Switching medication products during the treatment of psychiatric illness
Bibliographic record
Abstract
BACKGROUND: The common practice of switching between branded (reference) medications and their corresponding generic products, between generic products, or even from a generic product to a branded medication during the treatment of central nervous system (CNS) disorders may compromise efficacy and/or tolerability. METHODS: We assessed the published literature from March 1, 2010 through June 30, 2017 via PubMed using the MeSH term 'generics, drugs' alone and in combination with class-specific terms (e.g., 'anticonvulsants', 'mood stabilisers'), for studies detailing outcomes following product switches. RESULTS: Although some studies comparing the initiation of reference versus generic drugs suggest equivalence between products, several studies detailing a switch between reference and generic products describe reductions in efficacy, reduced medication adherence and persistence, and increased overall health care resource utilization and costs associated with generic substitution. CONCLUSION: When product switches are considered, they should only proceed with the full knowledge of both patient and provider.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".