Workshops
Monday, May 21, 2018
11:00 AM - 12:00 PM
BREAKOUT SESSION
Economic Outcomes Research

11:00 AM - 12:00 PM
Room: Ballroom II (Level 400)

W1: TIME TO LOOK BEYOND KAPLAN-MEIER CURVES? CHALLENGES AND OPPORTUNITIES IN OVERALL SURVIVAL EXTRAPOLATIONS FOR IMMUNO-ONCOLOGY TRIALS -- SCIENTIFIC RATIONALE FOR USING PATIENT-LEVEL BIOMEDICAL INFORMATION

Discussion Leaders:

Andrew Briggs, DPhil, William R. Lindsay Chair of Health Economics, Health Economics & Health Technology Assessment, Institute of Health and Wellbeing, University of Glasgow, Glasgow, Scotland, UK

Scott D. Ramsey, MD, PhD, Director, Public Health Sciences, Fred Hutchinson Cancer Research Center and University of Washington, Seattle, WA, USA

Yiduo Zhang, PhD, Director, Health Economics and Payer Analytics, Global Payer Evidence and Pricing, AstraZeneca, Gaithersburg, MD, USA

Pralay Mukhopadhyay, PhD, Statistician, AstraZeneca, Gaithersburg, MD, USA

PURPOSE:

It is common for the long term overall survival (OS) benefit to represent a major source of uncertainty due to the immaturity of data from clinical trials. The emergence of immuno-oncology (IO) agents and their new mechanism of action add further layers of complexity in OS extrapolation. For typical OS extrapolation relying on fitting parametric curves under a set of standard distribution assumptions, the main challenges for IO agents are the large variation in the extrapolations, and how to decide the best clinically plausible curve. In recent reimbursement submissions, rich patient-level biomedical data collected in IO trials were not typically used to help with reducing the uncertainty of OS extrapolation, presumably due to their complex nature. The objective of this workshop is to discuss the scientific rationale for looking beyond Kaplan-Meier curves in OS extrapolation and harnessing patient-level biomedical data, such as repeated longitudinal tumor measurement data, to help inform the best clinically plausible scenario and thus reduce uncertainty in OS extrapolation. The workshop will build upon previous workshops held at the 2016 and 2017 ISPOR meetings and provide practical examples of how patient-level data could be used to improve the precision and validity in OS extrapolation.

DESCRIPTION:

The workshop will begin with a description of biomedical measures in oncology and their potential in informing OS extrapolation. The high degree of uncertainty introduced by standard parametric curve fitting will be reiterated with an overview of recent reimbursement submissions. Several emerging approaches for OS extrapolation employing patient-level biomedical information will be presented, including examples from IO trials. The strengths and weaknesses of using biomedical measures to support OS projections will also be highlighted by the panelists, together with suggestions for future research. Attendees will be invited to contribute their own experiences of using patient-level biomedical data for supporting OS assumptions.

Patient-Reported Outcomes & Patient Preference Research

11:00 AM - 12:00 PM
Room: Ballroom III (Level 400)

W2: WHAT IS PATIENT EXPERIENCE DATA? THE REGULATORY PERSPECTIVE

Discussion Leaders:

Martin Ho, MS, Associate Director for Quantitative Innovation, Center for Devices and Radiological Health (CDRH), U.S. Food and Drug Administration, Silver Springs, MD, USA

Megan Moncur, MS, Senior Advisor, Science of Patient Input, Center for Biologics Evaluation and Research (CBER), U.S. Food and Drug Administration, Silver Spring, MD, USA

Pujita Vaidya, MPH, Director (Acting), Decision Support and Analysis Team, Office of Strategic Programs/Office of Program and Strategic Analysis, Center for Drug Evaluation and Research (CDER), U.S. Food and Drug Administration, Silver Spring, MD, USA

PURPOSE:

This workshop will focus on defining patient experience data (PED) as described by the 21st Century Cures Act, how the FDA Reauthorization Act of 2017 (FDARA) supports the science of patient input, and what this data could look like when submitted to the FDA. Workshop participants will have the opportunity to discuss these topics and study considerations.

DESCRIPTION:

Over the past five years, the FDA has made strides in incorporating the patient voice in medical product decision-making. The Patient-Focused Drug Development and Patient Preference initiatives, begun under the Food and Drug Administration Safety and Innovation Act (FDASIA) of 2012, led to 24 public meetings to learn from patients about their disease experience and a guidance document about patient preference information in medical device applications. This momentum has now been solidified in the 21st Century Cures Act with the continuation of Patient-Focused Drug Development and the new FDA initiative to acknowledge PED included in medical product submissions. FDARA supports capacity-building and public meetings to discuss approaches for incorporating patient input in medical product submissions. The FDA is developing a series of guidances on how to incorporate the patient’s voice in medical product development and decision-making. But what is PED? This workshop will give participants an opportunity to discuss this topic and hear the perspectives of FDA’s three medical product centers. This workshop will inform participants about a) how FDA has been evolving in capturing the patient’s voice; b) how PED is defined in the regulatory setting; c) considerations when designing studies to collect PED and, d) using PED throughout the medical product lifecycle. Discussion leaders will represent CDER, CDRH, and CBER and will engage participants in a conversation about challenges to collecting PED and how different types of PED may be appropriate for answering different types of regulatory questions.

