Abstract
Little guidance exists to date on how to select antipsychotic medications for patients with first-episode schizophrenia. To develop a preliminary individualized treatment rule (ITR) for patients with first-episode schizophrenia. This prognostic study obtained data from Taiwan's National Health Insurance Research Database on patients with prescribed antipsychotic medications, ambulatory claims, or discharge diagnoses of a schizophrenic disorder between January 1, 2005, and December 31, 2011. An ITR was developed by applying a targeted minimum loss-based ensemble machine learning method to predict treatment success from baseline clinical and demographic data in a 70% training sample. The model was validated in the remaining 30% of the sample. The probability of treatment success was estimated for each medication for each patient under the model. The analysis was conducted between July 16, 2018, and July 15, 2019. Fifteen different antipsychotic medications. Treatment success was defined as not switching medication and not being hospitalized for 12 months. Among the 32 277 patients in the analysis, the mean (SD) age was 36.7 (14.3) years, and 15 752 (48.8%) were male. In the validation sample, the treatment success rate (SE) was 51.7% (1.0%) under the ITR and was 44.5% (0.5%) in the observed population (Z = 7.1; P < .001). The estimated treatment success if all patients were given a prescription for 1 medication was significantly lower for each of the 13 medications than under the ITR (Z = 4.2-16.8; all P < .001). Aripiprazole (3088 [31.9%]) and amisulpride (2920 [30.2%]) were the medications most often recommended by the ITR. Only 1054 patients (10.9%) received ITR-recommended medications. Observed treatment success, although lower than the success under the ITR, was nonetheless significantly higher than if medications had been randomized (44.5% [SE, 0.55%] vs 41.3% [SE, 0.4%]; Z = 6.9; P < .001), although only marginally higher than if medications had been randomized in their observed population proportions (44.5% [SE, 0.5%] vs 43.5% [SE, 0.4%]; Z = 2.2; P = .03]). These results suggest that an ITR may be associatded with an increase in the treatment success rate among patients with first-episode schizophrenia, but experimental evaluation is needed to confirm this possibility. If confirmed, model refinement that investigates biomarkers, clinical observations, and patient reports as additional predictors in iterative pragmatic trials would be needed before clinical implementation.
Highlights
Schizophrenia is a severe and persistent mental disorder.[1,2] The standard treatment of antipsychotic medication reduces symptoms and relapse.[3]
These results suggest that an individualized treatment rule (ITR) may be associatded with an increase in the treatment success rate among patients with first-episode schizophrenia, but experimental evaluation is needed to confirm this possibility
Meaning Results of this study suggest that a clinically useful individualized treatment rule for antipsychotic medication selection could be associated with an increase in the treatment success in first-episode schizophrenia, a clinical trial and replication of this result with an expanded predictor set would be needed before clinical implementation
Summary
Schizophrenia is a severe and persistent mental disorder.[1,2] The standard treatment of antipsychotic medication reduces symptoms and relapse.[3]. Numerous clinical trials and observational studies have investigated comparative treatment effects and risk profiles of antipsychotic drugs.[3,7,8] Others have searched for reliable prognostic predictors of antipsychotic treatment response (ie, factors associated with treatment response regardless of treatment type) to help guide the decisions about adjunctive psychosocial treatment and psychoeducation,[9] while a small number of recent studies have searched for reliable prescriptive predictors of antipsychotic treatment response (ie, predictors of which antipsychotic medications are best for which patients).[10,11] The prescriptive predictors found so far have been too weak to be of clinical value individually,[12,13] leading to a focus on composite models to develop individualized treatment rules (ITRs).[14,15] promising results have been reported in ITR development,[14,15] no practical ITR has yet been proposed. In the absence of such information, treatment decisions must rely on considerations of pharmacokinetics and pharmacodynamics and trial-and-error investigations of tolerability.[16]
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