Combined anatomical parameters predict benign prostatic hyperplasia-related lower urinary tract symptom severity: a volume-stratified study

Introduction

Background

Benign prostatic hyperplasia (BPH) is a common urological condition among middle-aged and older men, and the prevalence increases significantly with age. Histologically characterized by stromal and glandular hyperplasia, BPH is frequently accompanied by lower urinary tract symptoms (LUTS), such as dysuria (1,2). In severe BPH, LUTS may progress to complications, including acute urinary retention and renal impairment, which substantially diminish quality of life (QoL) and impose a significant psychological burden. Therefore, early assessment of LUTS severity holds important clinical significance.

Rationale and knowledge gap

In clinical practice, symptoms are typically assessed using the International Prostate Symptom Score (IPSS) and uroflowmetry, while prostate volume (PV) is used to evaluate the degree of hyperplasia. However, numerous studies have revealed a lack of consistent correlation between the PV and the severity of LUTS (3,4). Notably, many patients with small prostates still experience significant symptoms, which poses limitations in relying solely on volume for assessment. Ultrasonography is currently the most convenient and economical imaging method for evaluating the prostate. Particularly, the biplanar transrectal probe can more clearly display the internal structure of the prostate and its anatomical relationship with the urethra and bladder (5). Compared to PV, anatomical parameters, such as the prostatic urethral angle (PUA) and intravesical prostatic protrusion (IPP), better reflect LUTS severity and correlate more closely with treatment outcomes (6-8). However, few studies have comprehensively examined the association between these anatomical parameters and LUTS severity in patients with BPH, and systematic evaluation regarding the combined effects of multiple parameters is particularly lacking.

Objective

This study aimed to systematically investigate the association between prostate anatomical parameters and both the IPSS and maximum urinary flow rate (Qmax) across different PV strata. Furthermore, we sought to develop a predictive model for voiding dysfunction to aid in precise evaluation and clinical decision-making in patients with BPH. We present this article in accordance with the TRIPOD reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-1-919/rc).

Methods

Patients

This retrospective study enrolled patients diagnosed with BPH who presented with LUTS at The First Affiliated Hospital of Jinan University between January 2023 and March 2024. The exclusion criteria were as follows: (I) patients with recurrent urinary retention, severe urinary tract infection, or renal insufficiency; (II) history of conservative or surgical interventions for BPH; (III) previous diagnosis of urogenital malignancies or prostate cancer; (IV) suspected prostate malignancy or elevated total prostate-specific antigen (tPSA >4 ng/mL); (V) concurrent bladder dysfunction or any condition potentially compromising normal detrusor activity; (VI) communication barriers or inability to cooperate during transrectal ultrasound examination; (VII) urethral deviation preventing acquisition of the prostatic midsagittal plane; or (VIII) suboptimal image quality compromising diagnostic interpretation. In total, 257 eligible patients were included in the final analysis.

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of The First Affiliated Hospital of Jinan University (No. KY-2025-091) and informed consent was taken from all the patients.

Outcome measures and assessment methods

Assessment of clinical symptoms

LUTS were assessed using the IPSS questionnaire, which includes seven symptom questions and a QoL question (9). The International Prostate Symptom Score total score (IPSS-t) ranges from 0 to 35. For detailed analysis, the total score was divided into storage subscore (IPSS-s, items 2, 4, 7) and voiding subscore (IPSS-v, items 1, 3, 5, 6). Qmax was measured using a standard uroflowmeter. Both outcome measures were assessed during the same clinical visit.

Ultrasonographic measurement of prostatic anatomical parameters

All prostate anatomical parameters were measured by a single sonographer who was blinded to the patients’ IPSS and Qmax results. PV and transition zone volume (TZV) were measured on maximal sagittal and transverse sections, and volumes were calculated using the prolate ellipsoid formula (length × width × height × 0.52). The transition zone index (TZI) was defined as the TZV divided by the total PV. The IPP was measured as the vertical distance from the base of the bladder to the prostatic protrusion tip in the sagittal plane. The PUA was defined as the angle between the proximal and distal urethral axes at the verumontanum on the midsagittal view. The prostatic urethral length (PUL) was measured by tracing the urethra along its entire intraprostatic course, from the apex to the base. The bladder neck angle (BNA) was defined as the angle that formed between the anterior and posterior bladder walls at the level of the internal urethral orifice. All measurements were taken from clearly delineated anatomical landmarks.

