Deriving input parameters for cost-effectiveness modeling: taxonomy of data types and approaches to their statistical synthesis

A model-based cost-utility analysis of an automated notification system for deteriorating patients on general wards

BACKGROUND

Delayed response to clinical deterioration of hospital inpatients is common. Deployment of an electronic automated advisory vital signs monitoring and notification system to signal clinical deterioration is associated with significant improvements in clinical outcomes but there is no evidence on the cost-effectiveness compared with routine monitoring, in the National Health Service (NHS) in the United Kingdom (UK).

METHODS

A decision analytic model was developed to estimate the cost-effectiveness of an electronic automated advisory notification system versus standard care, in adults admitted to a district general hospital. Analyses considered: (1) the cost-effectiveness of the technology based on secondary analysis of patient level data of 3787 inpatients in a before-and-after study; and (2) the cost-utility (cost per quality-adjusted life-year (QALY)) over a lifetime horizon, extrapolated using published data. Analysis was conducted from the perspective of the NHS. Uncertainty in the model was assessed using a range of sensitivity analyses.

RESULTS

The study population had a mean age of 68 years, 48% male, with a median inpatient stay of 6 days. Expected life expectancy at discharge was assumed to be 17.74 years. (1) Cost-effectiveness analysis: The automated notification system was more effective (-0.027 reduction in mean events per patient) and provided a cost saving of -£12.17 (-182.07 to 154.80) per patient admission. (2) Cost-utility analysis: Over a lifetime horizon the automated notification system was dominant, demonstrating a positive incremental QALY gain (0.0287 QALYs, equivalent to ~10 days of perfect health) and a cost saving of £55.35. At a threshold of £20,000 per QALY, the probability of automated monitoring being cost-effective in the NHS was 81%. Increased use of cableless sensors may reduce cost-savings, however, the intervention remains cost-effective at 100% usage (ICER: £3,107/QALY). Stratified cost-effectiveness analysis by age, National Early Warning Score (NEWS) on admission, and primary diagnosis indicated the automated notification system was cost-effective for most strategies and that use representative of the patient population studied was the most cost-saving strategy.

CONCLUSION

Automated notification system for adult patients admitted to general wards appears to be a cost-effective use in the NHS; adopting this technology could be good use of scarce resources with significance for patient safety.

Challenges and Opportunities in Interdisciplinary Research and Real-World Data for Treatment Sequences in Health Technology Assessments

With an ever-increasing number of treatment options, the assessment of treatment sequences has become crucial in health technology assessment (HTA). This review systematically explores the multifaceted challenges inherent in evaluating sequences, delving into their interplay and nuances that go beyond economic model structures. We synthesised a 'roadmap' of literature from key methodological studies, highlighting the evolution of recent advances and emerging research themes. These insights were compared against HTA guidelines to identify potential avenues for future research. Our findings reveal a spectrum of challenges in sequence evaluation, encompassing selecting appropriate decision-analytic modelling approaches and comparators, deriving appropriate clinical effectiveness evidence in the face of data scarcity, scrutinising effectiveness assumptions and statistical adjustments, considering treatment displacement, and optimising model computations. Integrating methodologies from diverse disciplines-statistics, epidemiology, causal inference, operational research and computer science-has demonstrated promise in addressing these challenges. An updated review of application studies is warranted to provide detailed insights into the extent and manner in which these methodologies have been implemented. Data scarcity on the effectiveness of treatment sequences emerged as a dominant concern, especially because treatment sequences are rarely compared in clinical trials. Real-world data (RWD) provide an alternative means for capturing evidence on effectiveness and future research should prioritise harnessing causal inference methods, particularly Target Trial Emulation, to evaluate treatment sequence effectiveness using RWD. This approach is also adaptable for analysing trials harbouring sequencing information and adjusting indirect comparisons when collating evidence from heterogeneous sources. Such investigative efforts could lend support to reviews of HTA recommendations and contribute to synthesising external control arms involving treatment sequences.

Exploring the cost-effectiveness of high versus low perioperative fraction of inspired oxygen in the prevention of surgical site infections among abdominal surgery patients in three low- and middle-income countries

Background

This study assessed the potential cost-effectiveness of high (80-100%) vs low (21-35%) fraction of inspired oxygen (FiO2) at preventing surgical site infections (SSIs) after abdominal surgery in Nigeria, India, and South Africa.

Methods

Decision-analytic models were constructed using best available evidence sourced from unbundled data of an ongoing pilot trial assessing the effectiveness of high FiO2, published literature, and a cost survey in Nigeria, India, and South Africa. Effectiveness was measured as percentage of SSIs at 30 days after surgery, a healthcare perspective was adopted, and costs were reported in US dollars ($).

Results

High FiO2 may be cost-effective (cheaper and effective). In Nigeria, the average cost for high FiO2 was $216 compared with $222 for low FiO2 leading to a -$6 (95% confidence interval [CI]: -$13 to -$1) difference in costs. In India, the average cost for high FiO2 was $184 compared with $195 for low FiO2 leading to a -$11 (95% CI: -$15 to -$6) difference in costs. In South Africa, the average cost for high FiO2 was $1164 compared with $1257 for low FiO2 leading to a -$93 (95% CI: -$132 to -$65) difference in costs. The high FiO2 arm had few SSIs, 7.33% compared with 8.38% for low FiO2, leading to a -1.05 (95% CI: -1.14 to -0.90) percentage point reduction in SSIs.

Conclusion

High FiO2 could be cost-effective at preventing SSIs in the three countries but further data from large clinical trials are required to confirm this.

Economic evaluation of fluoride varnish application in preschoolers: A systematic review

BACKGROUND

Fluoride varnish (FV) is a convenient way of professionally applying fluoride in preschoolers. However, its modest anticaries effect highlights the need for economic evaluations.

AIM

To assess economic evaluations reporting applications of FV to reduce caries incidence in preschoolers.

DESIGN

We included full economic evaluations with preschool participants, in which the intervention was FV and the outcome was related to dentin caries. We searched in CENTRAL; MEDLINE via PubMed; WEB OF SCIENCE; EMBASE; SCOPUS; LILACS; BBO; and BVS Economia em saúde, OpenGrey, and EconoLit. Clinical trial registers, thesis and dissertations, and meeting abstracts were hand searched, as well as 11 dental journals. Risk of bias in the included studies was assessed using the Philips' and Drummond's (full and simplified) tools.

RESULTS

Titles and abstracts of 2871 articles were evaluated, and 200 were read in full. Eight cost-effectiveness studies were included: five modeling and three within-trial evaluations. None of the studies gave sufficient information to allow a thorough assessment using the bias tools. We did not combine the results of the studies due to the great heterogeneity among them. Four studies reported that FV in preschool children was a cost-effective measure, but in one of these studies, sealants and fluoride toothpaste were more cost-effective measures than the varnish, and three studies used limited data that compromised the generalizability of their results. The other four studies showed a large increase in costs due to the application of varnish and/or low cost-effectiveness.

CONCLUSION

We did not find convincing overall evidence that applying FV in preschoolers is an anticaries cost-effective measure. The protocol of this systematic review is available at Open Science Framework (https://osf.io/xw5va/).

