Venlafaxine is a 5-hydroxytryptamine-adrenergic reuptake inhibitor (SNRI) antidepressant widely used in the treatment of major depression, generalized anxiety disorder, and depressive co-morbidities, and China's Expert Consensus on Clinical Application of Psychiatric Therapeutic Drug Monitoring (2022 edition) suggests that venlafaxine can be feasibly monitored for blood concentration during treatment to avoid the use of over-alert concentrations, which can lead to the occurrence of adverse reactions or unsatisfactory therapeutic effects. However, the influence of patient physiology, genetic polymorphisms and other factors on the over-alert value of blood concentration is controversial.

To investigate the factors influencing venlafaxine blood concentration exceeding the alert threshold in patients with depression and to develop a risk prediction model for elevated venlafaxine concentrations, providing a reference for individualized venlafaxine therapy.

A retrospective analysis was conducted on 590 hospitalized patients who received venlafaxine treatment and underwent TDM at the First Hospital of Hebei Medical University between January 2021 and August 2024. Patients were categorized into a target concentration group (100-400 ng/mL) and an above-alert group (>800 ng/mL) based on their venlafaxine plasma concentrations. Demographic and clinical variables, including sex, age, BMI, average daily dose, plasma albumin level, concomitant medications, liver and kidney function, were collected and compared between groups. Multivariate Logistic regression analysis was performed to identify independent risk factors associated with venlafaxine concentrations exceeding the alert threshold. A nomogram prediction model was constructed based on the identified factors and was subsequently validated.

A total of 590 patients were included in this study, including 203 (34.4%) males and 387 (65.6%) females, with a mean age of (51.9±16.4) years. Among the 590 patients, there were 516 (87.5%) patientsin the target group, and 74 (12.5%) in the ultra-alert group. Multivariate Logistic regression analysis revealed that average daily dose≥225 mg (OR=26.628, 95%CI=12.912-54.916, P<0.001), renal impairment (OR=2.429, 95%CI=1.215-4.854, P=0.012), and concomitant use of CYP2D6 inhibitors (OR=5.232, 95%CI=2.781-9.844, P<0.001) were independent risk factors for venlafaxine concentrations exceeding the alert threshold. The model for predicting venlafaxine plasma concentrations exceeding alert threshold in patients with depression showed an area under the ROC curve of 0.899 (95%CI=0.864-0.935), sensitivity of 48.65%, specificity of 95.74%, positive predictive value of 62.07%, and negative predictive value of 92.86%. Bootstrap validation demonstrated good consistency (Brier score=0.072), and the Hosmer-Lemeshow test indicated good calibration (χ²=3.160, P=0.531). Decision curve analysis demonstrated clinical utility for threshold probabilities of 0.05-0.80.

Average daily dose≥225 mg, renal impairment, and concomitant use of CYP2D6 inhibitors are independent risk factors for venlafaxine plasma concentrations exceeding the alert threshold in patients with depression. The constructed nomogram model effectively predicts the risk of venlafaxine concentration exceeding the alert range and has significant clinical application value.

文拉法辛为5-羟色胺肾上腺素再摄取抑制剂（SNRI）类抗抑郁药，广泛用于治疗重度抑郁、广泛性焦虑障碍和抑郁共病，《中国精神科治疗药物监测临床应用专家共识（2022年版）》提出在治疗过程中，文拉法辛可行血药浓度监测，避免超警戒浓度使用而导致不良反应发生或治疗效果不理想。但患者生理、基因多态性等因素对其血药浓度超警戒值的影响存在一定争议。

探索抑郁患者文拉法辛血药浓度超警戒值的影响因素，并构建文拉法辛血药浓度超警戒值的风险预测模型，为文拉法辛个体化用药提供参考。

回顾性分析2021年1月—2024年8月于河北医科大学第一医院服用文拉法辛进行治疗并接受血药浓度监测住院患者的临床资料，将所纳入患者按文拉法辛血药浓度监测值分为达标组（血药浓度100~400 ng/mL）和超警戒组（血药浓度>800 ng/mL），收集两组患者的性别、年龄、BMI、日均服药剂量、血浆白蛋白、合并用药、肝肾功能情况，采用多因素Logistic回归分析筛选文拉法辛血药浓度超警戒值的独立影响因素，根据筛选出的独立影响因素构建列线图预测模型，并对该模型进行验证。

本研究共纳入患者590例，其中男203例（34.4%）、女387例（65.6%），平均年龄（51.9±16.4）岁。590例患者中达标组516例（87.5%）、超警戒组74例（12.5%）。多因素Logistic回归分析结果显示，日均服药剂量≥225 mg（OR=26.628，95%CI=12.912~54.916，P<0.001）、肾损害（OR=2.429，95%CI=1.215~4.854，P=0.012）、合用细胞色素P450（CYP）2D6抑制剂（OR=5.232，95%CI=2.781~9.844，P<0.001）是文拉法辛血药浓度超出警戒值的危险因素。根据所筛选出的独立影响因素，建立了文拉法辛血药浓度超警戒值的列线图预测模型，该模型预测抑郁患者文拉法辛血药浓度超警戒值的ROC曲线下面积（AUC）为0.899（95%CI=0.864~0.935），灵敏度为48.65%，特异度为95.74%，阳性预测值为62.07%，阴性预测值为92.86%；Bootstrap法验证结果显示，校正曲线与实际曲线一致性良好（Brier评分=0.072）；Hosmer-Lemeshow检验结果显示，列线图预测模型的校准度良好（χ²=3.160，P=0.531）；临床决策曲线分析（DCA）结果显示，当阈值为0.05~0.80时，列线图模型具有较好的临床实用性。

日均服药剂量≥225 mg、存在肾损害、合并使用CYP2D6抑制剂是抑郁患者血药浓度超警戒值的独立危险因素，据此构建的列线图模型能有效预测抑郁患者文拉法辛血药浓度超警戒风险程度，具有较高的临床应用价值。