Clinical Outcomes Research

11:00 AM - 12:00 PM
Room: 309 (Level 300)

W3: DIGITAL HEALTH: EVALUATING THE EVIDENCE, IDENTIFYING GAPS, PRODUCING BETTER SCIENCE

Discussion Leaders:

Penny Mohr, MA, Senior Advisor, Emerging Technology and Delivery System Innovation Research Initiatives, Patient Centered Outcomes Research Institute (PCORI), Washington, DC, USA

Karen Schoelles, MD, SM, Director, ECRI Institute HTA Consulting Service, ECRI Institute, Plymouth Meeting, PA, USA

Murray Aitken, MBA, Executive Director, IQVIA Institute for Human Data Science, New York, NY, USA

Jasmine Bihm, DrPH, MPH, Staff Fellow, Center for Evidence and Practice Improvement, Agency for Healthcare Research and Quality (AHRQ), Rockville, MD, USA

PURPOSE:

This workshop will examine the landscape of digital health. Discussion leaders will describe methods used to evaluate digital health in clinical studies and evidence synthesis, including evaluating clinical effectiveness, usability by patients, fit with clinical workflow, and issues of patient privacy and data security. Discussion leaders will engage participants in conversation about how to design studies that can help fill the evidence gaps and what information and incentives are needed to bring effective digital health interventions to patients.

DESCRIPTION:

The number of digital health applications is rapidly growing, with many different apps available to coach patients in wellness behaviors, remind patients to take medication, monitor patient vital signs and movement, and communicate health information back to physicians. Penny Mohr will describe PCORI’s portfolio to evaluate these apps in clinical studies. Karen Schoelles, Murray Aitken and Elise Berliner will describe recent reviews of digital health effectiveness, the growing body of evidence related to digital health and where there are evidence gaps. Participants will have the opportunity to provide perspective on what are the important metrics to evaluate these apps and what is needed to provide help for patients, providers and payers to choose which of the different apps to adopt. This interactive workshop will be valuable for app developers, and all stakeholders who are thinking about adopting and implementing apps in clinical practice.

3:45 PM - 4:45 PM
BREAKOUT SESSION
Use of Real World Data

3:45 PM - 4:45 PM
Room: Ballroom I (Level 400)

W4: BIOSIMILARS, UTILIZATION, AND POST-MARKETING SURVEILLANCE IN THE UNITED STATES (INVITED WORKSHOP)

Discussion Leaders:

Cate Lockhart, PharmD, PhD, Program Director, Biologics and Biosimilars Collective Intelligence Consortium, Alexandria, VA, USA

Mark J. Cziraky, PharmD, CLS, Vice President of Research, Healthcore, Wilmington, DE, USA

Mike Blum, MD, MPH, Deputy Director, Office of Pharmacovigilance and Epidemiology, U.S. Food & Drug Administration, Silver Spring, MD, USA

PURPOSE:

This workshop will focus on the current state of post-marketing surveillance of biosimilar products in the United States. Participants will gain familiarity with the challenges and approaches and from three perspectives: payers, regulators and researchers. Faculty will discuss the need for surveillance, how the outcomes from research can inform utilization patterns of biosimilars in the current marketplace, highlight key contributions of individual organizations, and the evolving learnings from a collaborative, multi-stakeholder approach.

DESCRIPTION:

Participants will be presented with an overview of the current biosimilar market, the need for surveillance in the US, and the research activities using real-world evidence (RWE). We will explore the current approach to pharmacovigilance of biosimilar products in the US, and describe one collaborative approach to post-marketing research. Participants will have the opportunity to learn how the outcomes of this research may provide evidence for payers and healthcare organizations in making decisions on utilization of newly marketed biosimilar products, and how it may support regulatory initiatives such as interchangeability and post-marketing surveillance.

Clinical Outcomes Research

3:45 PM - 4:45 PM
Room: Ballroom III (Level 400)

W5: ADJUSTING FOR BETWEEN-TRIAL DIFFERENCES IN THE SCHEDULE OF ASSESSMENT FOR DISEASE PROGRESSION IN IMMUNO-ONCOLOGY AND ITS IMPACT ON INDIRECT TREATMENT COMPARISONS

Discussion Leaders:

Venediktos Kapetanakis, PhD, Lead Statistician, Evidera, London, UK

Michael Schlichting, Director, Global Biostatistics and Epidemiology, Merck KGaA, Darmstadt, Germany

John William Stevens, PhD, Director, HEDS, ScHARR, Reader in Decision Science, University of Sheffield, Sheffield, UK

PURPOSE:

Several immuno-oncology (IO) agents have been approved for the treatment of various cancers, but there are relatively few head-to-head randomized trials; highlighting a need for indirect treatment comparisons (ITCs). Additionally, there are differences in scheduled clinical and imaging assessments to detect disease progression across trials. This can impact the comparison of progression-free survival (PFS), as treatments evaluated with a delayed initial assessment may demonstrate an artificial advantage. This “assessment-time bias” (ATB) may be accentuated in the case of IO therapies where the phenomenon of hyper-progression has been observed. ATB can have an impact on ITCs, which in turn, can affect cost-effectiveness assessments. This workshop will present statistical approaches for accounting for ATB. Familiarity and use of the proposed techniques to adjust for ATB in ITCs may inform the comparative assessment of new IO agents.

