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Record W2470369710 · doi:10.1093/ehjqcco/qcw037

Scientific, societal, and economic consequences of releasing interim data from clinical trials

2016· editorial· en· W2470369710 on OpenAlexaff
Abhinav Sharma, Robert Bigelow, Michael Pencina

Bibliographic record

VenueEuropean Heart Journal - Quality of Care and Clinical Outcomes · 2016
Typeeditorial
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInterimClinical trialPolitical sciencePsychologyPositive economicsEconomicsMedicineLaw

Abstract

fetched live from OpenAlex

When interim clinical trial data are released, vigorous discussion frequently ensues, either supporting or lamenting the decision. Two recent early terminations of clinical trials in obesity and hypertension opened heated discussions about the scientific, societal, and economic consequences of prematurely stopping on-going studies and releasing interim clinical trial data. The Cardiovascular Outcomes Study of Naltrexone SR/Bupropion SR in Overweight and Obese Subjects with Cardiovascular Risk Factors (LIGHT Study), sponsored by Orexigen and Takeda (https://clinicaltrials.gov/ct2/show/[NCT01601704][1]?term=contraver patients were to be enrolled on treatment for 3–4 years. The release of this information was not authorized by the trial executive steering committee or the independent data monitoring committee (IDMC) and violated the FDA confidentiality terms of agreement. When 50% of MACE events occurred, the cardiovascular benefit seen earlier was gone (HR 0.88, 95% CI 0.66–1.17). The trial steering committee halted the study, and the FDA required a second trial to be conducted (http://my.clevelandclinic.org/about-cleveland-clinic/newsroom/releases-videos-newsletters/2015-5-12-clinical-trial-testing-safety-of-obesity-drug-contrave-halted (accessed 17 May 2016)). The Systolic Blood Pressure Intervention Trial (SPRINT)—sponsored by the National Heart, Lung, and Blood Institute (NHLBI)—was an open label randomized … [↵][2]*Corresponding author. Tel: +1 919 668 8580, Email: as684{at}duke.edu [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT01601704&atom=%2Fehjqcco%2F3%2F1%2F9.atom [2]: #xref-corresp-1-1

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)0.575
metaresearch head score (Gemma)0.618
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.260
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.5750.618
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0160.008
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0020.001
Open science0.0040.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.938
GPT teacher head0.715
Teacher spread0.223 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations1
Published2016
Admission routes1
Has abstractyes

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