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BACKGROUND AND AIMS: Long-term strong opioid use for chronic non-malignant pain (CNMP) represents a significant public health challenge, associated with reduced health-related quality of life (HRQoL) and increased mortality. The Improving the Wellbeing of people with Opioid Treated CHronic pain (I-WOTCH) trial demonstrated that a multicomponent intervention supporting opioid withdrawal in people with CNMP successfully reduced opioid consumption compared with best usual care (BUC), without adversely affecting perceived pain levels. This study aimed to assess the value-for-money of the strategies tested in the I-WOTCH trial, from the perspective of the United Kingdom National Health Service (NHS) and Personal and Social Services.
DESIGN, SETTING AND PARTICIPANTS: Within-trial cost-consequence (CCA) and model-based cost-effectiveness analyses (CEA), over one year and lifetime horizons, respectively. Data were sourced from the I-WOTCH trial, which recruited 608 participants from 191 primary care centres in England between May 2017 and January 2019 and followed them up for up to 12 months. Participants received either BUC or 3 group sessions (lasting one day each) led by a trained intervention nurse and by a lay person with CNMP and lived experience with opioid tapering. These sessions, designed to develop self-management skills, were supplemented by ongoing one-to-one support from nursing and lay personnel during follow-up. We used a probabilistic state-transition model to predict expected quality-adjusted life years (QALYs) and costs (in UK £) of each strategy over the lifetime of an individual. Model input parameters were derived mostly from the I-WOTCH trial. Opioid-related excess mortality and fracture rates were extracted from the literature.
MEASUREMENTS: Individual-level healthcare resource use and generic HRQoL [measured using the EuroQOL five dimensions questionnaire (Equation 5D)] were collected at baseline, 4, 8 and 12 months, and analysed to estimate total costs and health consequences for the I-WOTCH and BUC groups.
FINDINGS: I-WOTCH had higher costs and similar HRQoL outcomes compared with BUC at 12 months. When accounting for long-term reductions in mortality and morbidity from decreased exposure to strong opioids, our long-term model predicted I-WOTCH to yield higher costs and higher QALYs than BUC over the patient's lifetime, resulting in a base case incremental cost-effectiveness ratio of £29 543/QALY (2019 prices). Results were sensitive to structural assumptions in the model (i.e. cohort starting age, treatment effect weaning rate). Our probabilistic sensitivity analysis found I-WOTCH to have a 50% probability of being cost-effective compared with BUC for willingness-to-pay thresholds ranging between 0 and £100 000/QALY.
CONCLUSIONS: The Improving the Wellbeing of people with Opioid Treated CHronic pain intervention supporting opioid withdrawal in people with chronic non-malignant pain appears to be cost-effective on average, but further research is warranted to reduce current levels of decision uncertainty.
Systematic reviews of health economic evaluations (SR-HEEs) are perceived as mandatory components of the health technology assessment (HTA) process in many jurisdictions. However, HTA agencies vary in how they prescribe reviews of HEEs should be conducted and the explicit purpose they serve. This article identifies the requirements of prominent HTA agencies, reports on the real-world conduct of SR-HEEs by health technology developers (HTDs), and explores their utility in the HTA process. International HTA guidelines were consulted, alongside a targeted review of SR-HEEs submitted to the National Institute for Health and Care Excellence (NICE) in 2024. While a systematic approach is a constant requirement to reviews of HEEs, it is defined inconsistently across agencies, with clinical and safety systematic reviews (SRs) receiving more rigid prescription. Consequently, SR-HEEs submitted to NICE demonstrated mixed methods. Despite these pragmatic deviations of SR-HEEs, External Assessment Groups (EAGs) raised no major concerns, and reimbursement decisions do not appear to be influenced. Our findings suggest a rigor gap between SR theory and practice, driven by the inherent heterogeneity of economic models, which renders quantitative pooling inappropriate. We submit that a more pragmatic approach to reviews of HEEs would be appropriate for HTA. To maximize utility and reduce resource waste, we propose a two-stage framework: early pragmatic “landscape mapping” to inform early model conceptualization, followed by a formal SR-HEE only when a specific useful research question is identified. This strategic realignment, possibly supported by emerging technologies, would enable HTA resources to be reallocated toward higher-value activities.
