| Abstract: | Second‐generation antipsychotics (SGAs) are recommended for maintenance treatment in schizophrenia. However, comparative long‐term effectiveness among SGAs is unclear. Here we provide a systematic review and meta‐analysis of randomized trials lasting ≥?6 months comparing SGAs head‐to‐head in schizophrenia and related disorders. The primary outcome was all‐cause discontinuation. Secondary outcomes included efficacy and tolerability, i.e., psychopathology, inefficacy‐related and intolerability‐related discontinuation, relapse, hospitalization, remission, functioning, quality of life, and adverse events. Pooled risk ratio and standardized mean difference were calculated using random‐effects models. Across 59 studies (N=45,787), lasting 47.4±32.1 weeks (range 24‐186), no consistent superiority of any SGA emerged across efficacy and tolerability outcomes. Regarding all‐cause discontinuation, clozapine, olanzapine and risperidone were significantly (p<0.05) superior to several other SGAs, while quetiapine was inferior to several other SGAs. As to psychopathology, clozapine and olanzapine were superior to several other SGAs, while quetiapine and ziprasidone were inferior to several other SGAs. Data for other efficacy outcomes were sparse. Regarding intolerability‐related discontinuation, risperidone was superior and clozapine was inferior to several other SGAs. Concerning weight gain, olanzapine was worse than all other compared non‐clozapine SGAs, and risperidone was significantly worse than several other SGAs. As to prolactin increase, risperidone and amisulpride were significantly worse than several other SGAs. Regarding parkinsonism, olanzapine was superior to risperidone, without significant differences pertaining to akathisia. Concerning sedation and somnolence, clozapine and quetiapine were significantly worse than some other SGAs. In summary, different long‐term SGA efficacy and tolerability patterns emerged. The long‐term risk‐benefit profiles of specific SGAs need to be tailored to individual patients to optimize maintenance treatment outcomes. |
