MétaCan
Menu
Back to cohort
Record W115939940

The Regulation of Nutrigenetic Testing: A Role for Civil Society Organisations?

2008· article· en· W115939940 on OpenAlexvenueaboutno aff
Stuart Hogarth

Bibliographic record

VenueHealth law review · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsGenetic testingCommissionRegulatory scienceCriticismPolitical sciencePublic relationsPublic economicsLaw and economicsLawEconomicsMedicine
DOInot available

Abstract

fetched live from OpenAlex

Introduction In March 2005, Pharmacogenetics Reporter ran a story describing how the nutrigenetic biotechnology company, Sciona, was moving its operations from the United Kingdom to the United States. (1) The report suggested that the move was largely motivated by the failure to create a consumer market for its testing services in the UK and the expectation that the US would provide a far more receptive market. In the UK, Sciona had been the subject of criticism from scientists, nutritionists, the Human Genetics Commission and civil society organisations (CSOs). The Sciona controversy sparked a review of the regulatory framework for consumer genetics in the UK. This paper uses the Sciona controversy and the resulting policy debate as a case study to discuss the role of CSOs in the regulation of commercial genetic testing services. As genomics research advances, the appropriate regulation of genetic testing becomes increasingly important. This issue has troubled clinicians, patient groups, policy makers and regulators for over ten years. In Canada, the US, Europe and Australia, high-level committees have considered the issue and made their recommendations in weighty reports. (2) Analysis of the policy issues requires an understanding of the concerns the regulation is supposed to address as well as the regulatory space, including the regulatory framework and the actors involved. Concerns raised regarding genetic testing can be broadly categorized as consumer harms and social costs. Consumer harms range from the fear of a 'new eugenics' based on discrimination and stigmatisation, to fears that tests of limited predictive value will mislead consumers, either providing false reassurance that they are genetically predisposed to good health or causing undue alarm and expanding the ranks of the 'worried well' relying on expensive and potentially harmful medications, diets or other interventions for questionable reasons. The potential social costs of genetic testing include a negative impact on the nation's health, if by focusing on genetic risks well-established environmental factors, such as exercise, diet, pollution and smoking, are neglected or minimized. In the case of tests marketed directly to the public, there is a fear that busy family doctors will be further burdened by patients who have been tested commercially and then seek either reassurance or action as a consequence of the test results, especially if the testing company has not provided adequate counselling or advice. The regulatory challenges include ensuring that consumers have full opportunity to give informed consent, assuring quality of lab procedures to promote accurate testing, policing promotional claims to halt misleading advertising, protecting privacy of genetic data, and requiring premarket review of tests to evaluate fitness for purpose (that is, can the test diagnose or predict disease with the accuracy that the test developer claims?). As a result of these concerns, a debate has developed about how best to regulate the practice of genetic testing to prevent harm and maximize benefits. The debate is fairly sophisticated in that a range of regulatory mechanisms are generally advanced--from statutory licensing and use of existing consumer protection law to voluntary codes of conduct, best practice guidelines and consumer education. Much of the debate has revolved around the relative importance of these different mechanisms. (3) To caricature, regulatory hardliners view a robust regulator as essential to good regulation--an entity with 'command and control' authority to oversee compliance. Conversely, regulatory libertarians posit industry self-regulation coupled with education of consumers and healthcare professionals as the crucial mechanisms. Regulatory Theory and the Role of CSOs The debate over regulation of genetic testing is underway when regulation itself is undergoing change. …

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)0.030
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0110.051
Scholarly communication0.0230.018
Open science0.0030.011
Research integrity0.0480.031
Insufficient payload (model declined to judge)0.0140.004

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 head0.038
GPT teacher head0.306
Teacher spread0.268 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
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

Citations0
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueHealth law reviewSame topicNutrition, Genetics, and DiseaseFrench-language works237,207