Current Phase II proprotein convertase subtilisin/kexin 9 inhibitor therapies for dyslipidemia
Bibliographic record
Abstract
INTRODUCTION: Reduction of plasma low-density lipoprotein (LDL) cholesterol concentration with statins reduces adverse cardiovascular outcomes. However, lack of efficacy and intolerance of statins in many patients requires alternative treatments. Currently available non-statin alternatives include bile acid sequestrants, the cholesterol absorption inhibitor ezetimibe, niacin-based preparations and fibrates; however, each of these has limitations. Newer agents for LDL cholesterol reduction include the cholesterol ester transfer protein inhibitors, the microsomal triglyceride transfer protein inhibitor lomitapide, the apolipoprotein B antisense oligonucleotide mipomersen and several molecules that inhibit or interfere with proprotein convertase subtilisin/kexin 9 (PCSK9). AREAS COVERED: Among the various PCSK9 inhibitors, human data are available for monoclonal antibodies against PCSK9 of which the two most advanced are alirocumab (SAR236553/REGN727) and AMG 145. Phase II studies of these agents as monotherapy or in combination with statins have shown reductions of LDL cholesterol by > 70%, with acceptable safety and tolerability so far. EXPERT OPINION: Despite their biochemical efficacy, clinical efficacy, reflected by reduction of cardiovascular end points, remains to be shown for two leading monoclonal antibodies against PSCK9. Other issues to be evaluated with these agents over the longer term include development of rare adverse effects and potential attenuation of efficacy.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".