Escaping the Long Shadow Cast by Agranulocytosis: Reflections on Clozapine Pharmacovigilance Focused on the United Kingdom.

PURPOSE/BACKGROUND: A recent article in this journal presented a US perspective regarding the modernization of clozapine prescription and proposed an escape from the long shadow cast by agranulocytosis. METHODS: Here, an international group of collaborators discusses a point of view complementary to the US view by focusing on worldwide outcomes of clozapine usage that may be uneven in terms of frequency of clozapine adverse drug reactions. FINDINGS/RESULTS: Studies from the Scandinavian national registries (Finland and Denmark) did not find increased mortality in clozapine patients or any clear evidence of the alleged toxicity of clozapine. Data on clozapine-associated fatal outcomes were obtained from 2 recently published pharmacovigilance studies and from the UK pharmacovigilance database. A pharmacovigilance study focused on physician reports to assess worldwide lethality of drugs from 2010 to 2019 found 968 clozapine-associated fatal outcomes in the United Kingdom. Moreover, the United Kingdom accounted for 55% (968 of 1761) of worldwide and 90% (968 of 1073) of European fatal clozapine-associated outcomes. In a pharmacovigilance study from the UK database (from 2008 to 2017), clozapine was associated with 383 fatal outcomes/year including all reports from physicians and nonphysicians. From 2018 to 2021, UK clozapine-associated fatal outcomes increased to 440/year. IMPLICATIONS/CONCLUSIONS: The interpretation of fatal outcomes in each country using pharmacovigilance databases is limited and only allows gross comparisons; even with those limitations, the UK data seem concerning. Pneumonia and myocarditis may be more important than agranulocytosis in explaining the uneven distribution of fatal outcomes in clozapine patients across countries.

Actionable Predictive Factors of Homelessness in a Psychiatric Population: Results from the REHABase Cohort Using a Machine Learning Approach.

BACKGROUND: There is a lack of knowledge regarding the actionable key predictive factors of homelessness in psychiatric populations. Therefore, we used a machine learning model to explore the REHABase database (for rehabilitation database-n = 3416), which is a cohort of users referred to French psychosocial rehabilitation centers in France. METHODS: First, we analyzed whether the different risk factors previously associated with homelessness in mental health were also significant risk factors in the REHABase. In the second step, we used unbiased classification and regression trees to determine the key predictors of homelessness. Post hoc analyses were performed to examine the importance of the predictors and to explore the impact of cognitive factors among the participants. RESULTS: &nbsp;First, risk factors that were previously found to be associated with homelessness were also significant risk factors in the REHABase. Among all the variables studied with a machine learning approach, the most robust variable in terms of predictive value was the nature of the psychotropic medication (sex/sex relative mean predictor importance: 22.8, σ = 3.4). Post hoc analyses revealed that first-generation antipsychotics (15.61%; p < 0.05 FDR corrected), loxapine (16.57%; p < 0.05 FWER corrected) and hypnotics (17.56%; p < 0.05 FWER corrected) were significantly associated with homelessness. Antidepressant medication was associated with a protective effect against housing deprivation (9.21%; p < 0.05 FWER corrected). CONCLUSIONS: Psychotropic medication was found to be an important predictor of homelessness in our REHABase cohort, particularly loxapine and hypnotics. On the other hand, the putative protective effect of antidepressants confirms the need for systematic screening of depression and anxiety in the homeless population.