Modelling Methods of Economic Evaluations of HIV Testing Strategies in Sub-Saharan Africa: A Systematic Review

BACKGROUND AND OBJECTIVE

Economic evaluations, a decision-support tool for policy makers, will be crucial in planning and tailoring HIV prevention and treatment strategies especially in the wake of stalled and decreasing funding for the global HIV response. As HIV testing and treatment coverage increase, case identification becomes increasingly difficult and costly. Determining which subset of the population these strategies should be targeted to becomes of vital importance as well. Generating quality economic evidence begins with the validity of the modelling approach and the model structure employed. This study synthesises and critiques the reporting around modelling methodology of economic models in the evaluation of HIV testing strategies in sub-Saharan Africa.

METHODS

The following databases were searched from January 2000 to September 2020: MEDLINE, Embase, Scopus, EconLit and Global Health. Any model-based economic evaluation of a unique HIV testing strategy conducted in sub-Saharan Africa presenting a cost-effectiveness measure published from 2013 onwards was eligible. Data were extracted around three components: general study characteristics; economic evaluation design; and quality of model reporting using a novel tool developed for the purposes of this study.

RESULTS

A total of 21 studies were included; 10 cost-effectiveness analyses, 11 cost-utility analyses. All but one study was conducted in Eastern and Southern Africa. Modelling approaches for HIV testing strategies can be broadly characterised as static aggregate models (3/21), static individual models (6/21), dynamic aggregate models (5/21) and dynamic individual models (7/21). Adequate reporting around data handling was the highest of the three categories assessed (74%), and model validation, the lowest (45%). Limitations to model structure, justification of chosen time horizon and cycle length, and description of external model validation process were all adequately reported in less than 40% of studies. The predominant limitation of this review relates to the potential implications of the narrow inclusion criteria.

CONCLUSIONS

This review is the first to synthesise economic evaluations of HIV testing strategies in sub-Saharan Africa. The majority of models exhibited dynamic, stochastic and individual properties. Model reporting against the 13 criteria in our novel tool was mixed. Future model-based economic evaluations of HIV testing strategies would benefit from transparency around the choice of modelling approach, model structure, data handling procedures and model validation techniques.

Meta-analysis of health state utility values measured by EuroQol 5-dimensions (EQ5D) questionnaire in Chinese women with breast cancer

BACKGROUND

To synthesise EQ5D health state utility values in Chinese women with breast cancer for parameterising a cost utility model.

METHODS

Eligible studies had to report health state utility values measured by EQ-5D in Chinese women diagnosed with breast cancer. Risk of bias was assessed using the Newcastle Ottawa Scale (NOS). Data from single arm studies was pooled using meta-analysis of single proportions to provide overall point estimates and 95% confidence intervals for fixed and random effects models using the inverse variance and Der Simonian-Laird methods respectively. Heterogeneity was evaluated using the I2 statistic and sensitivity analysis and meta-regression were conducted.

RESULTS

Five papers were included, when all studies were combined (n = 4,100) the mean utility (95% confidence interval) for random effects model was 0.83 (0.78, 0.89); for TNM 0-1 0.85 (0.75, 0.95); for TNM II 0.85 (0.78, 0.93); for TNM III 0.83 (0.77, 0.90) and for TNM IV 0.73 (0.63, 0.82).The utility of patients in State P (first year after primary breast cancer) 0.84 (0.80, 0.88); in State R (first year after recurrence) 0.73 (0.69, 0.76), in State S (second and following years after primary breast cancer or recurrence) 0.88 (0.83, 0.92); and in State M (metastatic disease) 0.78 (0.74, 0.82). Mean utility for duration since diagnosis 13 to 36 months was 0.88 (0.80, 0.96, I2 =95%); for 37 to 60 months 0.89 (0.82, 0.96, I2 =90%); for more than 60 months 0.86 (0.76, 0.96, I2 =90%). Mean utility for chemotherapy was 0.86 (0.79, 0.92, I2 =97%); for radiotherapy 0.83 (0.69, 0.96, I2 =97%); surgery 0.80 (0.69, 0.91, I2 =98%); concurrent chemo-radiation 0.70 (0.60, 0.81, I2 =86%) and endocrine therapy 0.90 (0.83, 0.97, I2 =91%).

CONCLUSION

This study synthesises the evidence for health state utility values for Chinese women with breast cancer which is useful to inform cost utility models.

Health State Utility Values for Type 2 Diabetes and Related Complications in East and Southeast Asia: A Systematic Review and Meta-Analysis

OBJECTIVES

East and Southeast Asia has the greatest burden of diabetes in the world. We sought to derive a reference set of utility values for type 2 diabetes without complication and disutility (utility decrement) values for important diabetes-related complications to better inform economic evaluation.

METHODS

A systematic review to identify utility values for diabetes and related complications reported in East and Southeast Asia. We searched MEDLINE (OVID) from inception to May 26, 2020 for utility values elicited using direct and indirect methods. Identified studies were assessed for quality based on the National Institute of Health and Care Excellence guidelines. Utility and disutility estimates were pooled by meta-analyses with subgroup analyses to evaluate differences by nationality and valuation instrument. (PROSPERO: CRD42020191075).

RESULTS

We identified 17 studies for the systematic review from a total of 13 035 studies in the initial search, of which 13 studies met the quality criteria for inclusion in the meta-analyses. The pooled utility value for diabetes without complication was 0.88 (95% CI 0.83-0.93), with the pooled utility decrement for associated complications ranged from 0.00 (for excess BMI) to 0.18 (for amputation). The utility values were consistently more conservative than previous estimates derived in Western populations. Utility decrements were comparable for SF-6D and EQ-5D valuation instruments and for Chinese and other Asian groups.

CONCLUSIONS

A reference set of pooled disutility and utility values for type 2 diabetes and its complications in East and Southeast Asian populations yielded more conservative estimates than Western populations.

Combining Model-Based Clinical Trial Simulation, Pharmacoeconomics, and Value of Information to Optimize Trial Design

The Bayesian decision‐analytic approach to trial design uses prior distributions for treatment effects, updated with likelihoods for proposed trial data. Prior distributions for treatment effects based on previous trial results risks sample selection bias and difficulties when a proposed trial differs in terms of patient characteristics, medication adherence, or treatment doses and regimens. The aim of this study was to demonstrate the utility of using pharmacometric‐based clinical trial simulation (CTS) to generate prior distributions for use in Bayesian decision‐theoretic trial design. The methods consisted of four principal stages: a CTS to predict the distribution of treatment response for a range of trial designs; Bayesian updating for a proposed sample size; a pharmacoeconomic model to represent the perspective of a reimbursement authority in which price is contingent on trial outcome; and a model of the pharmaceutical company return on investment linking drug prices to sales revenue. We used a case study of febuxostat versus allopurinol for the treatment of hyperuricemia in patients with gout. Trial design scenarios studied included alternative treatment doses, inclusion criteria, input uncertainty, and sample size. Optimal trial sample sizes varied depending on the uncertainty of model inputs, trial inclusion criteria, and treatment doses. This interdisciplinary framework for trial design and sample size calculation may have value in supporting decisions during later phases of drug development and in identifying costly sources of uncertainty, and thus inform future research and development strategies.

