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Surrogate endpoints and emerging surrogate endpoints for risk reduction of cardiovascular disease

2008· review· en· W1584844577 on OpenAlexaffabout
Crystal M Rasnake, Paula R. Trumbo, Therèse Heinonen

Bibliographic record

VenueNutrition Reviews · 2008
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsSurrogate endpointMedicineDiseaseIntensive care medicineClinical endpointFood and drug administrationInternal medicineClinical trialPharmacology

Abstract

fetched live from OpenAlex

This article reviews surrogate endpoints and emerging biomarkers that were discussed at the annual "Cardiovascular Biomarkers and Surrogate Endpoints" symposium cosponsored by the US Food and Drug Administration (FDA) and the Montreal Heart Institute. The FDA's Center for Food Safety and Applied Nutrition (CFSAN) uses surrogate endpoints in its scientific review of a substance/disease relationship for a health claim. CFSAN currently recognizes three validated surrogate endpoints: blood pressure, blood total cholesterol, and blood low-density lipoprotein (LDL) concentration in its review of a health claim for cardiovascular disease (CVD). Numerous potential surrogate endpoints of CVD are being evaluated as the pathophysiology of heart disease is becoming better understood. However, these emerging biomarkers need to be validated as surrogate endpoints before they are used by CFSAN in the evaluation of a CVD health claim.

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)0.017
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.930
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.441
GPT teacher head0.452
Teacher spread0.010 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
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

Citations17
Published2008
Admission routes2
Has abstractyes

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