Literature DB >> 18786800

Partin Tables cannot accurately predict the pathological stage at radical prostatectomy.

N Bhojani1, S Ahyai, M Graefen, U Capitanio, N Suardi, S F Shariat, C Jeldres, A Erbersdobler, T Schlomm, A Haese, T Steuber, H Heinzer, F Montorsi, H Huland, P I Karakiewicz.   

Abstract

PURPOSE: The Partin Tables represent the most commonly used staging tool for radical prostatectomy (RP) candidates. The Partin Tables' predictions are used to guide the type (nerve preserving RP) and/or the extent (RP with wide resection) of RP. We examined the ability of the Partin Tables' predictions incorrectly assigning the stage at RP.
METHODS: The testing of the Partin Tables (external validation) was based on 3105 patients treated with RP at a single European institution. Standard validation metrics were used (area under the receiver operating characteristics curve, AUC) to test the three endpoints predicted by the Partin Tables, namely the presence of extracapsular extension (ECE), seminal vesicle invasion (SVI), and lymph node invasion (LNI).
RESULTS: Ideal predictions are denoted with 100% accuracy vs. 50% for entirely random predictions. For the 2001 version of the Tables the accuracy defined by the AUC was 79.7, 77.8, and 73.0 for ECE, SVI, and LNI, respectively. For the 2007 version of the Tables the corresponding accuracy estimates were 79.8, 80.5, and 76.2. The relationship between predicted probabilities and observed rates was poor.
CONCLUSION: The Partin Tables are meant to guide clinicians about the safety of nerve bundle preservation at RP, about the need for seminal vesicle resection or for lymphadenectomy. Therefore, the use of the Partin Tables predictions may significantly affect the type and/or the extent of RP. In their present format the Partin Tables are not accurate enough to influence the pre-operative decision making regarding the type or extent of RP.

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Year:  2008        PMID: 18786800     DOI: 10.1016/j.ejso.2008.07.013

Source DB:  PubMed          Journal:  Eur J Surg Oncol        ISSN: 0748-7983            Impact factor:   4.424


  7 in total

Review 1.  Predictive and prognostic models in radical prostatectomy candidates: a critical analysis of the literature.

Authors:  Giovanni Lughezzani; Alberto Briganti; Pierre I Karakiewicz; Michael W Kattan; Francesco Montorsi; Shahrokh F Shariat; Andrew J Vickers
Journal:  Eur Urol       Date:  2010-08-06       Impact factor: 20.096

Review 2.  Biomarker research in prostate cancer--towards utility, not futility.

Authors:  Sheng Fei Oon; Stephen R Pennington; John M Fitzpatrick; R William G Watson
Journal:  Nat Rev Urol       Date:  2011-03       Impact factor: 14.432

3.  Novel predictive tools for Irish radical prostatectomy pathological outcomes: development and validation.

Authors:  D M Fanning; F Yue; J M Fitzpatrick; R W G Watson
Journal:  Ir J Med Sci       Date:  2009-07-14       Impact factor: 1.568

4.  Outcome of patients with localized prostate cancer treated by radiotherapy after confirming the absence of lymph node invasion.

Authors:  Noriyuki Suzuki; Masaki Shimbo; Yoshiyasu Amiya; Susumu Tomioka; Takayuki Shima; Shino Murakami; Hiroomi Nakatsu; Sayako Oota; Jun Shimazaki
Journal:  Jpn J Clin Oncol       Date:  2010-04-08       Impact factor: 3.019

5.  Prospective Study of the Clinical Impact of Epithelial and Mesenchymal Circulating Tumor Cells in Localized Prostate Cancer.

Authors:  Hailong Liu; Jie Ding; Yanyuan Wu; Di Wu; Jun Qi
Journal:  Cancer Manag Res       Date:  2020-06-15       Impact factor: 3.989

6.  External validation of risk classification in patients with docetaxel-treated castration-resistant prostate cancer.

Authors:  Kazuhiko Nakano; Kenji Komatsu; Taro Kubo; Shinsuke Natsui; Akinori Nukui; Shinsuke Kurokawa; Minoru Kobayashi; Tatsuo Morita
Journal:  BMC Urol       Date:  2014-04-18       Impact factor: 2.264

7.  Evaluation of prediction models for the staging of prostate cancer.

Authors:  Susie Boyce; Yue Fan; Ronald William Watson; Thomas Brendan Murphy
Journal:  BMC Med Inform Decis Mak       Date:  2013-11-15       Impact factor: 2.796

  7 in total

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