| 郑晨.恶性腹膜间皮瘤患者生存预后的因素分析及风险预测Nomogram模型构建[J].安徽医药,待发表. |
| 恶性腹膜间皮瘤患者生存预后的因素分析及风险预测Nomogram模型构建 |
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| 投稿时间：2025-01-16 录用日期：2025-05-06 |
| DOI： |
| 中文关键词: 恶性腹膜间皮瘤 生存预后 影响因素 Nomogram模型 |
| 英文关键词: |
| 基金项目: |
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| 摘要点击次数: 50 |
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| 中文摘要: |
| 目的 分析恶性腹膜间皮瘤（MPM）生存预后的影响因素，并构建、验证风险预测Nomogram模型。方法 回顾性分析2013年8至2023年8月来医院就诊的MPM患者210例，经计算机产生随机数表以7:3将其分为训练集（147例）、验证集（63例）。所有患者均随访至2023年12月，将死亡患者纳入不良组，存活患者纳入良好组。比较训练集、验证集一般资料；比较训练集不良组、良好组一般资料；采用Cox回归模型分析MPM生存预后的影响因素，建立回归方程及风险预测Nomogram模型；绘制受试者工作特征曲线（ROC）、Calibration曲线验证模型效能。结果 随访时间4~76个月，中位随访时间38（13，56）个月；训练集死亡率为62.59%；Cox回归模型分析显示，年龄、石棉暴露史、美国东部肿瘤协作组（ECOG）评分、血小板计数（PLT）是MPM生存预后的影响因素（P＜0.05）；建立Cox回归方程：Y=1.060X1＋1.116X2＋1.156X3＋1.112X4；基于训练集Cox回归分析结构建立MPM生存预后的风险预测Nomogram模型；绘制ROC曲线评估风险预测Nomogram模型的区分度，训练集的曲线下面积（AUC）为0.948，灵敏度为94.57%，特异度为92.73%，验证集的AUC为0.906，灵敏度为87.18%，特异度为87.50%；Hosmer-Lemeshow检验显示，训练集、验证集Calibration曲线差异无统计学意义（χ2=0.478，P=0.216；χ2=0.412，P=0.274），Bootstrap法内部验证结果显示，C-index指数分别为0.940（95% CI：0.812~0.965）、0.903（95% CI：0.841~0.942）。结论 MPM生存预后的影响因素包括年龄、石棉暴露史、ECOG评分、PLT，根据其构建的风险预测Nomogram模型对MPM生存预后的预测效能良好。 |
| 英文摘要: |
| Objective To analyze the prognostic factors of malignant peritoneal mesothelioma (MPM) and construct and validate the corresponding risk prediction Nomogram model. Methods A retrospective analysis of 210 MPM patients who visited the hospital from August 2013 to August 2023 was performed, and they were randomly divided into training set (147 cases) and validation set (63 cases) by computer-generated random number table with a ratio of 7:3. All patients were followed up until December 2023, and the deceased patients were included in the adverse group, and the surviving patients were included in the good group. The general data of the training set and the validation set were compared. The general data of the adverse group and the good group of the training set were compared. Cox regression model was used to analyze the prognostic factors of MPM, a Nomogram model of regression equation and risk prediction were established. The receiver operating characteristic curve (ROC) and Calibration curve were used to verify the model efficacy. Results The follow-up time was 4~76 months, and the median follow-up time was 38 (13,56) months. The mortality rate of the training set was 62.59%. Cox regression model analysis showed that age, asbestos exposure history, eastern cooperative oncology group (ECOG) score, platelet count (PLT) were the prognostic factors of MPM (P<0.05). Cox regression equation was established: Y=1.060X1+1.116X2+1.156X3+1.112X4. Based on the training set Cox regression analysis structure, establish the risk prediction Nomogram model for MPM survival prognosis. ROC curve was used to evaluate the discrimination of the risk prediction Nomogram model, the AUC of the training set was 0.948, the sensitivity was 94.57%, the specificity was 92.73%, the AUC of the validation set was 0.906, the sensitivity was 87.18%, the specificity was 87.50%. Hosmer-Lemeshow test showed that there was no statistical significance in the difference of Calibration curve between the training set and the validation set (χ2=0.478, P=0.216. χ2=0.412, P=0.274), and the Bootstrap method internal validation results showed that the C-index index was 0.940 (95% CI: 0.812~0.965) and 0.903 (95% CI: 0.841~0.942), respectively. Conclusion The prognostic factors of MPM include age, asbestos exposure history, ECOG score, PLT. The risk prediction Nomogram model constructed according to them has good prediction efficacy for MPM survival prognosis. |
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