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恶性胸膜间皮瘤列线图预后预测模型的建立及验证

Development and validation of prognostic nomogram for malignant pleural mesothelioma

摘要目的:建立恶性胸膜间皮瘤(MPM)临床预后预测模型模型。方法:2007年3月至2020年5月于楚雄彝族自治州人民医院、昆明医科大学第一附属医院和昆明医科大学第三附属医院经病理确诊的MPM患者210例,根据首次入院时间将患者分为训练集(112例)和验证集(98例)。收集患者的人口学、症状、病史、临床评分及分期、血常规及血生化、肿瘤标志物、病理、治疗等8个方面36项指标的信息资料,采用Cox比例风险模型对训练集112例患者进行预后影响因素分析。根据多因素Cox回归分析结果,建立生存列线图预测模型。采用C指数和校准曲线在训练和验证集中评估列线图预测模型的区分度和校准度。以训练集患者风险评分的中位数为界值分别将训练集和验证集患者划分为高风险组和低风险组,采用Log rank检验比较两组的生存率。结果:210例MPM患者的中位总生存时间为384 d(IQR=472 d),6个月、1年、2年和3年生存率分别为75.7%、52.6%、19.7%和13.0%。Cox多因素回归分析结果显示,居住地( HR=2.127,95% CI:1.154~3.920)、血清白蛋白( HR=1.583,95% CI:1.017~2.464)、临床分期(Ⅳ期: HR=3.073,95% CI:1.366~6.910)和有无化疗( HR=0.476,95% CI:0.292~0.777)为MPM患者预后的独立影响因素。基于Cox多因素回归分析结果建立的MPM患者生存列线图预测模型在训练集和验证集中的C指数分别为0.662和0.613。训练集和验证集的校准曲线显示,MPM患者6个月、1年和2年的预测生存概率与实际生存率的一致性尚可。在训练集和验证集中,低风险组患者的生存率均高于高风险组( P值分别为0.001和0.003)。 结论:基于临床常规指标建立的MPM患者生存列线图预测模型为该病的临床预后判断及风险分层提供了可靠的工具。

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abstractsObjective:To development the prognostic nomogram for malignant pleural mesothelioma (MPM).Methods:Two hundred and ten patients pathologically confirmed as MPM were enrolled in this retrospective study from 2007 to 2020 in the People′s Hospital of Chuxiong Yi Autonomous Prefecture, the First and Third Affiliated Hospital of Kunming Medical University, and divided into training ( n=112) and test ( n=98) sets according to the admission time. The observation factors included demography, symptoms, history, clinical score and stage, blood cell and biochemistry, tumor markers, pathology and treatment. The Cox proportional risk model was used to analyze the prognostic factors of 112 patients in the training set. According to the results of multivariate Cox regression analysis, the prognostic prediction nomogram was established. C-Index and calibration curve were used to evaluate the model′s discrimination and consistency in raining and test sets, respectively. Patients were stratified according to the median risk score of nomogram in the training set. Log rank test was performed to compare the survival differences between the high and low risk groups in the two sets. Results:The median overall survival (OS) of 210 MPM patients was 384 days (IQR=472 days), and the 6-month, 1-year, 2-year, and 3-year survival rates were 75.7%, 52.6%, 19.7%, and 13.0%, respectively. Cox multivariate regression analysis showed that residence ( HR=2.127, 95% CI: 1.154-3.920), serum albumin ( HR=1.583, 95% CI: 1.017-2.464), clinical stage (stage Ⅳ: HR=3.073, 95% CI: 1.366-6.910) and the chemotherapy ( HR=0.476, 95% CI: 0.292-0.777) were independent prognostic factors for MPM patients. The C-index of the nomogram established based on the results of Cox multivariate regression analysis in the training and test sets were 0.662 and 0.613, respectively. Calibration curves for both the training and test sets showed moderate consistency between the predicted and actual survival probabilities of MPM patients at 6 months, 1 year, and 2 years. The low-risk group had better outcomes than the high-risk group in both training ( P=0.001) and test ( P=0.003) sets. Conclusion:The survival prediction nomogram established based on routine clinical indicators of MPM patients provides a reliable tool for prognostic prediction and risk stratification.

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