Korean J Urol.
2003 Aug;44(8):753-758.
Nomograms for the Prediction of the Pathological Stage of the Clinically Localized Prostate Cancer in Korean Men
- Affiliations
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- 1Department of Urology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea. hjahn@amc.seoul.kr
- 2Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
Abstract
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PURPOSE: The data of Korean men with prostate cancer from a single institute were analyzed to construct nomograms predicting the pathological stage and to compare the outcomes with pre-existing nomograms.
MATERIALS AND METHODS
A total of 254 Korean men, with clinically localized prostate cancer, who underwent radical retropubic prostatectomy at Asan Medical Center, between June 1990 and April 2002, were included in this study. A multinomial log-linear regression analysis was performed for the simultaneous prediction of organ-confined disease(OC), seminal vesicle invasion(SVI) or lymph node metastasis(LN) using serum PSA, Gleason scores and clinical stages. Nomograms representing the percentage probabilities were constructed, and compared with the preexisting nomograms presented in the work of Partin et al. and Egawa et al., by calculating the area under the receiver operating characteristics(ROC) curves.
RESULTS
Nomograms predicting the likelihood of OC, SVI and LN were derived from the combination of the aforementioned preoperative variables. When the nomograms were compared using the ROC curves, with the Partin table, the areas under the curves were 0.758, 0.762 and 0.766 for OC, SVI and LN, respectively, and with the Egawa table, 0.766 and 0.669 for OC and SVI, respectively. In the multiple measures analysis, which tested the differences between each corresponding data with respect to each preoperative variable, all the tested differences were revealed to be statistically significant.
CONCLUSIONS
Comparison of the prediction nomograms revealed notable differences, especially in the OC and SVI. Therefore, it is recommended that each table should be applied to its corresponding population.