DESCRIPTION:

Methods to adjust for imbalances in baseline patient characteristics between trials are available and often used in health technology assessments. However, these methods cannot adjust for trial design differences including the schedule of assessments for disease progression. Statistical approaches for accounting for ATB, including methods i) adjusting for interval-censoring as progression can only be assessed at certain times, and ii) estimating PFS under a hypothetical progression-assessment schedule and ways for validating observed treatment effects through simulation will be presented. All underlying assumptions will be discussed. The merits and challenges of each method will be illustrated by examples and simulations explaining when each method is most appropriate to use. The interpretation and presentation of results and implications for ITCs will be presented. Audience participation will be encouraged through active discussion. Participants will gain an understanding of how to account for ATB when comparing PFS between trials, the underlying assumptions and appropriate use. The workshop is directed at healthcare decision-makers, statisticians and individuals commissioning health-economic evaluations.

Economic Outcomes Research

3:45 PM - 4:45 PM
Room: Ballroom IV (Level 400)

W6: ECONOMIC EVALUATION OF VACCINATION PROGRAMS: EXPLORING MULTIPLE METHODS

Discussion Leaders:

Josephine Mauskopf, PhD, MHA, Vice President, Health Economics, RTI Health Solutions, Durham, NC, USA

David E Bloom, PhD, Clarence James Gamble Professor of Economics and Demography, TH Chan School of Public Health, Harvard University, Boston, MA, USA

Americo Cicchetti, PhD, Professor/Director, Graduate School of Health Economics and Management, Università Cattolica del Sacro Cuore, Rome, Italy

PURPOSE:

The objective for the workshop is to discuss the value of vaccination and alternative methods of economic evaluation for vaccination programs. There are multiple agents whose decisions impinge upon or determine the size and scope of vaccination programs, including those responsible for determining the size of the health sector budget, those responsible for allocating that budget to different health programs, and those providing funding for the promotion and protection of health in low-income countries. These decision makers need economic analyses that are consistent with these different decision contexts. Participants in the workshop will be introduced to several alternative methods for performing economic evaluations of vaccination programs for decision makers in these different decision contexts. The workshop will conclude with a general discussion by the participants and presenters of the different methods including how to ensure the availability of credible data.

DESCRIPTION:

In this workshop, a brief overview of cost-effectiveness analysis, constrained optimization, and fiscal returns-on-investment modeling for the evaluation of vaccination programs will be presented by Dr Mauskopf. Dr Bloom will then discuss the full social and economic benefits of vaccination and compare and contrast benefit-cost analysis and cost-effectiveness analysis approaches to the rational allocation of resources to vaccination programs. Other approaches, including multi-criteria decision analysis and social welfare approaches will also be discussed, along with corresponding data requirements and opportunities. Examples will also be sketched. Dr Cicchetti will give an example of his work in estimating returns on investment in adult vaccination programs from a government tax revenue distribution perspective. The workshop leaders will then invite the participants to share their opinions on the alternative methods of economic evaluation and their ideas as to how to generate credible information on the benefits and costs to populate the economic evaluation models.

5:00 PM - 6:00 PM
BREAKOUT SESSION
Health Policy Development Using Outcomes Research

5:00 PM - 6:00 PM
Room: Ballroom III (Level 400)

W7: ARTIFICIAL INTELLIGENCE AND PRECISION MEDICINE: DOES THE HEALTH ECONOMIST NEED TO ADAPT TO THE MACHINE?

Discussion Leaders:

Augustin Terlinden, MSc, Actuary and Health Economist, Independent Researcher, Brussels, Belgium

Patricia A Deverka, MD, MS, MBE, Senior Researcher, American Institutes for Research, Chapel Hill, NC, USA

Amine Aissaoui, PharmD, MSc, Researcher, LEDA-LEGOS, Paris Dauphine University, PSL, Paris, France

Olivier Ethgen, MSc, PhD, Scientific Director, SERFAN innovation, Namur, Belgium

PURPOSE:

Over the last decade, the volume and diversity of imaging, genetic, and biochemical data has been growing exponentially. This phenomenon paves the way to precision medicine, which aims to improve human health by accounting for individual variations in genes, environment and lifestyle in both disease treatment and prevention strategies. To maximize the benefits from this big data revolution and more efficiently tailor prevention, diagnosis and treatment strategy, the healthcare industry has started to adopt new data analysis techniques. Thanks to concurrent advances in computer power and theoretical knowledge, artificial intelligence (AI) is now becoming the backbone technology for many medical devices. Through practical examples, this interactive workshop aims to discuss the implications of this new AI-backed medical device category for the patient, payer, device and drug developer.

