Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological review of health technology assessments

Barriers, enablers, benefits, and drawbacks to point-of-care testing: a survey of the general practice out-of-hours service in Scotland

BACKGROUND

The general practice out-of-hours (GPOOH) service is under pressure to treat more patients in less time, while reducing referrals and minimising diagnostic errors. Point-of-care (POC) testing involves rapid clinical tests that can be used to generate results during the consultation, and has the potential to facilitate managing these competing demands safely.

AIM

To describe current availability of POC tests in GPOOH in Scotland, and identify barriers, enablers, benefits, and drawbacks to its use.

DESIGN & SETTING

Cross-sectional mixed-methods study, which surveyed opinions of clinicians working in the GPOOH service in NHS Scotland.

METHOD

An electronic questionnaire was developed, designed, piloted, and distributed to clinicians, which had closed questions and areas for free text.

RESULTS

In total, 142 responses were received. Urine dipstick testing (99.2%), pregnancy tests (98.5%), oxygen saturation (97.7%), and blood glucose testing (93.9%), were the only POC tests commonly available in GPOOH in NHS Scotland. There was strongest support for the provision of POC tests, particularly C-reactive protein (CRP; 79.4%), strep A (76.0%), and D-dimer (75.2%). Responders felt that POC tests would improve confidence (92.3%) and safety (89.8%) surrounding clinical decision making, improve patient satisfaction (80.6%), and reduce hospital and secondary care referrals (77.5%). Barriers to POC test use were availability of the test kits and machines (94.5%), training requirements on how to use the machine (71.1%) and interpret results (56.3%), and time to do the test (62.0%).

CONCLUSION

Few POC tests are in regular use in GPOOH in Scotland. GPOOH clinicians are supportive of using POC testing. They identified a number of benefits to its use, with very few drawbacks. Increased provision of POC testing in GPOOH in NHS Scotland should be considered urgently.

Evidence Synthesis and Linkage for Modelling the Cost-Effectiveness of Diagnostic Tests: Preliminary Good Practice Recommendations

OBJECTIVES

To develop preliminary good practice recommendations for synthesising and linking evidence of treatment effectiveness when modelling the cost-effectiveness of diagnostic tests.

METHODS

We conducted a targeted review of guidance from key Health Technology Assessment (HTA) bodies to summarise current recommendations on synthesis and linkage of treatment effectiveness evidence within economic evaluations of diagnostic tests. We then focused on a specific case study, the cost-effectiveness of troponin for the diagnosis of myocardial infarction, and reviewed the approach taken to synthesise and link treatment effectiveness evidence in different modelling studies.

RESULTS

The Australian and UK HTA bodies provided advice for synthesising and linking treatment effectiveness in diagnostic models, acknowledging that linking test results to treatment options and their outcomes is common. Across all reviewed models for the case study, uniform test-directed treatment decision making was assumed, i.e., all those who tested positive were treated. Treatment outcome data from a variety of sources, including expert opinion, were utilised for linked clinical outcomes. Preliminary good practice recommendations for data identification, integration and description are proposed.

CONCLUSION

Modelling the cost-effectiveness of diagnostic tests poses unique challenges in linking evidence on test accuracy to treatment effectiveness data to understand how a test impacts patient outcomes and costs. Upfront consideration of how a test and its results will likely be incorporated into patient diagnostic pathways is key to exploring the optimal design of such models. We propose some preliminary good practice recommendations to improve the quality of cost-effectiveness evaluations of diagnostics tests going forward.

Evaluating the Value for Money of Precision Medicine from Early Cycle to Market Access: A Comprehensive Review of Approaches and Challenges

OBJECTIVES

This study aimed to perform a comprehensive review of modeling approaches and methodological and policy challenges in the economic evaluation (EE) of precision medicine (PM) across clinical stages.

METHODS

First, a systematic review was performed to assess the approaches of EEs in the past 10 years. Next, a targeted review of methodological articles was conducted for methodological and policy challenges in performing EEs of PM. All findings were synthesized into a structured framework that focused on patient population, Intervention, Comparator, Outcome, Time, Equity and ethics, Adaptability and Modeling aspects, named the "PICOTEAM" framework. Finally, a stakeholder consultation was conducted to understand the major determinants of decision making in PM investment.