We have read with great interest the published network meta-analysis (NMA) by Wang et al. (2026) in Frontiers in Endocrinology, which synthesised available randomised controlled trial (RCT) evidence to evaluate the relative efficacy and safety of rearranged during transfection (RET)-targeted agents for the treatment of advanced medullary thyroid cancer (MTC) (1). Through a comprehensive systematic literature review and NMA, their study provides relative effect estimates comparing RET-targeted agents, addressing a critical evidence gap due to the lack of direct evidence. Five studies were included in the NMA: ZETA (vandetanib) (2), EXAM (cabozantinib) (3), ALTER01031 (anlotinib) (4), LIBRETTO-531 (selpercatinib) (5), and EORTC-1209 (nintedanib) (6). All studies used placebo as the control arm except LIBRETTO-531, which used physician’s choice of cabozantinib or vandetanib. It should be noted that the publication incorrectly references the phase 1–2 LIBRETTO-001 trial instead of the phase 3 LIBRETTO-531 trial (reference 13 in Section 2.6.2 of the original publication). While the study demonstrated that selpercatinib exhibits superior efficacy, in terms of progression-free survival (PFS) and objective response rate (ORR), and a more favourable safety profile compared with other RET-targeted agents for advanced MTC, there are some important points for consideration that may affect the interpretation of the results. However, it should be noted that we did not reperform the NMA as part of this commentary, and the points we raise are methodological rather than quantifying their impact on the derived treatment effect estimates.
Firstly, in four of the five studies included, eligible patients were required to have documented disease progression. However, this criterion was not required in the ZETA trial (2). Differences in the median PFS in the placebo arms across trials, derived from observed Kaplan-Meier plots, suggest that patients included in the ZETA trial were healthier than patients enrolled in other trials where disease progression was an eligibility criterion (Table 1). If disease progression is a treatment effect modifier, this will introduce bias and violate the assumption of transitivity in the NMA. Therefore, it could be argued that the patients from the ZETA trial included in the current analysis represent a different treatment population compared to the other studies included in the analysis. However, it should be noted that despite these potential differences in population, the NMA-derived PFS treatment effect for cabozantinib versus vandetanib was not statistically significantly different (HR 0.61; 95% CI 0.35 to 1.05).
BACKGROUND: Research has shown that smoking post-diagnosis negatively impacts cancer outcomes. This study aimed to assess the health and cost impacts of introducing smoking cessation services at cancer diagnosis for people who smoke.
METHODS: A cost-effectiveness model was developed using a UK National Health Service (NHS) and Personal Social Services perspective. A partitioned survival model was built and survival analysis was used to estimate the proportion of the cohort in each health state (progression-free, progressed and dead) based on smoking status. Four populations were explored: lung cancer (stage 1–3a), head and neck cancer (stage 3–4), kidney cancer, and general cancer.
FINDINGS: Over a lifetime time horizon, offering smoking cessation at diagnosis resulted in an incremental cost-effectiveness ratio of £2606, £5495 and £4055 per quality-adjusted life-year (QALY), for lung, head and neck, and general cancer, respectively. The intervention was dominant for kidney cancer. Offering smoking cessation extended life by 2–8 months and slowed cancer progression by 2–6 months.
INTERPRETATION: This analysis indicates that implementing smoking cessation into NHS cancer care is cost effective at a £20,000 per QALY willingness-to-pay threshold, and provides large health benefits. Smoking cessation aligns with the NHS 10-year plan to move from treating sickness to preventing illnesses.
OBJECTIVE: We aimed to assess the carbon footprint and clinical outcomes of once-weekly semaglutide in people with overweight or obesity in the UK using a disease modelling approach.