Statistical analysis

All statistical analyses were conducted using IBM SPSS Statistics version 27.0 (IBM Corp., Armonk, NY, USA) and R software (version 4.5.1). Continuous variables are presented as median (P25, P75). All variables of interest had complete data with no missing values. A total of 257 patients were stratified by PV using the 30 mL threshold. This cutoff is endorsed by major urological guidelines for predicting BPH progression and is associated with an approximately threefold higher risk of acute urinary retention in patients with PV ≥30 mL (10-12). Between-group differences in the continuous variables were ascertained using the Mann-Whitney U test. Spearman’s rank correlation was used to assess associations between anatomical parameters and both IPSS and Qmax.

Explanatory modeling

Univariable and multivariable linear regression analyses were conducted in both groups to identify independent predictors of IPSS and Qmax. Variables were initially screened using univariable analysis (P<0.20), followed by multivariable analysis. This approach aimed to explain how specific anatomical features contribute to IPSS and Qmax within each volume stratum.

Predictive modeling

We used univariable and multivariable logistic regression analyses to identify predictors of voiding dysfunction (Qmax <10 mL/s) and subsequently developed a combined predictive model. The predictive model was developed using a two-stage variable selection strategy. First, potential predictors were screened through univariable logistic regression (P<0.10). Subsequently, LASSO regression (with λ value selected via ten-fold cross-validation) was applied to these preliminary candidates to identify the final set of predictive factors. Based on this set, a standard multivariable logistic regression model was constructed as the final predictive model.

All continuous variables were included in their original form, assuming a linear relationship with the outcome. The variance inflation factor was used to assess multicollinearity.

Model validation and performance evaluation

Internal validation was performed via 1,000 bootstrap resampling iterations to correct for overfitting and to calculate optimism-corrected performance metrics, such as the area under the curve (AUC). The model’s performance was evaluated using receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and calibration curves. The statistical significance level was set at P<0.05.

Results

Baseline characteristics

A total of 257 patients were included in the final analysis. The patient flow chart is shown in Figure 1. Patients were divided into small-volume (PV <30 mL, n=166) and large-volume (PV ≥30 mL, n=91) groups. As shown in Table 1, the large-volume group had significantly higher age, prostate measurements (PV, TZV, IPP, PUA, PUL, BNA), more severe symptom scores, and lower Qmax values (all P<0.001).

Figure 1 Patient flowchart. BPH, benign prostatic hyperplasia; LUTS, lower urinary tract symptoms; PV, prostate volume; tPSA, total prostate-specific antigen; TRUS, transrectal ultrasound.

Correlations between anatomical parameters and LUTS

Spearman’s correlation analysis revealed significant associations between anatomical parameters and the LUTS severity in both groups (Figure 2). In the large-volume group (Figure 2A), all parameters (including age, TZV, TZI, IPP, BNA, PUA, and PUL) significantly correlated with IPSS and Qmax (P<0.05). In the small-volume group (Figure 2B), age, TZV, TZI, BNA, and PUL correlated with both outcomes, whereas the IPP was associated only with IPSS-v (P=0.02), and the PUA showed no correlation with IPSS-s (P=0.17).

Figure 2 Spearman correlations in both groups. (A) Spearman correlations for IPSS and Qmax in the large-volume group. (B) Spearman correlations for IPSS and Qmax in the small-volume group. Statistical significance is denoted by asterisks: ***, P<0.001; **, P<0.01; *, P<0.05. BNA, bladder neck angle; IPP, intravesical prostatic protrusion; IPSS-s, International Prostate Symptom Score storage subscore; IPSS-t, International Prostate Symptom Score total score; IPSS-v, International Prostate Symptom Score voiding subscore; PUA, prostatic urethral angle; PUL, prostatic urethral length; PV, prostate volume; Qmax, maximum urinary flow rate; TZI, transition zone index; TZV, transition zone volume.

Predictors of the IPSS-t and Qmax

Univariable and multivariable linear regression analyses identified independent predictors of IPSS-t and Qmax. In the large-volume group (Table 2), IPP (β=−0.21, P<0.001) and PUA (β=−0.09, P<0.001) were independent predictors of Qmax; moreover, IPP (β=0.29, P=0.007), age (β=0.14, P=0.01), BNA (β=0.09, P=0.009), and PUA (β=0.08, P=0.03) independently predicted IPSS-t. In the small-volume group (Table 3), PUL (β=−0.29, P<0.001) and BNA (β=−0.09, P<0.001) were independent predictors of Qmax; age (β=0.11, P=0.003), PUL (β=0.20, P=0.03) and BNA (β=0.12, P<0.001) independently predicted IPSS-t.

Logistic regression analysis and model evaluation for prediction of voiding dysfunction (Qmax <10 mL/s) in the large-volume group

Subgroup analysis was performed by stratifying the large-volume group, into a low-flow subgroup (Qmax <10 mL/s, n=47) and a high-flow subgroup (Qmax ≥10 mL/s, n=41). Univariable and multivariable logistic regression identified IPP [odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.08–1.63, P=0.01], BNA (OR =1.11, 95% CI: 1.05–1.18, P<0.001), and PUA (OR =1.08, 95% CI: 1.01–1.16, P=0.04) as independent risk factors of low Qmax (Table 4).

