The research team, led by analysts at the York Health Economics Consortium and clinicians at Manchester University NHS Foundation Trust, built a cost-effectiveness model aligned with the National Institute for Health and Care Excellence reference case. They simulated four distinct patient populations: people with early-stage lung cancer (stages 1 to 3a), people with late-stage head and neck cancer (stages 3 and 4), people with kidney cancer at any stage, and an exploratory general cancer population mixing several diagnoses. In every population examined, offering cessation support at diagnosis proved cost effective against the standard threshold of £20,000 per quality-adjusted life year, or QALY, gained.

The technical machinery behind the analysis is considerable. The model tracked a cohort of adults aged 18 and over who had recently been diagnosed with cancer and currently smoked, splitting them into those who quit and those who continued based on natural quit rates, service uptake, and five-year relapse rates. Each group then moved through a partitioned survival model with three health states: progression-free disease, progressed disease, and death. Survival trajectories were derived from published Kaplan–Meier curves, which the team digitised and converted into pseudo-individual participant data using the Guyot algorithm, before fitting six standard parametric distributions — exponential, Weibull, Gompertz, log-normal, log-logistic, and generalised gamma — to extrapolate long-term overall and progression-free survival beyond the observed follow-up periods.

Beyond cancer itself, the model accounted for seven smoking-related comorbidities: chronic obstructive pulmonary disease, coronary heart disease, myocardial infarction, type 2 diabetes, stroke, dementia, and asthma. Age- and gender-specific prevalence estimates for non-smokers were multiplied by smoking-status relative risks to generate weighted comorbidity risks for quitters and continuing smokers alike. Costs and QALYs were discounted at 3.5 percent per annum over a lifetime horizon — 25 years for the lung cancer cohort and 30 years for the others — with monthly cycles capturing clinical events, treatment costs, and health-related quality of life.

The headline numbers are striking in their asymmetry. In the lung cancer population, median time to death rose from 4.08 to 4.25 years, at an incremental cost of just £292 per person, yielding an incremental cost-effectiveness ratio of £2,606 per QALY. For head and neck cancer, median survival improved by four months at an additional £1,074 per person, an ICER of £5,495. Kidney cancer delivered the most emphatic result: the intervention was dominant, meaning it both saved money — £189 per person — and added 0.45 QALYs, driven by reduced spending on second-line treatment and end-of-life care. The general cancer population gained 0.10 QALYs at £392 extra per person, an ICER of £4,055.

Probabilistic sensitivity analysis, run across 1,000 iterations, reinforced confidence in these findings. Smoking cessation at diagnosis remained cost effective in 99.70 percent of iterations for lung cancer, 99.90 percent for head and neck cancer, 100 percent for kidney cancer, and 97.80 percent for the general cancer population. In the kidney cancer scenario, the intervention was outright dominant — cheaper and better — in 70.40 percent of simulations. Threshold analyses identified the boundaries of the result: the intervention stops being cost effective only if uptake falls below roughly 12 to 14 percent, or if the per-person implementation cost climbs above £2,000 to £6,600 depending on the population. Both boundaries sit comfortably away from realistic estimates, since uptake of cessation support offered during lung cancer screening in the UK has been measured at around 74 percent.

The biological rationale for the survival gains is well established. Smoking during treatment impairs overall survival, raises cancer-specific mortality, and increases treatment-related complications such as surgical site infections and pulmonary problems after surgery. Tobacco alters the biological characteristics of cancer cells and speeds the metabolism of anticancer drugs, meaning chemotherapeutic agents are cleared faster in smokers. Conversely, quitting after diagnosis has been shown in prospective cohort studies to reduce the risk of progression, cancer-specific death, and all-cause mortality compared with continued smoking. The model’s assumption that treatments themselves do not differ by smoking status is therefore conservative, since patients who quit may in fact be eligible for more treatment options, including surgery.

Scaled across the population, the implications are substantial. Around 57,000 cases of cancer are attributed to smoking in the UK each year, and the authors estimate that rolling out cessation services at diagnosis could generate a net monetary benefit upwards of £88 million based on the general cancer population. The cost of the cessation package itself — an estimated £257 per person, including an e-consultation proxy cost of £45.98 to cover NHS system restructuring and the pharmacological and behavioural treatments — represents between 0.34 and 0.53 percent of the total costs the NHS incurs during cancer care. By comparison, NICE-recommended immunotherapies such as durvalumab for limited-stage small cell lung cancer cost an estimated £141,335 per person, and nivolumab for head and neck cancer around £31,693.

The study is not without limitations, and the authors are candid about them. Survival data for the lung and kidney cancer populations came from a Russian cohort, an assumption judged reasonable by consulting oncologists who found no genetic or population characteristics that would materially alter outcomes in a UK setting. The Kaplan–Meier studies were predominantly male — roughly 80 percent across the three cancer-specific populations, against 50 to 70 percent in the wider cancer population — and natural quit rates and relapse rates were drawn from non-cancer populations due to data scarcity. The general cancer analysis required averaging costs and utilities across tumour types, and the authors caution that its results should be treated as exploratory. Several assumptions, such as equal relapse rates in each year after the first and identical treatment regardless of smoking status, deliberately bias the model against the intervention.

Beyond the immediate clinical economics, the findings carry broader significance. Tobacco smoking remains the largest single cause of health inequalities in England, and cancer mortality is almost 60 percent higher in the most deprived areas compared with the least; prior distributional cost-effectiveness work suggests cessation interventions reduce absolute health inequality. Reducing smoking would also cut second-hand smoke exposure, which is linked to ischaemic heart disease, COPD, respiratory infections, and stroke. The authors note that embedding cessation at diagnosis aligns squarely with the NHS 10-year plan’s stated shift from treating sickness to preventing it, and that effective first-line cancer treatment in non-smokers should reduce demand for costly second-line care. The remaining challenge, they conclude, is practical: delivering integrated services will require initial investment in staff and capacity, and policymakers must weigh rollout against the demonstrated value for money that this analysis makes abundantly clear.

Subject of Research: Cost-effectiveness of integrating smoking cessation services into NHS cancer care pathways in England

Article Title: Economic and health impact of integrating smoking cessation services into NHS cancer care pathways in England: a modelling study

Article References: Green, M., Harper, S., Telfer-Thomas, E., Agrawal, S., Callister, M. E., Lane, J. L., Warren, G., Murray, R. L., Evison, M., Sheikh, M., & Malcolm, R. (2026). Economic and health impact of integrating smoking cessation services into NHS cancer care pathways in England: a modelling study. The Lancet Regional Health – Europe, 71, Article 101869. https://doi.org/10.1016/j.lanepe.2026.101869

Image Credits: AI Generated

DOI: 10.1016/j.lanepe.2026.101869

Keywords: smoking cessation, cancer care, cost-effectiveness, NHS, health economics, QALY, lung cancer, head and neck cancer, kidney cancer, tobacco, modelling study, health inequalities