Construction and Validation of a Pain Risk Assessment Model for Transperineal Prostate Biopsy

Abstract

Transperineal prostate biopsy (TPPB) is a critical diagnostic procedure for prostate cancer. Despite its utility, patients often report varying levels of pain during the procedure. Understanding the risk factors associated with pain can aid in refining patient selection and enhancing patient comfort. The primary aim of this study is to construct and validate a pain risk assessment model specifically for TPPB, identifying key predictors of pain and implementing a scoring system for clinical application. By integrating various demographic, clinical, and procedural variables, a robust tool was created to assist in preoperative planning and improve patient outcomes. A retrospective cohort study was conducted involving patients who underwent TPPB. Data on demographic, clinical, and procedural factors were collected. Various statistical analyses, including logistic regression, were utilized to identify predictors of pain. The model’s performance was validated using a separate cohort. The final model included age, prostate volume, previous biopsy history, and anxiety levels as significant predictors. The model demonstrated good discrimination (AUC = 0.85) and calibration.The developed pain risk assessment model for TPPB can serve as a valuable tool for clinicians to predict and manage pain, ultimately improving patient experiences.Future research should focus on validating this model in diverse populations and integrating additional risk factors to enhance its predictive power.