The diagnostic performance of these parameters was evaluated using ROC analysis (Figure 3 and Table 5). Each parameter individually showed strong diagnostic performance: BNA (AUC =0.87; cutoff =73.9°; sensitivity =0.89, specificity =0.77), IPP (AUC =0.84; cutoff =6.55; sensitivity =0.68, specificity =0.89) and PUA (AUC =0.80; cutoff =57.5°; sensitivity =0.64, specificity =0.91). The combined model (IPP + BNA + PUA) yielded the highest accuracy (AUC =0.94; sensitivity =0.79, specificity =0.96). The DeLong test confirmed that the AUC of the combined model was significantly larger than those of the individual models for IPP, BNA, and PUA (adjusted P=0.004, 0.030, and 0.001, respectively).

Figure 3 ROC analysis curves of different models. AUC, area under the curve; BNA, bladder neck angle; IPP, intravesical prostatic protrusion; PUA, prostatic urethral angle; ROC, receiver operating characteristic.

As shown in Figure 4A, the calibration curve for the combined model demonstrated excellent agreement between predicted and observed outcomes (Hosmer-Lemeshow test, P=0.95). After 1,000 Bootstrap iterations, the corrected AUC was 0.945 (95% CI: 0.894–0.979) with an optimism of −0.001. The results indicate that the model has stable discriminative ability. To evaluate the model’s clinical utility, we performed DCA (Figure 4B), which revealed that, compared with any single parameter, the combined model can provide higher net benefits over a wide range of risk acceptance levels, which makes it well-suited for clinical risk assessment and decision-making.

Figure 4 Clinical performance of the predictive models for voiding dysfunction in the large-volume group. (A) Calibration plot of the combined predictive model, showing the concordance between model-estimated probabilities and actual prevalence of voiding dysfunction. (B) DCA plot evaluating the standardized net benefit of adopting different models. BNA, bladder neck angle; DCA, decision curve analysis; IPP, intravesical prostatic protrusion; PUA, prostatic urethral angle.

Detailed results of the univariate analyses and the variable selection process are available in Tables S1-S3.

Discussion

Consistent with the explanatory aim of this study, linear regression analyses were conducted to elucidate the distinct anatomical drivers of LUTS severity across prostate size categories. The results indicated that for patients with smaller PVs, the severity of LUTS was primarily and independently associated with PUL and BNA, with PUL showing the strongest correlation. In contrast, LUTS severity in patients with large prostates was independently associated with IPP, BNA, and PUA, with IPP showing the strongest correlation.

In alignment with the majority of prior research, our study also found that volumetric parameters (TZI and TZV) either demonstrated only weak correlations or no significant association with LUTS severity (8,13,14). This finding supports the perspective that these volumetric parameters are of secondary importance in evaluating BPH/LUTS, whereas structural alterations in the urethra and bladder neck may represent the primary etiological factor.

PUL refers to the longitudinal measurement of the urethral segment that traverses the prostate gland. The urethra itself is a narrow, elongated tubular structure, and in patients with BPH, the urethral lumen may become elongated and irregular owing to uneven glandular hyperplasia, which further increasing the energy requirement for micturition. Current evidence on its clinical impact remains inconsistent. While Ko et al. found no significant correlation between PUL and IPSS or Qmax in cohorts stratified by PV (15), Kim et al. reported that a higher PUL was associated with an increased risk of surgical intervention (16). In our study, linear regression analysis in the small-prostate group indicated PUL as an independent predictor of IPSS-t and Qmax, whereas this independent association was absent in the large prostate group.

PUA is defined as the angle of the urethral bend at the prostatic portion. Previous studies have reported that a larger PUA correlates with higher IPSS and lower Qmax values (8,17). Furthermore, Shim et al.’s study demonstrated that PUA significantly correlated with LUTS severity in patients with BPH and PV <50 mL whereas no correlation was observed in those with PV ≥50 mL (18). Consistent with the volume-dependent role of PUA, the present study found that PUA was independently associated with IPSS-t and Qmax in patients with large prostates.

The BNA exhibits a funnel-shaped structure in the sagittal plane—a morphology that is conducive to urination. However, in patients with BPH, hyperplasia of the median or lateral lobes alters this funnel shape and thereby impairs voiding. A widened BNA can induce turbulence at the urethral orifice, increasing energy expenditure, elevating voiding resistance, and exacerbating urinary difficulty. Consistent with the findings of Li et al., who reported that BNA independently correlates with both Qmax and IPSS-t and is significantly higher in patients with acute urinary retention (19), our study further identified BNA as an independent factor influencing IPSS-t and Qmax in the small-volume group, as well as IPSS-t in the large-volume group.

