Cost-effectiveness of acceptance and commitment therapy for people living with motor neuron disease, and their health-related quality of life.

BACKGROUND: Given the degenerative nature of the condition, people living with motor neuron disease (MND) experience high levels of psychological distress. The purpose of this research was to investigate the cost-effectiveness of acceptance and commitment therapy (ACT), adapted for the specific needs of this population, for improving quality of life. METHODS: A trial-based cost-utility analysis over a 9-month period was conducted comparing ACT plus usual care (n = 97) versus usual care alone (n = 94) from the perspective of the National Health Service. In the primary analysis, quality-adjusted life years (QALYs) were computed using health utilities generated from the EQ-5D-5L questionnaire. Sensitivity analyses and subgroup analyses were also carried out. RESULTS: Difference in costs was statistically significant between the two arms, driven mainly by the intervention costs. Effects measured by EQ-5D-5L were not statistically significantly different between the two arms. The incremental cost-effectiveness was above the £20,000 to £30,000 per QALY gained threshold used in the UK. However, the difference in effects was statistically significant when measured by the McGill Quality of Life-Revised (MQOL-R) questionnaire. The intervention was cost-effective in a subgroup experiencing medium deterioration in motor neuron symptoms. CONCLUSIONS: Despite the intervention being cost-ineffective in the primary analysis, the significant difference in the effects measured by MQOL-R, the low costs of the intervention, the results in the subgroup analysis, and the fact that ACT was shown to improve the quality of life for people living with MND, suggest that ACT could be incorporated into MND clinical services.

A model-based economic analysis of the CFHealthHub intervention to support adherence to inhaled medications for people with cystic fibrosis in the UK.

BACKGROUND: Adherence to preventative inhaled therapies in people with cystic fibrosis (CF) is low, resulting in potentially avoidable health losses and the need for costly rescue therapies. OBJECTIVES: To estimate the cost-effectiveness of the CFHealthHub (CFHH) intervention to support adherence to inhaled medications. METHODS: A state transition model was developed to assess the cost-effectiveness of the CFHH intervention versus usual care from the perspective of the UK National Health Service and Personal Social Services over a lifetime horizon. Costs and health outcomes were discounted at a rate of 3.5 percent per annum. Costs were valued at 2021/22 prices. The model structure includes health states defined by survival status, level of lung function, and transplant history. Treatment effects were modeled by changing the probabilities of transitioning between lung function states and reducing exacerbation rates. Model parameters were informed by the CFHH trial, CF Registry data, routine cost databases, literature, and expert opinion. Deterministic and probabilistic sensitivity analyses were undertaken to assess uncertainty. RESULTS: The CFHH intervention is expected to generate additional health gains and cost savings compared with usual care. Assuming that it is delivered for 10 years, the CFHH intervention is expected to generate 0.17 additional quality-adjusted life years and cost savings of GBP 1,600 (EUR 1,662) per patient. CONCLUSIONS: The CFHH intervention is expected to dominate usual care, irrespective of the duration over which the intervention is delivered. The modeled benefits and cost savings are smaller than initially expected and are sensitive to relative treatment effects on lung function.

Self-management intervention to reduce pulmonary exacerbations by supporting treatment adherence in adults with cystic fibrosis: a randomised controlled trial.

