Selective Serotonin Reuptake Inhibitor (SSRI) Add-On Therapy for the Negative Symptoms of Schizophrenia
Bibliographic record
Abstract
BACKGROUND: Negative symptoms are among the most chronic symptoms of schizophrenia. Even with the advent of atypical antipsychotic drugs, negative symptoms remain mostly refractory to treatment. It has been proposed that selective serotonin reuptake inhibitor (SSRI) augmentation therapy in schizophrenia could provide a greater relief of these symptoms. Published studies, however promising, have produced conflicting results. OBJECTIVE: To overcome this discrepancy in results, we performed a meta-analysis of studies assessing SSRI add-on therapy for the negative symptoms of schizophrenia. DATA SOURCES AND STUDY SELECTION: A search was performed using the computerized search engines PsycINFO, PubMed (MEDLINE), and Current Contents. Keywords used were schizophrenia and (for SSRI) sertraline, citalopram, paroxetine, fluoxetine, and fluvoxamine. Hand search of published review articles as well as cross-referencing were carried out, too. Pharmaceutical companies were also contacted. Studies were retained if (1) SSRI add-on therapy was compared with antipsychotic monotherapy among schizophrenia-spectrum disorder patients; (2) the clinical trial was randomized, double-blind, placebo-controlled with parallel-arm design; (3) negative symptoms were assessed with the Scale for the Assessment of Negative Symptoms or the Positive and Negative Syndrome Scale-negative subscale. DATA EXTRACTION: With a consensus, authors (A.A.S. and S.P.) extracted and checked the data independently on the basis of predetermined exclusion and inclusion criteria. Effect size estimates were calculated using Comprehensive Meta-Analysis software. DATA SYNTHESIS: Eleven studies responded to our inclusion criteria. Within a random-effects model, a nonsignificant composite effect size estimate for (end point) negative symptoms was obtained (N = 393; adjusted Hedges' g = 0.178; p = .191). However, when studies were divided according to severity of illness, a moderate and significant effect size emerged for the studies involving so-called "chronic patients" (N = 274; adjusted Hedges' g = 0.386; p = .014). CONCLUSION: The current meta-analysis provides no global support for an improvement in negative symptoms with SSRI augmentation therapy in schizophrenia.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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".