Linked Pharmacometric-Pharmacoeconomic Modeling and Simulation in Clinical Drug Development

Market access and pricing of pharmaceuticals are increasingly contingent on the ability to demonstrate comparative effectiveness and cost-effectiveness. As such, it is widely recognized that predictions of the economic potential of drug candidates in development could inform decisions across the product life cycle. This may be challenging when safety and efficacy profiles in terms of the relevant clinical outcomes are unknown or highly uncertain early in product development. Linking pharmacometrics and pharmacoeconomics, such that outputs from pharmacometric models serve as inputs to pharmacoeconomic models, may provide a framework for extrapolating from early-phase studies to predict economic outcomes and characterize decision uncertainty. This article reviews the published studies that have implemented this methodology and used simulation to inform drug development decisions and/or to optimize the use of drug treatments. Some of the key practical issues involved in linking pharmacometrics and pharmacoeconomics, including the choice of final outcome measures, methods of incorporating evidence on comparator treatments, approaches to handling multiple intermediate end points, approaches to quantifying uncertainty, and issues of model validation are also discussed. Finally, we have considered the potential barriers that may have limited the adoption of this methodology and suggest that closer alignment between the disciplines of clinical pharmacology, pharmacometrics, and pharmacoeconomics, may help to realize the potential benefits associated with linked pharmacometric-pharmacoeconomic modeling and simulation.

Comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analyses

OBJECTIVES

Within cost-effectiveness models, prevalence figures can inform transition probabilities. The methodological quality of studies can inform the choice of prevalence figures but no single obvious candidate tool exists for assessing quality of the observational epidemiological studies for selecting prevalence estimates. We aimed to compare different tools to assess the risk of bias of studies reporting prevalence, and develop and compare possible numerical scoring systems using these tools to set a threshold for inclusion of reports of prevalence in an economic analysis of neonatal hypoglycaemia.

DESIGN

Assessments of bias using two tools (Joanna Briggs Institute (JBI) Checklist for Prevalence Studies and a modified version of Risk Of Bias In Non-randomised Studies-of Interventions (ROBINS-I)) were compared for 18 studies relevant to a single setting (neonatal hypoglycaemia). Inclusions of studies for use in a decision analysis model were considered based on summary scores derived from these tools.

RESULTS

Both tools were considered easy to use and produced dispersed scores for each of the 40 study-outcome combinations. The modified ROBINS-I scores were more skewed than the JBI scores, particularly at higher thresholds. The studies selected for inclusion are generally the same using either tool; if 50% was used as the cut-off threshold using the Applicable Score both tools would yield the same results. However, the JBI tool is shorter and may be easier to interpret and apply to studies that do not involve a control group, while the modified ROBINS-I tool assesses more methodological detail in studies that include a control group.

CONCLUSION

Both tools performed well for systematically assessing studies that report on outcome prevalence and provided similar discrimination between studies for risk of bias. This convergent validity supports use of both tools for the purpose of assessing risk of bias and selecting studies that report prevalence for inclusion in economic analyses.

Benefit-Risk Assessment of Vaccines. Part II: Proposal Towards Consolidated Standards of Reporting Quantitative Benefit-Risk Models Applied to Vaccines (BRIVAC)

INTRODUCTION

Quantitative benefit-risk models (qBRm) applied to vaccines are increasingly used by public health authorities and pharmaceutical companies as an important tool to help decision makers with supporting benefit-risk assessment (BRA). However, many publications on vaccine qBRm provide insufficient details on the methodological approaches used. Incomplete and/or inadequate qBRm reporting may affect result interpretation and confidence in BRA, highlighting a need for the development of standard reporting guidance.

OBJECTIVES

Our objective was to provide an operational checklist for improved reporting of vaccine qBRm.

METHODS

The consolidated standards of reporting quantitative Benefit-RIsk models applied to VACcines (BRIVAC) were designed as a checklist of key information to report in qBRm scientific publications regarding the assessed vaccines, the methodological considerations and the results and their interpretation.

RESULTS

In total, 22 items and accompanying definitions, recommendations, explanations and examples were provided and divided into six main sections corresponding to the classic subdivisions of a scientific publication: title and abstract (items 1-2), introduction (items 3-4), methods (items 5-15), results (items 16-17), discussion (items 18-20) and other (items 21-22).

CONCLUSIONS

The BRIVAC checklist is the first initiative providing an operational checklist for improved reporting of qBRm applied to vaccines in scientific articles. It is intended to assist authors, peer-reviewers, editors and readers in their critical appraisal. Future initiatives are needed to provide methodological guidance to perform qBRm while taking into account the vaccine specificities.

Health state utility values in schizophrenia: protocol for a systematic review and meta-analysis

INTRODUCTION

Cost-effectiveness analyses that use quality-adjusted life-years (QALYs) allow comparing the value for money of interventions across different health problems. Health state utility values (HSUVs) are crucial to calculate QALYs. These are weights attached to a given health state reflecting preferences in health-related quality of life (HRQoL). In schizophrenia, there is extensive evidence about the consequences of this condition on HRQoL. Besides, several interventions have claimed to be cost-effective in terms of QALYs gained. Despite this evidence, a systematic review of HSUVs has not been conducted. Therefore, we aim to synthesise the evidence about HSUVs in schizophrenia.

METHODS AND ANALYSIS

We will conduct a systematic review of the literature about HSUVs in people with schizophrenia following the Preferred Reporting Items for Systematic review and Meta-Analysis and the International Society for Pharmacoeconomics and Outcomes Research task force recommendations. The submissions records of eight electronic peer-reviewed databases and three health technology assessment (HTA) agencies will be searched. Quantitative synthesis will be carried out in comparable studies, using random-effects meta-analysis. Heterogeneity will be explored using meta-regression if more than 10 studies per covariate are found. A narrative synthesis and methodological quality of included studies will be also reported.

DISCUSSION

This review will provide a synthesis of the HSUVs estimated for different states experienced by people with schizophrenia. This will inform analysts when calculating QALYs, using values in a more transparent and accountable manner. Finally, it will shed light on evidence gaps and limitations about this measure in mental health.

PROSPERO REGISTRATION NUMBER

CRD42019123582.

Health Utility Book (HUB)-Cancer: Protocol for a Systematic Literature Review of Health State Utility Values in Cancer

Background. Treatment options in oncology are rapidly advancing, and public payer systems are increasingly under pressure to adopt new but expensive cancer treatments. Cost-utility analyses (CUAs) are used to estimate the relative costs and effects of competing interventions, where health outcomes are measured using quality-adjusted life years (QALYs). Health state utility values (HSUVs) are used to reflect health-related quality of life or health status in the calculation of QALYs. To support reimbursement agencies in the appraisal of oncology drug submissions, which typically include a CUA component, we have proposed a systematic literature review of published HSUV estimates in the field of oncology. Methods. The following databases will be searched: MEDLINE, EMBASE, EconLit, and CINAHL. A team of reviewers, working independently and in duplicate, will evaluate abstracts and full-text publications for eligibility against broad inclusion criteria. Studies using a direct, indirect, or combination approach to eliciting preferences related to cancer or cancer treatments are eligible. Data extraction will capture details of study methodology, participants, health states, and corresponding HSUVs. We will summarize our findings with descriptive analyses at this stage. A pilot review in thyroid cancer is presented to illustrate the proposed methods. Discussion. This systematic review will generate a comprehensive summary of the oncology HSUV literature. As a component of the Health Utility Book (HUB) project, we anticipate that this work will assist both health economic modelers as well as critical reviewers in the development and appraisal of CUAs in oncology.

