Real-life effectiveness of transitioning from paliperidone palmitate 1-monthly to paliperidone palmitate 3-monthly long-acting injectable formulation
Bibliographic record
Abstract
Background: Non-adherence to antipsychotics in schizophrenia is associated with an increased risk of psychotic relapse and hospitalization, a risk that is reduced with the use of long-acting injectable (LAI) antipsychotics. Randomized clinical trials (RCTs) have demonstrated the efficacy of paliperidone palmitate 3-monthly (PP3M) for psychotic relapse prevention in schizophrenia, but it remains poorly documented among individuals treated in real-life settings who can benefit the most out of LAIs. Objectives: The objective of this study was to evaluate the effectiveness of PP3M in relapse prevention among patients with schizophrenia. Methods: This is a multicentre retrospective study conducted in four outpatients’ clinics across Canada. All consecutive patients with a main diagnosis of schizophrenia who initiated PP3M between June 2016 and March 2020 were included. The primary outcome was psychotic relapse, defined using broad and clinically relevant criteria. Results: Among 178 consecutive patients who were switched to PP3M, the 12-month relapse rate was 18.5% and the relapse-free survival probability was 0.788 (95% confidence interval [CI] = 0.725–0.856). Comorbid diagnoses of personality disorders and substance use disorders were associated with hazard rates (HRs) of 3.6 (95% CI = 1.8–7.3, p < 0.001) and 3.1 (95% CI = 1.6–6.2), respectively. Increased psychopathology severity was associated with an increased likelihood of relapse, while having a job or being in school was protective. Conclusion: These findings reinforce the necessity of conducting research in patients with comorbid psychiatric disorders who are typically underrepresented in RCTs, yet overrepresented in real-life settings, in order to better inform and guide clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".