INTRODUCTION: Recurrent pulmonary exacerbations lead to progressive lung damage in cystic fibrosis (CF). Inhaled medications (mucoactive agents and antibiotics) help prevent exacerbations, but objectively measured adherence is low. We investigated whether a multi-component (complex) self-management intervention to support adherence would reduce exacerbation rates over 12 months. METHODS: Between October 2017 and May 2018, adults with CF (aged ≥16 years; 19 UK centres) were randomised to the intervention (data-logging nebulisers, a digital platform and behavioural change sessions with trained clinical interventionists) or usual care (data-logging nebulisers). Outcomes included pulmonary exacerbations (primary outcome), objectively measured adherence, body mass index (BMI), lung function (FEV1) and Cystic Fibrosis Questionnaire-Revised (CFQ-R). Analyses were by intent to treat over 12 months. RESULTS: Among intervention (n=304) and usual care (n=303) participants (51% female, median age 31 years), 88% completed 12-month follow-up. Mean exacerbation rate was 1.63/year with intervention and 1.77/year with usual care (adjusted ratio 0.96; 95% CI 0.83 to 1.12; p=0.64). Adjusted mean differences (95% CI) were in favour of the intervention versus usual care for objectively measured adherence (9.5% (8.6% to 10.4%)) and BMI (0.3 (0.1 to 0.6) kg/m2), with no difference for %FEV1 (1.4 (-0.2 to 3.0)). Seven CFQ-R subscales showed no between-group difference, but treatment burden reduced for the intervention (3.9 (1.2 to 6.7) points). No intervention-related serious adverse events occurred. CONCLUSIONS: While pulmonary exacerbations and FEV1 did not show statistically significant differences, the intervention achieved higher objectively measured adherence versus usual care. The adherence difference might be inadequate to influence exacerbations, though higher BMI and lower perceived CF treatment burden were observed.

Cost and health impacts of adherence to the National Institute for Health and Care Excellence schizophrenia guideline recommendations.

BACKGROUND: Discrepancies between the National Institute for Health and Care Excellence (NICE) schizophrenia guideline recommendations and current clinical practice in the UK have been reported. AIMS: We aim to assess whether it is cost-effective to improve adherence to the NICE schizophrenia guideline recommendations, compared with current practice. METHOD: A previously developed whole-disease model for schizophrenia, using the discrete event simulation method, was adapted to assess the cost and health impacts of adherence to the NICE recommendations. Three scenarios to improve adherence to the clinical guidelines were modelled: universal provision of cognitive-behavioural therapy for patients at clinical high risk of psychosis, universal provision of family intervention for patients with first-episode psychosis and prompt provision of clozapine for patients with treatment-resistant schizophrenia. The primary outcomes were lifetime costs and quality-adjusted life-years gained. RESULTS: The results suggest full adherence to the guideline recommendations would decrease cost and improve quality-adjusted life-years. Based on the NICE willingness-to-pay threshold of £20 000-£30 000 per quality-adjusted life-year gained, prompt provision of clozapine for patients with treatment-resistant schizophrenia results in the greatest net monetary benefit, followed by universal provision of cognitive-behavioural therapy for patients at clinical high risk of psychosis, and universal provision of family intervention for patients with first-episode psychosis. CONCLUSIONS: Our results suggest that adherence to guideline recommendations would decrease cost and improve quality-adjusted life-years. Greater investment is needed to improve guideline adherence and therefore improve patient quality of life and realise potential cost savings.

A systematic review of meta-analyses assessing the validity of tumour response endpoints as surrogates for progression-free or overall survival in cancer.

BACKGROUND: Tumour response endpoints, such as overall response rate (ORR) and complete response (CR), are increasingly used in cancer trials. However, the validity of response-based surrogates is unclear. This systematic review summarises meta-analyses assessing the association between response-based outcomes and overall survival (OS), progression-free survival (PFS) or time-to-progression (TTP). METHODS: Five databases were searched to March 2019. Meta-analyses reporting correlation or regression between response-based outcomes and OS, PFS or TTP were summarised. RESULTS: The systematic review included 63 studies across 20 cancer types, most commonly non-small cell lung cancer (NSCLC), colorectal cancer (CRC) and breast cancer. The strength of association between ORR or CR and either PFS or OS varied widely between and within studies, with no clear pattern by cancer type. The association between ORR and OS appeared weaker and more variable than that between ORR and PFS, both for associations between absolute endpoints and associations between treatment effects. CONCLUSIONS: This systematic review suggests that response-based endpoints, such as ORR and CR, may not be reliable surrogates for PFS or OS. Where it is necessary to use tumour response to predict treatment effects on survival outcomes, it is important to fully reflect all statistical uncertainty in the surrogate relationship.

The Type and Impact of Evidence Review Group Exploratory Analyses in the NICE Single Technology Appraisal Process.

