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The Future of Precision Medicine: What Does it Mean for Nice?
A404
VA L U E I N H E A LT H 2 0 ( 2 0 1 7 ) A 3 9 9 – A 8 1 1
exceed $500,000). In the traditional approach for medicine reimbursement, payers are purchasing health care (e.g. treatment for disease) rather than health (e.g. extended life expectancy). For such transformative therapies this would mean a substantial upfront investment from healthcare payers alongside the significant risk that real-world patients do not obtain the expected benefits, especially as many will likely be approved on early clinical data through expedited regulatory pathways. Therefore, there has been a move towards exploring innovative types of reimbursement, including leasing, performance-based reimbursement, budgetary caps and dynamic pricing. These schemes can offer means for payers and manufacturers to agree coverage by sharing risks and managing affordability but they also involve additional complexity and costs in terms of management and administration. Each of these schemes offers distinct opportunities and risks for both manufacturers and payers with the simpler ones (e.g. budgetary caps) being cruder in how they manage risk/payment but being relatively simple to administer and the more complex ones (e.g. performance-based reimbursement and leasing) being potentially fairer in managing risk/payment but this may be outweighed by the associated complexities/ costs. Indeed, there have been some notable examples of where such complexities have fatally undermined such schemes (the UK Multiple Sclerosis Risk Sharing Scheme and Conditional Financing in the Netherlands). There will not likely be a best-in-class scheme but different ones will be utilised depending on the health system infrastructure and the specific therapy, manufacturer and patient population. CP2 Using Outcome Data to Inform Healthcare Professional – Patient Discussion: A Database of Treatment Effects Gilbert J National Guideline Centre, London, UK
Introduction: Healthcare professionals (HCPs) are expected to discuss benefits and harms of treatment decisions with their patients to allow for shared decisionmaking. Ideally, these discussions involve a neutral presentation of the magnitude of expected benefits and harms for each treatment option. These discussions are rarely, if ever, feasible particularly because estimates of treatment effect are not readily available to HCPs. NICE (National Institute for Health and Care Excellence) produce predominantly single condition guidelines that make recommendations based on systematic literature reviews. Estimates of benefit and harm from interventions are available in NICE guidelines, although not presented in the final recommendations. This information allows for condition specific decision aids but patients rarely make decisions in the context of a single condition. Current Work: The National Guideline Centre (NGC), commissioned by NICE, recently developed a guideline on multimorbidity. As part of this guideline, the NGC produced a Database of Treatment Effects (DoTE), designed to support patients and HCPs faced with these challenging decisions. We identified all currently available NICE guidelines that include efficacy estimates of common treatments aimed at prognostic benefit. We extracted point estimates (and confidence intervals) of efficacy for each treatment, control group risks and the duration of the source trials. This information was compiled into a tool, DoTE, that allows for the comparison of relative and absolute expected effects of the relevant treatments. The associated NICE recommendations, trial populations and uncertainty of each result can be presented alongside the effect estimate. Conclusions: DoTE is a tool that provides information for unbiased discussions around the expected benefits and harms of treatment choices. Compiling DoTE was not simple and it is important that users fully appreciate the methods involved and their limitations. However, without a resource like DoTE, many HCPs are left facing an impossible task on a daily basis. CP3 The Future of Precision Medicine: What Does it Mean for Nice? Rejon-Parrilla JC1, Lovett RE2, Chalkidou A3, Love-Koh J4, Wood H4, Ennis K4, Peel A4, Taylor M4 1National Institute for Health and Care Excellence (NICE), Manchester, UK, 2National Institute for Health and Care Excellence (NICE), London, UK, 3King’s Technology Evaluation Centre (KiTEC), King’s College London, London, UK, 4York Health Economics Consortium, University of York, York, UK
Objectives: The potential of precision medicine to streamline pathways of tailored prevention and care has been widely discussed. However appraising the costs and benefits of such changes in care pathways is often challenging. This scoping project aims to: 1) identify the types of heath technologies and services that fall under the umbrella of precision medicine and are likely to launch within the next 10 years; 2) explore the challenges facing NICE in evaluating them, and; 3) discuss what methods research or piloting, if any, might be a priority for NICE. Methods: The project covered several NICE programmes including those that produce guidance on pharmaceuticals, diagnostics, medical technologies and clinical guidelines. We identified the types of health technologies and services falling under the umbrella of precision medicine that are likely to launch in the next 10 years, and whether these can be evaluated by existing NICE programmes and methods. To do that, we chose to review both peer-reviewed and grey literature. We also interviewed 13 experts, both from within NICE and external researchers with specialised knowledge in the area. Results: Having identified emerging technologies and care pathways, we assessed whether these interventions would meet the topic-selection criteria for NICE’s existing programmes. Additionally, we identified a number of areas where innovative methods research or piloting could help NICE prepare for the future of precision medicine, including challenges related to equity, data generation and scoping. At the time of writing, this is work in progress – more detailed results will be available by November. Conclusions: NICE has already published guidance for companion diagnostics and treatments approved for patient subpopulations defined by a specific biomarker. This project will help NICE to focus and target our research and piloting activities, to help us to produce robust evidence-based guidance for future precision medicine technologies and services.
