Predictors and predictive performance of immune–inflammation indices for symptom severity in benign prostatic hyperplasia

Although the relatively unchanging consequences of age and genetic factors significantly contribute to the development and progression of Benign Prostatic Hyperplasia (BPH), numerous modifiable factors play a role in preventing progression or alleviating symptoms. Identifying predictors of symptom severity and objective biomarkers is beneficial for effective management. This study aimed to determine the predictors of BPH symptom severity and assess the predictive performance of hematologically derived inflammatory markers in patients attending Dessie Comprehensive Specialized Hospital in Ethiopia. A cross-sectional study was conducted from August to October 2024. Data was collected through face-to-face interviews performed by well-trained health professionals using the KoboCollect application. STATA version 17 was utilized for statistical data analysis. Bivariable and multivariable logistic regression analyses were employed to identify predictors of BPH severity, with a p-value of < 0.05 considered statistically significant in the multivariable logistic regression. The predictive performance of immune-inflammatory index levels for the severity of BPH was evaluated using receiver operating characteristic (ROC) curve analysis, and pairwise comparisons of Area Under the Curve (AUC) were conducted using DeLong's test. Ethical clearance was obtained from the Ethics Review Committee of Wollo University. A total of 232 BPH patients were included in this study, of whom 84 (36.21%) presented with severe symptoms. Age ≥ 65 years (AOR = 2.55, 95% CI: 1.19, 5.45), low physical activity (AOR = 2.56, 95% CI: 1.22-5.35), central obesity (AOR = 2.79, 95% CI: 1.07-7.25), and elevated immune-inflammatory markers [SII > 564.92 × 10³ (AOR = 2.97, 95% CI: 1.10-7.98), PII > 273.3 × 10⁶ (AOR = 2.46, 95% CI: 1.04-5.86), and NLR ≥ 1.368 (AOR = 2.87, 95% CI: 1.01-8.14)] were significantly associated with severe BPH symptoms (p-value < 0.05). In ROC analysis, SII exhibited the highest predictive performance for severe symptoms with an AUC of 0.736 (95% CI: 0.67, 0.801); optimal cut-off: 564.92 × 10³; specificity - 72%, sensitivity - 69%; PII demonstrated similar performance with an AUC of 0.729 (95% CI: 0.66, 0.796); optimal cut-off: 273.3 × 10⁶; specificity and sensitivity of 69%. Although it was not significantly associated with severe BPH, PLR also demonstrated moderate predictive performance (AUC = 0.67, specificity 66%, sensitivity 68%), while LMR exhibited poor predictive ability (AUC = 0.403; 95% CI: 0.328, 0.477). Pairwise DeLong's tests confirmed that SII had significantly higher accuracy than NLR (p-value = 0.0003) and PLR (p-value 0.044), but not PII (p-value = 0.769). The LOESS curve further revealed a non-linear, monotonically positive association between SII and the probability of severe BPH, with a marked rise in risk at higher SII levels. Advanced age, adverse lifestyle factors, and elevated systemic inflammatory markers (SII, PII, NLR) were significant predictors of BPH severity. SII and PII, derived from routine blood tests, showed moderate predictive value for identifying patients with severe BPH, with SII showing superior discriminative accuracy, and may serve as accessible, non-invasive adjunct biomarkers. LMR was not identified as a useful predictor in this context. These findings highlighted the role of inflammation in BPH severity and suggest markers for clinical assessment. Further studies are recommended to validate these findings and explore their implications in therapeutic decision-making.