Prospective validation of an algorithm with systematic sextant biopsy to predict pelvic lymph node metastasis in patients with clinically localized prostatic carcinoma
- PMID: 11792910
- DOI: 10.1016/S0022-5347(01)69077-3
Prospective validation of an algorithm with systematic sextant biopsy to predict pelvic lymph node metastasis in patients with clinically localized prostatic carcinoma
Abstract
Purpose: We prospectively validate an algorithm to predict pelvic lymph node metastasis in patients with clinically localized prostatic carcinoma.
Material and methods: 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.
Results: 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.
Conclusions: 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.
Comment in
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Prostate biopsy quantitative histology as a staging and prognostic factor.J Urol. 2002 Feb;167(2 Pt 1):526-7. doi: 10.1016/S0022-5347(01)69078-5. J Urol. 2002. PMID: 11792911 No abstract available.
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