practical solution for physician decision-making under these circumstances.

There are some limitations in this study. On the one hand, there may have been inevitable selection bias, as certain patients were excluded from this study because of data limitations, even though we prospectively enrolled all consecutive patients from January 2019 to November 2023 in the Third Affiliated Hospital of Sun Yat-sen University. On the other hand, subjective bias may have occurred when selecting IPSS and QoL parameters to investigate the impact of urinary catheterization on biopsy-related voiding impairment under different PVR conditions. Due to insufficient follow-up data, 2 objective parameters, namely, average urinary flow rate and maximum urinary flow rate, were excluded from this study. Therefore, additional large-sample multicenter studies are needed to confirm our conclusions.

Conclusions

In this study, we defined >200 mL as the optimal PVR for indwelling catheters in patients with AUR after TRPB and developed a nomogram to predict the occurrence of AUR in patients who underwent prostate biopsy, considering 3 risk factors: PUA, PUL, and hypercholesterolemia. We aspire to enhance preprocedural consultation among clinical practitioners with the aid of this predictive model while also providing insights for the timely recognition and intervention of postprocedural urinary retention.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-24-399/rc

Data Sharing Statement: Available at https://tau.amegroups.com/article/view/10.21037/tau-24-399/dss

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-24-399/prf

Funding: This work was supported by the Guangdong Natural Science Foundation (grant No. 2021A1515012322) and the Science and Technology Project of Guangzhou City (No. 2023A03J0200).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-24-399/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Medical Ethics Board of The Third Affiliated Hospital of Sun Yat-sen University (No. II2024-156-02) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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(English Language Editor: J. Jones)