The Value of Further Research: The Added Value of Individual-Participant Level Data

Judgements based on average cost-effectiveness estimates may disguise significant heterogeneity in net health outcomes. Decisions about coverage of new interventions are often more efficient when they consider between-patient heterogeneity, which is usually operationalized as different selections for different subgroups. While most model-based cost-effectiveness studies are populated with aggregated-level sub-group estimates, individual-level data are recognized as the best source of evidence to produce unbiased and efficient estimates to explore this heterogeneity. This paper extends a previously published framework to assesses the added value of having access to individual-level data, compared to using aggregate-level data only, in the absence/presence of mutually exclusive population subgroups. Supported by a case study on the cost-effectiveness of interventions to increase uptake of smoke-alarms, the extended framework provided a quantification of the benefits foregone of not using individual-level data, pointed to the optimal number of subgroups and where further research should be undertaken. Although not indicating changes in reimbursement decisions, results showed that irrespective of using aggregate or individual-level data, no substantial additional gains are obtained if more than two subgroups are taken into account. However, depending on the evidence type used, different subgroups are revealed as warranting larger research funds. The use of individual-level data, rather than aggregate, may however influence not only the extent to which an appropriate understanding of existing heterogeneity is attained, but, more importantly, it may shape approval decisions for particular population subgroups and judgements of future research.

A systematic review of decision analytic modeling techniques for the economic evaluation of dental caries interventions

OBJECTIVES

Dental caries occur through a multifactorial process that may influence all tooth surfaces throughout an individual's life. The application of decision analytical modeling (DAM) has gained an increasing level of attention in long-term outcome assessment and economic evaluation of interventions on caries in recent years. The objective of this study was to systematically review the application of DAM and assess their methodological quality in the context of dental caries.

METHODS

A systematic review of the literature published to 31st December 2018 was conducted in Medline, EMBASE, NHSEED, and Web of Science electronic databases. The main information and model characteristics of studies was extracted with the methodological quality of included studies reviewed and assessed using the Philips' checklist.

RESULTS

Twenty five studies from different settings were included. Modeling techniques mainly comprised main type of modeling including Markov models (n = 12), Markov/microsimulation mixed model (n = 7), systematic dynamic models (n = 3), microsimulation models (n = 2) and decision tree (n = 1). The mean number of criteria fulfilled was 25.1 out of 60 items, which varied between year of study and research groups. The percentage of criteria fulfilled for data dimension was lower than for the structure and consistency dimension. Critical issues were data quality, incorporation of utility values, and uncertainty analysis in modeling.

CONCLUSION

The current review revealed that the methodological quality of DAM in dental caries economic evaluations is unsatisfied. Future modeling studies should adhere more closely to good practice guidelines, especially with respect to data quality evaluation, utility values incorporation, and uncertainty analysis in DAM based studies.

Cost-Effectiveness Analysis of the Use of Point-of-Care C-Reactive Protein Testing to Reduce Antibiotic Prescribing in Primary Care

More appropriate and measured use of antibiotics may be achieved using point-of-care (POC) C-reactive protein (CRP) testing, but there is limited evidence of cost-effectiveness in routine practice. A decision analytic model was developed to estimate the cost-effectiveness of testing, compared with standard care, in adults presenting in primary care with symptoms of acute respiratory tract infection (ARTI). Analyses considered (1) pragmatic use of testing, reflective of routine clinical practice, and (2) testing according to clinical guidelines. Threshold and scenario analysis were performed to identify cost-effective scenarios. In patients with symptoms of ARTI and based on routine practice, the incremental cost-effectiveness ratios of CRP testing were £19,705 per quality-adjusted-life-year (QALY) gained and £16.07 per antibiotic prescription avoided. Following clinical guideline, CRP testing in patients with lower respiratory tract infections (LRTIs) cost £4390 per QALY gained and £9.31 per antibiotic prescription avoided. At a threshold of £20,000 per QALY, the probabilities of POC CRP testing being cost-effective were 0.49 (ARTI) and 0.84 (LRTI). POC CRP testing as implemented in routine practice is appreciably less cost-effective than when adhering to clinical guidelines. The implications for antibiotic resistance and Clostridium difficile infection warrant further investigation.

Decision modelling for economic evaluation of liver transplantation

As the gap between a shortage of organs and the immense demand for liver grafts persists, every available donor liver needs to be optimized for utility, urgency and equity. To overcome this challenge, decision modelling might allow us to gather evidence from previous studies as well as compare the costs and consequences of alternative options. For public health policy and clinical intervention assessment, it is a potentially powerful tool. The most commonly used types of decision analytical models include decision trees, the Markov model, microsimulation, discrete event simulation and the system dynamic model. Analytic models could support decision makers in the field of liver transplantation when facing specific problems by synthesizing evidence, comprising all relevant options, generalizing results to other contexts, extending the time horizon and exploring the uncertainty. For modeling studies of economic evaluation for transplantation, understanding the current nature of the disease is crucial, as well as the selection of appropriate modelling techniques. The quality and availability of data is another key element for the selection and development of decision analytical models. In addition, good practice guidelines should be complied, which is important for standardization and comparability between economic outputs.

Matching the model with the evidence: comparing discrete event simulation and state-transition modeling for time-to-event predictions in a cost-effectiveness analysis of treatment in metastatic colorectal cancer patients

BACKGROUND

Individual patient data, e.g. from clinical trials, often need to be extrapolated or combined with additional evidence when assessing long-term impact in cost-effectiveness modeling studies. Different modeling methods can be used to represent the complex dynamics of clinical practice; the choice of which may impact cost-effectiveness outcomes. We compare the use of a previously designed cohort discrete-time state-transition model (DT-STM) with a discrete event simulation (DES) model.

METHODS

The original DT-STM was replicated and a DES model developed using AnyLogic software. Models were populated using individual patient data of a phase III study in metastatic colorectal cancer patients, and compared based on their evidence structure, internal validity, and cost-effectiveness outcomes. The DT-STM used time-dependent transition probabilities, whereas the DES model was populated using parametric distributions.

RESULTS

The estimated time-dependent transition probabilities for the DT-STM were irregular and more sensitive to single events due to the required small cycle length and limited number of event observations, whereas parametric distributions resulted in smooth time-to-event curves for the DES model. Although the DT-STM and DES model both yielded similar time-to-event curves, the DES model represented the trial data more accurately in terms of mean health-state durations. The incremental cost-effectiveness ratio (ICER) was €172,443 and €168,383 per Quality Adjusted Life Year gained for the DT-STM and DES model, respectively.

CONCLUSION

DES represents time-to-event data from clinical trials more naturally and accurately than DT-STM when few events are observed per time cycle. As a consequence, DES is expected to yield a more accurate ICER.

