Joly Florence, Henry-Amar Michel
Centre Francois Baclesse, 3, avenue Général-Harris, 14076 Caen Cedex.
Bull Cancer. 2007 Jul;94(7 Suppl):F35-43.
In prostate cancer, whatever the stage of the disease, the selection of a treatment strategy is based on prognostic factors. Clinical stage, serum PSA concentration and Gleason score are among the most recognised factors. A combination of these three parameters leads to a score used to define prognostic groups that are routinely used in daily practice. More recently, predictive statistical models have been developed that were associated with nomograms. The objective of nomograms is, for a given patient, to calculate his probability to develop disease extension or relapse based on clinical, biological, histological and therapeutic (radiotherapy, hormonotherapy) data. Such nomograms are not all validated and their application in daily practice is more difficult than that of classical prognostic classifications. Nowadays, the progress and accessibility to novel technologies applied to biology will make possible in the near future the assessment of new prognostic profiles based on genetic and/or proteomic tumour characteristics.
在前列腺癌中，无论疾病处于何种阶段，治疗策略的选择都基于预后因素。临床分期、血清前列腺特异抗原（PSA）浓度和 Gleason 评分是最广为人知的因素。这三个参数的组合得出一个分数，用于定义日常临床实践中常规使用的预后分组。最近，已经开发出与列线图相关的预测统计模型。列线图的目的是，对于特定患者，根据临床、生物学、组织学和治疗（放疗、激素治疗）数据，计算其发生疾病进展或复发的概率。此类列线图并非全部经过验证，而且它们在日常实践中的应用比经典预后分类更困难。如今，应用于生物学的新技术的进步和可及性将在不久的将来使基于肿瘤基因和/或蛋白质组特征评估新的预后特征成为可能。
