The cost effectiveness of pharmacological smoking cessation therapies in developing countries: a case study in the Seychelles
Bibliographic record
Abstract
OBJECTIVE: To examine the incremental cost effectiveness of the five first line pharmacological smoking cessation therapies in the Seychelles and other developing countries. DESIGN: A Markov chain cohort simulation. SUBJECTS: Two simulated cohorts of smokers: (1) a reference cohort given physician counselling only; (2) a treatment cohort given counselling plus cessation therapy. INTERVENTION: Addition of each of the five pharmacological cessation therapies to physician provided smoking cessation counselling. MAIN OUTCOME MEASURES: Cost per life-year saved (LYS) associated with the five pharmacotherapies. Effectiveness expressed as odds ratios for quitting associated with pharmacotherapies. Costs based on the additional physician time required and retail prices of the medications. RESULTS: Based on prices for currently available generic medications on the global market, the incremental cost per LYS for a 45 year old in the Seychelles was 599 US dollars for gum and 227 dollars for bupropion. Assuming US treatment prices as a conservative estimate, the incremental cost per LYS was significantly higher, though still favourable in comparison to other common medical interventions: 3712 dollars for nicotine gum, 1982 dollars for nicotine patch, 4597 dollars for nicotine spray, 4291 dollars for nicotine inhaler, and 1324 dollars for bupropion. Cost per LYS increased significantly upon application of higher discount rates, which may be used to reflect relatively high opportunity costs for health expenditures in developing countries with highly constrained resources and high overall mortality. CONCLUSION: Pharmacological cessation therapy can be highly cost effective as compared to other common medical interventions in low mortality, middle income countries, particularly if medications can be procured at low prices.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".