Health state utility values among children and adolescents with disabilities: protocol for a systematic review

INTRODUCTION

Increasingly, assessment of healthcare technologies and interventions requires the assessment of both costs and utilities. Health state utility values (HSUVs) are measured using a range of generic and condition-specific measures. While reviews have identified that generic measures of HSUVs may lack validity in adults with conditions that result in physical disability, there is little information available on the methods used to obtain HSUVs in children and adolescents with disabilities. The objectives of this systematic review are to describe the methods used to obtain HSUVs, including mode of administration and psychometric properties, and provide summary statistics for HSUVs among children and adolescents with disabilities.

METHODS AND ANALYSIS

The following databases will be searched from inception for English-language studies of any design: PubMed, PsychInfo, Medline, Scopus, CINAHL Plus, Econlit and EMBASE databases. Two reviewers will independently screen titles, abstracts and full text articles for studies reporting HSUVs and/or data on the psychometric properties of preference-based measures for children and adolescents with disabilities aged up to 19 years. Two reviewers will independently extract data items including descriptors of the study methods and sample, instruments used to capture HSUVs, summary statistics for HSUVs and items relating to the quality of reporting. A descriptive summary of results from included studies and summary statistics for HSUVs will be presented. If sufficient data is identified, we will pool summary statistics for HSUVs according to the method used to obtain the HSUV using a random effects model. In addition, we will explore the determinants of the HSUVs using a meta-regression.

ETHICS AND DISSEMINATION

Ethical approval will not be required as no original data will be collected as part of this review. The completed review will be submitted for publication in a peer-reviewed journal and presentation at conferences.

PROSPERO REGISTRATION NUMBER

CRD42018086574.

Dynamic transmission models for economic analysis applied to health care-associated infections: A review of the literature

BACKGROUND

Cost-effectiveness analyses are an important methodology in assessing whether a health care technology is suitable for widespread adoption. Common models used by economists, such as decision trees and Markov models, are appropriate for noninfectious diseases where treatment and exposure are independent. Diseases whose treatment and exposure are dependent require dynamic models to incorporate the nonlinear transmission effect. Two different types of models are often used for dynamic cost-effectiveness analyses: compartmental models and individual models. In this methodology-focused literature review, we describe each model type and summarize the literature associated with each using the example of health care-associated infections (HAIs).

METHODS

We conducted a review of the literature to identify dynamic cost-effectiveness analyses that examined interventions to prevent or treat HAIs. To be included in the review, studies needed to have each of 3 necessary components: involve economics, such as cost-effectiveness analysis and evidence of economic theory, use a dynamic transmission model, and examine HAIs.

RESULTS

Of the 9 articles published between 2005 and 2016 that met criteria to be included in our study, 3 used compartmental models and 6 used individual models.

CONCLUSIONS

Very few published studies exist that use dynamic transmission models to conduct economic analyses related to HAIs and even fewer studies have used these models to perform cost-effectiveness analyses.

Using environmental engineering to increase hand hygiene compliance: a cross-over study protocol

INTRODUCTION

Compliance with hand hygiene recommendations in hospital is typically less than 50%. Such low compliance inevitably contributes to hospital-acquired infections that negatively affect patients' well-being and hospitals' finances. The design of the present study is predicated on the assumption that most people who fail to clean their hands are not doing so intentionally, they just forget. The present study will test whether psychological priming can be used to increase the number of people who clean their hands on entering a ward. Here, we present the protocol for this study.

METHODS AND ANALYSIS

The study will use a randomised cross-over design. During the study, each of four wards will be observed during four conditions: olfactory prime, visual prime, both primes and neither prime. Each condition will be experienced for 42 days followed by a 7-day washout period (total duration of trial=189 days). We will record the number of people who enter each ward and whether they clean their hands during observation sessions, the amount of cleaning material used from the dispensers each week and the number of hospital-acquired infections that occur in each period. The outcomes will be compared using a regression analysis. Following the initial trail, the most effective priming condition will be rolled out for 3 months in all the wards.

ETHICS AND DISSEMINATION

Research ethics approval was obtained from the South Central-Oxford C Research Ethics Committee (16/SC/0554), the Health Regulatory Authority and the sponsor.

TRIAL REGISTRATION NUMBER

ISRCTN (15397624); Edge ID 86357.

Establishing benchmark EQ-5D-3L population health state utilities and identifying their correlates in Gansu Province, China

PURPOSES

Despite a flurry of cost utility analyses conducted in the Chinese population in recent years, a standard set of health state utilities (HSUs) for the Chinese population is lacking. The aims of this study were to (1) determine benchmark age- and sex-specific HSUs for a Chinese population, and (2) assess key correlates of HSUs in this population.

METHODS

Quality-of-life was evaluated using the validated EQ-5D-3L questionnaire. HSUs were calculated using data collected from Gansu Province (n = 9833). Overall differences in HSUs were analysed using linear regression and a two-tailed p value <0.05 was determined to be statistically significant. The minimal difference in weighted index was set at 0.074.

RESULTS

HSUs decreased with age in both males and females. Living in the non-capital areas, being separated/divorced/widowed or never married, being never educated, diagnosed with chronic disease, and no regular physical activity were associated with lower HSUs. HSUs for women were lower than for men in univariate regression analysis; however, no differences were found after adjusting for other covariates. In addition, the difference in HSU reached the level of minimal difference in weighted index for participants with chronic disease. HSUs for those who were diagnosed with chronic disease were 0.098 (0.092-0.104) lower than those without chronic disease.

CONCLUSIONS

This study reports HSUs for a Chinese population in Gansu and investigates the key correlates of HSUs in this population. In addition, the use of EQ-5D-3L in assessing population health is limited given the high ceiling effect and skewed HSUs.

Acupuncture for chronic pain and depression in primary care: a programme of research

Background

There has been an increase in the utilisation of acupuncture in recent years, yet the evidence base is insufficiently well established to be certain about its clinical effectiveness and cost-effectiveness. Addressing the questions related to the evidence base will reduce uncertainty and help policy- and decision-makers with regard to whether or not wider access is appropriate and provides value for money.

Aim

Our aim was to establish the most reliable evidence on the clinical effectiveness and cost-effectiveness of acupuncture for chronic pain by drawing on relevant evidence, including recent high-quality trials, and to develop fresh evidence on acupuncture for depression. To extend the evidence base we synthesised the results of published trials using robust systematic review methodology and conducted a randomised controlled trial (RCT) of acupuncture for depression.

