TY - JOUR PY - 2021// TI - Using classification and regression tree modelling to investigate treatment response to a single low-dose ketamine infusion: Post hoc pooled analyses of randomized placebo-controlled and open-label trials JO - Journal of affective disorders A1 - Chen, Mu-Hong A1 - Wu, Hui-Ju A1 - Li, Cheng-Ta A1 - Lin, Wei-Chen A1 - Bai, Ya-Mei A1 - Tsai, Shih-Jen A1 - Hong, Chen-Jee A1 - Tu, Pei-Chi A1 - Cheng, Chih-Ming A1 - Su, Tung-Ping SP - 865 EP - 871 VL - 281 IS - N2 - BACKGROUND: Evidence suggests that clinical markers, such as comorbid anxiety, body weight, and others can assist in predicting response to low-dose ketamine infusion in treatment resistant depression patients. However, whether a composite of clinical markers may improve the predicted probability of response is uncertain. METHODS: The current study investigated the results of our previous randomized placebo-controlled and open-label trials in which 73 patients with treatment-resistant depression (TRD) received a single ketamine infusion of 0.5 mg/kg. Clinical characteristics at baseline, including depression severity, duration of the current episode, obesity, comorbidity of anxiety disorder, and current suicide risk, were assessed as potential predictors in a classification and regression tree model for treatment response to ketamine infusion. RESULTS: The predicted probability of a composite of age at disease onset, depression severity, duration of current episode, and obesity/overweight was significantly greater (area under curve = .736, p = .001) than that of any one marker (all p > .05). The most powerful predictors of treatment response to ketamine infusion were younger age at disease onset and obesity/overweight. The strongest predictors of treatment nonresponse were longer duration of the current episode and greater depression severity at baseline. DISCUSSION: Depression severity, duration of the current episode, obesity, and age at disease onset may predict treatment response versus nonresponse to low-dose ketamine infusion. However, whether our predicted probability for a single infusion may be applied to repeated infusions would require further investigation. CLINICAL TRIAL REGISTRATION: UMIN Clinical Trials Registry (UMIN000023581 and UMIN000016985).

Language: en

LA - en SN - 0165-0327 UR - http://dx.doi.org/10.1016/j.jad.2020.11.045 ID - ref1 ER -