CP4 Challenges in Optimising Real World Evidence for Alzheimer’s Disease Reed C1, de Reydet de Vulpillieres F2, Gallacher J3 Lilly and Company Ltd, Windlesham, UK, 2NOVARTIS PHARMA AG, Basel, Switzerland, 3Oxford University, Oxford, UK
1Eli
Alzheimer’s disease (AD) is a gradually progressive condition with increasing humanistic and economic burden for patients, families and society. Due to the long term nature of the disease (up to 20 years) characterised by cognitive and functional decline, and behavioural changes, there are challenges in identifying meaningful clinical milestones along this continuum and in demonstrating the value of slowing disease progression within clinical trials and beyond. Societal costs of AD, including those of informal caregiving costs, are well recognised when considering the totality of the disease, but when new treatments enter the market, the potential impact on future healthcare costs for providers and payers is anticipated to be considerable. The methods for determining how HTA and payer agencies value developments in AD must be put in the context of health and medical care policy while balancing this potential high budget impact. Real World Outcomes across the AD spectrum for better care: Multi-modal data Access Platform (ROADMAP) is a public-private consortium funded by the Innovative Medicines Initiative’s Big Data for Better Outcomes programme to evaluate the validity of linking RCT and real world data to demonstrate the benefit of new AD therapies. Using pilot studies, ROADMAP will develop scalable and transferable tools and methods to support disease progression and economic modelling relevant for national and regional HTA bodies, payers, and regulators, with concomitant patient advocacy engagement. Feedback from these key stakeholders will set new standards for the collation and evaluation of real world evidence in AD to support demonstrating the value of new AD treatments. ROADMAP will play a role in challenging current paradigms in the assessment of novel treatments by decision makers and describe innovations for assessing new therapies to treat AD. Funding: This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking (ROADMAP grant n° 116020).