BACKGROUND: As part of the UK National Institute for Health and Care Excellence (NICE) single technology appraisal process, independent evidence review groups (ERGs) critically appraise a company's submission relating to a specific technology and indication. OBJECTIVES: To explore the type of additional exploratory analyses conducted by ERGs and their impact on the recommendations made by NICE. METHODS: The 100 most recently completed single technology appraisals with published guidance were selected for inclusion. A content analysis of relevant documents was undertaken to identify and extract relevant data, and narrative synthesis was used to rationalize and present these data. RESULTS: The types of exploratory analysis conducted in relation to companies' models were fixing errors, addressing violations, addressing matters of judgment, and the provision of a new, ERG-preferred base case. Ninety-three of the 100 ERG reports contained at least one of these analyses. The most frequently reported type of analysis in these 93 ERG reports related to the category "Matters of judgment," which was reported in 83 reports (89%). At least one of the exploratory analyses conducted and reported by an ERG is mentioned in 97% of NICE appraisal consultation documents and 94% of NICE final appraisal determinations, and had a clear influence on recommendations in 72% of appraisal consultation documents and 47% of final appraisal determinations. CONCLUSIONS: These results suggest that the additional analyses undertaken by ERGs in the appraisal of company submissions are highly influential in the policy-making and decision-making process.

Fractional exhaled nitric oxide for the management of asthma in adults: a systematic review.

The aim of this review was to evaluate the clinical effectiveness of fractional exhaled nitric oxide (FeNO) measured in a clinical setting for the management of asthma in adults.13 electronic databases were searched and studies were selected against predefined inclusion criteria. Quality assessment was conducted using QUADAS-2. Class effect meta-analyses were performed.Six studies were included. Despite high levels of heterogeneity in multiple study characteristics, exploratory class effect meta-analyses were conducted. Four studies reported a wider definition of exacerbation rates (major or severe exacerbation) with a pooled rate ratio of 0.80 (95% CI 0.63-1.02). Two studies reported rates of severe exacerbations (requiring oral corticosteroid use) with a pooled rate ratio of 0.89 (95% CI 0.43-1.72). Inhaled corticosteroid use was reported by four studies, with a pooled standardised mean difference of -0.24 (95% CI -0.56-0.07). No statistically significant differences for health-related quality of life or asthma control were found.FeNO guided management showed no statistically significant benefit in terms of severe exacerbations or inhaled corticosteroid use, but showed a statistically significant reduction in exacerbations of any severity. However, further research is warranted to clearly define which management protocols (including cut-off points) offer best efficacy and which patient groups would benefit the most.

Distributional cost-effectiveness analysis of health care programmes--a methodological case study of the UK Bowel Cancer Screening Programme.

This paper presents an application of a new methodological framework for undertaking distributional cost-effectiveness analysis to combine the objectives of maximising health and minimising unfair variation in health when evaluating population health interventions. The National Health Service bowel cancer screening programme introduced in 2006 is expected to improve population health on average and to worsen population health inequalities associated with deprivation and ethnicity--a classic case of 'intervention-generated inequality'. We demonstrate the distributional cost-effectiveness analysis framework by examining two redesign options for the bowel cancer screening programme: (i) the introduction of an enhanced targeted reminder aimed at increasing screening uptake in deprived and ethnically diverse neighbourhoods and (ii) the introduction of a basic universal reminder aimed at increasing screening uptake across the whole population. Our analysis indicates that the universal reminder is the strategy that maximises population health, while the targeted reminder is the screening strategy that minimises unfair variation in health. The framework is used to demonstrate how these two objectives can be traded off against each other, and how alternative social value judgements influence the assessment of which strategy is best, including judgements about which dimensions of health variation are considered unfair and judgements about societal levels of inequality aversion.

Dry powder inhalers in cystic fibrosis: same old drugs but different benefits?

PURPOSE OF REVIEW: Newer 'innovative' formulations of antibiotics for Pseudomonas aeruginosa lung infection in patients with cystic fibrosis include colistimethate sodium and tobramycin in the form of dry powders for inhalation (DPIs). Whilst these DPIs are anticipated to improve patient adherence because of increased convenience and ease of administration, questions remain concerning whether they are as clinically effective, safe and cost-effective as nebulized antibiotics. RECENT FINDINGS: This review describes the recent findings of a health technology assessment of the clinical effectiveness and cost-effectiveness of colistimethate sodium and tobramycin DPIs with regard to how innovative treatments may be judged to be incrementally better than existing treatments. The original assessment was undertaken to inform the National Institute for Health and Care Excellence's Technology Appraisal Programme to inform national clinical guidance on the use of these new treatments in the National Health Service. SUMMARY: Three trials were included in the systematic review. Issues surrounding the clinical effectiveness and cost-effectiveness of colistimethate sodium DPI and tobramycin DPI are discussed in light of the considerable uncertainties associated with the available evidence.