The IPP refers to the extent of prostatic tissue protruding into the bladder lumen. Its mechanism for causing urinary difficulty primarily involves the protrusion of glandular tissue into the bladder that elevates and distorts the bladder neck, which results in urinary obstruction. Most previous studies have indicated that IPP is associated with bladder outlet obstruction (BOO) and BPH/LUTS, establishing it as a widely recognized marker of BOO (6,20-22). The results of this study demonstrate that IPP was an independent predictor of both IPSS-t and Qmax in the large-volume group, while no significant association was observed in the small-volume group. These findings further confirm the significant clinical value of the IPP in assessing symptom burden among patients with large-volume BPH, thereby underscoring the clinical necessity of conducting volume-stratified research in patients with BPH.

Comprehensive analysis revealed a key distinction between the two groups: PUL served as an independent predictor of LUTS only in the small-volume group, while IPP demonstrated greater predictive value in the large-volume group. This discrepancy suggests distinct underlying mechanisms for BPH-related LUTS: symptoms in the small-volume group may primarily stem from urethral structural and morphological alterations whereas symptoms in the large-volume group are predominantly driven by BOO caused by glandular protrusion. Therefore, the transrectal ultrasound evaluation of patients with BPH of different volumes should prioritize their specific anatomical parameters to achieve more precise individualized diagnosis and treatment.

As Qmax <10 mL/s is a recognized indicator of BOO or voiding dysfunction (23), we developed a preliminary predictive model specifically for patients in the large-volume subgroup with this condition. In contrast, owing to the limited number of outcome events, a corresponding predictive model could not be constructed for the small-volume group (24). The results revealed that the IPP, BNA, and PUA are independent predictors of reduced urinary flow rate in large-volume BPH. A combined model that incorporated all three parameters demonstrated outstanding predictive performance (AUC =0.94, sensitivity =0.79, specificity =0.96). DCA further confirmed that the model provides significant net benefit across a wide range of threshold probabilities, demonstrating its potential clinical utility for risk assessment and individualized decision support. This finding contributes to the growing body of evidence supporting the use of ultrasonographic anatomical parameters as noninvasive diagnostic adjuncts for LUTS, a strategy that has been systematically reviewed and advocated for in recent literature (25).

While the combined model demonstrated promising discriminative ability, it is essential to contextualize its current stage of development. Derived from a single-center retrospective cohort, the model is presented primarily as a hypothesis-generating and proof-of-concept tool; its performance may reflect optimism bias, and external validation is mandatory before any consideration of clinical deployment. To illustrate its translational potential, a practical implementation pathway can be envisaged: clinicians would (I) obtain standardized IPP, BNA, and PUA measurements; (II) calculate an individual risk score using the coefficients; and (III) interpret this score against thresholds supported by our DCA to inform diagnostic or therapeutic discussions. This pathway underscores the model’s clinical logic while emphasizing that its real-world utility awaits future prospective evaluation and integration into point-of-care tools.

There are some limitations in this study. First, the single-center retrospective design may introduce selection bias. Second, the limited number of voiding dysfunction events in the large‑volume subgroup constrains the events‑per‑variable ratio, which may affect coefficient stability, increase the risk of overfitting, and lead to optimistic performance estimates—even with the application of LASSO regression and bootstrap internal validation. Third, dichotomization based on the guideline-recommended threshold of 30 mL may not fully capture the continuous nature of the relationship between volume and obstruction, and the sensitivity of the results to this specific cutoff warrants further investigation. Fourth, although reliance on a single sonographer for all measurements ensures internal consistency, it limits assessment of inter‑observer reproducibility. Fifth, dynamic changes in anatomical parameters during voiding and other potential confounders (e.g., urethral compliance) were not evaluated. Therefore, prospective, multicenter validation is warranted to establish the model’s transportability across diverse populations and clinical settings.

Conclusions

This study demonstrates that the association between prostate anatomical parameters and the severity of LUTS is volume-dependent. A predictive model integrating IPP, BNA, and PUA shows favorable predictive performance for voiding dysfunction in patients with large-volume BPH. These findings underscore the clinical utility of ultrasonographic anatomical assessment and support the adoption of volume-stratified management. External validation in prospective multicenter cohorts remains essential to advance this model toward clinical translation as a decision-support tool.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-1-919/rc

Data Sharing Statement: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-1-919/dss

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-1-919/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-1-919/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 and its subsequent amendments. The study was approved by the Ethics Committee of The First Affiliated Hospital of Jinan University (No. KY-2025-091) and informed consent was taken from all the patients.

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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