breakout sESSION VIII
P8: CARDIOVASCULAR STUDIES CV1 Interim Results of A Multi-Country Survey to Evaluate Productivity Loss and Indirect Costs after Cardiovascular Events in Europe Gerlier L1, Sidelnikov E2, Kutikova L2, Lamotte M1, Amarenco P3, Kotseva K4, Annemans L5 1QuintilesIMS, Zaventem, Belgium, 2Amgen (Europe) GmbH, Zug, Switzerland, 3Bichat HospitalClaude Bernard, Paris, France, 4National Heart & Lung Institute, Imperial College London, London, UK, 5Ghent University - Brussels University, Ghent, Belgium
Objectives: To present interim results of a multi-country cross-sectional survey aiming to estimate the productivity losses/indirect costs of patients in the first year after a cardiovascular event (CVE) in 12 European countries. Methods: Patients previously hospitalized for myocardial infarction or unstable angina (acute coronary syndrome [ACS]) or a stroke were enrolled during a routine cardiologist or neurologist visit 3-12 months after index CVE hospitalization and ≥ 4 weeks after return to work. Productivity losses in the past 4 weeks were collected using the patientreported Productivity Cost Questionnaire (iPCQ). Hours lost were extrapolated to 1 year, combined with initial hospitalization and sick leave, and valued according to each country’s labour cost (2015). Hours lost were converted into 8-hour workdays. Results: N= 104 patients were analyzed (51 ACS, 53 stroke, 87% men, mean age 52 years). On average there were 83.6 (standard deviation = 65.4) work-days missed during the first year after the CVE, which amounts to about 40% of annual working days. Long-term absenteeism (patient’s index hospitalization followed by initial sick leave) accounted for 40.8 (41.1) days. After returning to work, 13.5 (26.3) days were missed due to short-term absenteeism and another 8.2 (10.7) days due to presenteeism. Annual caregiver help time was 21.1 (36.3) days, which represents 25% of the total time lost. In ACS patients, the average indirect costs in the year post-CVE were € 5,375 (4,095), € 16,922 (12,894) and € 26,537 (20,220) for participating countries in Eastern, Southern, and Northern European regions respectively. For stroke the respective indirect costs per patient were € 5,004 (4,040), € 15,755 (12,720) and € 24,707 (19,947). Conclusions: The interim results suggest that indirect costs of CVE are substantial in the first year following a CVE. The main drivers of indirect costs are the initial hospitalization and post-hospitalization sick leave, followed by caregiver help. CV2 A Framework for the Cost-Effectiveness Analysis of Novel Biomarker Testing in Cardiovascular Disease Kohli-Lynch CN, Boyd K, Briggs A, Delles C University of Glasgow, Glasgow, UK
Objectives: Individuals are often prioritised for preventive cardiovascular disease (CVD) therapy based on 10-year risk of experiencing a primary CVD event. In Scotland, this risk is estimated with the ASSIGN risk score. Recent research has focused on identifying novel biomarkers to improve CVD risk diagnosis. The objective of this study was to develop a framework for the cost-effectiveness analysis (CEA) of novel biomarker testing given the inherent sparsity of data related to novel biomarkers. The framework was applied in the CEA of the urinary proteomic biomarker HF1. Methods: Gompertz regression was performed on data from the FLEMish Study on Environment, Genes, and Health Outcomes to establish
VA L U E I N H E A LT H 2 0 ( 2 0 1 7 ) A 3 9 9 – A 8 1 1
exceed $500,000). In the traditional approach for medicine reimbursement, payers are purchasing health care (e.g. treatment for disease) rather than health (e.g. extended life expectancy). For such transformative therapies this would mean a substantial upfront investment from healthcare payers alongside the significant risk that real-world patients do not obtain the expected benefits, especially as many will likely be approved on early clinical data through expedited regulatory pathways. Therefore, there has been a move towards exploring innovative types of reimbursement, including leasing, performance-based reimbursement, budgetary caps and dynamic pricing. These schemes can offer means for payers and manufacturers to agree coverage by sharing risks and managing affordability but they also involve additional complexity and costs in terms of management and administration. Each of these schemes offers distinct opportunities and risks for both manufacturers and payers with the simpler ones (e.g. budgetary caps) being cruder in how they manage risk/payment but being relatively simple to administer and the more complex ones (e.g. performance-based reimbursement and leasing) being potentially fairer in managing risk/payment but this may be outweighed by the associated complexities/ costs. Indeed, there have been some notable examples of where such complexities have fatally undermined such schemes (the UK Multiple Sclerosis Risk Sharing Scheme and Conditional Financing in the Netherlands). There will not likely be a best-in-class scheme but different ones will be utilised depending on the health system infrastructure and the specific therapy, manufacturer and patient population. CP2 Using Outcome Data to Inform Healthcare Professional – Patient Discussion: A Database of Treatment Effects Gilbert J National Guideline Centre, London, UK
