Literature DB >> 21504650

Comparison of accuracy among three generations of Partin tables in a Chinese cohort.

Wen-Jun Xiao1, Ding-Wei Ye, Xu-Dong Yao, Shi-Lin Zhang, Bo Dai, Chao-Fu Wang, Jian Wang, Hai-Liang Zhang, Yi-Jun Shen, Yao Zhu, Yi-Ping Zhu, Guo-Hai Shi, Chun-Guang Ma, Xiao-Jian Qin, Guo-Wen Lin.   

Abstract

INTRODUCTION: To perform a head to head comparison among three generations of Partin tables, namely from 1997, 2001 and the last updated version of 2007, in a Chinese cohort of prostate cancer.
MATERIAL AND METHODS: Clinical and pathological data of 198 consecutive Chinese patients were retrospectively analyzed, who underwent radical prostatectomy for clinically localized prostate cancer between January 2005 and May 2010. Three versions of the Partin tables were compared for their accuracy and performance to predict final pathological stage using receiver operating characteristic (ROC) curve.
RESULTS: Of the whole cohort 58.6% were presented with organ-confined disease (OCD), 10.1% had lymph node involvement (LNI), and 31.3% had locally advanced disease (LAD), while 21.2% had extraprostatic extension (ECE) and 10.1% showed seminal vesicle involvement (SVI). The area under the ROC curve (AUC) of the Partin Tables 1997, 2001 and 2007 was 0.732, 0.722 and 0.695 for OCD; 0.647, 0.594 and 0.577 for LAD; 0.856, 0.872 and 0.829 for LNI, respectively.
CONCLUSION: All three generations of the Partin tables showed a good accuracy to predict OCD, and LNI. However, the predictive accuracy for LAD was more limited. Overall, the newer versions of the Partin tables could not exceed the version of 1997 in their predictive accuracy for the present Chinese cohort. Our results suggest caution when using newly introduced predictive tools that are not supported by population-specific accuracy tests.

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Year:  2011        PMID: 21504650

Source DB:  PubMed          Journal:  Can J Urol        ISSN: 1195-9479            Impact factor:   1.344


  1 in total

1.  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

  1 in total

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