Pericyazine for schizophrenia

Matar, Hosam E; Almerie, Muhammad Qutayba; Makhoul, Samer; Xia, Jun; Humphreys, Pamela

doi:10.1002/14651858.cd007479.pub2

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…There is no mention of pericyazine in any guideline on the National Institute for Health and Care Excellence (NICE) website, the main source of clinical guidelines in England. A 2014 Cochrane review on pericyazine identified only 5 studies suitable for inclusion, could not determine the effect of pericyazine in schizophrenia given the low quality of evidence, and found a higher incidence of side effects compared to atypical antipsychotics [ 16 ]. A PubMed search identified only 73 publications that contain the word “pericyazine” [ 17 ] in any way since 1965 compared with over 22,000 results for haloperidol and 11,000 for risperidone.…”

Section: Discussionmentioning

confidence: 99%

Identifying Patterns of Clinical Interest in Clinicians’ Treatment Preferences: Hypothesis-free Data Science Approach to Prioritizing Prescribing Outliers for Clinical Review

et al. 2022

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Background Data analysis is used to identify signals suggestive of variation in treatment choice or clinical outcome. Analyses to date have generally focused on a hypothesis-driven approach. Objective This study aimed to develop a hypothesis-free approach to identify unusual prescribing behavior in primary care data. We aimed to apply this methodology to a national data set in a cross-sectional study to identify chemicals with significant variation in use across Clinical Commissioning Groups (CCGs) for further clinical review, thereby demonstrating proof of concept for prioritization approaches. Methods Here we report a new data-driven approach to identify unusual prescribing behaviour in primary care data. This approach first applies a set of filtering steps to identify chemicals with prescribing rate distributions likely to contain outliers, then applies two ranking approaches to identify the most extreme outliers amongst those candidates. This methodology has been applied to three months of national prescribing data (June-August 2017). Results Our methodology provides rankings for all chemicals by administrative region. We provide illustrative results for 2 antipsychotic drugs of particular clinical interest: promazine hydrochloride and pericyazine, which rank highly by outlier metrics. Specifically, our method identifies that, while promazine hydrochloride and pericyazine are barely used by most clinicians (with national prescribing rates of 11.1 and 6.2 per 1000 antipsychotic prescriptions, respectively), they make up a substantial proportion of antipsychotic prescribing in 2 small geographic regions in England during the study period (with maximum regional prescribing rates of 298.7 and 241.1 per 1000 antipsychotic prescriptions, respectively). Conclusions Our hypothesis-free approach is able to identify candidates for audit and review in clinical practice. To illustrate this, we provide 2 examples of 2 very unusual antipsychotics used disproportionately in 2 small geographic areas of England.

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Section: Discussionmentioning

confidence: 99%

Identifying Patterns of Clinical Interest in Clinicians’ Treatment Preferences: Hypothesis-free Data Science Approach to Prioritizing Prescribing Outliers for Clinical Review

et al. 2022

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“…5 There is no mention of pericyazine in any guideline on the National Institute for Health and Care Excellence (NICE) website 6 , the main source of clinical guidelines in England. A 2014 Cochrane review on pericyazine identified only five studies suitable for inclusion, could not determine pericyazine’s effect in schizophrenia given the low quality of evidence, and found a higher incidence of side effects compared to other antipsychotics 7 . A PubMed search identified only 73 publications that contain the word pericyazine in any way since 1965 compared with over 22,000 results for haloperidol, and 11,000 for risperidone.…”

Section: Discussionmentioning

confidence: 99%

Using data science to identify unusual treatment choices in England: illustrative findings of uncommon antipsychotics Pericyazine and Promazine

MacKenna

Curtis

Walker

et al. 2022

Preprint

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Background Data analysis can be used to identify signals suggestive of variation in treatment choice or clinical outcome. Analyses to date have generally focused on an hypothesis-driven approach. Methods Here we report an innovative hypothesis-blind approach (calculating chemical-class proportions for every chemical substance prescribed in each Clinical Commissioning Group and ranking chemicals by (a) their kurtosis and (b) a ratio between inter-centile differences) applied to England's national prescribing data, and demonstrate how this identified unusual prescribing of two antipsychotics. Outcomes We identified that, while promazine and pericyazine are barely used by most clinicians, they make up a substantial proportion of all antipsychotic prescribing in two small geographic regions in England. Interpretation Data-driven approaches can be effective at identifying unusual clinical choices. More widespread adoption of such approaches, combined with clinician and decision-maker engagement could lead to better optimised patient care. Funding NIHR Biomedical Research Centre, Oxford; Health Foundation; National Institute for Health Research (NIHR) School of Primary Care Research and Research for Patient Benefit

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“…76 Parkinson por mais de trinta anos e já descrito por sua ação anticolinesterásica. 83,84,85 Dentre os resultados obtidos, os autores destacam a importância da descoberta da alta potência e seletividade do derivado quinolizidinila (28c), a periciazina, 86 um fármaco antipsicótico com ação sedativa e cujas ações anti-BuChE descobertas merecem melhor investigação para possível emprego no tratamento pacientes com DA associada a desordens psicóticas.…”

Section: Derivados Benzimidazólicosunclassified

Butyrylcholinesterase - BuChE: A Potential Target for Development of Drugs for Alzheimer's Disease Treatment

Goulart¹,

Caruso²,

Nadur³

et al. 2021

Rev. Virtual Quim.

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Pericyazine for schizophrenia

Cited by 8 publications

References 28 publications

Identifying Patterns of Clinical Interest in Clinicians’ Treatment Preferences: Hypothesis-free Data Science Approach to Prioritizing Prescribing Outliers for Clinical Review

Identifying Patterns of Clinical Interest in Clinicians’ Treatment Preferences: Hypothesis-free Data Science Approach to Prioritizing Prescribing Outliers for Clinical Review

Using data science to identify unusual treatment choices in England: illustrative findings of uncommon antipsychotics Pericyazine and Promazine

Butyrylcholinesterase - BuChE: A Potential Target for Development of Drugs for Alzheimer's Disease Treatment

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