Identification and review of cost-effectiveness model parameters: a qualitative study.

OBJECTIVES: Health economic models are developed as part of the health technology assessment process to determine whether health interventions represent good value for money. These models are often used to directly inform healthcare decision making and policy. The information needs for the model require the use of other types of information beyond clinical effectiveness evidence to populate the model's parameters. The purpose of this research study was to explore issues concerned with the identification and use of information for the development of such models. METHODS: Three focus groups were held in February 2011 at the University of Sheffield with thirteen UK HTA experts. Attendees included health economic modelers, information specialists and systematic reviewers. Qualitative framework analysis was used to analyze the focus group data. RESULTS: Six key themes, with related sub-themes, were identified dealing with decisions and judgments; searching methods; selection and rapid review of evidence; team communication; modeler experience and clinical input and reporting methods. There was considerable overlap between themes. CONCLUSIONS: Key issues raised by the respondents included the need for effective communication and teamwork throughout the model development process, the importance of using clinical experts as well as the need for transparent reporting of methods and decisions.

Validation of surrogate endpoints in advanced solid tumors: systematic review of statistical methods, results, and implications for policy makers.

OBJECTIVES: Licensing of, and coverage decisions on, new therapies should rely on evidence from patient-relevant endpoints such as overall survival (OS). Nevertheless, evidence from surrogate endpoints may also be useful, as it may not only expedite the regulatory approval of new therapies but also inform coverage decisions. It is, therefore, essential that candidate surrogate endpoints be properly validated. However, there is no consensus on statistical methods for such validation and on how the evidence thus derived should be applied by policy makers. METHODS: We review current statistical approaches to surrogate-endpoint validation based on meta-analysis in various advanced-tumor settings. We assessed the suitability of two surrogates (progression-free survival [PFS] and time-to-progression [TTP]) using three current validation frameworks: Elston and Taylor's framework, the German Institute of Quality and Efficiency in Health Care's (IQWiG) framework and the Biomarker-Surrogacy Evaluation Schema (BSES3). RESULTS: A wide variety of statistical methods have been used to assess surrogacy. The strength of the association between the two surrogates and OS was generally low. The level of evidence (observation-level versus treatment-level) available varied considerably by cancer type, by evaluation tools and was not always consistent even within one specific cancer type. CONCLUSIONS: Not in all solid tumors the treatment-level association between PFS or TTP and OS has been investigated. According to IQWiG's framework, only PFS achieved acceptable evidence of surrogacy in metastatic colorectal and ovarian cancer treated with cytotoxic agents. Our study emphasizes the challenges of surrogate-endpoint validation and the importance of building consensus on the development of evaluation frameworks.

Empirical Testing of Alternative Search Methods to Retrieve Utility Values for Health Economic Modelling.

OBJECTIVES: The objective of this study is to compare different information retrieval methods that can be used to identify utility inputs for health economic models. METHODS: The usual practice of using systematic review methods was compared with two alternatives (iterative searching and rapid review), using a health technology assessment (HTA) case study in ulcerative colitis (UC). We analysed whether there were differences in the utility values identified when using the alternative search methods. Success was evaluated in terms of time, burden and relevance of identified information. The identified utility values were tested in an executable health economic model developed for UC, and the model results were compared. RESULTS: The usual practice of using systematic review search approaches identified the most publications but was also the least precise method and took longest to complete. The inclusion of data from the different search methods in the model did not lead to different conclusions across search methods. CONCLUSIONS: In this case study, usual practice was less efficient and resulted in the same health economic model conclusions as the alternative search methods. Further case studies are required to examine whether this conclusion might be generalisable.

