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Record W2152059213 · doi:10.1586/14779072.2014.954551

Alirocumab: PCSK9 inhibitor for LDL cholesterol reduction

2014· review· en· W2152059213 on OpenAlexaff
Hagai Tavori, M. Melone, Shirya Rashid

Bibliographic record

VenueExpert Review of Cardiovascular Therapy · 2014
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsDalhousie UniversityMcMaster UniversityThrombosis and Atherosclerosis Research Institute
Fundersnot available
KeywordsPCSK9AlirocumabMedicineEzetimibeLDL receptorProprotein convertaseKexinFamilial hypercholesterolemiaCholesterolEvolocumabInternal medicineEndocrinologyPharmacologyLipoprotein

Abstract

fetched live from OpenAlex

The proof of concept that proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibition affects cholesterol levels was first established after the demonstration that PCSK9 loss-of-function mutations result in a significant drop in circulating LDL cholesterol levels. Subsequent studies revealed that PCSK9 binds the epidermal growth factor precursor homology domain-A on the surface LDL Receptor (LDLR) and directs LDLR and PCSK9 for lysosomal degradation. Alirocumab (also known as SAR236553/REGN727) is a monoclonal antibody that binds circulating PCSK9 and blocks its interactions with surface LDLR. Alirocumab clinical trials with different doses on different administration schedules were shown to significantly reduce LDL cholesterol both as a mono-therapy and in combination with statins or ezetimibe. Although there is great potential for anti-PCSK9 therapies in the management of cholesterol metabolism, there is no clear evidence yet that blocking PCSK9 reduces cardiovascular disease outcome. This is being investigated in ongoing Phase III clinical trials with alirocumab.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.790
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0120.024
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.370
Teacher spread0.326 · 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

Citations22
Published2014
Admission routes1
Has abstractyes

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