Objectives: To test the accuracy of a previously externally validated sextant biopsy nomogram in referred men exposed to > or =10 or more biopsy cores. Moreover, we explored the hypothesis that a more accurate predictive tool could be developed.
Methods: Previous nomogram predictors (age, digital rectal examination, prostate-specific antigen, and percent free PSA) were used to assess the accuracy of our previous nomogram in a cohort consisting of 2900 men referred for prostatic evaluation. Moreover, these variables were complemented with sampling density (SD) (i.e., ratio of gland volume and the number of planned biopsy cores) within multivariable logistic regression models (LRM) predicting presence of prostate cancer (pCA) on the initial 10 or more core biopsy. The LRMs were used to develop and internally validate (200 bootstrap resamples) a new nomogram in 1162 men from Hamburg, Germany. The LRMs' external validity was tested in three separate cohorts (Hamburg, n=582; Milan, n=961; Seattle, n=195).
Results: The contemporary external validation of the previously validated sextant nomogram demonstrated 70% accuracy. Internal validation of the new nomogram demonstrated 77% accuracy, and external cohorts demonstrated 73-76% accuracy.
Conclusions: In the era of extended biopsy schemes, previously developed predictive models are less accurate in predicting the probability of pCA on initial biopsy. We developed a new tool that allows obtaining more accurate predictions. Moreover, before biopsy, it also allows defining the ideal ratio between gland volume and the number of planned biopsy cores that would yield the ideal biopsy rate.