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Record W128099815

Ethics review of multi-centre clinical trials in Canada.

2005· article· en· W128099815 on OpenAlexaboutno aff
Michael E. Enzle, Rodney Schmaltz

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionResearch ethicsInstitutional review boardConsistency (knowledge bases)Human researchPolitical sciencePublic relationsEngineering ethicsLawMedicineEngineeringComputer science
DOInot available

Abstract

fetched live from OpenAlex

Human research conducted at institutions receiving funding from any of the three federal Canadian funding agencies must be reviewed and approved in advance by a human research ethics board (REB). The Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (1) (TCPS) requires that each institution be fully responsible for the ethics review of human research conducted under its auspices (Article 1.2). (2) This provision has been interpreted to mean that one institution cannot pro forma accept the REB decision of another institution when the same research is proposed for conduct at both institutions. This interpretation is most clearly at issue in cases of multi-centre clinical trials, wherein researchers from two or more institutions are invited to participate in trials using standardized research protocols. Many researchers, research ethics boards, clinical trial sponsors, and institutional administrators have complained informally about several inter-related consequences of TCPS Article 1.2. They argue that this Article has resulted in institutions and their REBs being concerned that reliance on another institution's REB decision would either constitute non-compliance with the TCPS, or would expose them to unknown, and therefore unacceptable, liability risks. Other critics argue that the multiple reviews resulting from this state of uncertainty about institutional responsibility are unnecessarily redundant in view of the common standards for protection of human subjects established by the TCPS. They claim that this redundancy creates wasted human resources, wasted material resources, and wasted time. Another concern centres on decision consistency, because it is possible for one REB to reject the same proposal judged acceptable in whole or part by another REB. Thus, the same protocol can be found acceptable for implementation at one site, but not at another. Pharmaceutical companies and investigators (3) also complain that they receive many demands for protocol revisions from different REBs, some of which are diametrically opposed to one another. Such demands pose difficult challenges for the designers and sponsors of multi-centre trials, as homogeneity of methods across sites is a critical element of scientific control. The critics of multiple REB reviews for multi-centre trials also cite a negative public health consequence: Research with important health implications may be delayed unnecessarily, or even discouraged, thereby indirectly depriving the populace of the best possible healthcare. There have been three main reactions to these criticisms and warnings. One response is that redundancy and the attendant costs of multiple REB reviews is justified and desirable, as the effect is to enhance the protection of human research subjects. A second is that a national, centralized, system of review for multi-centre clinical trials should be established. The third reaction, a fait accompli, is an amendment to the TCPS Article 1.2 that permits institutions to form affiliations in which mutual acceptance of each other's REB findings can occur. (4) 1. Benefits of Redundancy Despite the apparent validity of the inefficiency and inconsistency arguments about multiple REB reviews, we have suggested elsewhere that multiple reviews may promote human research protections. (5) Critics of decentralized multiple reviewing implicitly claim that inconsistency among REB decisions amounts to poor reliability among REBs. They argue that a common, easily understood set of standards exist in the TCPS, and that inconsistency therefore represents a misapplication of the standards by REBs. This approach assumes, moreover, that minority opinion is wrong and reflects a lack of expertise or negligent application of ethics standards. We do not think that this is necessarily the case. Our reasoning stems from a common phenomenon at REB meetings--that in which a single REB member identifies a significant ethical issue, and persuades all remaining members of the REB that the protocol requires substantial changes or should be rejected. …

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)0.381
metaresearch head score (Gemma)0.455
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.864

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3810.455
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0080.010
Science and technology studies0.0110.010
Scholarly communication0.0140.003
Open science0.0070.007
Research integrity0.0100.010
Insufficient payload (model declined to judge)0.0080.003

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 head0.865
GPT teacher head0.663
Teacher spread0.202 · 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 designObservational
DomainMethods
GenreEmpirical

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

Citations18
Published2005
Admission routes1
Has abstractyes

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