Perphenazine 2mg tablets

BackgroundThere are no recommendations based on the efficacy of specific drugs for the treatment of psychotic depression. To address this evidence gap, we did a network meta-analysis to assess and compare the efficacy and safety of pharmacological treatments for psychotic depression.MethodsIn this systematic review and network meta-analysis, we searched ClinicalTrials.gov, CENTRAL, Embase, PsycINFO, PubMed, Scopus, and Web of Science from inception to Nov 23, 2023 for randomised controlled trials published in any language that assessed pharmacological treatments for individuals of any age with a diagnosis of a major depressive episode with psychotic features, in the context of major depressive disorder or bipolar disorder in any setting. We excluded continuation or maintenance trials. We screened the study titles and abstracts identified, and we extracted data from relevant studies after full-text review. If full data were not available, we requested data from study authors twice. We analysed treatments for individual drugs (or drug combinations) and by grouping them on the basis of mechanisms of action. The primary outcomes were response rate (ie, the proportion of participants who responded to treatment) and acceptability (ie, the proportion who discontinued treatment for any reason). We calculated risk ratios and did separate frequentist network meta-analyses by using random-effects models. The risk of bias of individual studies was assessed with the Cochrane risk-of-bias tool and the confidence in the evidence with the Confidence-In-Network-Meta-Analysis (CINeMA). This study was registered with PROSPERO, CRD42023392926.FindingsOf 6313 reports identified, 16 randomised controlled trials were included in the systematic review, and 14 were included in the network meta-analyses. The 16 trials included 1161 people with psychotic depression (mean age 50·5 years [SD 11·4]). 516 (44·4%) participants were female and 422 (36·3%) were male; sex data were not available for the other 223 (19·2%). 489 (42·1%) participants were White, 47 (4·0%) were African American, and 12 (1·0%) were Asian; race or ethnicity data were not available for the other 613 (52·8%). Only the combination of fluoxetine plus olanzapine was associated with a higher proportion of participants with a treatment response compared with placebo (risk ratio 1·91 [95% CI 1·27-2·85]), with no differences in terms of safety outcomes compared with placebo. When treatments were grouped by mechanism of action, the combination of a selective serotonin reuptake inhibitor with a second-generation antipsychotic was associated with a higher proportion of treatment responses than was placebo (1·89 [1·17-3·04]), with no differences in terms of safety outcomes. In head-to-head comparisons of active treatments, a significantly higher proportion of participants had a response to amitriptyline plus perphenazine (3·61 [1·23-10·56]) and amoxapine (3·14 [1·01-9·80]) than to perphenazine, and to fluoxetine plus olanzapine compared with olanzapine alone (1·60 [1·09-2·34]). Venlafaxine, venlafaxine plus quetiapine (2·25 [1·09-4·63]), and imipramine (1·95 [1·01-3·79]) were also associated with a higher proportion of treatment responses overall. In head-to-head comparisons grouped by mechanism of action, antipsychotic plus antidepressant combinations consistently outperformed monotherapies from either drug class in terms of the proportion of participants with treatment responses. Heterogeneity was low. No high-risk instances were identified in the bias assessment for our primary outcomes.InterpretationAccording to the available evidence, the combination of a selective serotonin reuptake inhibitor and a second-generation antipsychotic-and particularly of fluoxetine and olanzapine-could be the optimal treatment choice for psychotic depression. These findings should be taken into account in the development of clinical practice guidelines. However, these conclusions should be interpreted cautiously in view of the low number of included studies and the limitations of these studies.FundingNone.

Abstract licence: CC BY-NC-ND

Objective Matching each patient to the most effective treatment option(s) remains a challenging problem in psychiatry. Clinical rating scales often fail to differentiate between treatments because most treatments improve the scores of all individual items at only slightly varying degrees. As a result, nearly all clinical trials in psychiatry fail to differentiate between active treatments. Methods We introduce a new statistical technique called Supervised Varimax (SV) that corrects this problem by accurately detecting large treatment differences directly from original clinical trial data. The algorithm combines the individual items of a clinical rating scale that only slightly differ between treatments into a few scores that greatly differ between treatments. We applied SV to multi-center, double-blind and randomized clinical trials called CATIE and STAR*D which were long thought to identify few to no differential treatment effects. Results SV identified optimal outcomes harboring large differential treatment effects in Phase I of CATIE (absolute sum = 1.279, p = 0.002). Post-hoc analyses revealed that olanzapine is more effective than quetiapine and ziprasidone for hostility in chronic schizophrenia (difference = −0.284, p FWER = 0.047; difference = −0.283, p FWER = 0.048), and perphenazine is more effective than ziprasidone for emotional dysregulation (difference = −0.313, p FWER = 0.020). SV also discovered that bupropion augmentation is more effective than buspirone augmentation for treatment-resistant depression with increased appetite from Level 2 of STAR*D (difference = −0.280, p FWER = 0.003). Conclusions SV represents a powerful methodology that enables precision psychiatry from clinical trials by optimizing the outcome measures to differentiate between treatments.

