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首页> 外文期刊>Diseases of the esophagus: official journal of the International Society for Diseases of the Esophagus >A competing-risks nomogram and recursive partitioning analysis for cause-specific mortality in patients with esophageal neuroendocrine carcinoma
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A competing-risks nomogram and recursive partitioning analysis for cause-specific mortality in patients with esophageal neuroendocrine carcinoma

机译:对食管神经内分泌癌患者造成致原因的竞争风险NOMACHOM和递归分配分析

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摘要

The objective of this study is to estimate the probability of cause-specific mortality using a competing-risks nomogram and recursive partitioning analysis in a large population-based cohort of patients with esophageal neuroendocrine carcinoma. The surveillance, epidemiology and end results database was used to identify 162 patients diagnosed with esophageal neuroendocrine carcinoma from 1998 to 2014. We estimated a cumulative incidence function for cause-specific mortality. A nomogram was constructed by using a proportional subdistribution hazard model, validated using bootstrap cross-validation, and evaluated with a decision curve analysis to assess its clinical utility. Finally, we performed risk stratification using a recursive partitioning analysis to divide patients with esophageal neuroendocrine carcinoma into clinically useful prognostic groups. Tumor location, distant metastasis, surgery, radiotherapy, and chemotherapy were significantly associated with cause-specific mortality. The calibration plots demonstrated good concordance between the predicted and actual outcomes. The discrimination performance of a Fine-Gray model was evaluated by using the c-index, which was 0.723 for cause-specific mortality. The decision curve analysis ranged from 0.268 to 0.968 for the threshold probability at which the risk model provided net clinical benefits relative to hypothetical all-screening and no-screening scenarios. The risk groups stratified by a recursive partitioning analysis allowed significant distinction between cumulative incidence curves. We determined the probability of cause-specific mortality in patients with esophageal neuroendocrine carcinoma and developed a nomogram and recursive partitioning analysis stratification system based on a competing-risks model. The nomogram and recursive partitioning analysis appear to be suitable for risk stratification of cause-specific mortality in patients with esophageal neuroendocrine carcinoma and will help clinicians to identify patients at increased risk of cause-specific mortality to guide treatment and surveillance decisions.
机译:本研究的目的是利用竞争风险的竞争风险罗维图和递归分区分析来估计原因特异性死亡率的概率,并在大量的食管神经内分泌癌患者患者群体中进行递归分配分析。监测,流行病学和最终结果数据库用于鉴定1998年至2014年被诊断患有食管神经内分泌癌的162名患者。我们估计了累计发生原因的死亡率。通过使用比例分布危险模型构建了一种铭文,使用引导交叉验证验证,并通过决策曲线分析评估以评估其临床实用程序。最后,我们使用递归分配分析进行风险分层将食管神经内分泌癌患者分为临床上有用的预后组。肿瘤位置,远处转移,手术,放疗和化疗与特异性死亡率显着相关。校准图在预测和实际结果之间表现出良好的一致性。通过使用C折射率来评估细灰模型的辨别性能,即为原因特异性死亡率为0.723。决策曲线分析范围为0.268至0.968,用于风险模型提供相对于假设的全屏和无筛选方案的净临床效益。通过递归分配分析的风险群体允许累积发射曲线之间的显着区别。我们确定食管神经内分泌癌患者的原因特异性死亡率,并基于竞争风险模型制定了一种铭文和递归分析分析分层系统。 NOM图和递归分区分析似乎适用于食管神经内分泌癌患者的原因特异性死亡率的风险分层,并将有助于临床医生识别患者,以提高原因特异性死亡率,以指导治疗和监测决策。

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