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PharmacoEconomics

, Volume 36, Issue 9, pp 1101–1112 | Cite as

Smoking Cessation: A Comparison of Two Model Structures

  • Becky PenningtonEmail author
  • Alex Filby
  • Lesley Owen
  • Matthew Taylor
Original Research Article

Abstract

Background

Most economic evaluations of smoking cessation interventions have used cohort state-transition models. Discrete event simulations (DESs) have been proposed as a superior approach.

Objective

We developed a state-transition model and a DES using the discretely integrated condition event (DICE) framework and compared the cost-effectiveness results. We performed scenario analysis using the DES to explore the impact of alternative assumptions.

Methods

The models estimated the costs and quality-adjusted life years (QALYs) for the intervention and comparator from the perspective of the UK National Health Service and Personal Social Services over a lifetime horizon. The models considered five comorbidities: chronic obstructive pulmonary disease, myocardial infarction, coronary heart disease, stroke and lung cancer. The state-transition model used prevalence data, and the DES used incidence. The costs and utility inputs were the same between two models and consistent with those used in previous analyses for the National Institute for Health and Care Excellence.

Results

In the state-transition model, the intervention produced an additional 0.16 QALYs at a cost of £540, leading to an incremental cost-effectiveness ratio (ICER) of £3438. The comparable DES scenario produced an ICER of £5577. The ICER for the DES increased to £18,354 when long-term relapse was included.

Conclusions

The model structures themselves did not influence smoking cessation cost-effectiveness results, but long-term assumptions did. When there is variation in long-term predictions between interventions, economic models need a structure that can reflect this.

Notes

Data Availability Statement

Both economic models are available to reviewers, subject to signing relevant forms. To request access to the Markov model, please contact NICE (SmokingCessationServices@nice.org.uk) with details of your request and attach the completed confidentiality form (https://www.nice.org.uk/get-involved/stakeholder-registration/confidentiality-agreement). To request access to the DES, please email the corresponding author.

Author Contributions

AF identified inputs for and built the Markov model, with support from MT. LO advised on the design of and inputs to the Markov model, and quality assured the final version of the model. BP identified additional inputs for and built the DES. BP wrote the first draft of this manuscript, and all co-authors reviewed and suggested changes. All authors reviewed and approved the final draft.

Compliance with Ethical Standards

Funding

When this work was undertaken, Becky Pennington and Lesley Owen were employed by the NICE. Alex Filby and Matthew Taylor were employed by York Health Economics Consortium, who received payment from the NICE to build the state-transition model. The DICE simulation framework shell was made available by Evidera. Authors received no funding from Evidera.

Conflict of interest

Becky Pennington reports no conflicts of interest. Lesley Owen reports no conflicts of interest. Alex Filby reports no conflicts of interest. Matthew Taylor reports no conflicts of interest

Supplementary material

40273_2018_657_MOESM1_ESM.docx (13 kb)
Supplementary material 1 (DOCX 13 kb)

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Health and Related ResearchUniversity of SheffieldSheffieldUK
  2. 2.National Institute for Health and Care ExcellenceLondonUK
  3. 3.York Health Economics Consortium, Enterprise HouseUniversity of YorkYorkUK

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