Study on the Predictive Value of a Risk Prediction Model for Venlafaxine Plasma Concentration Exceeding the Safety Threshold postprint

Abstract: Background　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. Objective　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. Methods　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 VEN 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. Logistic regression analysis was performed to identify independent risk factors associated with VEN concentrations exceeding the alert threshold. A nomogram prediction model was constructed based on the identified factors and was subsequently validated. Results　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. 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 VEN concentrations exceeding the alert threshold. The nomogram model showed an AUC 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. Conclusion　Average daily dose ≥ 225 mg，renal impairment，and concomitant use of CYP2D6 inhibitors are independent risk factors for VEN plasma concentrations exceeding the alert threshold. The constructed nomogram model effectively predicts the risk of venlafaxine concentration exceeding the alert range and has significant clinical application value.