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.

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).