Methods and results

We synthesised the evidence from high-quality trials of acupuncture for chronic pain, consisting of musculoskeletal pain related to the neck and low back, osteoarthritis of the knee, and headache and migraine, involving nearly 18,000 patients. In an individual patient data (IPD) pairwise meta-analysis, acupuncture was significantly better than both sham acupuncture (p < 0.001) and usual care (p < 0.001) for all conditions. Using network meta-analyses, we compared acupuncture with other physical therapies for osteoarthritis of the knee. In both an analysis of all available evidence and an analysis of a subset of better-quality trials, using aggregate-level data, we found acupuncture to be one of the more effective therapies. We developed new Bayesian methods for analysing multiple individual patient-level data sets to evaluate heterogeneous continuous outcomes. An accompanying cost-effectiveness analysis found transcutaneous electrical nerve stimulation (TENS) to be cost-effective for osteoarthritis at a threshold of £20,000 per quality-adjusted life-year when all trials were synthesised. When the analysis was restricted to trials of higher quality with adequate allocation concealment, acupuncture was cost-effective. In a RCT of acupuncture or counselling compared with usual care for depression, in which half the patients were also experiencing comorbid pain, we found acupuncture and counselling to be clinically effective and acupuncture to be cost-effective. For patients in whom acupuncture is inappropriate or unavailable, counselling is cost-effective.

Conclusion

We have provided the most robust evidence from high-quality trials on acupuncture for chronic pain. The synthesis of high-quality IPD found that acupuncture was more effective than both usual care and sham acupuncture. Acupuncture is one of the more clinically effective physical therapies for osteoarthritis and is also cost-effective if only high-quality trials are analysed. When all trials are analysed, TENS is cost-effective. Promising clinical and economic evidence on acupuncture for depression needs to be extended to other contexts and settings. For the conditions we have investigated, the drawing together of evidence on acupuncture from this programme of research has substantially reduced levels of uncertainty. We have identified directions for further research. Our research also provides a valuable basis for considering the potential role of acupuncture as a referral option in health care and enabling providers and policy-makers to make decisions based on robust sources of evidence.

Trial registration

Current Controlled Trials ISRCTN63787732.

Funding

The National Institute for Health Research Programme Grants for Applied Research programme.

Methods to construct a step-by-step beginner's guide to decision analytic cost-effectiveness modeling

BACKGROUND

Although guidance on good research practice in health economic modeling is widely available, there is still a need for a simpler instructive resource which could guide a beginner modeler alongside modeling for the first time.

AIM

To develop a beginner's guide to be used as a handheld guide contemporaneous to the model development process.

METHODS

A systematic review of best practice guidelines was used to construct a framework of steps undertaken during the model development process. Focused methods review supplemented this framework. Consensus was obtained among a group of model developers to review and finalize the content of the preliminary beginner's guide. The final beginner's guide was used to develop cost-effectiveness models.

RESULTS

Thirty-two best practice guidelines were data extracted, synthesized, and critically evaluated to identify steps for model development, which formed a framework for the beginner's guide. Within five phases of model development, eight broad submethods were identified and 19 methodological reviews were conducted to develop the content of the draft beginner's guide. Two rounds of consensus agreement were undertaken to reach agreement on the final beginner's guide. To assess fitness for purpose (ease of use and completeness), models were developed independently and by the researcher using the beginner's guide.

CONCLUSION

A combination of systematic review, methods reviews, consensus agreement, and validation was used to construct a step-by-step beginner's guide for developing decision analytical cost-effectiveness models. The final beginner's guide is a step-by-step resource to accompany the model development process from understanding the problem to be modeled, model conceptualization, model implementation, and model checking through to reporting of the model results.

Methods for network meta-analysis of continuous outcomes using individual patient data: a case study in acupuncture for chronic pain

BACKGROUND

Network meta-analysis methods, which are an extension of the standard pair-wise synthesis framework, allow for the simultaneous comparison of multiple interventions and consideration of the entire body of evidence in a single statistical model. There are well-established advantages to using individual patient data to perform network meta-analysis and methods for network meta-analysis of individual patient data have already been developed for dichotomous and time-to-event data. This paper describes appropriate methods for the network meta-analysis of individual patient data on continuous outcomes.

METHODS

This paper introduces and describes network meta-analysis of individual patient data models for continuous outcomes using the analysis of covariance framework. Comparisons are made between this approach and change score and final score only approaches, which are frequently used and have been proposed in the methodological literature. A motivating example on the effectiveness of acupuncture for chronic pain is used to demonstrate the methods. Individual patient data on 28 randomised controlled trials were synthesised. Consistency of endpoints across the evidence base was obtained through standardisation and mapping exercises.

RESULTS

Individual patient data availability avoided the use of non-baseline-adjusted models, allowing instead for analysis of covariance models to be applied and thus improving the precision of treatment effect estimates while adjusting for baseline imbalance.

CONCLUSIONS

The network meta-analysis of individual patient data using the analysis of covariance approach is advocated to be the most appropriate modelling approach for network meta-analysis of continuous outcomes, particularly in the presence of baseline imbalance. Further methods developments are required to address the challenge of analysing aggregate level data in the presence of baseline imbalance.

Determination of a Testing Threshold for Lumbar Puncture in the Diagnosis of Subarachnoid Hemorrhage after a Negative Head Computed Tomography: A Decision Analysis

OBJECTIVE

The objective was to determine the testing threshold for lumbar puncture (LP) in the evaluation of aneurysmal subarachnoid hemorrhage (SAH) after a negative head computed tomography (CT). As a secondary aim we sought to identify clinical variables that have the greatest impact on this threshold.

METHODS

A decision analytic model was developed to estimate the testing threshold for patients with normal neurologic findings, being evaluated for SAH, after a negative CT of the head. The testing threshold was calculated as the pretest probability of disease where the two strategies (LP or no LP) are balanced in terms of quality-adjusted life-years. Two-way and probabilistic sensitivity analyses (PSAs) were performed.

RESULTS

For the base-case scenario the testing threshold for performing an LP after negative head CT was 4.3%. Results for the two-way sensitivity analyses demonstrated that the test threshold ranged from 1.9% to 15.6%, dominated by the uncertainty in the probability of death from initial missed SAH. In the PSA the mean testing threshold was 4.3% (95% confidence interval = 1.4% to 9.3%). Other significant variables in the model included probability of aneurysmal versus nonaneurysmal SAH after negative head CT, probability of long-term morbidity from initial missed SAH, and probability of renal failure from contrast-induced nephropathy.

CONCLUSIONS

Our decision analysis results suggest a testing threshold for LP after negative CT to be approximately 4.3%, with a range of 1.4% to 9.3% on robust PSA. In light of these data, and considering the low probability of aneurysmal SAH after a negative CT, classical teaching and current guidelines addressing testing for SAH should be revisited.

Pharmacoeconomic comparison of aripiprazole once-monthly and paliperidone palmitate from a head-to-head clinical trial in schizophrenia: a US analysis

Schizophrenia presents a substantial clinical and economic burden to the health-care system. In QUAlity of LIfe with AbiliFY Maintena (QUALIFY), a randomized head-to-head study of aripiprazole once-monthly 400 mg (AOM 400) compared with paliperidone palmitate (PP; 78-234 mg/mo), AOM 400 demonstrated greater improvement in health-related quality of life and functioning in patients with stable schizophrenia. The present analysis used health economics assessment data collected during the QUALIFY study to determine the direct medical and pharmacy costs and the cost-effectiveness associated with each treatment over 6 months. Compared with those receiving PP, patients receiving AOM 400 incurred significantly lower direct total costs ($8908±186 vs $9675±190, p=0.005) and treatment costs ($7967±113 vs $8706±116, p<0.001). Effectiveness results in the subset of patients included in the cost analyses were similar to the overall population: mean (95% CI) improvement in Heinrichs-Carpenter Quality of Life Scale total score was greater with AOM 400 (5.97 [3.87; 8.08]) compared with PP (2.85 [0.56; 5.08]). Likewise, Clinical Global Impression-Severity improved more in the AOM 400 group (-0.59 [-0.71; -0.47]) compared with PP group (-0.37 [-0.46; -0.27]). Therefore, the analysis of data from stabilized patients with schizophrenia in the QUALIFY study indicated that AOM 400 is associated with lower health-care costs and greater effectiveness compared with PP and thus represents the economically dominant strategy.

