Development and internal validation of preoperative transition zone prostate cancer nomogram.
OBJECTIVE
Up to 20% of men may harbor a transition zone (TZ) prostate cancer (PCa) at radical prostatectomy (RP). TZ PCa may be associated with more favorable RP pathologic findings than peripheral zone (PZ) PCa. To identify these men, we developed a model capable of predicting the probability of TZ PCa at RP.


METHODS
The study cohort consisted of 945 consecutive men treated with RP, with clinical stage, prostate-specific antigen (PSA) level, and detailed biopsy and RP pathology data available. The preoperative variables were used as predictors in the multivariate logistic regression models to predict the rate of TZ PCa at RP. PCa was defined as a TZ tumor when more than 50% of the planimetrically measured tumor volume was situated within the TZ. Regression coefficients were used to develop nomograms, which were subjected to 200 bootstrap resamples to reduce overfit bias.


RESULTS
TZ PCa at the final pathologic examination was recorded in 110 patients (11.6%). After 200 bootstraps, the most parsimonious and most accurate nomogram was 77.3% accurate in predicting the probability of TZ PCa.


CONCLUSIONS
This nomogram is ideally suited to identify patients with markedly elevated, nearly metastatic serum PSA levels who harbor a TZ tumor that is highly treatable by RP.
Steuber
Thomas
T
Department of Urology, University of Hamburg, Hamburg, Germany.
Chun
Felix K-H
FK
Erbersdobler
Andreas
A
Briganti
Alberto
A
Haese
Alexander
A
Graefen
Markus
M
Schlomm
Thorsten
T
Valiquette
Luc
L
Huland
Hartwig
H
Karakiewicz
Pierre I
PI
D000328:Adult; D000368:Aged; D001707:Biopsy, Needle; D019160:Endosonography; D006801:Humans; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging / Q000592:standards; D049451:Nomograms; D011300:Preoperative Care; D011379:Prognosis; D011468:Prostatectomy; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology* / Q000601:surgery; D012189:Retrospective Studies; D012720:Severity of Illness Index