A Review of Outcomes and Effect Sizes
from Part I - Neuroscience
Published online by Cambridge University Press: 29 April 2026
The origins and treatment-target related mechanisms of schizophrenia remain to be more fully understood. Pharmacological and non-pharmacological treatments require expansion and improvements to meet more peoples’ needs and goals. Nevertheless, antipsychotics are a cornerstone when managing schizophrenia, being essential for reducing symptom severity, preventing relapse, improving long-term functional outcomes and reducing premature mortality risk. This narrative review synthesizes key evidence on the efficacy and risks associated with antipsychotic medications. The concept of effect sizes is introduced allowing to compare antipsychotics across trials with different ratings instruments and across different conditions. The available evidence in schizophrenia and comparison with medications used for medical conditions counters the sometimes voiced criticism that antipsychotics “do not work”. Instead, for a substantial group of people with schizophrenia, positive psychotic symptoms and global psychopathology improve with a medium effect size of about 0.4 vs. placebo. These results are comparable to median effect sizes across commonly used medications for somatic disorders. When patients with initial response are continued on antipsychotics, the effect size increases to 0.9 for relapse prevention, translating into a number-needed-to-treat of about three to prevent on more relapse versus no treatment. This number-needed-to-treat is 10-20 times higher than for the prevention of poor outcomes in some common medical conditions. Nevertheless, further development is needed regarding preventive interventions, the development of medications with mechanisms other than postsynaptic dopamine receptor blockade, with broader efficacy for positive, negative, cognitive, suicidality and/or reward dysregulation symptomatology, and the identification of illness mechanism/biomarker-targeting treatments to enhance treatment personalization.
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