Press Release: Substantial Improvements in Cancer Trials Not likely Caused By Placebo Effects
Bibliographic record
Abstract
An analysis of placebo effects in randomized double-blinded placebo-controlled trials of cancer treatments has found that placebos are sometimes associated with improved control of symptoms such as pain and appetite but rarely with objective tumor response. The findings appear in a review article in the January 1 issue of the Journal of the National Cancer Institute. The placebo effect is an effect seen in patients given an intervention, such as a placebo, that has no pharmacologically-mediated action against the disease. Previous studies have suggested that some cancer patients who had received a placebo for pain reported a reduction in pain after the intervention. To determine the probability that a placebo will lead to improvement of symptoms and tumor response, Gisèle Chvetzoff, M.D., of the Centre Léon Bérard in Lyon, France, and Ian F. Tannock, M.D., Ph.D., of the Princess Margaret Hospital in Toronto, reviewed reports of 37 randomized controlled trials that compared a group receiving active treatment with a group receiving a placebo. The authors also reviewed reports of 10 randomized controlled trials that compared a group receiving active treatment plus best supportive care with a group receiving best supportive care alone. Some of the trials looked at individual responses, and other trials looked at group responses.
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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 | 0.321 | 0.620 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".