RESULTS

In 39 methodological articles, we identified major challenges to the EE of PM. These challenges include that PM applications involve complex and evolving clinical decision space, that clinical evidence is sparse because of small subgroups and complex pathways in PM settings, a one-time PM application may have lifetime or intergenerational impacts but long-term evidence is often unavailable, and that equity and ethics concerns are exceptional. In 275 EEs of PM, current approaches did not sufficiently capture the value of PM compared with targeted therapies, nor did they differentiate Early EEs from Conventional EEs. Finally, policy makers perceived the budget impact, cost savings, and cost-effectiveness of PM as the most important determinants in decision making.

CONCLUSIONS

There is an urgent need to modify existing guidelines or develop a new reference case that fits into the new healthcare paradigm of PM to guide decision making in research and development and market access.

A Cost-effectiveness Analysis of iGlarLixi Versus IDegAsp and Appropriate Price Exploration of iGlarLixi for Type 2 Diabetes Mellitus Patients in China

BACKGROUND AND OBJECTIVE

The efficacy and safety of iGlarLixi, a fixed-ratio combination (FRC) of basal insulin glargine plus lixisenatide, have been demonstrated in type 2 diabetes mellitus (T2DM) patients. However, no relevant economic analysis of iGlarLixi has been done in China. Thus, the primary objective of this study is to evaluate the cost effectiveness of iGlarLixi versus IDegAsp in Chinese T2DM patients, and then back-calculate the appropriate drug price of iGlarLixi to support its pricing after listing in China.

METHODS

The United Kingdom Prospective Diabetes Study Outcome Model 2 (UKPDS OM2) was applied to estimate lifetime health and economic outcomes from the Chinese health-care system perspective. As no head-to-head comparison data are currently available, the baseline cohort characteristics and the initial clinical data for iGlarLixi were derived from the randomized LixiLan-L-China trial. The relative treatment effects for IDegAsp were based on an indirect treatment comparison. Due to the unavailability of iGlarLixi pricing data, the annual medication cost of iGlarLixi was assumed to be equal to that of IDegAsp at the beginning of the study. Afterwards, a break-even analysis using comparator drug price and the willingness-to-pay (WTP) threshold was performed to back-calculate the appropriate drug price of iGlarLixi. One-way sensitivity analysis, scenario analysis and probabilistic sensitivity analysis (PSA) were conducted to assess the robustness of the model.

RESULTS

Based on the initial assumption of equal annual medication cost of iGlarLixi and IDegAsp, iGlarLixi was cost effective compared to IDegAsp with an incremental cost-effectiveness ratio (ICER) far below the WTP threshold in Chinese T2DM patients. From the back calculation for the price of iGlarLixi, the annual medication cost of iGlarLixi was $656.96 and $1075.96 to obtain an ICER of iGlarLixi versus IDegAsp close to 1 × GDP and 3 × GDP, respectively. When the discount rate was changed from the base value to 8% (the most sensitive parameter to the model results in one-way sensitivity analysis), the ICER was nearly equal to 1 × GDP and 3 × GDP with the annual medication cost of iGlarLixi decreasing to $590.41 and $865.03, respectively. Thus, iGlarLixi was dominant over IDegAsp with an annual medication cost of $590.41 to $865.03. The findings were robust to one-way sensitivity analysis, PSA and scenario analysis.

CONCLUSION

This long-term cost-effectiveness analysis in Chinese T2DM patients indicates that iGlarLixi, assuming equal price to IDegAsp, is cost-effective versus IDegAsp with an ICER far below the WTP threshold. With 1 × GDP and 3 × GDP threshold set we back-calculate the appropriate annual medication cost of iGlarLixi to be $590.41 to $865.03, respectively.

Health technology assessment of diagnostic tests: a state of the art review of methods guidance from international organizations

OBJECTIVES

To identify which international health technology assessment (HTA) agencies are undertaking evaluations of medical tests, summarize commonalities and differences in methodological approach, and highlight examples of good practice.

METHODS

A methodological review incorporating: systematic identification of HTA guidance documents mentioning evaluation of tests; identification of key contributing organizations and abstraction of approaches to all essential HTA steps; summary of similarities and differences between organizations; and identification of important emergent themes which define the current state of the art and frontiers where further development is needed.