DESCRIPTION:

First, the concept of AI-backed precision medicine will be introduced, along with likely advantages and challenges for the healthcare ecosystem in terms of clinical, patient and reimbursement decision-making. Second, three real-world examples will be presented where “intelligent” (or AI-backed) medical devices received a positive Health Technology Assessment or are seeking reimbursement approval. Each device uses a specific type of data source and artificial intelligence technique. For instance, the analysis of imaging data through deep neural networks brings superior accuracy in diagnosing iron overload in cancer survivors whereas cerebrospinal biomarkers analyzed through bootstrap aggregating techniques can be used to prompt the management of Alzheimer Disease patients and avoid inappropriate treatments of patients with false negative diagnoses. Along with a brief background, we will discuss how the superior accuracy and lack of interpretability of “intelligent” devices drive clinical and economic value. Finally, the workshop attendees will be asked to share their view and personal experience on the clinical integration and reimbursement of “intelligent” medical devices.

Patient-Reported Outcomes & Patient Preference Research

5:00 PM - 6:00 PM
Room: Ballroom IV (Level 400)

W8: ASSESSING PATIENT FUNCTIONING IN DRUG DEVELOPMENT USING PERFORMANCE OUTCOME ASSESSMENTS: EVIDENTIARY, METHODOLOGICAL, AND OPERATIONAL CONSIDERATIONS

Discussion Leaders:

Elektra Papadopoulos, MD, MPH, Associate Director, Clinical Outcome Assessments Staff, Office of New Drugs, Center for Drug Evaluation and Research (CDER), U.S. Food and Drug Administration, Silver Spring, MD, USA

Heather Adams, PhD, Associate Professor, Department of Neurology & Pediatrics, University of Rochester Medical Center, Rochester, NY, USA

Daniel S. Rooks, PhD, Director, Musculoskeletal Diseases, Novartis Institutes for BioMedical Research, Cambridge, MA, USA

Daniel C. Chung, DO, MA, Clinical Ophthalmic Lead, Spark Therapeutics, Philadelphia, PA, USA

PURPOSE:

To highlight opportunities, challenges, and potential solutions for developing, implementing, and interpreting performance outcome (PerfO) assessments to assess patient functioning in drug development. Participants will hear the current thinking of the regulators on developing and implementing PerfO assessment to support drug development and important considerations when implementing PerfO assessments in clinical studies including special considerations in pediatric patient populations. A case study will showcase the development and implementation of the Multi-luminance Mobility Test (MLMT), a standardized obstacle course for assessment of visual function in low vision.

DESCRIPTION:

Participants will be presented with evidentiary, methodological, and operational considerations for developing and implementing PerfO assessments to support drug development by speakers from the regulator, industry, and academia. The workshop will 1) provide an overview of the FDA’s current thinking of supporting PerfO assessments as fit-for-purpose outcome measures that reflect meaningful interpretation of daily-life functioning; 2) share practical considerations for implementing PerfOs in clinical trials and standardizing training; 3) highlight special considerations of implementing PerfO assessments for pediatric patient populations; 4) present the development of the MLMT as a case study. Dr. Patel will provide an overview of FDA’s current thinking on PerfO assessment including the working definition, the evidentiary considerations for demonstrating that PerfO measures reflect daily-life functioning, and the challenge of determining meaningful within-patient change. Dr. Rooks will share the experiences on implementing PerfOs as key outcomes in clinical trials and on standardizing training of study staff to improve the data quality. Dr. Adams will present the special considerations for the design and implementation of PerfO assessments in pediatric patient populations including the span of the developmental range of the PerfO assessment and the understanding of child development at different ages. Dr. Chung will present the development of the MLMT, which was used successfully to support a drug development program.

Tuesday, May 22, 2018
11:00 AM - 12:00 PM
BREAKOUT SESSION
Patient-Reported Outcomes & Patient Preference Research

11:00 AM - 12:00 PM
Room: Ballroom I (Level 400)

W9: NUMBERS OR NOISE? INTERPRETING INTERNAL VALIDITY TESTS OF STATED-PREFERENCE DATA

Discussion Leaders:

Kathryn O’Callaghan, PhD, Assistant Director of Strategic Programs, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD, USA

F. Reed Johnson, PhD, Professor, Population Health Sciences, School of Medicine, Duke University, Durham, NC, USA

Kevin Marsh, PhD, Executive Director, Outcomes Research, Evidera Ltd, London, UK

Jui-Chen Yang, MEM, Research Economist, Preference Evaluation Research Group, Duke Clinical Research Institute, Durham, NC, USA

PURPOSE:

To help participants interpret results of internal validity tests for evaluating the quality of stated­-preference data.

