Cessation of Medication for People With Schizophrenia Already Stable on Chlorpromazine
Bibliographic record
Abstract
People with schizophrenia are often encouraged to take medication for protracted periods of time in order to postpone or stop deterioration. It is, nevertheless, difficult for clinicians to provide a quantitative estimate of risk of relapse should medication be stopped. Because protracted use of any medication carries a risk of adverse effects, it seems reasonable to seek this evidence. To investigate the effects of stopping chlorpromazine for people with schizophrenia already stable on that drug, primarily for outcomes of global state, improvement, and relapse. We searched the Cochrane Schizophrenia Group Trials Register (March 2006). This is compiled by systematic searches of major databases, journals, and conference proceedings. We also inspected references of all identified studies for further trials. All clinical randomized controlled trials (RCTs) involving people with schizophrenia comparing the withdrawal of chlorpromazine with maintaining the medication. We independently inspected references located through electronic or reference searches. Full texts of these articles were then read, also independently, to decide whether they met our criteria. Disagreement was resolved by discussion. We reliably assessed study quality and extracted data. We used the relative risk (RR) for dichotomous data and the weighted mean differences for continuous data. Where heterogeneity existed (determined by I-square test), a random effects model was used. We included 10 trials (total N = 1042). People already stable and maintained on chlorpromazine were found to experience significantly less relapse compared with those who were asked to stop taking their medication (n = 850, 6 RCTs, RR relapse between 9 weeks and 6 months 4.04 confidence interval [CI] 2.81 to 5.8, number needed to harm (NNH) 4 CI 3 to 7; n = 510, 3 RCTs, RR relapse beyond 6 months 1.70 CI 1.44 to 2.01, NNH 4 CI 3 to 6). Even in the short term, results showed a significant increase in relapse rate of people who stopped medication (n = 376, 3 RCTs, RR relapse before 8 weeks 6.76 CI 3.37 to 13.54, NNH 4 CI 2 to 8) (see figure 1). Regarding global state improvement, only one study reported usable data at about 8 weeks favoring chlorpromazine continuation (n = 95, 1 RCT, RR not improved 2.46 CI 1.51 to 3.99, NNH 3 CI 2 to 8). More detailed findings are reported in the full version of this review.1 Relapse Across Time of Cessation of Chlorpromazine This review confirms much that clinicians already know but provides quantification to support clinical impression. For people with established illnesses, chlorpromazine withdrawal shows significant increase in relapse across all time periods. The epidemiology of schizophrenia consistently suggests that over 10% of people with their first episode will not go on to have further relapses. We did not find evidence to quantify risk of stopping medication in those in their first episode of schizophrenia. Relapse, however, incurs risks and costs that would probably be judged by everyone as greater than those associated with stable use of chlorpromazine. More reviews of trials focusing on cessation of other drugs would provide opportunities for replication. New trials of drug cessation for those at low risk of relapse may be possible to justify.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".