METHODS: A per-patient carbon footprint analysis was conducted to estimate emissions related to obesity management with semaglutide 2.4 mg as an add on to diet and exercise versus diet and exercise alone. A Markov state-transition cohort model (Core Obesity Model) was used for the analysis. Data were sourced from STEP and SELECT trials across three populations: (1) body mass index [BMI] ≥ 30 or ≥ 27 with one or more obesity-related complications (BMI30+/BMI27+C), (2) BMI ≥ 27 with one or more complications, including type 2 diabetes mellitus (BMI27+C), and (3) BMI ≥ 27 with established cardiovascular disease (BMI27+CVD). Carbon emissions were estimated using resource-based and cost-based methods. Key outcomes included life-years, quality-adjusted life-years, and incremental carbon footprint effectiveness ratio.
RESULTS: In the BMI30+/BMI27+C and BMI27+C populations, semaglutide was dominant, yielding 0.30 and 0.25 additional life-years, 0.51 and 0.46 additional quality-adjusted life-years, while reducing lifetime carbon emissions by 1.8% (9850 vs 10,030 kg of CO2 equivalent [CO2e]) and 1.9% (9792 vs 9983 kg CO2e), respectively. Manufacturing emissions of semaglutide were offset by reductions in carbon emissions resulting from fewer obesity-related complications. In the BMI27+CVD population, semaglutide improved life-years by 0.56 and quality-adjusted life-years by 0.59, but emissions increased (14,700 vs 14,444 kg CO2e) because of longer survival and increased monitoring. Scenario and sensitivity analyses confirmed the robustness of the results.
CONCLUSIONS: Semaglutide offers both clinical and environmental benefits in obesity management, supporting the UK’s net-zero emissions goals.
BACKGROUND: Interpreting meaningful change in patient-reported outcome measures (PROMs) is essential for assessing hip replacement outcomes. The Oxford Hip Score (OHS) is widely used, yet statistically detectable change may not align with patient-perceived improvement.
OBJECTIVES: To compare Rasch-based classifications of OHS change, following Hobart’s effect size methodology, with anchor-based interpretations derived from patient Global Impression of Change (GIC).
METHODS: OHS data from a large hip replacement cohort (N = 184,509) were analysed using two complementary approaches. Rasch analysis transformed ordinal scores into interval-level person measures, and effect sizes with confidence intervals classified patients as significantly improved, non-significantly improved, unchanged, or worse. MIC was estimated using a five-point patient GIC. Median pre-operative, post-operative, and change scores were summarised per category.
RESULTS: Both methods demonstrated graded outcome patterns. Concordance was strongest for large improvements, with statistically significant change closely matching reports of being “much better.” Divergence occurred for modest improvement and worsening: patients often reported little or no benefit despite measurable OHS improvement.
CONCLUSIONS: Rasch-based and anchor-based approaches capture overlapping but distinct constructs. Integrating both provides a nuanced interpretation of PROM change after hip replacement.
Missing Health-Related Quality of Life (HRQoL) data in clinical studies risk propagating bias into health technology assessments (HTAs) and cost-utility analyses. Despite this, current National Institute for Health and Care Excellence (NICE) guidance offers no specific recommendations for handling missing HRQoL values. Using Monte Carlo simulations (1000 datasets), this study evaluated nine imputation methods, across the missing completely at random (MCAR), missing at random (MAR) and missing not at random (MNAR) assumptions at levels ranging from 5% to 50%. Performance was assessed using bias, variance, and coverage of the true HRQoL mean. While multiple imputation by chained equations (MICE)-based approaches performed best under MCAR and MAR, all methods showed bias under MNAR, with a delta-pattern mixture model performing the best (relative bias ≤2.1% at all missingness levels but coverage falls to 35.4% at 50% missingness). The choice of imputation method is key to preventing biased results from propagating into cost-effectiveness analysis, which in theory may lead to suboptimal reimbursement decisions and inefficient healthcare spending. To address the lack of explicit guidance from HTA bodies, we have developed a preliminary policy that could be used for HTA submissions: If the missingness pattern is not known and missingness ≤5%, it is suggested that most methods (except GLM) are acceptable (though care should be taken when using CCA and LOCF if MNAR is suspected). It is also suggested that MICE-based techniques are used as the base case for missingness >5%, and delta-PMM used as a sensitivity analysis when data are not MCAR. Further simulation studies would be required to strengthen the suggestions in this preliminary policy; however, the development of universal recommendations would lead to improved consistency and reliability of HTA globally.