DESCRIPTION:

Recent guidance on incorporating patient-preference information in benefit­-risk assessments from FDA’s Center for Devices and Radiological Health calls for checks on the “logical soundness” of stated­-preference studies used to inform clinical, product-­development, or regulatory decision making. FDA has sponsored development of a validity-test tool for discrete-choice experiment (DCE) data that is freely available to researchers. The tool provides summary results for various tests of internal consistency, stability, transitivity, and logic. However, it is not clear what choice patterns qualify as a validity-test failure, how to diagnose the reasons for apparent failures, and how such observations should be treated in estimating preference parameters.

Kathryn O’Callaghan will introduce FDA’s interest in this topic and chair the workshop. Reed Johnson will summarize the results from an FDA-sponsored study that collected validity test results from 50 DCE datasets. Kevin Marsh will present an analysis of 14 DCE studies that included a dominated-pair test and discuss 3 possible explanations for apparent failures. Jui-Chen Yang will discuss a DCE study in which nearly 1/3 of respondents failed a dominated-pair test and evaluate the possible cognitive, preference, and statistical implications of the test failures.

Health Policy Development Using Outcomes Research

11:00 AM - 12:00 PM
Room: Ballroom II (Level 400)

W10: MILLION DOLLAR THERAPIES FOR RARE CONDITIONS: RETHINKING VALUE

Discussion Leaders:

Louis P. Garrison, PhD, Professor Emeritus, The Comparative Health Outcomes, Policy and Economics (CHOICE) Institute, University of Washington, Seattle, WA, USA

Clifford Goodman, PhD, Senior Vice President and Director, Center for Comparative Effectiveness Research, The Lewin Group, Falls Church, VA, USA

Paul Melmeyer, MPP, Director of Federal Policy, National Organization for Rare Disorders (NORD), Washington, DC, USA

PURPOSE:

Breakthrough therapies for rare conditions using novel mechanisms of action, e.g., CAR-T and CRISPR/Cas9, present unprecedented challenges to value assessment. This workshop will examine the application of current economic evaluation methods for emerging high-priced therapies for rare diseases, and discuss whether these methods are fit for purpose or require evolved paradigms. The audience will participate in interactive discussion, reflecting on and responding to distinct value perspectives of the health economist, patient, and decision-maker.

DESCRIPTION:

Dr. Garrison will present current practices from a health economics lens. Participants will learn about methodological challenges of assessing therapies for rare conditions i.e., unmet need, disease burden, direct and indirect costs (including productivity losses), conventional cost-effectiveness thresholds, budget impact, value of innovation, and shortcomings in evidence, i.e., small sample sizes, single arm study design, outcome selection, fatal disease course, and incomplete understanding of natural history of disease.

Paul Melmeyer will present a patient perspective, conveying factors that may not be captured in traditional value assessments, i.e., rarity of disease, availability of alternative therapies, patient-reported outcomes, benefit-risk trade-offs, and value of hope. Also addressed will be societal relevance of cost-effectiveness thresholds

Dr. Goodman will discuss challenges of decision makers who see expensive emerging therapies for an increasing number of rare diseases. While traditionally payers and providers have based their decisions on rigorous evidence, they must now recalibrate their assessment of value while facing limited evidence of effectiveness and safety, different trade-offs of pre- and post-market data collection, shifting societal expressions of willingness to pay, emerging value-based payment options, and heightened cost-containment pressures.

With this background, presenters will share early experiences and outlook for value assessment for the diverse pipeline of “million dollar therapies” for rare conditions, with implications for innovation for unmet medical needs. Audience discussion will embrace related international developments, including low/middle-income countries.

Economic Outcomes Research

11:00 AM - 12:00 PM
Room: Hall A (Level 100)

W11: CHOOSING THE APPROPRIATE MODELING METHOD: CAUSAL MODELING, HEALTH ECONOMIC MODELING, CONSTRAINED OPTIMIZATION OR SIMULATION?

Discussion Leaders:

William H Crown, PhD, Chief Scientific Officer, OptumLabs, Cambridge, MA, USA

Praveen Thokala, MASc, PhD, Research Fellow, The University of Sheffield, Sheffield, UK

Deborah A Marshall, PhD, Professor, University of Calgary, Calgary, AB, Canada

Kalyan S. Pasupathy, PhD, Faculty, Healthcare Policy & Research and Co- Scientific Director, Healthcare Systems Engineering Program, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA

PURPOSE:

There are a variety of methods for approaching health economic evaluation problems. Most ISPOR workshops concentrate on presenting a particular method. This workshop will focus on the higher order issue of choosing the correct method to address a specific evaluation problem.

DESCRIPTION:

Researchers tend to have expertise in a specific analytic method, or subset of methods, such as causal inference from health econometrics/epidemiology, health economic modeling, constrained optimization or simulation. These methods are often highly complementary.

