Zhang Haolin, Zhang Xi, Li Xiaosheng, Xu Qianjie, Yuan Yuliang, Hu Zuhai, Zhao Yulan, Liu Yao, Zhang Yunyun, Lei Haike
Chongqing Cancer Multi-Omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing 400030, China.
Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, Chongqing 400030, China.
Biomedicines. 2025 Mar 21;13(4):770. doi: 10.3390/biomedicines13040770.
Venous thromboembolism (VTE) is a significant complication in patients with multiple myeloma (MM) that adversely affects morbidity, mortality, and treatment outcomes. This study aimed to develop and validate a predictive nomogram for assessing VTE risk in MM patients using clinicopathological factors. Clinical data, including 25 candidate risk factors, were collected. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for VTE. The nomogram was constructed using these variables, and its performance was evaluated by plotting receiver operating characteristic (ROC) curves, calculating the area under the curve (AUC), and conducting calibration and decision curve analysis (DCA). Additionally, an online calculator was developed for clinical use. In total, 148 patients (17.5%) developed VTE in this study. The independent risk factors included age, Karnofsky performance status (KPS), anticoagulation therapy, erythropoietin use, and hemoglobin (Hb), platelet (PLT), calcium (Ca), activated partial thromboplastin time (APTT), and D-dimer levels. The nomogram demonstrated robust discriminative ability, with a C-index of 0.811 in the training cohort and 0.714 in the validation cohort. The calibration curves exhibited a high level of agreement between the predicted and observed probabilities. DCA confirmed the nomogram's clinical utility across various threshold ranges, outperforming the "treat all" and "treat none" strategies. This study successfully developed and validated a nomogram for predicting VTE risk in MM patients, demonstrating substantial predictive accuracy and clinical applicability. The nomogram and accompanying online calculator provide valuable tools for individualized VTE risk assessment and informed clinical decision-making.
静脉血栓栓塞症(VTE)是多发性骨髓瘤(MM)患者的一种严重并发症,会对发病率、死亡率及治疗结果产生不利影响。本研究旨在利用临床病理因素开发并验证一种用于评估MM患者VTE风险的预测列线图。收集了包括25个候选风险因素在内的临床数据。进行单因素和多因素逻辑回归分析以确定VTE的独立风险因素。使用这些变量构建列线图,并通过绘制受试者操作特征(ROC)曲线、计算曲线下面积(AUC)以及进行校准和决策曲线分析(DCA)来评估其性能。此外,还开发了一个供临床使用的在线计算器。在本研究中,共有148例患者(17.5%)发生了VTE。独立风险因素包括年龄、卡氏功能状态(KPS)、抗凝治疗、促红细胞生成素使用情况以及血红蛋白(Hb)、血小板(PLT)、钙(Ca)、活化部分凝血活酶时间(APTT)和D-二聚体水平。该列线图显示出强大的判别能力,在训练队列中的C指数为0.811,在验证队列中的C指数为0.714。校准曲线显示预测概率与观察概率之间具有高度一致性。DCA证实了该列线图在各种阈值范围内的临床实用性,优于“全部治疗”和“不治疗”策略。本研究成功开发并验证了一种用于预测MM患者VTE风险的列线图,显示出较高的预测准确性和临床适用性。该列线图及配套的在线计算器为个性化VTE风险评估和明智的临床决策提供了有价值的工具。