Cost effectiveness analysis of a fixed dose combination pill for primary prevention of cardiovascular disease from an individual participant data meta-analysis
Bibliographic record
Abstract
Background: Cardiovascular disease (CVD) continues to impart a large burden on the global population, especially in lower income countries where affordability limits the use of cardiovascular medicines. A fixed dose combination strategy of at least 2 blood pressure lowering medications and a statin with aspirin in a single pill has been shown to reduce the risk of incident CVD by 38% in primary prevention in a recent meta-analysis. We report the in-trial (median follow-up: 5 years) cost-effectiveness of a fixed dose combination (FDC) pill in different income groups based on data from that meta-analysis. Methods: Countries were categorized using World Bank economic groups: Lower Middle Income Countries (LMIC), Upper Middle Income Countries (UMIC) and High Income Countries (HIC). Country specific costs were obtained for hospitalized events, procedures, and non-study medications (2020 USD). FDC price was based on the cheapest equivalent substitute (CES) for each component. Findings: For the CES-FDC pill versus control the difference in cost was $346 (95% CI: $294-$398) per participant in Lower Middle Income Countries, $838 (95% CI: $781-$895) in Upper Middle Income Countries and $42 (95% CI: -$155 to $239) (cost-neutral) in High Income Countries. During the study period the CES-FDC pill was associated with incremental gain in quality-adjusted life years of 0.06 (95% CI: 0.04-0.08) resulting in an incremental cost-effectiveness ratio (ICER) of $5767 (95% CI: 5735-$5799), $13,937 (95% CI: $13,893-$14,041) and $700 (95% CI: $662-$738) respectively. In subgroups analyses, the highest 10 years CVD risk subgroup had ICERs of $2033, $7322 and -$6000/QALY. Interpretation: A FDC pill produced at CES costs is cost-neutral in HIC. Governments of LMI and UMI countries should assess these results based on the ICER threshold accepted in their own country and own specific health care priorities but should consider prioritizing this strategy for patients with high 10 years CVD risk as a first step. Funding: Population Health Research Institute.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".