RESULTS

Seven key organizations were identified from 216 screened. The main themes were: elucidation of claims of test benefits; attitude to direct and indirect evidence of clinical effectiveness (including evidence linkage); searching; quality assessment; and health economic evaluation. With the exception of dealing with test accuracy data, approaches were largely based on general approaches to HTA with few test-specific modifications. Elucidation of test claims and attitude to direct and indirect evidence are where we identified the biggest dissimilarities in approach.

CONCLUSIONS

There is consensus on some aspects of HTA of tests, such as dealing with test accuracy, and examples of good practice which HTA organizations new to test evaluation can emulate. The focus on test accuracy contrasts with universal acknowledgment that it is not a sufficient evidence base for test evaluation. There are frontiers where methodological development is urgently required, notably integrating direct and indirect evidence and standardizing approaches to evidence linkage.

Fast Methods for Drug Approval: Research Perspectives for Pandemic Preparedness

Public heath emergencies such as the outbreak of novel infectious diseases represent a major challenge for drug regulatory bodies, practitioners, and scientific communities. In such critical situations drug regulators and public health practitioners base their decisions on evidence generated and synthesised by scientists. The urgency and novelty of the situation create high levels of uncertainty concerning the safety and effectiveness of drugs. One key tool to mitigate such emergencies is pandemic preparedness. There seems to be, however, a lack of scholarly work on methodology for assessments of new or existing drugs during a pandemic. Issues related to risk attitudes, evidence production and evidence synthesis for drug approval require closer attention. This manuscript, therefore, engages in a conceptual analysis of relevant issues of drug assessment during a pandemic. To this end, we rely in our analysis on recent discussions in the philosophy of science and the philosophy of medicine. Important unanswered foundational questions are identified and possible ways to answer them are considered. Similar problems often have similar solutions, hence studying similar situations can provide important clues. We consider drug assessments of orphan drugs and drug assessments during endemics as similar to drug assessment during a pandemic. Furthermore, other scientific fields which cannot carry out controlled experiments may guide the methodology to draw defeasible causal inferences from imperfect data. Future contributions on methodologies for addressing the issues raised here will indeed have great potential to improve pandemic preparedness.

The comparative interrupted time series design for assessment of diagnostic impact: methodological considerations and an example using point-of-care C-reactive protein testing

BACKGROUND

In diagnostic evaluation, it is necessary to assess the clinical impact of a new diagnostic as well as its diagnostic accuracy. The comparative interrupted time series design has been proposed as a quasi-experimental approach to evaluating interventions. We show how it can be used in the design of a study to evaluate a point-of-care diagnostic test for C-reactive protein in out-of-hours primary care services, to guide antibiotic prescribing among patients presenting with possible respiratory tract infection. This study consisted of a retrospective phase that used routinely collected monthly antibiotic prescribing data from different study sites, and a prospective phase in which antibiotic prescribing rates were monitored after the C-reactive protein diagnostic was introduced at some of the sites.

METHODS

Of 8 study sites, 3 were assigned to receive the diagnostic and 5 were assigned as controls. We obtained retrospective monthly time series of respiratory tract targeted antibiotic prescriptions at each site. Separate ARIMA models at each site were used these to forecast monthly prescription counts that would be expected in the prospective phase, using simulation to obtain a set of 1-year predictions alongside their standard errors. We show how these forecasts can be combined to test for a change in prescription rates after introduction of the diagnostic and estimate power to detect this change.

RESULTS

Fitted time series models at each site were stationary and showed second-order annual seasonality, with a clear December peak in prescriptions, although the timing and extent of the peak varied between sites and between years. Mean one-year predictions of antibiotic prescribing rates based on the retrospective time series analysis differed between sites assigned to receive the diagnostic and those assigned to control. Adjusting for the trend in the retrospective time series at each site removed these differences.

CONCLUSIONS

Quasi-experimental designs such as comparative interrupted time series can be used in diagnostic evaluation to estimate effect sizes before conducting a full randomised controlled trial or if a randomised trial is infeasible. In multi-site studies, existing retrospective data should be used to adjust for underlying differences between sites to make outcome data from different sites comparable, when possible.