However, analytic opportunities are sometimes lost because deep methodological domain knowledge keeps researchers locked within their own methodological silos. The goal of this workshop is to consider the characteristics of a range of health economic evaluation problems and then show how these characteristics guide the selection of the best analytic method to be utilized.

We will also show that these broader categories of methods are not necessarily mutually exclusive. For example, some constrained optimization problems are best solved by simulation. Similarly, discrete event simulation methods are widely used in health economic modeling. Causal modeling methods are often a precursor to estimate the parameters in health economic models or building the structural equations in a simulation model.

The workshop will consist of four brief presentations on model selection criteria (10 minutes each) with respect to causal modeling, health economic modeling, constrained optimization, and simulation. These presentations will also address the selection of specific methods within each broad category based upon the characteristics of the research problem being addressed. Following the presentations, the audience will be presented with several problem scenarios and asked to select the appropriate methods. The distribution of answers will then be used to guide a question and answer session.

Presented by the ISPOR Optimization Methods in Healthcare Delivery Emerging Good Practices Task Force

2:15 PM - 3:15 PM
BREAKOUT SESSION
Use of Real World Data

2:15 PM - 3:15 PM
Room: Ballroom II (Level 400)

W12: COMPLEX REAL-WORLD EVIDENCE: NETWORKED AND MISSING DATA

Discussion Leaders:

Laura Hatfield, PhD, Associate Professor, Department of Health Care Policy, Harvard Medical School, Boston, MA, USA

Sherri Rose, PhD, Associate Professor, Department of Health Care Policy, Harvard Medical School, Boston, MA, USA

Alisa Stephens-Shields, PhD, Assistant Professor, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA

Amanda Mejia, PhD, Assistant Professor, Department of Statistics, Indiana University, Bloomington, IN, USA

PURPOSE:

There is a strong need in health economics and outcomes research to move toward analytic systems that can take large healthcare databases and estimate quantities of interest both quickly and robustly. The quality of these data pose formidable challenges. In order to provide accurate real-world evidence, the research question may necessitate the integration of multiple data sources as well as techniques that account for complex relationships between variables and observations. Given the size and intricacies of the new data structures found in electronic health record data, standard statistical methods may not be suitable or feasible. This workshop will address four examples of successful analyses using patient­ level healthcare databases to handle these complex relationships, solving important missing data problems.

DESCRIPTION:

The first case study will focus on providing missing information for health care trajectories using observed utilization patterns. The second example will proceed to directly impute missing information on disease stage drawing on variables from an integrated registry and claims database. The third study will demonstrate how ignoring the network dependence (e.g., familial relationships) in population-level studies for real-world evidence can produce erroneous results. Lastly, the fourth example will identify networks in individual subjects while merging population-level information into the analysis. The potential of these methods is considerable; they can provide avenues for researchers to apply the interactive and fast, yet robust methods they desire for use in practice. The presentations will be formatted to include audience participation, including case studies from audience members that were successes and failures. The workshop discussion leaders will give input on these examples, highlighting common aspects relevant to the broad field of real world evidence. We anticipate that researchers and data scientists actively working with healthcare databases who are interested in producing more robust findings with novel yet practical approaches will benefit from this session.

3:45 PM - 4:45 PM
BREAKOUT SESSION
Patient-Reported Outcomes & Patient Preference Research

3:45 PM - 4:45 PM
Room: Ballroom III (Level 400)

W13: WHAT IS PATIENT-CENTERED AND FIT-FOR-PURPOSE PATIENT PREFERENCE INFORMATION?

Discussion Leaders:

Stephanie Christopher, MA, Program Director, Medical Device Innovation Consortium, Arlington, VA, USA

Anindita Saha, BSE, Director, External Expertise and Partnerships, Center for Devices & Radiological Health (CDRH), US Food & Drug Administration, Silver Spring, MD, USA

A. Brett Hauber, PhD, Senior Economist & Vice President, Health Preference Assessment, RTI Health Solutions, Research Triangle Park, NC, USA

Margaret Sheehan, JD, Patient Council, The Michael J. Fox Foundation for Parkinson's Research, New York, NY, USA

PURPOSE:

The 21st Century Cures Act directs the FDA to identify patient experience data submitted and reviewed as part of an application, and one type of patient experience data is patient preference information. This workshop will explore approaches for demonstrating both patient centeredness and regulatory relevance of patient preference information, through early engagement with patients and regulators. Participants will contribute to a discussion about the value of patient input, how end-user input may refine a patient preference survey, and how patient and regulator perspectives may be synthesized. We will identify opportunities for research to refine and inform good research practices in patient preference survey development.

DESCRIPTION:

Participants will be presented with a case study on the development of an instrument designed to elicit patient preference information regarding the benefits, risks, and other considerations associated with medical devices to treat Parkinson’s disease. In this study, a review of literature and clinical trials was used to generate a list of potential attributes. Patient input was solicited through discussion groups and a prioritization survey. Clinical and FDA perspectives on using these considerations for regulatory decision-making refined the list. Stephanie Christopher will provide an overview of the motivation, rationale, approach, and results. Margaret Sheehan will give a patient’s perspective on the process, including identification of key success drivers and suggestions for improvement. Anindita Saha will comment on the resulting instrument’s regulatory relevance and pathways for engaging with the FDA during instrument development. Dr. Brett Hauber will relate the work to good research practices and highlight research gaps in this space. Participants will engage in a discussion about research opportunities for patient-centered, fit-for-purpose patient experience data. Their comments will inform the development of a research roadmap.

