Predicting clinically significant prostate cancer in elderly patients: A nomogram approach with shear wave elastography.

PURPOSE

This study was to construct a nomogram utilizing shear wave elastography and assess its efficacy in detecting clinically significant prostate cancer (csPCa).

METHODS

290 elderly people with suspected PCa who received prostate biopsy and shear wave elastography (SWE) imaging were respectively registered from April 2022 to December 2023. The elderly participants were stratified into two groups: those with csPCa and those without csPCa, which encompassed cases of clinically insignificant prostate cancer (cisPCa) and non-prostate cancer tissue, as determined by pathology findings. The LASSO algorithm, known as the least absolute shrinkage and selection operator, was utilized to identify features. Logistic regression analysis was utilized to establish models. Receiver operating characteristic (ROC) and calibration curves were utilized to evaluate the discriminatory ability of the nomogram. Bootstrap (1000 bootstrap iterations) was employed for internal validation and comparison with two models. A decision curve and a clinical impact curve were employed to assess the clinical usefulness.

RESULTS

Our nomogram, which contained Emean, ΔEmean, prostate volume, prostate-specific antigen density (PSAD), and transrectal ultrasound (TRUS), showed better discrimination (AUC = 0.89; 95% CI: 0.83-0.94), compared to the clinical model without SWE parameters (p = 0.0007). Its accuracy, sensitivity and specificity were 0.83, 0.89 and 0.78, respectively. Based on the analysis of decision curve, the thresholds ranged from 5% to 90%. According to our nomogram, biopsying patients at a 20% probability threshold resulted in a 25% reduction in biopsies without missing any csPCa. The clinical impact curve demonstrated that the nomogram's predicted outcome is closer to the observed outcome when the probability threshold reaches 20% or greater.

CONCLUSION

Our nomogram demonstrates efficacy in identifying elderly individuals with clinically significant prostate cancer, thereby facilitating informed clinical decision-making based on diagnostic outcomes and potential clinical benefits.