Health economic evaluations of medical tests: Translating laboratory information into value - A case study example

Health-care providers and funders are focused on identifying value in all their services and that includes laboratories. This means that in order to gain a share of scarce resources, laboratory professionals must also understand and assess the value of tests and that includes their economic impact. This can be assessed using health economic modelling tools which, when used in conjunction with a detailed value proposition for the test, can translate laboratory information into value. While a variety of health economic assessment tools are available, this review will focus on the use of decision analytic models which essentially compare the outcomes from pathways with and without the new test, the value of which is being assessed. A step-by-step framework is provided to guide laboratory professionals through the essential steps of conducting the evaluation. Initial steps include mapping the clinical pathway, understanding the goal of the evaluation, identifying the key stakeholders and their needs and determining a suitable analytical model. Following collection of the actual data, the validity of the model must be checked, and the robustness of the outcomes tested through sensitivity analysis. The last step is to translate the findings into measures of value which can then inform appropriate decisions by the stakeholders. This review of basic health economic modelling should enable laboratory professionals to have an understanding of how modelling can be applied to tests in their own environment and help deliver their potential value.

Who Conducts Health Economic Evaluations of Laboratory Tests? A Scoping Review

Background

Health economic evaluations (HEEs) are effectively used to inform decision making in healthcare. We sought to assess the level of involvement of laboratory professionals (LPs) in HEEs of laboratory tests.

Methods

A systematic literature search was conducted in Medline (2013 to November 28, 2018) for original articles reporting HEEs of medical laboratory tests. Eligible studies were characterized by indication, utilization, region, setting, study design, primary outcome measures, and sponsorship. Authors were classified based on stated affiliation as clinician, scientist, public health expert, or LP.

Results

In total, 140 HEEs were included in the study, of which 24 (17.1%) had contributions from LPs. Studies were primarily focused on infectious disease (n = 68), oncology (n = 23), and cardiovascular disease (n = 16). Cost-utility or cost-effectiveness analyses (n = 117) were the most frequent study types, with effectiveness measured mainly in terms of quality-adjusted life-years (n = 57) and detected cases (n = 41). Overall, 76% of HEEs followed a social or health system perspective, whereas 15% took a hospital viewpoint. Partial or full funding was received from public health organizations or industry in 39% and 16% of studies, respectively. The involvement of LPs was associated with test utilization, secondary care, analytic perspective, and an immediate time horizon (all P < 0.05). Quality of studies was found to be lower in HEEs coauthored by LPs.

Conclusion

Multidisciplinary collaboration is essential to understanding the complexity of clinical pathways. HEEs are used effectively to inform healthcare decision making. The involvement of LPs in HEEs is low. This implies that laboratory expertise is frequently not considered in decision processes.

The Lean and Agile Multi-dimensional Process (LAMP) - a new framework for rapid and iterative evidence generation to support health-care technology design and development

Introduction: Health technology assessments (HTA) are tools for policymaking and resource allocation. Early HTAs are increasingly used in design and development of new technologies. Conducting early HTAs is challenging, due to a lack of evidence and significant uncertainties in the technology and the market. A multi-disciplinary approach is considered essential. However, an operational framework that can enable the integration of multi-dimensional evidence into commercialization remains lacking.Areas covered: We developed the Lean and Agile Multi-dimensional Process (LAMP), an early HTA framework, for embedding commercial decision-making in structured evidence generation activities, divided into phases. Diverse evidence in unmet needs, user acceptance, cost-effectiveness, and market competitiveness are being generated in increasing depth. This supports the emergence of design and value propositions that align technology capabilities and clinical and user needs.Expert opinion: We have been applying LAMP to working with medical device and diagnostic industry in the UK. The framework can be adapted to suit different technologies, decision needs, time scales, and resources. LAMP offers a practical solution to the multi-disciplinary approach. Methodologists drive the process by performing evidence generation and synthesis as and by enabling interactions between manufacturers, designers, clinicians, and other key stakeholders.

E-Synthesis: A Bayesian Framework for Causal Assessment in Pharmacosurveillance

Background: Evidence suggesting adverse drug reactions often emerges unsystematically and unpredictably in form of anecdotal reports, case series and survey data. Safety trials and observational studies also provide crucial information regarding the (un-)safety of drugs. Hence, integrating multiple types of pharmacovigilance evidence is key to minimising the risks of harm.