A Model-Based Economic Evaluation of Hypothetical Treatments for Amyotrophic Lateral Sclerosis in the UK: Implications for Pricing of New and Emerging Health Technologies.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a devastating disease which leads to loss of muscle function and paralysis. Historically, clinical drug development has been unsuccessful, but promising disease-modifying therapies (DMTs) may be on the horizon. OBJECTIVES: The aims of this study were to estimate survival, quality-adjusted life-years (QALYs) and costs under current care, and to explore the conditions under which new therapies might be considered cost effective. METHODS: We developed a health economic model to evaluate the cost effectiveness of future ALS treatments from a UK National Health Service and Personal Social Services perspective over a lifetime horizon using data from the ALS-CarE study. Costs were valued at 2021/22 prices. Two hypothetical interventions were evaluated: a DMT which delays progression and mortality, and a symptomatic therapy which improves utility only. Sensitivity analysis was conducted to identify key drivers of cost effectiveness. RESULTS: Starting from King's stage 2, patients receiving current care accrue an estimated 2.27 life-years, 0.75 QALYs and lifetime costs of £68,047. Assuming a 50% reduction in progression rates and a UK-converted estimate of the price of edaravone, the incremental cost-effectiveness ratio for a new DMT versus current care is likely to exceed £735,000 per QALY gained. Symptomatic therapies may be more likely to achieve acceptable levels of cost effectiveness. CONCLUSIONS: Regardless of efficacy, DMTs may struggle to demonstrate cost effectiveness, even at a low price. The cost effectiveness of DMTs is likely to be strongly influenced by drug price, the magnitude and durability of relative treatment effects, treatment starting/stopping rules and any additional utility benefits over current care.

Reviewing the evidence to inform the population of cost-effectiveness models within health technology assessments.

OBJECTIVES: Health technology assessments (HTAs) typically require the development of a cost-effectiveness model, which necessitates the identification, selection, and use of other types of information beyond clinical effectiveness evidence to populate the model parameters. The reviewing activity associated with model development should be transparent and reproducible but can result in a tension between being both timely and systematic. Little procedural guidance exists in this area. The purpose of this article was to provide guidance, informed by focus groups, on what might constitute a systematic and transparent approach to reviewing information to populate model parameters. METHODS: A focus group series was held with HTA experts in the United Kingdom including systematic reviewers, information specialists, and health economic modelers to explore these issues. Framework analysis was used to analyze the qualitative data elicited during focus groups. RESULTS: Suggestions included the use of rapid reviewing methods and the need to consider the trade-off between relevance and quality. The need for transparency in the reporting of review methods was emphasized. It was suggested that additional attention should be given to the reporting of parameters deemed to be more important to the model or where the preferred decision regarding the choice of evidence is equivocal. DISCUSSION: These recommendations form part of a Technical Support Document produced for the National Institute for Health and Clinical Excellence Decision Support Unit in the United Kingdom. It is intended that these recommendations will help to ensure a more systematic, transparent, and reproducible process for the review of model parameters within HTA.

Using whole disease modeling to inform resource allocation decisions: economic evaluation of a clinical guideline for colorectal cancer using a single model.

OBJECTIVE: To assess the feasibility and value of simulating whole disease and treatment pathways within a single model to provide a common economic basis for informing resource allocation decisions. METHODS: A patient-level simulation model was developed with the intention of being capable of evaluating multiple topics within National Institute for Health and Clinical Excellence's colorectal cancer clinical guideline. The model simulates disease and treatment pathways from preclinical disease through to detection, diagnosis, adjuvant/neoadjuvant treatments, follow-up, curative/palliative treatments for metastases, supportive care, and eventual death. The model parameters were informed by meta-analyses, randomized trials, observational studies, health utility studies, audit data, costing sources, and expert opinion. Unobservable natural history parameters were calibrated against external data using Bayesian Markov chain Monte Carlo methods. Economic analysis was undertaken using conventional cost-utility decision rules within each guideline topic and constrained maximization rules across multiple topics. RESULTS: Under usual processes for guideline development, piecewise economic modeling would have been used to evaluate between one and three topics. The Whole Disease Model was capable of evaluating 11 of 15 guideline topics, ranging from alternative diagnostic technologies through to treatments for metastatic disease. The constrained maximization analysis identified a configuration of colorectal services that is expected to maximize quality-adjusted life-year gains without exceeding current expenditure levels. CONCLUSIONS: This study indicates that Whole Disease Model development is feasible and can allow for the economic analysis of most interventions across a disease service within a consistent conceptual and mathematical infrastructure. This disease-level modeling approach may be of particular value in providing an economic basis to support other clinical guidelines.