Cost-effectiveness of the Cardiac Component of the Focused Assessment of Sonography in Trauma Examination in Blunt Trauma

BACKGROUND

Blunt cardiac injury severe enough to require surgical intervention (sBCI) is an exceedingly rare event occurring in approximately 1 out of every 1600 trauma patients. While performing the cardiac component of the Focused Assessment of Sonography in Trauma (cFAST) exam is effective in penetrating trauma, it is unclear whether it is of value in blunt trauma given the low prevalence of sBCI, the imperfect test characteristics of the FAST exam, and the rate of incidental pericardial effusion.

OBJECTIVE

The objective was to determine through decision analysis whether performing the cFAST exam is cost-effective in the evaluation of hypotensive and normotensive blunt trauma patients.

METHODS

We created two decision analytic models using commercially available software (TreeAgePro2011) to evaluate the cost-effectiveness of the cFAST in hypotensive (systolic blood pressure <90 mm Hg) and normotensive blunt trauma patients. Clinical probabilities were obtained from published data. Costs were estimated from Medicare reimbursement and charge data. The willingness-to-pay threshold was $50,000/quality-adjusted life-years (QALYs). Sensitivity analyses were performed over plausible ranges using available literature.

RESULTS

In hypotensive patients, for the base case scenario of a 34-year-old with blunt trauma, the cFAST strategy had a cost of $42,882.70 and an effectiveness of 25.3597 QALYs, whereas the no cFAST strategy had a cost of $42,753.52 and an effectiveness of 25.3532 QALYs. The incremental cost-effectiveness ratio (ICER) was $19,918/QALY. For normotensive patients the cFAST strategy had a cost of $18,331.03 and an effectiveness of 23.2817 QALYs, whereas the no cFAST strategy had a cost of $18,207.58 and an effectiveness of 23.2814 QALYs. The ICER was $465,867/QALY. In the sensitivity analyses, age, probability of death from sBCI with prompt treatment, and probability of sBCI were the main drivers of variability in the model outcomes.

CONCLUSIONS

The cFAST for blunt trauma is cost-effective for hypotensive but not for normotensive patients. The ICER for hypotensive patients was more than 20 times higher than the ICER for normotensive patients. Our results suggest that performing the cFAST exam may not be an effective use of resources in normotensive blunt trauma patients.

Cost-effectiveness of screening for HLA-A*31:01 prior to initiation of carbamazepine in epilepsy

OBJECTIVE

Carbamazepine causes severe cutaneous adverse drug reactions that may be predicted by the presence of the HLA-A*31:01 allele in northern European populations. There is uncertainty as to whether routine testing of patients with epilepsy is cost-effective. We conducted an economic evaluation of HLA-A*31:01 testing from the perspective of the National Health Service (NHS) in the United Kingdom.

METHODS

A short-term, decision analytic model was developed to estimate the outcomes and costs associated with a policy of routine testing (with lamotrigine prescribed for patients who test positive) versus the current standard of care, which is carbamazepine prescribed without testing. A Markov model was used to estimate total costs and quality-adjusted life-years (QALYs) over a lifetime to account for differences in drug effectiveness and the long-term consequences of adverse drug reactions.

RESULTS

Testing reduced the expected rate of cutaneous adverse drug reactions from 780 to 700 per 10,000 patients. The incremental cost-effectiveness ratio for pharmacogenetic testing versus standard care was £12,808 per QALY gained. The probability of testing being cost-effective at a threshold of £20,000 per QALY was 0.80, but the results were sensitive to estimated remission rates for alternative antiepileptic drugs (AEDs).

SIGNIFICANCE

Routine testing for HLA-A*31:01 in order to reduce the incidence of cutaneous adverse drug reactions in patients being prescribed carbamazepine for epilepsy is likely to represent a cost-effective use of health care resources.

Output correlations in probabilistic models with multiple alternatives

A comprehensive cost-effectiveness decision model will often go beyond a one-to-one comparison and will include a number of competing alternatives. Only a simultaneous assessment of all relevant treatment alternatives avoids comparing average cost-effectiveness ratios and allows a truly incremental analysis. Two issues arise if the analysis is probabilistic, namely, the occurrence of output correlations and difficulty in presenting the results. I have examined the role of output correlations using a screening model with eight alternatives and have shown that specifically cost-cost and quality-adjusted life years (QALY)-QALY correlations between alternatives have a major impact on decision uncertainty, as measured by the probability of the cost-effectiveness and expected value of perfect information. In particular, the latter strongly depends on between-alternative output correlations. This analysis shows that both the expected value of perfect information plots and acceptability curves/frontiers are sensitive to output correlations and thus appropriate for presentation of multiple alternatives. To avoid confusing statistical significance and economic importance I propose that acceptability curves be augmented by incremental net-benefit density plots at a given willingness to pay threshold.

Health state utility values for diabetic retinopathy: protocol for a systematic review and meta-analysis

BACKGROUND

People with diabetic retinopathy tend to have lower levels of health-related quality of life than individuals with no retinopathy. Strategies for screening and treatment have been shown to be cost-effective. In order to reduce the bias in cost-effectiveness estimates, systematic reviews of health state utility values (HSUVs) are crucial for health technology assessment and the development of decision analytic models. A review and synthesis of HSUVs for the different stages of disease progression in diabetic retinopathy has not previously been conducted.

METHODS/DESIGN

We will conduct a systematic review of the available literature that reports HSUVs for people with diabetic retinopathy, in correspondence with current stage of disease progression and/or visual acuity. We will search Medline, EMBASE, Web of Science, Cost-Effectiveness Analysis Registry, Centre for Reviews and Dissemination Database, and EconLit to identify relevant English-language articles. Data will subsequently be synthesized using linear mixed effects modeling meta-regression. Additionally, reported disease severity classifications will be mapped to a four-level grading scale for diabetic retinopathy.

DISCUSSION

The systematic review and meta-analysis will provide important evidence for future model-based economic evaluations of technologies for diabetic retinopathy. The meta-regression will enable the estimation of utility values at different disease stages for patients with particular characteristics and will also highlight where the design of the study and HSUV instrument have influenced the reported utility values. We believe this protocol to be the first of its kind to be published.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42014012891.

Comparative efficiency research (COMER): meta-analysis of cost-effectiveness studies

BACKGROUND

The aim of this study was to create a new meta-analysis method for cost-effectiveness studies using comparative efficiency research (COMER).

