Characterization of antipsychotic utilization before clozapine initiation for individuals with schizophrenia: an innovative visualization of trajectories using French National Health Insurance data

Abstract Aims Despite recommendations to initiate clozapine after two unsuccessful trials of antipsychotics, clozapine is underprescribed and initiated too late. The aim of this study was to describe different antipsychotic treatment sequences in the 36 months before the initiation of clozapine and to characterize clusters of treatment trajectories. Methods Using the French National Health Insurance database, a historical cohort study of the population in an area in western France was performed. The data from all new users of clozapine with a diagnosis of schizophrenia or schizoaffective disorder in the period of 2017–2018 were evaluated. All outpatient reimbursements for antipsychotics during the 36 months before clozapine initiation were analysed. Successive reimbursements for identical treatments were grouped into treatment trials (TTs), and different trajectories were clustered using a state sequence analysis. Results The results showed 1191 TTs for 287 individuals. The mean number of TTs per individual was 3.2. Risperidone, aripiprazole and haloperidol were the main treatments delivered. The frequencies of antipsychotics used differed between monotherapies and combination therapies. A three-cluster typology was identified: one cluster (n = 133) of ‘less treated’ younger individuals with fewer TTs and shorter TT durations; a second cluster (n = 53) of ‘more treated’ individuals with higher numbers of TTs and combinations of antipsychotics; and a third cluster (n = 103) of ‘treatment-stable’ older individuals with longer TT durations. Conclusions The results indicate that the median number of TTs during the 36 months before clozapine prescription was higher than the two recommended. The different trajectories were associated with individual characteristics and treatment differences, suggesting that additional studies of clinical parameters are needed to understand barriers to clozapine prescription

Publisher Correction: LifeTime and improving European healthcare through cell-based interceptive medicine.

A Correction to this paper has been published: https://doi.org/10.1038/s41586-021-03287-8.</jats:p

LifeTime and improving European healthcare through cell-based interceptive medicine

LifeTime aims to track, understand and target human cells during the onset and progression of complex diseases and their response to therapy at single-cell resolution. This mission will be implemented through the development and integration of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during progression from health to disease. Analysis of such large molecular and clinical datasets will discover molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. Timely detection and interception of disease embedded in an ethical and patient-centered vision will be achieved through interactions across academia, hospitals, patient-associations, health data management systems and industry. Applying this strategy to key medical challenges in cancer, neurological, infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade.We would like to acknowledge all participants that have attended and contributed to LifeTime meetings and workshops through many exciting presentations and discussions. We thank Johannes Richers for artwork. LifeTime has received funding from the European Unionʼs Horizon 2020 research and innovation framework programme under Grant agreement 820431

LifeTime and improving European healthcare through cell-based interceptive medicine

AUTEURS : LifeTime Community Working GroupsInternational audienceHere we describe the LifeTime Initiative, which aims to track, understand and target human cells during the onset and progression of complex diseases, and to analyse their response to therapy at single-cell resolution. This mission will be implemented through the development, integration and application of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during the progression from health to disease. The analysis of large molecular and clinical datasets will identify molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. The timely detection and interception of disease embedded in an ethical and patient-centred vision will be achieved through interactions across academia, hospitals, patient associations, health data management systems and industry. The application of this strategy to key medical challenges in cancer, neurological and neuropsychiatric disorders, and infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade