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Record W4381166389 · doi:10.3389/fcvm.2023.1206551

Regional differences in physicians’ behavior and factors influencing the intensity of PCSK9 inhibitor therapy with alirocumab: a subanalysis of the ODYSSEY APPRISE study

2023· article· en· W4381166389 on OpenAlexaboutno aff
Maciej Banach, Joanna Lewek, Kaja Pol, Daniel Rabczenko, Șerban Bălănescu, V. Bláha, R Češka, Piotr Jankowski, Stanisław Surma, Genovefa Kolovou, Evangelos Liberopoulos, Florin Mitu, Magda Mitu, Franjo Naji, György Paragh, Magdalena Popławska, Michal Vrablı́k, Daniel Pella

Bibliographic record

VenueFrontiers in Cardiovascular Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsnot available
FundersRegeneron PharmaceuticalsSanofi
KeywordsAlirocumabMedicinePCSK9Internal medicineDemographyTotal cholesterolLipoproteinCholesterol

Abstract

fetched live from OpenAlex

Background Despite better accessibility of the effective lipid-lowering therapies, only about 20% of patients at very high cardiovascular risk achieve the low-density lipoprotein cholesterol (LDL-C) goals. There is a large disparity between European countries with worse results observed for the Central and Eastern Europe (CEE) patients. One of the main reasons for this ineffectiveness is therapeutic inertia related to the limited access to appropriate therapy and suitable dosage intensity. Thus, we aimed to compare the differences in physicians’ therapeutic decisions on alirocumab dose selection, and factors affecting these in CEE countries vs. other countries included in the ODYSSEY APPRISE study. Methods ODYSSEY APPRISE was a prospective, single-arm, phase 3b open-label (≥12 weeks to ≤30 months) study with alirocumab. Patients received 75 or 150 mg of alirocumab every 2 weeks, with dose adjustment during the study based on physician's judgment. The CEE group in the study included Czechia, Greece, Hungary, Poland, Romania, Slovakia, and Slovenia, which we compared with the other nine European countries (Austria, Belgium, Denmark, Finland, France, Germany, Italy, Spain, and Switzerland) plus Canada. Results A total of 921 patients on alirocumab were involved [modified intention-to-treat (mITT) analysis], including 114 (12.4%) subjects from CEE countries. Therapy in CEE vs. other countries was numerically more frequently started with lower alirocumab dose (75 mg) at the first visit (74.6 vs. 68%, p = 0.16). Since week 36, the higher dose was predominantly used in CEE patients (150 mg dose in 51.6% patients), which was maintained by the end of the study. Altogether, alirocumab dose was significantly more often increased by CEE physicians (54.1 vs. 39.9%, p = 0.013). Therefore, more patients achieved LDL-C goal at the end of the study (<55 mg/dl/1.4 mmol/L and 50% reduction of LDL-C: 32.5% vs. 28.8%). The only factor significantly influencing the decision on dose of alirocumab was LDL-C level for both countries’ groups (CEE: 199.2 vs. 175.3 mg/dl; p = 0.019; other: 205.9 vs. 171.6 mg/dl; p < 0.001, for 150 and 75 mg of alirocumab, respectively) which was also confirmed in multivariable analysis (OR = 1.10; 95% CI: 1.07–1.13). Conclusions Despite larger unmet needs and regional disparities in LDL-C targets achievement in CEE countries, more physicians in this region tend to use the higher dose of alirocumab, they are more prone to increase the dose, which is associated with a higher proportion of patients reaching LDL-C goals. The only factor that significantly influences decision whether to increase or decrease the dose of alirocumab is LDL-C level.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.248
Teacher spread0.222 · 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 designObservational
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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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