重度血小板减少症患者预后列线图的构建和验证

Construction and validation of a Nomogram for prognosis of patients with severe thrombocytopenia

  • 摘要:
    目的 探讨列线图模型预测重度血小板减少症患者死亡风险的价值。
    方法 回顾性总结2020年5月—2022年5月在本院确诊重度血小板减少症的340例患者临床资料,按7∶3的比例随机分为模型组238例和验证组102例。对模型组死亡与存活患者的临床资料进行单因素和多因素Logistic回归分析以筛选主要危险因素,应用R软件构建列线图模型。
    结果 模型组病死率为34.0%(81/238), 验证组为29.4%(30/102), 差异无统计学意义(P=0.405)。多因素Logistic回归分析显示,脑血管疾病(OR=1.986, 95%CI: 1.524~2.659, P < 0.001)、恶性肿瘤(OR=2.056, 95%CI: 1.744~2.789, P < 0.001)、机械通气(OR=2.324, 95%CI: 1.856~3.121, P < 0.001)、血管升压药(OR=2.759, 95%CI: 2.425~3.562, P < 0.001)、持续肾脏替代治疗(OR=2.421, 95%CI: 2.012~3.123, P < 0.001)和凝血时间延长(OR=1.649, 95%CI: 1.232~2.011, P < 0.001)是重度血小板减少症患者死亡的独立危险因素。列线图总分240分, Bootstrap法计算模型组与验证组的C-index值分别为0.912和0.879, 表明模型的预测效能较好。校准曲线显示,模型组与验证组的预测概率与实测值基本一致。受试者工作特征(ROC)曲线计算模型组与验证组的曲线下面积(AUC)分别为0.889和0.856, 表明预测准确性较高。列线图与传统序贯器官功能衰竭评估(SOFA)评分和简化急性生理学评分Ⅱ(SAPS Ⅱ)评分相比, AUC值均增大,差异有统计学意义(P < 0.001)。决策曲线显示,模型组与验证组的临床净获益比均较好。
    结论 重度血小板减少症患者有较高的死亡风险,应用列线图模型能够更好地指导临床医生早期识别死亡高风险人群并进行积极干预,改善预后。

     

    Abstract:
    Objective To explore the value of a Nomogram model in predicting the death risk of patients with severe thrombocytopenia.
    Methods The clinical materials of 340 patients with severe thrombocytopenia diagnosed in authors' hospital from May 2020 to May 2022 were retrospectively summarized, and they were randomly divided into model group (n=238) and validation group (n=102) according to the ratio of 7 to 3. The clinical materials of death and survival patients in the model group were analyzed by single factor and multiple factor Logistic regression to screen the main risk factors, and R software was used to construct the Nomogram model.
    Results The mortality in the model group was 34.0% (81/238), which showed no significant difference when compared to 29.4% (30/102) in the validation group (P=0.405). Multivariate Logistic regression analysis showed that cerebrovascular diseases (OR=1.986, 95%CI, 1.524 to 2.659, P < 0.001), malignant tumors (OR=2.056, 95%CI, 1.744 to 2.789, P < 0.001), mechanical ventilation (OR=2.324, 95%CI, 1.856 to 3.121, P < 0.001), vasopressors (OR=2.759, 95%CI, 2.425 to 3.562, P < 0.001), continuous renal replacement therapy (OR=2.421, 95%CI, 2.012 to 3.123, P < 0.001) and prolonged coagulation time (OR=1.649, 95%CI, 1.232 to 2.011, P < 0.001) were the independent risk factors of death in patients with severe thrombocytopenia. The total score of the Nomogram was 240 points, and the C-index values of the model group and the validation group calculated by Bootstrap method were 0.912 and 0.879 respectively, indicating that the predictive efficiency of the model was good. The calibration curve showed that the predictive probabilities of the model group and the validation group were basically consistent with the measured values. The area under the curve (AUC) calculated by receiver operating characteristic (ROC) curve of the model group and the validation group were 0.889 and 0.856 respectively, indicating that the predictive accuracy was high. Compared with the traditional Sequential Organ Failure Assessment (SOFA) score and the Simplified Acute Physiology Score Ⅱ (SAPS Ⅱ) score, the AUC value of the Nomogram was significantly larger (P < 0.001). The decision curve showed that the clinical net benefit ratios of the model group and the validation group were better.
    Conclusion Severe thrombocytopenia has a high risk of death. Application of the Nomogram model can better guide clinicians to identify people with high risk of death in the early stage and actively implement intervention for improvement of the prognosis.

     

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