| 摘要: |
| ［摘要］ 目的 构建并验证多发性骨髓瘤（MM）并发神经系统损害的列线图预测模型。方法 回顾性分析2019年10月至2023年10月西南医科大学附属医院收治的202例MM患者的临床资料。根据随访期间神经系统损害发生情况将患者分为发生组（86例）和未发生组（116例）。采用多因素logistic回归分析MM并发神经系统损害的影响因素。建立MM并发神经系统损害的列线图预测模型。通过受试者工作特征（ROC）曲线、校准曲线、Hosmer-Lemeshow拟合优度检验和决策曲线分析（DCA）评价模型的预测效能。结果 MM并发神经系统损害的发生率为42.57%。多因素logistic回归分析结果显示，较大的年龄、较高的乳酸脱氢酶（LDH）水平、较高的免疫球蛋白（Ig）G水平、国际分期系统（ISS）分期为Ⅲ期是MM并发神经系统损害的独立危险因素（P<0.05），较长的活化部分凝血活酶时间（APTT）、较长的凝血酶原时间（PT）、较高的血红蛋白水平是MM并发神经系统损害的独立保护因素（P<0.05）。基于以上7个影响因素构建MM并发神经系统损害的列线图预测模型。ROC曲线分析结果显示，模型预测MM并发神经系统损害的曲线下面积为0.917（95%CI：0.861～0.956），灵敏度、特异度分别为95.35%、87.85%。Hosmer-Lemeshow拟合优度检验结果（χ2=2.944，P=0.872）证明模型具有较好的拟合优度。校准曲线显示模型预测概率和实际概率相近，具有良好的校准度。DCA显示模型预测阈值概率在20%～93%、94%～100%时可获得临床净收益。结论 基于年龄、LDH、IgG、APTT、PT、血红蛋白和ISS分期等7个影响因素构建的MM并发神经系统损害的列线图预测模型具有良好的预测价值。 |
| 关键词: 多发性骨髓瘤 神经系统损害 影响因素 列线图 预测模型 |
| DOI：10.3969/j.issn.1674-3806.2025.11.17 |
| 分类号:R 733.3 |
| 基金项目:泸州市人民政府 西南医科大学科技战略合作项目（编号：2023LZXNYDJ045） |
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| Construction and validation of a nomogram prediction model for multiple myeloma complicated with nervous system damage |
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MI Qiuwen, LUO Lixiu, WU Yanling, WEN Xiaoying, ZHAO Yu, LIU Yang, CHEN Xiaomin, HUANG Chunlan
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Department of Hematology, the Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
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| Abstract: |
| ［Abstract］ Objective To construct and validate a nomogram prediction model for multiple myeloma(MM) complicated with nervous system damage. Methods A retrospective analysis was conducted on the clinical data of 202 patients with MM who were admitted to the Affiliated Hospital of Southwest Medical University from October 2019 to October 2023. The patients were divided into the occurrence group(86 patients) and the non-occurrence group(116 patients) according to the occurrence of nervous system damage during the follow-up period. Multivariate logistic regression was used to analyze the influencing factors of MM complicated with nervous system damage. A nomogram prediction model for MM complicated with nervous system damage was constructed. The predictive efficacy of the model for MM complicated with nervous system damage was evaluated using receiver operating characteristic(ROC) curve, calibration curve, Hosmer-Lemeshow goodness-of-fit test and decision curve analysis(DCA). Results The incidence of MM complicated with nervous system damage was 42.57%. The results of multivariate logistic regression analysis showed that older age, higher levels of lactate dehydrogenase(LDH) and immunoglobulin(Ig) G, and International Staging System(ISS) stage Ⅲ were independent risk factors for MM complicated with nervous system damage(P<0.05), and longer activated partial thromboplastin time(APTT), longer prothrombin time(PT), and higher hemoglobin level were independent protective factors for MM complicated with nervous system damage(P<0.05). Based on the above 7 influencing factors, a nomogram prediction model for MM complicated with nervous system damage was constructed. The results of ROC curve analysis showed that the area under the curve of the model for predicting MM complicated with nervous system damage was 0.917(95%CI: 0.861-0.956), and the sensitivity and specificity were 95.35% and 87.85%, respectively. The Hosmer-Lemeshow goodness-of-fit test results(χ2=2.944, P=0.872) proved that the model had an adequate goodness-of-fit. The calibration curve showed that the predicted probability of the model was close to the actual probability, indicating a good calibration. DCA showed that net clinical benefits could be achieved when the prediction threshold probability of the model was between 20% and 93%, or between 94% and 100%. Conclusion The nomogram prediction model which is constructed for MM complicated with nervous system damage based on 7 influencing factors including age, LDH, IgG, APTT, PT, hemoglobin and ISS stage has good predictive value. |
| Key words: Multiple myeloma(MM) Nervous system damage Influencing factors Nomogram Prediction model |