Methods: In previous work, we began the development of a Bayesian framework for aggregating multiple types of evidence to assess the probability of a putative causal link between drugs and side effects. This framework arose out of a philosophical analysis of the Bradford Hill Guidelines. In this article, we expand the Bayesian framework and add “evidential modulators,” which bear on the assessment of the reliability of incoming study results. The overall framework for evidence synthesis, “E-Synthesis”, is then applied to a case study.

Results: Theoretically and computationally, E-Synthesis exploits coherence of partly or fully independent evidence converging towards the hypothesis of interest (or of conflicting evidence with respect to it), in order to update its posterior probability. With respect to other frameworks for evidence synthesis, our Bayesian model has the unique feature of grounding its inferential machinery on a consolidated theory of hypothesis confirmation (Bayesian epistemology), and in allowing any data from heterogeneous sources (cell-data, clinical trials, epidemiological studies), and methods (e.g., frequentist hypothesis testing, Bayesian adaptive trials, etc.) to be quantitatively integrated into the same inferential framework.

Conclusions: E-Synthesis is highly flexible concerning the allowed input, while at the same time relying on a consistent computational system, that is philosophically and statistically grounded. Furthermore, by introducing evidential modulators, and thereby breaking up the different dimensions of evidence (strength, relevance, reliability), E-Synthesis allows them to be explicitly tracked in updating causal hypotheses.

Value For Money In The Treatment Of Patients With Type 2 Diabetes Mellitus: Assessing The Long-Term Cost-Effectiveness Of IDegLira Versus iGlarLixi In Italy

Objective

Italian treatment guidelines for type 2 diabetes mellitus (T2DM) target good glycemic control but acknowledge the associated risk of hypoglycemia. Unlike traditional antidiabetic therapies, modern treatment options such as fixed-ratio combinations of basal insulin and glucagon-like peptide 1 receptor agonists are associated with improved glycemic control, reduced body weight and low risk of hypoglycemia. The cost-effectiveness of the fixed-ratio combinations of basal insulin and glucagon-like peptide 1 receptor agonists IDegLira and iGlarLixi was assessed for Italy in patients with T2DM uncontrolled on basal insulin, to evaluate how short-term clinical benefits translate into long-term health economic outcomes.

Methods

The IQVIA CORE Diabetes Model was used to project clinical and economic outcomes over patient lifetimes. Treatment effects were sourced from an indirect treatment comparison. The analysis captured direct medical costs (expressed in 2017 Euros) from the perspective of the Italian National Health Service (NHS) and patient-related quality of life. Sensitivity analyses were performed.

Results

IDegLira was associated with gains of 0.09 life years and 0.13 quality-adjusted life years (QALYs) relative to iGlarLixi, due to a lower cumulative incidence and delayed onset of diabetes-related complications. IDegLira was associated with an incremental cost of EUR 930 over patient lifetimes, leading to an incremental cost-effectiveness ratio of EUR 7,386 per QALY gained.

Conclusion

Over the lifetime of patients with T2DM uncontrolled on basal insulin, IDegLira was associated with improved clinical outcomes at higher costs relative to iGlarLixi. At a willingness-to-pay threshold of EUR 30,000 per QALY gained, IDegLira was considered to be cost-effective versus iGlarLixi from the perspective of the Italian NHS.

Use of Decision Modelling in Economic Evaluations of Diagnostic Tests: An Appraisal and Review of Health Technology Assessments in the UK