Using resource modelling to inform decision making and service planning: the case of colorectal cancer screening in Ireland.

BACKGROUND: Organised colorectal cancer screening is likely to be cost-effective, but cost-effectiveness results alone may not help policy makers to make decisions about programme feasibility or service providers to plan programme delivery. For these purposes, estimates of the impact on the health services of actually introducing screening in the target population would be helpful. However, these types of analyses are rarely reported. As an illustration of such an approach, we estimated annual health service resource requirements and health outcomes over the first decade of a population-based colorectal cancer screening programme in Ireland. METHODS: A Markov state-transition model of colorectal neoplasia natural history was used. Three core screening scenarios were considered: (a) flexible sigmoidoscopy (FSIG) once at age 60, (b) biennial guaiac-based faecal occult blood tests (gFOBT) at 55-74 years, and (c) biennial faecal immunochemical tests (FIT) at 55-74 years. Three alternative FIT roll-out scenarios were also investigated relating to age-restricted screening (55-64 years) and staggered age-based roll-out across the 55-74 age group. Parameter estimates were derived from literature review, existing screening programmes, and expert opinion. Results were expressed in relation to the 2008 population (4.4 million people, of whom 700,800 were aged 55-74). RESULTS: FIT-based screening would deliver the greatest health benefits, averting 164 colorectal cancer cases and 272 deaths in year 10 of the programme. Capacity would be required for 11,095-14,820 diagnostic and surveillance colonoscopies annually, compared to 381-1,053 with FSIG-based, and 967-1,300 with gFOBT-based, screening. With FIT, in year 10, these colonoscopies would result in 62 hospital admissions for abdominal bleeding, 27 bowel perforations and one death. Resource requirements for pathology, diagnostic radiology, radiotherapy and colorectal resection were highest for FIT. Estimates depended on screening uptake. Alternative FIT roll-out scenarios had lower resource requirements. CONCLUSIONS: While FIT-based screening would quite quickly generate attractive health outcomes, it has heavy resource requirements. These could impact on the feasibility of a programme based on this screening modality. Staggered age-based roll-out would allow time to increase endoscopy capacity to meet programme requirements. Resource modelling of this type complements conventional cost-effectiveness analyses and can help inform policy making and service planning.

A systematic review of whole disease models for informing healthcare resource allocation decisions.

BACKGROUND: Whole disease models (WDM) are large-scale, system-level models which can evaluate multiple decision questions across an entire care pathway. Whilst this type of model can offer several advantages as a platform for undertaking economic analyses, the availability and quality of existing WDMs is unknown. OBJECTIVES: This systematic review aimed to identify existing WDMs to explore which disease areas they cover, to critically assess the quality of these models and provide recommendations for future research. METHODS: An electronic search was performed on multiple databases (MEDLINE, EMBASE, the NHS Economic Evaluation Database and the Health Technology Assessment database) on 23rd July 2023. Two independent reviewers selected studies for inclusion. Study quality was assessed using the National Institute for Health and Care Excellence (NICE) appraisal checklist for economic evaluations. Model characteristics were descriptively summarised. RESULTS: Forty-four WDMs were identified, of which thirty-two were developed after 2010. The main disease areas covered by existing WDMs are heart disease, cancer, acquired immune deficiency syndrome and metabolic disease. The quality of included WDMs is generally low. Common limitations included failure to consider the harms and costs of adverse events (AEs) of interventions, lack of probabilistic sensitivity analysis (PSA) and poor reporting. CONCLUSIONS: There has been an increase in the number of WDMs since 2010. However, their quality is generally low which means they may require significant modification before they could be re-used, such as modelling AEs of interventions and incorporation of PSA. Sufficient details of the WDMs need to be reported to allow future reuse/adaptation.

