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Record W2170837457 · doi:10.1017/s0317167100005540

Alternatives to Placebo-Controlled Trials

2007· review· en· W2170837457 on OpenAlexaffvenue
David L. Streiner

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2007
Typereview
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPlaceboMedicineClinical trialRandomized controlled trialEquivalence (formal languages)Sample size determinationAdverse effectGold standard (test)DrugIntensive care medicineAlternative medicinePharmacologySurgeryInternal medicineStatisticsMathematicsPathology

Abstract

fetched live from OpenAlex

Until recently, the gold standard for assessing the efficacy and effectiveness of new medications has been the placebo-control randomized clinical trial (RCT). However, there are serious ethical concerns about placing patients on a placebo when effective treatments exist. Further, if a new agent is tested only against a placebo, there is no guarantee that it is more effective, or even as effective, as an existing agent. For these and other reasons, ethicists and regulatory bodies have said that, under these circumstances, new drugs should be tested against an active agent. There are three types of such trials: superiority, equivalence, and non-inferiority. In superiority trials, the goal is to establish that the new drug is better (i.e., more effective, or with a more benign side-effect profile) than the standard. Because such trials require much larger sample sizes than placebo-control studies, and are rarely required to bring a drug onto market, they are rarely done. In equivalence trials, the aim is to show that the new and standard agents have similar degrees of effectiveness or adverse events. Due to sample size requirements, most studies of new drugs are non-inferiority trials, in which it is sufficient to demonstrate that the new drug is not significantly worse than the existing ones. However, there are methodological concerns with equivalence and non-inferiority trials, including (a) an inability to determine if the drugs were equally good or equally bad; (b) poorly executed trials with low power can be mistaken for "proving" equivalence or non-inferiority; (c) the equivalence interval is arbitrary; (d) successive non-inferiority trials may lead to a gradual reduction in effectiveness; and (e) often larger trials are necessary. The paper also discusses "add on trials." It is recommended that, even when existing drugs exist, trials should consist of at least three arms, one of which is a placebo. This paper briefly considers the ethics of placebo, and conditions are stated under which such studies can be conducted.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.305
metaresearch head score (Gemma)0.497
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.695
Threshold uncertainty score0.858

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3050.497
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0060.006
Science and technology studies0.0020.013
Scholarly communication0.0100.013
Open science0.0080.007
Research integrity0.0190.017
Insufficient payload (model declined to judge)0.0650.012

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.

Opus teacher head0.195
GPT teacher head0.396
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
GenreReview

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".

Quick stats

Citations28
Published2007
Admission routes2
Has abstractyes

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