Diagnostic tests play an important role in the clinical decision-making process by providing information that enables patients to be identified and stratified to the most appropriate treatment and management strategies. Decision analytic modelling facilitates the synthesis of evidence from multiple sources to evaluate the cost effectiveness of diagnostic tests. This study critically reviews the methods used to model the cost effectiveness of diagnostic tests in UK National Institute for Health Research (NIHR) Health Technology Assessment (HTA) reports. UK NIHR HTA reports published between 2009 and 2018 were screened to identify those reporting an economic evaluation of a diagnostic test using decision analytic modelling. Existing decision modelling checklists were identified in the literature and a modified checklist tailored to diagnostic economic evaluations was developed, piloted and used to assess the diagnostic models in HTA reports. Of 728 HTA reports published during the study period, 55 met the inclusion criteria. The majority of models performed well with a clearly defined decision problem and analytical perspective (89% of HTAs met the criterion). The model structure usually reflected the care pathway and progression of the health condition. However, there are areas requiring improvement. These are predominantly systematic identification of treatment effects (20% met), poor selection of comparators (50% met) and assumed independence of tests used in sequence (32% took correlation between sequential tests into consideration). The complexity and constraints of performing decision analysis of diagnostic tests on costs and health outcomes makes it particularly challenging and, as a result, quality issues remain. This review provides a comprehensive assessment of modelling in HTA reports, highlights problems and gives recommendations for future diagnostic modelling practice.

Treating Patients with Type 2 Diabetes Mellitus Uncontrolled on Basal Insulin in the Czech Republic: Cost-Effectiveness of IDegLira Versus iGlarLixi

INTRODUCTION

Few patients with type 2 diabetes mellitus (T2DM) achieve recommended glycemic control targets in the Czech Republic. Novel therapies, such as fixed-ratio combinations of basal insulin plus glucagon-like peptide-1 receptor agonists, may contribute to better glycemic control. In the analysis presented here, the present analysis assessed the long-term cost-effectiveness of two fixed-ratio combinations, IDegLira (insulin degludec/liraglutide) and iGlarLixi (insulin glargine/lixisenatide), for the treatment of patients with T2DM inadequately controlled with basal insulin from a healthcare payer perspective in the Czech Republic.

METHODS

A cost-effectiveness analysis was performed over patient lifetimes using the IQVIA CORE Diabetes Model. Treatment effects were obtained from an indirect treatment comparison as no head-to-head data for IDegLira versus iGlarLixi are currently available. IDegLira was compared with two iGlarLixi pens (100 U/mL insulin glargine + 33 μg/mL and 50 μg/mL of lixisenatide, respectively). Direct medical costs associated with pharmaceutical interventions, screening and diabetes-related complications were captured. Deterministic and probabilistic sensitivity analyses were performed.

RESULTS

IDegLira was associated with gains in life expectancy of 0.11 years and in quality-adjusted life expectancy of 0.14 quality-adjusted life-years (QALYs) versus iGlarLixi, due to a lower cumulative incidence and delayed onset of diabetes-related complications. IDegLira was also associated with higher projected costs due to higher acquisition costs; however, these were partially offset by cost savings from avoided complications. IDegLira was associated with incremental cost-effectiveness ratios of Czech Koruna (CZK) 695,998 and CZK 348,323 per QALY gained versus iGlarLixi pens containing 33 and 50 μg/mL of lixisenatide, respectively. These ratios were below the commonly used willingness-to-pay threshold of CZK 1,200,000 per QALY gained.

CONCLUSION

The present analysis indicated that IDegLira was associated with clinical benefits relative to iGlarLixi over patient lifetimes and was likely to be cost-effective in the treatment of patients with T2DM uncontrolled on basal insulin in the Czech Republic.

FUNDING

Novo Nordisk. Plain language summary is available for this article.

Establishing the Value of Diagnostic and Prognostic Tests in Health Technology Assessment

In recent years, Health Technology Assessment (HTA) processes specific to diagnostics and prognostic tests have been created in response to the increased pressure on health systems to decide not only which tests should be used in practice but also the best way to proceed, clinically, from the information they provide. These technologies differ in the way value is accrued to the population of users, depending critically on the value of downstream health care choices. This paper defines an analytical framework for establishing the value of diagnostic and prognostic tests for HTA in a way that is consistent with methods used for the evaluation of other health care technologies. It assumes a linked-evidence approach where modeling is required, and incorporates considerations regarding several different areas of policy, such as personalized medicine. We initially focus on diagnostic technologies with dichotomous results, and then extend the framework by considering diagnostic tests that provide more complex information, such as continuous measures (for example, blood glucose measurements) or multiple categories (such as tumor classification systems). We also consider how the methods of assessment differ for prognostic information or for diagnostics without a reference standard. Throughout, we propose innovative graphical ways of summarizing the results of such complex assessments of value.