Introduction: Healthcare professionals (HCPs) are expected to discuss benefits and harms of treatment decisions with their patients to allow for shared decisionmaking. Ideally, these discussions involve a neutral presentation of the magnitude of expected benefits and harms for each treatment option. These discussions are rarely, if ever, feasible particularly because estimates of treatment effect are not readily available to HCPs. NICE (National Institute for Health and Care Excellence) produce predominantly single condition guidelines that make recommendations based on systematic literature reviews. Estimates of benefit and harm from interventions are available in NICE guidelines, although not presented in the final recommendations. This information allows for condition specific decision aids but patients rarely make decisions in the context of a single condition. Current Work: The National Guideline Centre (NGC), commissioned by NICE, recently developed a guideline on multimorbidity. As part of this guideline, the NGC produced a Database of Treatment Effects (DoTE), designed to support patients and HCPs faced with these challenging decisions. We identified all currently available NICE guidelines that include efficacy estimates of common treatments aimed at prognostic benefit. We extracted point estimates (and confidence intervals) of efficacy for each treatment, control group risks and the duration of the source trials. This information was compiled into a tool, DoTE, that allows for the comparison of relative and absolute expected effects of the relevant treatments. The associated NICE recommendations, trial populations and uncertainty of each result can be presented alongside the effect estimate. Conclusions: DoTE is a tool that provides information for unbiased discussions around the expected benefits and harms of treatment choices. Compiling DoTE was not simple and it is important that users fully appreciate the methods involved and their limitations. However, without a resource like DoTE, many HCPs are left facing an impossible task on a daily basis. CP3 The Future of Precision Medicine: What Does it Mean for Nice? Rejon-Parrilla JC1, Lovett RE2, Chalkidou A3, Love-Koh J4, Wood H4, Ennis K4, Peel A4, Taylor M4 1National Institute for Health and Care Excellence (NICE), Manchester, UK, 2National Institute for Health and Care Excellence (NICE), London, UK, 3King’s Technology Evaluation Centre (KiTEC), King’s College London, London, UK, 4York Health Economics Consortium, University of York, York, UK
Objectives: The potential of precision medicine to streamline pathways of tailored prevention and care has been widely discussed. However appraising the costs and benefits of such changes in care pathways is often challenging. This scoping project aims to: 1) identify the types of heath technologies and services that fall under the umbrella of precision medicine and are likely to launch within the next 10 years; 2) explore the challenges facing NICE in evaluating them, and; 3) discuss what methods research or piloting, if any, might be a priority for NICE. Methods: The project covered several NICE programmes including those that produce guidance on pharmaceuticals, diagnostics, medical technologies and clinical guidelines. We identified the types of health technologies and services falling under the umbrella of precision medicine that are likely to launch in the next 10 years, and whether these can be evaluated by existing NICE programmes and methods. To do that, we chose to review both peer-reviewed and grey literature. We also interviewed 13 experts, both from within NICE and external researchers with specialised knowledge in the area. Results: Having identified emerging technologies and care pathways, we assessed whether these interventions would meet the topic-selection criteria for NICE’s existing programmes. Additionally, we identified a number of areas where innovative methods research or piloting could help NICE prepare for the future of precision medicine, including challenges related to equity, data generation and scoping. At the time of writing, this is work in progress – more detailed results will be available by November. Conclusions: NICE has already published guidance for companion diagnostics and treatments approved for patient subpopulations defined by a specific biomarker. This project will help NICE to focus and target our research and piloting activities, to help us to produce robust evidence-based guidance for future precision medicine technologies and services.
CP4 Challenges in Optimising Real World Evidence for Alzheimer’s Disease Reed C1, de Reydet de Vulpillieres F2, Gallacher J3 Lilly and Company Ltd, Windlesham, UK, 2NOVARTIS PHARMA AG, Basel, Switzerland, 3Oxford University, Oxford, UK
1Eli
Alzheimer’s disease (AD) is a gradually progressive condition with increasing humanistic and economic burden for patients, families and society. Due to the long term nature of the disease (up to 20 years) characterised by cognitive and functional decline, and behavioural changes, there are challenges in identifying meaningful clinical milestones along this continuum and in demonstrating the value of slowing disease progression within clinical trials and beyond. Societal costs of AD, including those of informal caregiving costs, are well recognised when considering the totality of the disease, but when new treatments enter the market, the potential impact on future healthcare costs for providers and payers is anticipated to be considerable. The methods for determining how HTA and payer agencies value developments in AD must be put in the context of health and medical care policy while balancing this potential high budget impact. Real World Outcomes across the AD spectrum for better care: Multi-modal data Access Platform (ROADMAP) is a public-private consortium funded by the Innovative Medicines Initiative’s Big Data for Better Outcomes programme to evaluate the validity of linking RCT and real world data to demonstrate the benefit of new AD therapies. Using pilot studies, ROADMAP will develop scalable and transferable tools and methods to support disease progression and economic modelling relevant for national and regional HTA bodies, payers, and regulators, with concomitant patient advocacy engagement. Feedback from these key stakeholders will set new standards for the collation and evaluation of real world evidence in AD to support demonstrating the value of new AD treatments. ROADMAP will play a role in challenging current paradigms in the assessment of novel treatments by decision makers and describe innovations for assessing new therapies to treat AD. Funding: This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking (ROADMAP grant n° 116020).
