OBJECTIVE: To develop a methodology applicable to the morphologic study of the efficacy of finasteride on prostatic intraepithelial neoplasia (PIN), a putative precursor of prostate cancer. STUDY DESIGN: Three PIN foci were reviewed in two simple prostatectomy specimens from patients with clinical diagnoses of benign prostatic hyperplasia and treated with finasteride for six months. The feasibility of PIN diagnosis and grading based on "diagnostic distance" was investigated. It is a measure of the "extent" to which the observed features are different from those of the untreated prototypes representing the following diagnostic categories: normal prostate, low and high grade PIN and prostatic adenocarcinoma with a cribriform or large acinar pattern. Uncertainty in the PIN diagnosis and grading was dealt with by means of a Bayesian belief network (BBN). RESULTS: The distance measure values of the three PIN foci from the prototype of untreated, nonneoplastic prostate were 9, 7 and 8, respectively, in relative, arbitrary units. Their distance from the two prostate cancer patterns (large acinar and cribriform) was as high as 8-10. The distance of these foci from either low or high grade PIN were as low as 5, 3 and 2, and 3, 5 and 4, respectively. BBN produced the highest belief values for PIN, thus confirming the morphology-based and diagnostic distance-supported diagnosis; however, the belief values were low for both grades. CONCLUSION: The results provided by BBN analyses and diagnostic distance measures support the conclusion that this methodology is applicable to assessing the efficacy of finasteride treatment of PIN.
OBJECTIVE: To develop a methodology applicable to the morphologic study of the efficacy of finasteride on prostatic intraepithelial neoplasia (PIN), a putative precursor of prostate cancer. STUDY DESIGN: Three PIN foci were reviewed in two simple prostatectomy specimens from patients with clinical diagnoses of benign prostatic hyperplasia and treated with finasteride for six months. The feasibility of PIN diagnosis and grading based on "diagnostic distance" was investigated. It is a measure of the "extent" to which the observed features are different from those of the untreated prototypes representing the following diagnostic categories: normal prostate, low and high grade PIN and prostatic adenocarcinoma with a cribriform or large acinar pattern. Uncertainty in the PIN diagnosis and grading was dealt with by means of a Bayesian belief network (BBN). RESULTS: The distance measure values of the three PIN foci from the prototype of untreated, nonneoplastic prostate were 9, 7 and 8, respectively, in relative, arbitrary units. Their distance from the two prostate cancer patterns (large acinar and cribriform) was as high as 8-10. The distance of these foci from either low or high grade PIN were as low as 5, 3 and 2, and 3, 5 and 4, respectively. BBN produced the highest belief values for PIN, thus confirming the morphology-based and diagnostic distance-supported diagnosis; however, the belief values were low for both grades. CONCLUSION: The results provided by BBN analyses and diagnostic distance measures support the conclusion that this methodology is applicable to assessing the efficacy of finasteride treatment of PIN.