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Record W2100475901 · doi:10.7150/ijms.5.244

Acceptability of cancer chemoprevention trials: impact of the design

2008· article· en· W2100475901 on OpenAlexaff
Anne-Sophie Maisonneuve, Laëtitia Huiart, Laetitia Rabayrol, Doug Horsman, Rémi Didelot, Hagay Sobol, François Eisinger

Bibliographic record

VenueInternational Journal of Medical Sciences · 2008
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsBC Cancer Agency
FundersLigue Contre le Cancer
KeywordsMedicineBreast cancerLung cancerClinical trialCancerRandomized controlled trialPillInternal medicineRandomizationCancer preventionIncidence (geometry)OncologyGynecologyPhysical therapyPharmacology

Abstract

fetched live from OpenAlex

BACKGROUND: Chemoprevention could significantly reduce cancer burden. Assessment of efficacy and risk/benefit balance is at best achieved through randomized clinical trials. METHODS: At a periodic health examination center 1463 adults were asked to complete a questionnaire about their willingness to be involved in different kinds of preventive clinical trials. RESULTS: Among the 851 respondents (58.2%), 228 (26.8%) agreed to participate in a hypothetical chemoprevention trial aimed at reducing the incidence of lung cancer and 116 (29.3%) of 396 women agreed to a breast cancer chemoprevention trial. Randomization would not restrain participation (acceptability rate: 87.7% for lung cancer and 93.0% for breast cancer). In these volunteers, short-term trials (1 year) reached a high level of acceptability: 71.5% and 73.7% for lung and breast cancer prevention respectively. In contrast long-term trials (5 years or more) were far less acceptable: 9.2% for lung cancer (OR=7.7 CI(95%) 4.4-14.0) and 10.5 % for breast cancer (OR=6.9 CI(95%) 3.2-15.8). For lung cancer prevention, the route of administration impacts on acceptability with higher rate 53.1% for a pill vs. 7.9% for a spray (OR=6.7 CI(95%) 3.6-12.9). CONCLUSION: Overall healthy individuals are not keen to be involved in chemo-preventive trials, the design of which could however increase the acceptability rate.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.032
metaresearch head score (Gemma)0.104
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0320.104
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.805
GPT teacher head0.720
Teacher spread0.084 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations10
Published2008
Admission routes1
Has abstractyes

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