Early Placebo Improvement Is a Marker for Subsequent Placebo Response in Long-Acting Injectable Antipsychotic Trials for Schizophrenia
Bibliographic record
Abstract
OBJECTIVE: Placebo effects remain largely unexplored in clinical trials of long-acting injectable (LAI) antipsychotics for schizophrenia. This study aims to characterize patients showing improvements after placebo injections and to search for criteria for the prediction of subsequent response based on the magnitude of score changes after the first week of treatment. METHODS: Data from 450 patients with schizophrenia (DSM-IV) who received placebo injections in 4 double-blind randomized controlled trials evaluating efficacy of LAI paliperidone palmitate obtained through the Yale University Open Data Access (YODA) project were analyzed. These 4 studies were conducted from October 2003 to March 2008. Multiple logistic regression analyses were conducted to examine associations between placebo response and demographic and clinical characteristics. The predictive power of improvement at week 1 for response at week 9 was investigated; sensitivity and specificity of incremental 5% cutoff points between a 5% and 25% reduction in Positive and Negative Syndrome Scale (PANSS) total score at week 1 were calculated. RESULTS: Percent reduction in the PANSS total score at week 1 and a lower PANSS G12 item score (ie, better in judgment and insight) at baseline were significantly associated with placebo response at week 9 (odds ratio [OR] = 1.063; 95% CI, 1.040-1.087, P < .001; and OR= 0.739; 95% CI, 0.553-0.986, P = .040, respectively, in the per-protocol analysis). Cutoffs of a 10% (accuracy = 0.724 in the per-protocol analysis) and 15% (accuracy = 0.722 in the last-observation-carried-forward analysis) reduction in the PANSS total score at week 1 showed the highest predictive power. CONCLUSIONS: The appreciation that longer-term response following placebo injections can be predicted by a 10%-15% PANSS total score reduction at week 1 could guide the design of future clinical trials of LAI antipsychotics in schizophrenia to identify and exclude potential placebo responders early during the course of the study.
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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 | 0.084 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".