PP168 Combination Therapy Versus Intensification Of Statin Monotherapy
Bibliographic record
Abstract
INTRODUCTION: Coronary heart disease (CHD) is the most common cause of mortality globally. The burden of CHD is a challenge for Tunisia causing 27.14 percent of total mortality (1). Statins are the leading molecules used to prevent CHD in Tunisia. The amount paid by the national insurance fund for statins in 2015 represents 9 percent of total drug expenditures (2). INASanté has launched a Health Technology Assessment (HTA) study to compare the intensification of statin monotherapy versus a combination therapy for the CHD prevention in patients with moderate to high cardiovascular risk. The aim of this contextualized HTA report is to diminish prescription variability and not justified therapies. METHODS: Research was carried out in the following databases: CRD, NICE search evidence, Cochrane, Belgian Health Care Knowledge Centre (KCE), Canadian Agency for Drugs and Technologies in Health (CADTH), Adelaide Health Technology Assessment (AHTA), Institut National d'excellence En Santé et en Services Sociaux (INESS), Euroscan International Network, National Institute for Health Research (NIHR), Agency for Healthcare Research and Quality (AHRQ) and Haute Autorité de Santé (HAS) from 2006 to 2017. Title, abstract and full text screening were performed by two independent reviewers relying on prespecified eligibility criteria. Critical appraisal of literature was conducted using INAHTA and PRISMA checklists, FLC 2.0 and The European Network for HTA (EUnetHTA) adaptation toolkit. One review from AHRQ was retained. An adaptation process has been launched. Data on lipid lowering agents intake from key institutions have been gathered and a qualitative study has been started through interviews with thirty-three cardiologists and general practitioners from public, private sector and scientifc societies. Interviews have been analysed using NVivo. After results discussion with the working group, the report will be synthesized and validated. RESULTS: According to the AHRQ report, all evidence for clinical outcomes were graded insufficient when comparing the therapies. Results on lowering low density lipoprotein (LDL-C) depend on the combination agent Ezetimibe has shown remarkable results (3). The Tunisian context shows that there is no standardized method to assess the cardiovascular risk according to the preliminary results. The only combination therapy reported is with fibrates, mainly in case of associated hypertriglyceridemia. Ezetimibe has not yet obtained the marketing authorization. CONCLUSIONS: There are significant differences between contexts and among practitioners prescriptions. This can be related to the lack of common guidelines and inequitable access to drugs and healthcare resources in general.
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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 | 0.021 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.002 |
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".