Relating Lipoprotein(a) Concentrations to Cardiovascular Event Risk After Acute Coronary Syndrome: A Comparison of 3 Tests
Bibliographic record
Abstract
BACKGROUND: Lipoprotein(a) is a risk factor for cardiovascular events and modifies the benefit of PCSK9 (proprotein convertase subtilisin/kexin type 9) inhibitors. Lipoprotein(a) concentration can be measured with immunoassays reporting mass or molar concentration or a reference measurement system using mass spectrometry. Whether the relationships between lipoprotein(a) concentrations and cardiovascular events in a high-risk cohort differ across lipoprotein(a) methods is unknown. We compared the prognostic and predictive value of these types of lipoprotein(a) tests for major adverse cardiovascular events (MACE). METHODS: The ODYSSEY OUTCOMES trial (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) compared the PCSK9 inhibitor alirocumab with placebo in patients with recent acute coronary syndrome. We compared risk of a MACE in the placebo group and MACE risk reduction with alirocumab according to baseline lipoprotein(a) concentration measured by Siemens N-latex nephelometric immunoassay (IA-mass; mg/dL), Roche Tina-Quant turbidimetric immunoassay (IA-molar; nmol/L), and a noncommercial mass spectrometry–based test (MS; nmol/L). Lipoprotein(a) values were transformed into percentiles for comparative modeling. Natural cubic splines estimated continuous relationships between baseline lipoprotein(a) and outcomes in each treatment group. Event rates were also determined across baseline lipoprotein(a) quartiles defined by each assay. RESULTS: Among 11 970 trial participants with results from all 3 tests, baseline median (Q1, Q3) lipoprotein(a) concentrations were 21.8 (6.9, 60.0) mg/dL, 45.0 (13.2, 153.8) nmol/L, and 42.2 (14.3, 143.1) nmol/L for IA-mass, IA-molar, and MS, respectively. The strongest correlation was between IA-molar and MS (r=0.990), with nominally weaker correlations between IA-mass and MS (r=0.967) and IA-mass and IA-molar (r=0.972). Relationships of lipoprotein(a) with MACE risk in the placebo group were nearly identical with each test, with estimated cumulative incidences differing by ≤0.4% across lipoprotein(a) percentiles, and all were incrementally prognostic after accounting for low-density lipoprotein cholesterol levels (all spline P ≤0.0003). Predicted alirocumab treatment effects were also nearly identical for each of the 3 tests, with estimated treatment hazard ratios differing by ≤0.07 between tests across percentiles and nominally less relative risk reduction by alirocumab at lower percentiles for all 3 tests. Absolute risk reduction with alirocumab increased with increasing lipoprotein(a) measured by each test, with significant linear trends across quartiles. CONCLUSIONS: In patients with recent acute coronary syndrome, 3 lipoprotein(a) tests were similarly prognostic for MACE in the placebo group and predictive of MACE reductions with alirocumab at the cohort level. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01663402.
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 | 0.040 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".