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Derivation of genetic biomarkers for cancer risk stratification in Barrett's oesophagus: a prospective cohort study

机译:Barrett食管中癌症风险分层的遗传生物标志物的衍生:一项前瞻性队列研究

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摘要

The risk of developing adenocarcinoma in non-dysplastic Barrett's oesophagus is low and difficult to predict. Accurate tools for risk stratification are needed to increase the efficiency of surveillance. We aimed to develop a prediction model for progression using clinical variables and genetic markers. In a prospective cohort of patients with non-dysplastic Barrett's oesophagus, we evaluated six molecular markers: p16, p53, Her-2/neu, 20q, MYC and aneusomy by DNA fluorescence in situ hybridisation on brush cytology specimens. Primary study outcomes were the development of high-grade dysplasia or oesophageal adenocarcinoma. The most predictive clinical variables and markers were determined using Cox proportional-hazards models, receiver operating characteristic curves and a leave-one-out analysis. A total of 428 patients participated (345 men; median age 60 years) with a cumulative follow-up of 2019 patient-years (median 45 months per patient). Of these patients, 22 progressed; nine developed high-grade dysplasia and 13 oesophageal adenocarcinoma. The clinical variables, age and circumferential Barrett's length, and the markers, p16 loss, MYC gain and aneusomy, were significantly associated with progression on univariate analysis. We defined an 'Abnormal Marker Count' that counted abnormalities in p16, MYC and aneusomy, which significantly improved risk prediction beyond using just age and Barrett's length. In multivariate analysis, these three factors identified a high-risk group with an 8.7-fold (95% CI 2.6 to 29.8) increased HR when compared with the low-risk group, with an area under the curve of 0.76 (95% CI 0.66 to 0.86). A prediction model based on age, Barrett's length and the markers p16, MYC and aneusomy determines progression risk in non-dysplastic Barrett's oesophagus
机译:非发育不良的巴雷特食管患上腺癌的风险低,难以预测。需要使用准确的风险分层工具来提高监视效率。我们的目标是使用临床变量和遗传标记物开发进展预测模型。在非典型增生性Barrett食管患者的前瞻性队列中,我们通过刷细胞学标本上的DNA荧光原位杂交评估了六个分子标记:p16,p53,Her-2 / neu,20q,MYC和气肿。主要研究结果为高度不典型增生或食管腺癌的发展。使用Cox比例风险模型,接收者操作特征曲线和留一法分析确定最具预测性的临床变量和标志物。总共428例患者(345名男性;中位年龄60岁)参加了2019年患者年的累积随访(每位患者平均45个月)。在这些患者中,有22名进展。 9例发展为高度不典型增生,13例食道腺癌。临床变量,年龄和周长Barrett长度以及标志物p16丢失,MYC增高和气管切开术与单因素分析的进展密切相关。我们定义了一个“异常标记计数”,可以对p16,MYC和气管切开术中的异常进行计数,这不仅仅使用年龄和Barrett的长度就能显着改善风险预测。在多变量分析中,这三个因素确定了高风险组与低风险组相比,HR增加了8.7倍(95%CI为2.6至29.8),HR曲线下面积为0.76(95%CI 0.66)至0.86)。基于年龄,Barrett长度以及标记物p16,MYC和气肿的预测模型可确定非发育不良Barrett食道的进展风险

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