Individual participant data from digital sources informed and improved precision in the evaluation of predictive biomarkers in Bayesian network meta-analysis.

OBJECTIVES: We aimed to develop a network meta-analytic model for the evaluation of treatment effectiveness within predictive biomarker subgroups, by combining evidence from individual participant data (IPD) from digital sources (in the absence of randomized controlled trials) and aggregate data (AD). STUDY DESIGN AND SETTING: A Bayesian framework was developed for modeling time-to-event data to evaluate predictive biomarkers. IPD were sourced from electronic health records, using a target trial emulation approach, or digitized Kaplan-Meier curves. The model is illustrated using two examples: breast cancer with a hormone receptor biomarker, and metastatic colorectal cancer with the Kirsten Rat Sarcoma (KRAS) biomarker. RESULTS: The model allowed for the estimation of treatment effects in two subgroups of patients defined by their biomarker status. Effectiveness of taxanes did not differ in hormone receptor positive and negative breast cancer patients. Epidermal growth factor receptor inhibitors were more effective than chemotherapy in KRAS wild type colorectal cancer patients but not in patients with KRAS mutant status. Use of IPD reduced uncertainty of the subgroup-specific treatment effect estimates by up to 49%. CONCLUSION: Utilization of IPD allowed for more detailed evaluation of predictive biomarkers and cancer therapies and improved precision of the estimates compared to use of AD alone.

Whole disease modeling to inform resource allocation decisions in cancer: a methodological framework.

OBJECTIVES: This article presents a methodological framework for developing health economic models of whole systems of disease and treatment pathways to inform decisions concerning resource allocation-an approach referred to as "Whole Disease Modeling." This system-level approach can provide a consistent mathematical infrastructure for the economic evaluation of virtually any intervention across a disease pathway. METHODS: The framework has been developed for cancer but is broadly generalizable to other diseases. It has been informed by pilot work, a systematic review of economic analyses, a qualitative examination of model development processes, and other literature from the fields of operational research, statistics, and health economics. RESULTS: The framework is built on three principles: 1) the model boundary and breadth should capture all relevant aspects of the disease and its treatment-from preclinical disease through to death, 2) the model should be developed such that the decision node is conceptually transferable across the model, and 3) the costs and consequences of service elements should be structurally related. A generalized process for developing Whole Disease Models is presented. DISCUSSION: Although this approach involves a nontrivial investment of time and resource, its value may be realized when 1) multiple options for service change require economic analysis at a single time point, 2) a disease service changes rapidly and the model can be reused, 3) current services within a pathway have not been subjected to economic analysis, 4) upstream events are expected to have important downstream effects, or 5) simple cost-utility decision rules fail to reflect the complexity of the decision-makers' objectives.

Estimation of Transition Probabilities for State-Transition Models: A Review of NICE Appraisals.

State transition models are used to inform health technology reimbursement decisions. Within state transition models, the movement of patients between the model health states over discrete time intervals is determined by transition probabilities (TPs). Estimating TPs presents numerous issues, including missing data for specific transitions, data incongruence and uncertainty around extrapolation. Inappropriately estimated TPs could result in biased models. There is limited guidance on how to address common issues associated with TP estimation. To assess current methods for estimating TPs and to identify issues that may introduce bias, we reviewed National Institute for Health and Care Excellence Technology Appraisals published from 1 January, 2019 to 27 May, 2020. Twenty-eight models (from 26 Technology Appraisals) were included in the review. Several methods for estimating TPs were identified: survival analysis (n = 11); count method (n = 9); multi-state modelling (n = 7); logistic regression (n = 2); negative binomial regression (n = 2); Poisson regression (n = 1); and calibration (n = 1). Evidence Review Groups identified several issues relating to TP estimation within these models, including important transitions being excluded (n = 5); potential selection bias when estimating TPs for post-randomisation health states (n = 2); issues concerning the use of multiple data sources (n = 4); potential biases resulting from the use of data from different populations (n = 2), and inappropriate assumptions around extrapolation (n = 3). These issues remained unresolved in almost every instance. Failing to address these issues may bias model results and lead to sub-optimal decision making. Further research is recommended to address these methodological problems.