| 赵姣萍.预测老年早期肝癌患者术后发生肝衰竭的列线图模型建立[J].浙江中西医结合杂志,2020,30(9): |
| 预测老年早期肝癌患者术后发生肝衰竭的列线图模型建立 |
| Establishment of a nomogram model for predicting posthepatectomy liver failure in elderly patients with liver cancer |
| 投稿时间：2019-12-29 修订日期：2020-04-08 |
| DOI： |
| 中文关键词: 老年患者 早期肝癌 肝衰竭 列线图模型 |
| 英文关键词:Elderly patients Early liver cancer Liver failure Nomogram model |
| 基金项目: |
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| 中文摘要: |
| 目的 建立切实有效预测老年早期肝癌患者肝切除术后发生肝衰竭的列线图模型。方法 回顾性分析我院2009年6月至2019年6月收治并行肝部分切除的老年早期肝癌患者675例，通过多因素分析得到老年早期肝癌患者肝切除术后发生肝衰竭的独立危险因素，应用R语言软件包建立列线图模型并对该模型进行验证。结果 通过分析两组患者相关指标可知，年龄（OR=0.269，95%CI：0.155～0.468）、糖尿病（OR=0.364，95%CI：0.204～0.651）、肝硬化（OR=0.299，95%CI：0.170～0.524）、术前血清白蛋白（OR=0.319，95%CI：0.185～0.550）、残肝体积（OR=0.369，95%CI：0.215～0.632）以及肝血流阻断时间（OR=0.455，95%CI：0.259～0.798）为老年早期肝癌患者肝切除术后发生肝衰竭的独立危险因素，基于上述独立危险因素建立了列线图模型。经验证，预测值同实测值基本一致，说明本列线图预测模型具有较好的预测能力，同时采用Bootstrap内部验证法对其进行验证，C-index指数高达0.780（95%CI：0.725-0.835），说明此列线图模型具有良好的区分度和精准度。结论 基于年龄、糖尿病、肝硬化、术前血清白蛋白、残肝体积、肝血流阻断时间等6项危险因素建立的预测肝切除术后发生肝衰竭风险的列线图模型具有良好的精准度和区分度，对于临床预测肝癌术后肝衰竭有指导意义。 |
| 英文摘要: |
| Objective To establish a nomogram model for the effective prediction of hepatic failure after liver resection in elderly patients with liver cancer. Methods A retrospective analysis of 675 patients with early stage liver cancer who underwent partial hepatectomy in our hospital from June 2009 to June 2019 was conducted. Multivariate analysis was used to obtain independent risk factors for liver failure after liver resection in elderly patients with liver cancer. The R language package builds a nomogram model and validates the model. Results By analyzing the relevant indicators of the two groups, the age (OR=0.269, 95% CI: 0.155～0.468), diabetes (OR=0.364, 95% CI: 0.204～0.651), cirrhosis (OR=0.299, 95% CI) :0.170～0.524), preoperative serum albumin (OR=0.319, 95% CI: 0.185～0.550), residual liver volume (OR=0.369, 95% CI: (0.215～0.632) and hepatic blood flow blocking time ( OR=0.455, 95% CI: 0.259～0.798) is an independent risk factor for liver failure after liver resection in elderly patients with liver cancer. Based on the above independent risk factors, a nomogram model was established. The predicted values ??are basically the same as the measured values. Consistently, this chart predictive model has better predictive ability and is verified by Bootstrap internal verification method. The C-index index is as high as 0.780 (95% CI: 0.725-0.835), indicating that the nomogram model has good discrimination and precision. Conclusion A nomogram model based on age, diabetes, cirrhosis, preoperative serum albumin, residual liver volume, and hepatic blood flow blocking time to predict the risk of liver failure after hepatectomy has good accuracy, who has guiding significance for clinical prediction of liver failure after liver cancer surgery. |
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