Finding treatment‐resistant depression in real‐world data: How a data‐driven approach compares with expert‐based heuristics

• Published in: Depression and anxiety Vol. 35; no. 3; pp. 220 - 228
• Main Authors: Cepeda, M. Soledad, Reps, Jenna, Fife, Daniel, Blacketer, Clair, Stang, Paul, Ryan, Patrick
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.03.2018; John Wiley and Sons Inc
• Subjects: Adult; Affective disorders; Aged; Antidepressants; Antidepressive Agents - therapeutic use; Antipsychotic Agents - therapeutic use; Antipsychotics; Between-subjects design; decision tree; Dementia disorders; Depressive Disorder, Treatment-Resistant - diagnosis; Depressive Disorder, Treatment-Resistant - drug therapy; Electroconvulsive therapy; Epidemiology; Female; Heuristic; Heuristics; Humans; Machine learning; Male; Mental depression; Middle Aged; prevalence; Problem solving; Psychosis; Psychotropic drugs; Treatment resistance; Vagus nerve; databases; epidemiology; prevalence; decision tree; machine learning
• ISSN: 1091-4269; 1520-6394; 1520-6394
• DOI: 10.1002/da.22705

Background Depression that does not respond to antidepressants is treatment‐resistant depression (TRD). TRD definitions include assessments of treatment response, dose and duration, and implementing these definitions in claims databases can be challenging. We built a data‐driven TRD definition and evaluated its performance. Methods We included adults with depression, ≥1 antidepressant, and no diagnosis of mania, dementia, or psychosis. Subjects were stratified into those with and without proxy for TRD. Proxies for TRD were electroconvulsive therapy, deep brain, or vagus nerve stimulation. The index date for subjects with proxy for TRD was the procedure date, and for subjects without, the date of a randomly selected visit. We used three databases. We fit decision tree predictive models. We included number of distinct antidepressants, with and without adequate doses and duration, number of antipsychotics and psychotherapies, and expert‐based definitions, 3, 6, and 12 months before index date. To assess performance, we calculated area under the curve (AUC) and transportability. Results We analyzed 33,336 subjects with no proxy for TRD, and 3,566 with the proxy. Number of antidepressants and antipsychotics were selected in all periods. The best model was at 12 months with an AUC = 0.81. The rule transported well and states that a subject with ≥1 antipsychotic or ≥3 antidepressants in the last year has TRD. Applying this rule, 15.8% of subjects treated for depression had TRD. Conclusion The definition that best discriminates between subjects with and without TRD considers number of distinct antidepressants (≥3) or antipsychotics (≥1) in the last year.