PROSPECTIVE VALIDATION OF AN ALGORITHM WITH SYSTEMATIC SEXTANT BIOPSY TO PREDICT PELVIC LYMPH NODE METASTASIS IN PATIENTS WITH CLINICALLY LOCALIZED PROSTATIC CARCINOMA

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Abstract
We prospectively validate an algorithm to predict pelvic lymph node metastasis in patients with clinically localized prostatic carcinoma. A total of 293 patients with prostatic cancer were identified before pelvic lymph node dissection according to an algorithm developed with the classification and regression tree analysis as high-greater than 3 sextant biopsies containing any Gleason grade 4 or 5 cancer, intermediate-at least 1 biopsy dominated by Gleason grade 4 or 5 cancer but not high risk and low risk-all other patients. Observed and predicted frequencies of pelvic lymph node metastasis were compared. The observed frequencies of lymph node metastasis were remarkably similar to the predicted frequencies, including 2.8% versus 2.2% in 85.7% of patients in the low risk group, 16.7% versus 19.4% in 10.2% intermediate and 41.7% versus 45.5% in 4.1% high, respectively. If patients in the low risk group were considered to have node negative disease the specificity and negative predictive value of the algorithm were 88.4% and 97.2%, respectively. Our algorithm is valid as a simple and accurate tool for the prediction of pelvic lymph node metastasis in patients with clinically localized prostatic cancer. Those 85.7% of patients classified by the algorithm to have a low risk of lymphatic spread should not undergo pelvic lymph node dissection before definitive local treatment.