Abstract licence: CC BY-NC-ND

BackgroundAntipsychotic drugs are the mainstay of treatment for schizophrenia. Even though several novel second-generation antipsychotics (i.e. lurasidone, iloperidone and cariprazine) have been approved in recent years, typical antipsychotics (e.g. chlorpromazine, haloperidol, and fluphenazine) remain a crucial therapeutic option for the condition around the world. Little is known about the relative risk-to-benefit ratio of the 'latest' second-generation antipsychotics compared to the typical agents of 'established stature'.ObjectivesTo systematically review the efficacy and safety of lurasidone versus typical antipsychotics for adults with schizophrenia or schizophrenia-related disorders.Search methodsWe searched the Cochrane Schizophrenia Group's Study-Based Register of Trials on 5 June 2019. We also ran an update search in CENTRAL, MEDLINE, Embase, and three additional databases as well as two trial registers and the US Food and Drug Administration database on 1 April 2024.Selection criteriaWe searched for randomized controlled trials (RCTs) comparing lurasidonewith typical antipsychotic drugs (such as chlorpromazine, fluphenazine, haloperidol, loxapine, mesoridazine, molindone, perphenazine, thioridazine, thiothixene, zuclopenthixol) for adults with schizophrenia. No additional search restrictions were applied.Data collection and analysisWe followed standard Cochrane methodological procedures. We extracted information on participant characteristics, interventions, study outcomes, study design, trial methods, and funding sources. Two review authors independently extracted data and assessed the risk of bias. We assessed the certainty of evidence with GRADE for these key outcomes: change in mental state, death by suicide or natural cause, quality of life, total serious adverse events and severe adverse events (as defined by study authors).Main resultsWe included two studies with a total of 308 individuals diagnosed with schizophrenia (220 men and 85 women). A total of 223 participants received lurasidone (20, 40, or 80 mg/day), and 82 received haloperidol (up to 10 mg/day) or perphenazine (up to 32 mg/day); three people did not receive any study medication. Both studies were performed in the US. The duration of the follow-up was four to six weeks. Death by suicide/natural causes and quality of life were not reported by the two included studies. The evidence is very uncertain about the effects of lurasidone on change in mental state: the Brief Psychiatric Rating Scale (BPRS) (MD 3.74, 95% CI 0.57 to 6.90; 1 RCT, 281 participants; very low-certainty evidence); and the Positive and Negative Syndrome Scale (PANSS) (MD 6.68, 95% CI 2.45 to 10.91; 1 RCT, 281 participants; very low-certainty evidence). The evidence is also very uncertain about the effects of lurasidone on total serious adverse events (RR 0.98, 95% CI 0.37 to 2.60; 2 RCTs, 303 participants; very low certainty of evidence) and on severe adverse events (RR 1.70, 95% CI 0.46 to 6.32; 1 RCT, 281 participants; very low certainty of evidence).Authors' conclusionsWe are very uncertain about whether lurasidone offers benefits to the mental state, total serious adverse events, or severe adverse events when compared to typical antipsychotics for people with schizophrenia. The evidence included in this review is of very low certainty, derived from two small trials. Study limitations (risk of bias) and imprecise results impacted our confidence in the evidence. Furthermore, data on mortality (due to suicide or natural causes) or quality of life are unavailable. Further large-scale randomized studies are needed to provide clearer insights into the benefits and harms of lurasidone compared to typical antipsychotics for treating schizophrenia.

Abstract licence: CC BY-NC-ND

ObjectivesTo develop a statistical method that uncovers clinically meaningful differences between active psychiatric treatments, even when traditional rating scales fail to do so.MethodsWe introduce Supervised Varimax (SV), a novel algorithm that transforms individual items from clinical rating scales into a small set of optimized outcomes that maximally differentiate treatments. SV was applied to data from two large, multi-center, randomized controlled trials: CATIE (schizophrenia) and STAR*D (treatment-resistant depression).ResultsSV identified significant differential treatment effects that were not evident in the original analyses. In CATIE Phase I, olanzapine was more effective than quetiapine and ziprasidone for hostility, and perphenazine outperformed ziprasidone for emotional dysregulation. In Level 2 of STAR*D, bupropion augmentation was more effective than buspirone augmentation for patients with increased appetite. These findings were validated using post-hoc permutation testing and matched to clinical subgroups using simple, symptom-based rules.ConclusionsSV enables precision psychiatry by optimizing outcome definitions to enhance treatment differentiation in RCTs. This approach provides interpretable, clinically actionable insights using existing trial data, without requiring complex predictive modeling or additional biomarkers.Trial registrationCATIE (NCT00014001), STAR*D (NCT00021528).

Abstract licence: CC BY-NC-ND