维奈克拉治疗AML患者中性粒细胞减少风险预测模型的建立与验证

Construction of a nomogram to predict the risk of venetoclax-associated neutropenia and its validation

关键词:  急性髓系白血病  维奈克拉  中性粒细胞减少、列线图  预测模型

Key words:  acute myeloid leukemia (AML), venetoclax, neutropenia, nomogram, predictive model

摘要:

摘要：目的 探讨维奈克拉治疗急性髓系白血病(AML)患者发生中性粒细胞减少的独立危险因素，并构建列线图预测模型。方法 回顾性分析2022年9月至2025年3月在南昌大学第一附属医院接受维奈克拉治疗并进行治疗药物监测(TDM)的AML住院患者的临床资料，根据是否发生中性粒细胞减少分为病例组和对照组。采用单因素分析筛选潜在危险因素，通过二元Logistic回归分析确定独立危险因素，基于独立危险因素构建列线图预测模型并进行验证，通过决策曲线分析(DCA)来评估列线图的临床效用。结果 在138例患者中，53例(38.4%)发生了中性粒细胞减少。单因素分析显示，给药剂量、维奈克拉C0、维奈克拉C6、基础疾病、是否合用CYP3A酶抑制剂、白细胞计数(WBC)、红细胞计数(RBC)、血红蛋白(HGB)、血小板计数(PLT)、直接胆红素(DBIL)、白蛋白(ALB)、球蛋白(GLB)、以及尿酸(UA)与中性粒细胞减少发生显著相关(P < 0.05)。二元Logistic回归分析表明，C0升高(OR=2.79, 95% CI: 1.02-7.65, P=0.046)、存在基础疾病(高血压) (OR=30.185, 95% CI: 1.85-491.35, P=0.017)、WBC降低(OR=0.49, 95% CI: 0.29-0.84, P=0.009)、RBC降低(OR=0.021, 95% CI: 0.001-0.46, P=0.014)、ALB < 35 g/L(OR=0.091, 95% CI: 0.02-0.55, P=0.009)是中性粒细胞减少发生的独立危险因素。基于上述5项指标构建的列线图预测模型，受试者工作特征(ROC)曲线下面积(AUC)为0.929 (95% CI: 0.89-0.97)，校正曲线表明模型预测风险与实际观察风险具有高度一致性，DCA进一步证实，在0.1至0.4的合理高风险阈值范围内，该模型的临床应用能为患者管理带来显著的净获益。结论 维奈克拉C0、基础疾病(高血压)、WBC、RBC及ALB水平可作为预测 AML 患者维奈克拉治疗发生中性粒细胞减少的关键指标，所构建的模型有助于临床医生早期识别高危患者并进行干预，从而优化维奈克拉的临床应用。

Abstract:

ABSTRACT: OBJECTIVE To investigate the independent risk factors for neutropenia in patients with acute myeloid leukemia (AML) treated with venetoclax and to construct a nomogram prediction model. METHODS A retrospective analysis was conducted on the clinical data of hospitalized AML patients who received venetoclax treatment and underwent therapeutic drug monitoring (TDM) at the First Affiliated Hospital of Nanchang University between September 2022 and March 2025. Patients were divided into a case group and a control group based on the occurrence of neutropenia. Univariate analysis was used to screen potential risk factors, and binary logistic regression analysis was employed to identify independent risk factors. A nomogram prediction model was constructed based on the independent risk factors and validated. The clinical utility of the nomogram was evaluated using decision curve analysis (DCA). RESULTS Among the 138 patients, 53 (38.4%) developed neutropenia. Univariate analysis revealed that dosage, venetoclax C0, venetoclax C6, underlying disease (hypertension), concomitant use of CYP3A inhibitors, white blood cell count (WBC), red blood cell count (RBC), hemoglobin (HGB), platelet count (PLT), direct bilirubin (DBIL), albumin (ALB), globulin (GLB), and uric acid (UA) were significantly associated with the occurrence of neutropenia (P < 0.05). Binary logistic regression analysis indicated that elevated C0 (OR = 2.79, 95% CI: 1.02-7.65, P = 0.046), presence of underlying disease (hypertension) (OR = 30.185, 95% CI: 1.85-491.35, P = 0.017), decreased WBC (OR = 0.49, 95% CI: 0.29-0.84, P = 0.009), decreased RBC (OR = 0.021, 95% CI: 0.001-0.46, P = 0.014), and ALB < 35 g/L (OR = 0.091, 95% CI: 0.02-0.55, P = 0.009) were independent risk factors for neutropenia. The nomogram prediction model constructed based on these five indicators had an area under the receiver operating characteristic (ROC) curve (AUC) of 0.929 (95% CI: 0.89-0.97). The calibration curve demonstrated high consistency between the model-predicted risk and the actual observed risk. Decision curve analysis further confirmed that within a reasonable high-risk threshold range of 0.1 to 0.4, the clinical application of this model could provide significant net benefit for patient management. CONCLUSION Venetoclax C0, underlying disease (hypertension), WBC, RBC, and ALB levels can serve as key indicators for predicting the occurrence of neutropenia in AML patients treated with venetoclax. The constructed model can assist clinicians in early identification of high-risk patients and intervention, thereby optimizing the clinical application of venetoclax.