Use of Real World Data

3:45 PM - 4:45 PM
Room: Ballroom IV (Level 400)

W14: NETWORK META-ANALYSIS FOR VARIOUS STUDY DESIGNS: STEPPING OUTSIDE THE RANDOMIZED CONTROLLED TRIALS COMFORT ZONE INTO THE REAL WORLD

Discussion Leaders:

Christopher Schmid, PhD, Professor of Biostatistics, School of Public Health, Brown University, Providence, RI, USA

Ashley Pitcher, BSc, DPhil, Engagement Manager, IQVIA, London, UK

Andreas Karabis, PhD, Principal, RWI, IQVIA, Amsterdam, The Netherlands

PURPOSE:

The majority of network meta-analysis (NMA) applications in decision making in health care and in health technology assessment are focused mainly on the synthesis of evidence from randomized controlled trials (RCTs). Recent developments in methodology are opening opportunities for inclusion of greater variability in study design, broadening the evidence base and addressing limitations of RCTs.

Starting from the standard RCT NMAs, this workshop will walk the participants through various study designs that could be synthesized including single arm trials, N-of-1 trials, cohort prospective and retrospective studies, and the corresponding methods that could be used for this purpose (e.g. matching-adjusted indirect comparison, hierarchical models, bias-allowance models, informative priors).

Participants will gain a broad overview of important methods, their strengths and limitations, and will engage in exercises demonstrating the application to two case studies. The technical challenges and the interpretation of the results will be discussed as well as their potential use in the life cycle of a pharmaceutical product.

DESCRIPTION:

Dr. Andreas Karabis will briefly introduce the concept of NMA; present some key challenges for the inclusion of different non-randomized studies and real-world data, and will close this part with the proposed methods to address these challenges. Participants will be encouraged to provide their perspectives on the need for these methods and implications in their field.

Dr. Christopher Schmid will present an N-of-1 NMA studying chronic pain.

Dr. Ashley Pitcher will present the example of a NMA for type 2 diabetes mellitus first-line monotherapy, synthesizing the results of RCTs with a retrospective cohort study using EMR data.

A step-wise approach will be followed for the presentation of these case studies and participants will be encouraged to provide feedback at each step (show of hands and questions).

5:00 PM - 6:00 PM
BREAKOUT SESSION
Patient-Reported Outcomes & Patient Preference Research

5:00 PM - 6:00 PM
Room: Ballroom III (Level 400)

W15: PATIENT INVOLVEMENT THROUGHOUT THE STAGES OF PATIENT-REPORTED OUTCOME DEVELOPMENT AND CLINICAL TRIAL IMPLEMENTATION

Discussion Leaders:

Sarah L Knight, BSc, MSc, Consultant, Clinical Outcomes Assessment Team, DRG Abacus, Bicester, UK

Helen Kitchen, MSc, Senior Consultant, Clinical Outcomes Assessment, DRG Abacus, Manchester, UK

Ann Hartry, PhD, Vice President, Health Economics and Outcomes Research (HEOR), Lundbeck, Deerfield, IL, USA

Cindy Coney, M.Ed, BSc, President, and Patient Advocate, Monarch Training and Consulting, Tampa, FL, USA

PURPOSE:

To highlight the importance of including the patient voice in patient reported outcome (PRO) development and clinical trial programmes from different perspectives. This will be undertaken through explanation and practical demonstration of time points to incorporate patient perspectives and what activities may be most effective to undertake. Working examples and case studies will also be provided.

DESCRIPTION:

As pharmaceutical companies, health services, and reimbursement agencies drive to become increasingly patient centric, including relevant patient-focussed outcome assessments in clinical trials is more important than ever[1],[2]. Selecting, developing, and validating PRO measures requires input from various parties in addition to patients.

Inclusion of the patient voice in PRO development and the clinical trial programme is essential and can improve patient care and quality of life[3]. However, little practical advice on how outcome researchers and sponsors can best incorporate patient and other stakeholder’s (clinicians/caregivers etc.) perspectives in their research exists. There are clear points during PRO development where the patient perspective is particularly important. This workshop aims to inform the audience, via interactive participation and discussion, as to the most important and relevant time points to include the patient perspective and practical implementation (based on working experience from all discussion leaders).

Discussion leaders from an outcomes research consultancy, a pharmaceutical company, and a patient representative will provide the audience with different perspectives and opinions around engaging patients in PRO research, including potential benefits and challenges.

