Health economic model to evaluate the cost-effectiveness of smoking cessation services integrated within lung cancer screening
Notice bibliographique
Résumé
ABSTRACT Introduction Integrating smoking cessation support into lung cancer screening can improve abstinence rates. However, healthcare decision makers need evidence of cost effectiveness to understand the cost/benefit of adopting this approach. Methods To evaluate the cost-effectiveness of different smoking cessation interventions, and service delivery, we used a Markov model, adapted from previous National Institute for Health and Care Excellence guidelines on smoking cessation. This uses long-term epidemiological data to capture the prevalence of the smoking-related illnesses, where prevalence is estimated based on age, sex, and smoking status. Probabilistic sensitivity analysis was conducted to capture joint parameter uncertainty. Results All smoking cessation interventions appeared cost-effective at a threshold of £20,000 per quality-adjusted life year, compared to no intervention or behavioural support alone. Offering immediate smoking cessation as part of lung cancer screening appointments, compared with usual care (onward referral to stop smoking services) was also estimated to be cost-effective with a net monetary benefit of £2,198 per person, and a saving of between £34 and £79 per person in reduced workplace absenteeism among working age attendees. Estimated healthcare cost savings were more than four times greater in the most deprived quintile compared to the least deprived, alongside a fivefold increase in QALYs accrued. Conclusions Smoking cessation interventions within lung cancer screening are cost-effective and should be integrated so that treatment is initiated during screening visits. This is likely to reduce overall costs to the health service, and wider integrated care systems, improve quality and length of life, and may lessen health inequalities. Key messages What is already known on this topic? Smoking cessation interventions are known to be cost-effective in general. However, their cost-effectiveness specifically within lung cancer screening programmes, where they are not routinely commissioned, remains to be established. What this study adds This health economic analysis estimates that offering smoking cessation immediately within a lung cancer screening visits is a cost-effective intervention, with a substantial return on investment for the healthcare service, alongside a reduction in health inequalities and an increase in productivity for the wider economy. How this study might affect research, practice or policy This economic evaluation will provide those commissioning and planning healthcare services with evidence that supports the case for funding smoking cessation services integrated within lung cancer screening programmes as immediate, opt-out services.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».