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首页> 外文期刊>Seminars in Urologic Oncology >Nomograms and instruments for the initial prostate evaluation: the ability to estimate the likelihood of identifying prostate cancer.
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Nomograms and instruments for the initial prostate evaluation: the ability to estimate the likelihood of identifying prostate cancer.

机译：用于最初的前列腺评估的线型图和仪器：评估识别前列腺癌可能性的能力。

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摘要

As a result of prostate cancer screening programs, approximately 10% of otherwise healthy men will be found to have an elevated prostate-specific antigen (PSA) level and therefore be at risk for harboring prostate cancer. Patients with an elevated PSA level have a wide variation in the risk for having prostate cancer diagnosed by transrectal ultrasound (TRUS)-guided prostate biopsy. To adequately counsel these patients, some form of individualized risk assessment must be given. There are several tables, artificial neural network (ANN) models, and nomograms that are available to stratify an individual patients risk for having prostate cancer diagnosed by a TRUS biopsy, either initially or on subsequent biopsies after a previous negative biopsy. Presently, nomograms are also being developed to predict the risk not only for having prostate cancer but also for clinically significant prostate cancer. The difficulty in calculating this risk for an individual patient is that the multiple competing clinical and pathologic factors have varying degrees of effect on the overall risk. This problem of competing risk factors can be overcome by the use of nomograms or ANNs. This article reviews the available instruments that are available to the urologist to enable prediction of the risk for having prostate cancer diagnosed by TRUS-guided prostate biopsy. Copyright 2002, Elsevier Science (USA). All rights reserved.
机译：前列腺癌筛查计划的结果是，大约有10％的健康男性会发现前列腺特异性抗原（PSA）水平升高，因此有患前列腺癌的风险。 PSA水平升高的患者通过经直肠超声（TRUS）引导的前列腺活检诊断出前列腺癌的风险差异很大。为了给这些患者足够的咨询，必须进行某种形式的个体化风险评估。有几张表格，人工神经网络（ANN）模型和列线图可用于对单个患者进行TRUS活检诊断出患有前列腺癌的风险进行分层，无论是最初还是在先前的阴性活检后进行的后续活检中。当前，诺模图也正在被开发以不仅预测患有前列腺癌的风险，而且还预测具有临床意义的前列腺癌的风险。为单个患者计算此风险的困难在于，多个相互竞争的临床和病理因素对总风险的影响程度不同。可以通过使用列线图或人工神经网络克服竞争风险因素的问题。本文介绍了泌尿科医师可用的可用仪器，以预测由TRUS指导的前列腺活检诊断出患有前列腺癌的风险。版权所有（Elsevier Science）2002（美国）。版权所有。

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