Antipsychotic utilization trajectories three years after initiating or reinitiating treatment of schizophrenia: A state sequence analysis approach
Bibliographic record
Abstract
OBJECTIVE: This study aims to describe the utilization patterns of antipsychotic (AP) medication in patients with schizophrenia (SCZ), three years after initiating or reinitiating a given AP. METHODS: Based on medico-administrative information on patients living in Quebec (Canada), this retrospective cohort study included 6444 patients with a previous diagnosis of SCZ initiating or reinitiating AP medication between January 1, 2012, and December 31, 2014, with continuous coverage by public drug insurance. For each day of follow-up (1092 days), patient was either exposed to one of the chosen categories of APs, or to none. This patient's sequence of AP exposure overtime has been referred to as the "antipsychotic utilization trajectory". These trajectories were analyzed using a State Sequence Analysis, an innovative approach which provides useful visual information on the continuation and discontinuation patterns of use over time. RESULTS: Clozapine and long-acting injectable second-generation APs had the best continuation and discontinuation patterns over 3 years among all other groups, including less switching of APs, while oral first-generation APs had the poorest patterns. These findings were comparable among incident and non-incident cohorts. Oral second-generation antipsychotics, excluding clozapine, had a poorer continuation and discontinuation pattern than long-acting injectable antipsychotics. CONCLUSION: State Sequence Analysis provides a clear representation of treatment adherence in comparison with dichotomous indicators of adherence or discontinuation. Consequently, this innovative method has shed light on the impact of the AP chosen to initiate or reinitiate treatment in SCZ, which has been identified as a key factor for long-term treatment continuation and discontinuation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".