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10.03.2017 | Original Article – Cancer Research | Ausgabe 7/2017

Journal of Cancer Research and Clinical Oncology 7/2017

Prostate transitional zone volume-based nomogram for predicting prostate cancer and high progression prostate cancer in a real-world population

Zeitschrift:
Journal of Cancer Research and Clinical Oncology > Ausgabe 7/2017
Autoren:
Yanqing Wang, Shaowei Xie, Xun Shangguan, Jiahua Pan, Yinjie Zhu, Zhixiang Xin, Fan Xu, Xiaoguang Shao, Liancheng Fan, Jianjun Sha, Qiang Liu, Baijun Dong, Wei Xue
Wichtige Hinweise
Y. Wang and S. Xie contributed equally to the manuscript.

Abstract

Purpose

To evaluate and compare the efficacy of prostate volume (PV), transitional zone volume (TZV), and prostate volume index (PVI, the ratio of TZV to peripheral zone volume) in the identification of men at risk of prostate cancer (PCa) and high-progression PCa (HPPCa) at the initial biopsy (IBX) in a real-world population.

Methods

From Jul 2014 to Aug 2016, data on 1144 patients who had undergone the initial prostate biopsies were prospectively collected and analyzed. Univariate and multivariate logistic regression analyses were performed to identify the independent predictors for PCa and HPPCa. Based on independent predictors, nomogram models were developed and internally validated to assess a man’s risk of harboring PCa and HPPCa.

Results

The detection rates of PCa and HPPCa were 43.09% (493/1144) and 39.16% (448/1144), respectively. In the multivariate analyses, age, PSA, TZV, DRE, and TRUS instead of PV or PVI were independent predictors for PCa and HPPCa, percent free PSA was independent predictor for PCa not for HPPCa. Such independent predictors were finally included in the nomogram models. The AUCs of TZV-based nomogram models were 87.0% for PCa and 87.7% for HPPCa, which were higher than that of PSA alone or other predictive models.

Conclusions

TZV is a better predictive biomarker than PV or PVI for PCa and HPPCa, we recommend adding TZV but not PV or PVI to the nomogram models to improve the predictive accuracy of PCa and HPPCa at IBX.

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