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新诊断前列腺癌患者的预测模型。

Predictive models for newly diagnosed prostate cancer patients.

作者信息

Lowrance William T, Scardino Peter T

机构信息

Department of Surgery, Urology Service, Memorial Sloan-Kettering Cancer Center New York, NY.

出版信息

Rev Urol. 2009 Summer;11(3):117-26.

Abstract

Accurate risk assessment is of paramount importance to newly diagnosed prostate cancer patients and their physicians. Risk prediction models help identify those at high (or low) risk of disease progression and guide discussions about prognosis and treatment. Widely used, well-validated prediction tools are based on standard, readily available clinical and pathologic parameters, but do not include biomarkers, some of which may have an important role in predicting prognosis or determining therapeutic options. A new approach, known as systems pathology, may improve the accuracy of traditional prediction methods and provide patients with a more personalized risk assessment of clinically relevant outcomes. The ultimate goal of prediction models is to improve medical decision making.

摘要

准确的风险评估对新诊断的前列腺癌患者及其医生至关重要。风险预测模型有助于识别那些疾病进展风险高(或低)的患者,并指导有关预后和治疗的讨论。广泛使用且经过充分验证的预测工具基于标准的、易于获得的临床和病理参数,但不包括生物标志物,其中一些生物标志物可能在预测预后或确定治疗方案方面发挥重要作用。一种称为系统病理学的新方法可能会提高传统预测方法的准确性,并为患者提供更个性化的临床相关结局风险评估。预测模型的最终目标是改善医疗决策。

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