Achieving the Lowest Effective Antipsychotic Dose for Patients with Remitted Psychosis: A Proposed Guided Dose-Reduction Algorithm.

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Achieving the Lowest Effective Antipsychotic Dose for Patients with Remitted Psychosis: A Proposed Guided Dose-Reduction Algorithm.

CNS Drugs. 2019 Nov 18;:

Authors: Liu CC, Takeuchi H

Abstract
Continuing antipsychotic treatment in patients with schizophrenia under clinical remission remains controversial. Even though the mainstream opinion declares an outweighed balance against medication discontinuation, recent reviews and critiques suggest that some patients may remain symptom free and well functioning after stopping antipsychotics, but few predictors can identify who can try medication discontinuation, whilst no guidelines exist for reducing medication to reach the lowest effective dose safely. Analyzing the findings from studies employing different methodologies, adopting evidence from pharmacodynamic research, and observing dose reduction in stable patients, as well as taking inspiration from the metaphor of the Cantor set in natural philosophy, we introduce an alternative solution and propose a guided dose-reduction algorithm that follows a set of clear precautions and instructions. The algorithm recommends only a fraction (no more than 25%) of the dosage to be reduced at a time, with at least a 6-month stabilization period required before reducing another 25% of the dose. Patients are empowered to actively participate in decision making when they are ready for further dose tapering, or should they retreat to a previous dosage if warning signs of a relapse re-emerge. An intermittent or irregular dosing schedule can be used to adapt this algorithm to real-world practice. Our preliminary findings suggest that patients with remitted psychosis can do well along this path. We anticipate that this approach can help optimize the risk-benefit ratio and instill a hope in patients with schizophrenia that they can maintain in stable remission under a lower antipsychotic dose without an increased risk of relapse.

PMID: 31741178 [PubMed - as supplied by publisher]