Literature DB >> 9028364

Evaluation of a nomogram used to predict the pathologic stage of clinically localized prostate carcinoma.

M W Kattan1, A M Stapleton, T M Wheeler, P T Scardino.   

Abstract

BACKGROUND: A Nomogram based on pretreatment prostate specific antigen (PSA) level, tumor grade, and clinical stage has recently been developed and distributed to physicians. It was distributed to aid physicians in making treatment recommendations by predicting the probability of the final pathologic stage of clinically localized prostate carcinoma. The Nomogram was based on data for one patient population, and the validity of its application in general urologic practices had not yet been evaluated.
METHODS: In the current study, the authors tested the performance of the Nomogram against data from their series of 697 men who underwent radical prostatectomy during the PSA era. Predictions made with the Nomogram were applied to the authors' data set, and the predictions were compared with actual outcomes of the authors' patients. A localized least-squares regression smoothing technique was used to determine whether the Nomogram was calibrated accurately for the authors' data and whether it discriminated across a full spectrum of patient characteristics.
RESULTS: Many of the predicted probabilities of the Nomogram were accurate, but some were suboptimal when applied to the authors' data set. Although the Nomogram did discriminate quite well between organ-confined and nonconfined cancer, it had difficulty predicting high probabilities of seminal vesicle invasion and lymph node metastasis, which are the pathologic features with the most profound impact on prognosis.
CONCLUSIONS: The Nomogram predicted organ-confined disease accurately. However, because not all of its predictions were completely calibrated when applied to the authors' data set, the authors conclude that the Nomogram may not be totally applicable to general urologic practice until further validation and possible modifications are performed.

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Year:  1997        PMID: 9028364

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  35 in total

1.  Prediction of patient-specific risk and percentile cohort risk of pathological stage outcome using continuous prostate-specific antigen measurement, clinical stage and biopsy Gleason score.

Authors:  Ying Huang; Sumit Isharwal; Alexander Haese; Felix K H Chun; Danil V Makarov; Ziding Feng; Misop Han; Elizabeth Humphreys; Jonathan I Epstein; Alan W Partin; Robert W Veltri
Journal:  BJU Int       Date:  2010-09-28       Impact factor: 5.588

2.  Prostate cancer at the peripheral end of prostate biopsy specimen predicts increased risk of positive resection margin after radical prostatectomy: results of a prospective multi-institutional study.

Authors:  Anton Ponholzer; Sophina Trubel; Paul Schramek; Florian Wimpissinger; Hans Feichtinger; Christopher Springer; Clemens Wehrberger; Katja Fischereder; Karl Pummer; Thomas Martini; Roman Mayr; Armin Pycha; Stephan Madersbacher
Journal:  World J Urol       Date:  2014-02-08       Impact factor: 4.226

3.  Clinical impact of intraoperative frozen sections during nerve-sparing radical prostatectomy.

Authors:  Elmar Heinrich; Georg Schön; Frank Schiefelbein; Maurice Stephan Michel; Lutz Trojan
Journal:  World J Urol       Date:  2010-04-01       Impact factor: 4.226

Review 4.  Differentiation of lethal and non lethal prostate cancer: PSA and PSA isoforms and kinetics.

Authors:  H Ballentine Carter
Journal:  Asian J Androl       Date:  2012-02-20       Impact factor: 3.285

5.  A nomogram for predicting overall survival of women with endometrial cancer following primary therapy: toward improving individualized cancer care.

Authors:  N R Abu-Rustum; Q Zhou; J D Gomez; K M Alektiar; M L Hensley; R A Soslow; D A Levine; D S Chi; R R Barakat; A Iasonos
Journal:  Gynecol Oncol       Date:  2010-03       Impact factor: 5.482

6.  Updated nomogram to predict pathologic stage of prostate cancer given prostate-specific antigen level, clinical stage, and biopsy Gleason score (Partin tables) based on cases from 2000 to 2005.

Authors:  Danil V Makarov; Bruce J Trock; Elizabeth B Humphreys; Leslie A Mangold; Patrick C Walsh; Jonathan I Epstein; Alan W Partin
Journal:  Urology       Date:  2007-06       Impact factor: 2.649

Review 7.  Critical review of prostate cancer predictive tools.

Authors:  Shahrokh F Shariat; Michael W Kattan; Andrew J Vickers; Pierre I Karakiewicz; Peter T Scardino
Journal:  Future Oncol       Date:  2009-12       Impact factor: 3.404

8.  Nomograms for the prediction of pathologic stage of clinically localized prostate cancer in Korean men.

Authors:  Cheryn Song; Taejin Kang; Jae Y Ro; Moo-Song Lee; Choung-Soo Kim; Hanjong Ahn
Journal:  J Korean Med Sci       Date:  2005-04       Impact factor: 2.153

9.  Artificial neural network to predict skeletal metastasis in patients with prostate cancer.

Authors:  Jainn-Shiun Chiu; Yuh-Feng Wang; Yu-Cheih Su; Ling-Huei Wei; Jian-Guo Liao; Yu-Chuan Li
Journal:  J Med Syst       Date:  2009-04       Impact factor: 4.460

Review 10.  Robotic-assisted laparoscopic prostatectomy.

Authors:  N L Sharma; N C Shah; D E Neal
Journal:  Br J Cancer       Date:  2009-09-29       Impact factor: 7.640

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