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Record W2981502437 · doi:10.1093/eurheartj/ehz746.0015

4945Inclisiran-mediated reductions in Lp(a) in the ORION-1 trial

2019· article· en· W2981502437 on OpenAlexaff
Robert M. Stoekenbroek, Kausik K. Ray, Ulf Landmesser, L. A. Leiter, R. Scott Wright, P. Wijngaard, David Kallend, John J.P. Kastelein

Bibliographic record

VenueEuropean Heart Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicinePCSK9LDL receptorInternal medicineStatinGastroenterologyEndocrinologyCholesterolLipoprotein

Abstract

fetched live from OpenAlex

Abstract Background PCSK9 inhibitors and statins both lower LDL-C by increasing LDL-receptor (LDLR) function. PCSK9 inhibitors lower Lp(a) by 20–30%, whereas statins do not lower Lp(a). The mechanism by which PCSK9 inhibitors lower Lp(a) is unclear. We assessed the role of the LDLR in Lp(a) reductions produced by inclisiran, an siRNA which prevents hepatic synthesis of PCSK9. Methods ORION-1 was a phase 2 trial of inclisiran in subjects at high ASCVD risk with elevated LDL-C on optimized statin therapy. Subjects received one dose of inclisiran (200, 300, or 500 mg) or two doses at days 1 and 90 (100, 200, or 300 mg). We assessed the correlations between % change in Lp(a) and LDL-C at Day 180 for the inclisiran groups using Spearman correlation coefficients. We additionally assessed the correlation between % change in Lp(a) and absolute change in LDL-C as a proxy for LDLR expression. Lp(a) was measured using an isoform-independent assay and LDL-C with β-quantification. Results ORION-1 included 501 subjects; mean age 63; 65% male; 73% on statins. Median baseline Lp(a) was 37.0 nmol/l (IQR: 11.5–142.0 nmol/l), median LDL-C was 117.0 (IQR: 92.5–149.5 mg/dL). Inclisiran dose-dependently lowered Lp(a) by 14% to 26%. Overall, there was a significant but weak correlation between % change in Lp(a) LDL-C (Spearman coefficient 0.35, p<0.001). This correlation appeared to be stronger at higher inclisiran doses and with repeat dosing (table), as well as in statin-users versus non-users (Spearman coefficient 0.37 vs. 0.21). The correlation between % Lp(a) change and absolute LDL-C change was weaker (0.27, p<0.001). Correlation coefficients LDL-C – Lp(a) Single-dose groups Two-dose groups Inclisiran overall 200 mg (n=60) 300 mg (n=60) 500 mg (n=60) 100 mg (n=59) 200 mg (n=60) 300 mg (n=59) Lp(a) ∼ % change LDL-C 0.22 0.26 0.22 0.29 0.47 0.51 0.35 Lp(a) ∼ absolute change LDL-C 0.35 0.12 0.04 0.22 0.45 0.24 0.27 Lp(a) ∼ % change LDL-C - Statin users 0.16 0.28 0.28 0.31 0.45 0.55 0.37 Lp(a) ∼ % change LDL-C - Non statin users 0.80 -0.08 0.09 0.10 0.63 0.09 0.21 Conclusion The dose-dependent correlation between % changes in LDL-C and Lp(a) suggests that the LDLR may be partially responsible for Lp(a) reductions produced by inclisiran. The numerically stronger correlation in statin-users supports the idea that LDL-C may compete with Lp(a) for LDLR binding especially at low LDL-C levels. Acknowledgement/Funding The Medicines Company

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.041
GPT teacher head0.310
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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".

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Citations5
Published2019
Admission routes1
Has abstractyes

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