A Novel Scoring System for Prediction of Prostate Cancer Based on Shear Wave Elastography and Clinical Parameters.

OBJECTIVE

To develop a novel scoring system for the prediction of prostate cancer (PCa).

METHODS

We assessed 127 patients who underwent a prostate biopsy. Prior to biopsy, we performed shear wave elastography (SWE), transrectal ultrasound, digital rectal exam, total prostatic specific antigen, PSA density (PSAD), and free PSA/total PSA ratio (F/T). We developed an 11-point scoring system based on SWE and these clinical parameters.

RESULTS

PCa was diagnosed in 51 (40.2%) of 127 patients and 192 (25.2%) of 762 sextants on initial biopsy. ROC curve analyses showed that the cutoff value (COV) for SWE was 40.8 kpa at the sextant level. The AUC of score system based on the SWE and clinical parameters (0.911) was significantly different from scoring systems based on SWE alone (0.842) or clinical parameters alone (0.868). For this 11-point scoring system, the optimal COV, Youden index, sensitivity, specificity, PPV, NPV, and AUC were 3 points, 0.66, 76.5% 89.5%, 82.98%, 85.00%, and 0.911, respectively. There were 68 negative biopsy results in patients with 0-3 points, and the detection rate of PCa was 100% in patients with scores exceeding 6 points.

CONCLUSION

This 11-point scoring system based on SWE and clinical parameters has the good diagnostic performance for predicting PCa. It may be useful in selecting patients for biopsy, substantially reducing the number of unnecessary biopsies while ensuring that few cancers are missed.