Prostate Cancer P D:临床病理模型在高风险局部前列腺癌中的表现

2020-04-17 AlexYang MedSci原创

在已经建立的临床病理风险组中,前列腺癌表现出了生物学和临床的遗传异质性。Decipher genomic classifier(GC)是一个已经验证过的方法,用于进一步对前列腺癌患者进行风险分层,但是

在已经建立的临床病理风险组中,前列腺癌表现出了生物学和临床的遗传异质性。Decipher genomic classifier(GC)是一个已经验证过的方法,用于进一步对前列腺癌患者进行风险分层,但是其在美国国立综合癌症网络(NCCN)中的高风险疾病中的表现还未有更新。

最近,有研究人员对405名高风险前列腺癌男性进行了多机构回归性研究。这些患者从1995年到2005年在11个中心进行了根治性前列腺癌切除(RP)或者放疗结合雄激素阻断治疗(ADT)。研究平均随访时间为82个月,104名患者(26%)发展为转移性疾病。多变量分析表明GC得分的增加与转移疾病显著相关(HR: 1.34 per 0.1 unit增加, 95%CI: 1.19-1.50, p<0.001),而年龄、血清PSA、活检GG和临床T阶段不存在相关性(所有p>0.05)。在多变量分析中,GC得分(HR: 1.33 per 0.1 unit增加, 95% CI: 1.19-1.48, p<0.001)和GC高风险(vs低风险, HR: 2.95, 95% CI: 1.79-4.87, p<0.001)与转移显著相关。将GC得分加入到基于NCCN风险组的回归模型中能够改善AUC(0.46到0.67)和CAPRA(0.59到0.71)。、

最后,研究人员指出,在高风险前列腺癌男性中,传统的临床病理数据区分转移疾病风险分层效果差。GC得分是转移的明显的和独立的预测因子,并且有助于鉴定出最适合的治疗强度和阶梯治疗。

原始出处:

Jeffrey J. Tosoian, Samuel R. Birer, R. Jeffrey Karnes et al. Performance of clinicopathologic models in men with high risk localized prostate cancer: impact of a 22-gene genomic classifier. Prostate Cancer P D. 30 Mar 2020

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    2020-04-19 lsndxfj
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    2020-04-19 chg122
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    2020-04-19 sunylz
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    2020-04-17 misszhang

    前列腺癌相关研究,学习了,谢谢梅斯

    0

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    2020-04-17 CHANGE

    梅斯里提供了很多疾病的模型计算公式,赞一个!

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