Increasing placebo responses over time in U.S. clinical trials of neuropathic pain
Bibliographic record
Abstract
Recent failures of clinical trials of novel analgesics designed to treat neuropathic pain have led to much speculation about the underlying reasons. One often discussed possibility is that the placebo response in these trials has increased in recent years, leading to lower separation between the drug and placebo arms. Whether this has indeed occurred has not yet been adequately addressed. Here, we extracted data from published randomized controlled trials (RCTs) of drugs for the treatment of chronic neuropathic pain over the years 1990 to 2013. We find that placebo responses have increased considerably over this period, but drug responses have remained stable, leading to diminished treatment advantage. This trend has been driven by studies conducted in the United States. Consideration of participant and study characteristics revealed that in the United States but not elsewhere, RCTs have increased in study size and length. These changes are associated with larger placebo response. Analysis of individual RCT time courses showed different kinetics for the treatment vs placebo responses, with the former evolving more quickly than the latter and plateauing, such that maximum treatment advantage was achieved within 4 weeks.
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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 | 0.123 | 0.267 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".