breakout sESSION VIII
P8: CARDIOVASCULAR STUDIES CV1 Interim Results of A Multi-Country Survey to Evaluate Productivity Loss and Indirect Costs after Cardiovascular Events in Europe Gerlier L1, Sidelnikov E2, Kutikova L2, Lamotte M1, Amarenco P3, Kotseva K4, Annemans L5 1QuintilesIMS, Zaventem, Belgium, 2Amgen (Europe) GmbH, Zug, Switzerland, 3Bichat HospitalClaude Bernard, Paris, France, 4National Heart & Lung Institute, Imperial College London, London, UK, 5Ghent University - Brussels University, Ghent, Belgium
Objectives: To present interim results of a multi-country cross-sectional survey aiming to estimate the productivity losses/indirect costs of patients in the first year after a cardiovascular event (CVE) in 12 European countries. Methods: Patients previously hospitalized for myocardial infarction or unstable angina (acute coronary syndrome [ACS]) or a stroke were enrolled during a routine cardiologist or neurologist visit 3-12 months after index CVE hospitalization and ≥ 4 weeks after return to work. Productivity losses in the past 4 weeks were collected using the patientreported Productivity Cost Questionnaire (iPCQ). Hours lost were extrapolated to 1 year, combined with initial hospitalization and sick leave, and valued according to each country’s labour cost (2015). Hours lost were converted into 8-hour workdays. Results: N= 104 patients were analyzed (51 ACS, 53 stroke, 87% men, mean age 52 years). On average there were 83.6 (standard deviation = 65.4) work-days missed during the first year after the CVE, which amounts to about 40% of annual working days. Long-term absenteeism (patient’s index hospitalization followed by initial sick leave) accounted for 40.8 (41.1) days. After returning to work, 13.5 (26.3) days were missed due to short-term absenteeism and another 8.2 (10.7) days due to presenteeism. Annual caregiver help time was 21.1 (36.3) days, which represents 25% of the total time lost. In ACS patients, the average indirect costs in the year post-CVE were € 5,375 (4,095), € 16,922 (12,894) and € 26,537 (20,220) for participating countries in Eastern, Southern, and Northern European regions respectively. For stroke the respective indirect costs per patient were € 5,004 (4,040), € 15,755 (12,720) and € 24,707 (19,947). Conclusions: The interim results suggest that indirect costs of CVE are substantial in the first year following a CVE. The main drivers of indirect costs are the initial hospitalization and post-hospitalization sick leave, followed by caregiver help. CV2 A Framework for the Cost-Effectiveness Analysis of Novel Biomarker Testing in Cardiovascular Disease Kohli-Lynch CN, Boyd K, Briggs A, Delles C University of Glasgow, Glasgow, UK
Objectives: Individuals are often prioritised for preventive cardiovascular disease (CVD) therapy based on 10-year risk of experiencing a primary CVD event. In Scotland, this risk is estimated with the ASSIGN risk score. Recent research has focused on identifying novel biomarkers to improve CVD risk diagnosis. The objective of this study was to develop a framework for the cost-effectiveness analysis (CEA) of novel biomarker testing given the inherent sparsity of data related to novel biomarkers. The framework was applied in the CEA of the urinary proteomic biomarker HF1. Methods: Gompertz regression was performed on data from the FLEMish Study on Environment, Genes, and Health Outcomes to establish