Prospective validation of an algorithm with systematic sextant biopsy to predict pelvic lymph node metastasis in patients with clinically localized prostatic carcinoma.
OBJECTIVE
We prospectively validate an algorithm to predict pelvic lymph node metastasis in patients with clinically localized prostatic carcinoma.


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.
Conrad
Stefan
S
Department of Urology, Institute of Mathematics and Computer Science in Medicine, University of Hamburg, Eppendorf University Hospital, Hamburg, Germany.
Graefen
Markus
M
Pichlmeier
Uwe
U
Henke
Rolf-Peter
RP
Erbersdobler
Andreas
A
Hammerer
Peter G
PG
Huland
Hartwig
H
D000465:Algorithms; D001706:Biopsy / Q000379:methods; D006801:Humans; D008207:Lymphatic Metastasis / Q000473:pathology; D008297:Male; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D011446:Prospective Studies; D011471:Prostatic Neoplasms / Q000473:pathology*; D018570:Risk Assessment