METHODS

We built a new score named total incremental net benefit (TINB), with inverse variance weighting of incremental net benefits (INB). This permits determination of whether an alternative is cost-effective, given a specific threshold (TINB > 0 test). Before validation of the model, the structure of dependence between costs and quality-adjusted life years (QoL) was analysed using copula distributions. The goodness-of-fit of a Spanish prospective observational study (n = 498) was analysed using the Independent, Gaussian, T, Gumbel, Clayton, Frank and Placket copulas. Validation was carried out by simulating a copula distribution with log-normal distribution for costs and gamma distribution for disutilities. Hypothetical cohorts were created by varying the sample size (n: 15-500) and assuming three scenarios (1-cost-effective; 2-non-cost-effective; 3-dominant). The COMER result was compared to the theoretical result according to the incremental cost-effectiveness ratio (ICER) and the INB, assuming a margin of error of 2,000 and 500 monetary units, respectively.

RESULTS

The Frank copula with positive dependence (-0.4279) showed a goodness-of-fit sufficient to represent costs and QoL (p-values 0.524 and 0.808). The theoretical INB was within the 95% confidence interval of the TINB, based on 15 individuals with a probability > 80% for scenarios 1 and 2, and > 90% for scenario 3. The TINB > 0 test with 15 individuals showed p-values of 0.0105 (SD: 0.0411) for scenario 1, 0.613 (SD: 0.265) for scenario 2 and < 0.0001 for scenario 3.

CONCLUSIONS

COMER is a valid tool for combining cost-effectiveness studies and may be of use to health decision makers.

Network meta-analysis of (individual patient) time to event data alongside (aggregate) count data

BACKGROUND

Network meta-analysis methods extend the standard pair-wise framework to allow simultaneous comparison of multiple interventions in a single statistical model. Despite published work on network meta-analysis mainly focussing on the synthesis of aggregate data, methods have been developed that allow the use of individual patient-level data specifically when outcomes are dichotomous or continuous. This paper focuses on the synthesis of individual patient-level and summary time to event data, motivated by a real data example looking at the effectiveness of high compression treatments on the healing of venous leg ulcers.

METHODS

This paper introduces a novel network meta-analysis modelling approach that allows individual patient-level (time to event with censoring) and summary-level data (event count for a given follow-up time) to be synthesised jointly by assuming an underlying, common, distribution of time to healing. Alternative model assumptions were tested within the motivating example. Model fit and adequacy measures were used to compare and select models.

RESULTS

Due to the availability of individual patient-level data in our example we were able to use a Weibull distribution to describe time to healing; otherwise, we would have been limited to specifying a uniparametric distribution. Absolute effectiveness estimates were more sensitive than relative effectiveness estimates to a range of alternative specifications for the model.

CONCLUSIONS

The synthesis of time to event data considering individual patient-level data provides modelling flexibility, and can be particularly important when absolute effectiveness estimates, and not just relative effect estimates, are of interest.

Cost-effectiveness of insulin degludec compared with insulin glargine for patients with type 2 diabetes treated with basal insulin - from the UK health care cost perspective

AIMS

The aim of this analysis was to evaluate the cost-effectiveness of insulin degludec (IDeg) versus insulin glargine (IGlar) in adults with type 2 diabetes mellitus (T2DM) who are considered appropriate for treatment with a basal insulin analogue, using a short-term economic model.

METHODS

Meta-analysis data from three phase III clinical studies were used to populate a simple and transparent short-term model. The costs and effects of treatment with IDeg versus IGlar were calculated over a 12-month period. The analysis was conducted from the perspective of the UK National Health Service. Sensitivity analyses were conducted to assess the degree of uncertainty surrounding the results.

RESULTS

IDeg is a cost-effective treatment option versus IGlar in patients with T2DM using basal insulin. Base case incremental cost-effectiveness ratios (ICERs) were estimated at £15,795 per quality-adjusted life-year (QALY) and £13,078 per QALY, which are below commonly accepted thresholds for cost-effectiveness. Sensitivity analyses demonstrated that hypoglycaemia event rates had an important effect on the results. With higher event rates for non-severe hypoglycaemia IDeg was less costly and more effective than IGlar (dominant). Conversely, using lower event rates for severe hypoglycaemia generated higher ICERs. Using hypoglycaemia rates from a subgroup of patients who experienced ≥1 hypoglycaemic event per year IDeg was highly cost-effective versus IGlar; with estimated ICERS of £4887 and £2625 per QALY.

CONCLUSIONS

This short-term modelling approach allows the economic evaluation of newer insulin analogues when advanced long-term modelling based on HbA1c differences is inappropriate. For patients with T2DM who are considered appropriate for treatment with a basal insulin analogue, IDeg is a cost-effective treatment option compared with IGlar and offers additional benefits to subgroups of patients, such as those suffering from recurrent hypoglycaemia.

Squinting through layers of fog: assessing the cost effectiveness of treatments for multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a chronic neurological disorder, which can lead to a wide range of disabling symptoms. The condition has a significant negative impact on health-related quality of life, and the economic cost of the disease is substantial. Decision-making regarding treatments for MS, and particularly disease-modifying interventions, has been hampered by limitations in the data and evaluative framework for assessing their cost effectiveness. Whilst attention has been drawn to these weaknesses, the scope and extent of the challenges in this area have not been fully set out to date.

AIMS

The aims of this review were to identify all published economic evaluations of MS treatments in order to provide a statement on the scope and characteristics of the cost-effectiveness literature in the area of MS and to provide a basis on which to suggest practical recommendations for future research to aid decision-making.

METHOD

A systematic search was undertaken to identify economic evaluations of treatments for people with MS published in English up to December 2011. Included studies were reviewed to provide a comprehensive description of the characteristics of the currently applied framework for cost effectiveness in MS, with the following key methodological components considered: methods for estimating disease progression, the impact of treatment and health outcomes and costs associated with MS.

RESULTS

Thirty-seven papers were identified. Most studies (n = 32) were model-based evaluations of disease-modifying drugs. All models used disability stages defined by the Expanded Disability Status Scale (EDSS) to characterise disease progression, and the impact of treatment was based on data from clinical trials and epidemiological cohorts. Outcomes were primarily based on quality-adjusted life-years (n = 22) and/or related to relapse (n = 14). Estimates for health state utility values (HSUVs), costs and the impact of treatment on the course of MS varied considerably between studies, depending on the data sources used and the methods used to incorporate data into models. The scope of the studies was narrow, with a sparsity of economic evaluations of symptomatic and/or non-pharmacological interventions; exclusion of direct non-medical, indirect and informal care costs from analyses; and a narrow view of the potential impact of treatment, concentrating on disability, according to the EDSS, and relapses. In addition, there were issues concerning how to capture losses in HSUVs due to relapses in a way that reflects their salience to people with MS, the wide variation in costs and outcomes from different sources and from potentially unrepresentative samples and modelling disease progression from natural history data from over 30 years ago.

CONCLUSION

There are many complexities for those designing and reporting cost-effectiveness studies of treatments for MS. Analysts, and ultimately decision makers, face multiple data and methodological challenges. Policy makers, technology developers, clinicians, patients and researchers need to acknowledge and address these challenges and to consider recommendations that will improve the current scenario. There is a need for further research that can constructively inform decision-making regarding the funding of treatments for MS.

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.