[1] Johnson et al. The patient voice in research—evolution of a role. Research Involvement and Engagement, 2016; 2:6

[2] Dean et al. ‘The patient is speaking’: discovering the patient voice in ophthalmology. Br J Opthalmol, 2017; 0:1-9.

[3] Basch E. Patient-reported Outcomes- Harnessing Patients’ Voices to Improve Clinical Care, N Eng J Med, 2017; 376: 105-108.

Use of Real World Data

5:00 PM - 6:00 PM
Room: Ballroom I (Level 400)

W16: CHOOSING HOW TO CHOOSE: COLLECTIVE DECISION MAKING IN HEALTHCARE ORGANIZATIONS

Discussion Leaders:

Charles E. Phelps, PhD, MBA, University Professor & Provost Emeritus, Office of the Provost, University of Rochester, Rochester, NY, USA

Guru Madhavan, PhD, MBA, Senior Program Officer, Health and Medicine, National Academies of Science, Engineering, and Medicine, Washington, DC, USA

PURPOSE:

To help participants understand various voting methods for health technology assessments and policy-making and to help participants choose among various methods available for group decision making. Ranking research proposals, selecting officers of scientific societies, and choosing among prospective colleagues in academic and scientific organizations all require similar voting mechanisms, so information about voting options has wide applicability.

DESCRIPTION:

We briefly discuss key elements of social choice methods, including various voting criteria, strategic voting and agenda manipulation issues, and how different voting methods work. This will highlight two key aspects of voting rules -- what type of input voters provide and how that information is transformed into a group statement. Then, using a set of potential medical investments participants will select among options using different types of ballots (for example, “vote for one,” ranking, categorical grading and numerical scoring). We will show how each type of ballot uses a different algorithm to reach a social choice, and we will demonstrate and discuss how different types of voting systems lead to different choices, even for the same set of preferences. This discussion will emphasize the human factors associated with each type of ballot – ease of use, ability to express one’s preferences with clarity, and ease of understanding how individual ballots are converted to a group preference in each of the six voting (choice) mechanisms. In conclusion, we will ask voter to select which type of ballot they would use in the future, and discuss their choices and preferences with the participants.

Wednesday, May 23, 2018
8:30 AM - 9:30 AM
BREAKOUT SESSION
Economic Outcomes Research

8:30 AM - 9:30 AM
Room: Ballroom III (Level 400)

W17: DO CUTTING-EDGE ONE-TIME TREATMENTS NEED EQUALLY INNOVATIVE-, OUTCOMES-, OR ANNUITY-BASED PAYMENT MODELS?

Discussion Leaders:

Mark Chalmers, PhD, Principal & EU Lead, CBPartners, London, UK

Andrew Gould, MS, Principal, CBPartners, New York, NY, USA

Maximilian Hunt, BSc, Principal, CBPartners, New York, NY, USA

Omar Ali, BSc, DipClinPharm, MRPharmS, ACPP, Pharmacy Director, QIPP Adviser Commissioning Payer Network & former ERG Cost Impact Modelling, NICE, London, UK

PURPOSE:

The objective of this workshop is to discuss the pricing and reimbursement challenges posed by innovative one-time treatments, such as CAR-Ts and gene therapies, explore implementation considerations of potential novel payment models (outcomes-based, annuity payments & coverage with evidence development) and their feasibility for different global payer archetypes.

DESCRIPTION:

Majority of new drugs are priced with the expectation that they will be used on a regular basis for an extended period, spreading total cost over months or years. The price tags of CAR-T treatments or gene therapies, on the other hand, will correspond to a single one-time treatment cost that may create a potential affordability challenge in many markets. Moreover, while such new therapies offer potential long term clinical benefits there is often a lack of robust long-term data at launch that creates “uncertainty” in the value of the product.

New payment schemes are emerging in the context of high-cost one-time treatments to overcome payer objections and make these novel, often curative treatments available. Manufacturers and payers might also accept novel “instalment or annuity payment” schemes that can distribute cost over a longer period.

During the workshop, panelists and the participants will discuss implementation considerations of different emerging payment models from different stakeholders’ perspective. The moderators will guide the conversation to ensure that differences among different market archetypes are reflected in the feedback.

The final output will be feedback on a set of payment strategies prioritized based on the technology, disease and treatment outcomes as well as market archetype, HTA system, and payer value drivers.


8:30 AM - 9:30 AM
Room: Ballroom IV (Level 400)

W18: OPEN SOURCE SOFTWARE FOR BUILDING HEALTH ECONOMIC MODELS

Discussion Leaders:

Joseph F Levy, BS, Postdoctoral Fellow, Pharmaceutical Health Services Research, University of Maryland School of Pharmacy, Baltimore, MD, USA

Fernando Alarid-Escudero, PhD, Post-Doctoral Associate, Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN, USA

Erik J Dasbach, PhD, Executive Director, Outcomes Research, Merck & Co. Inc., Kenilworth, NJ, USA

PURPOSE:

This workshop will describe several new open source software tools for conducting health economic evaluations. Participants will observe how to build and execute various model types using these software packages and will gain understanding of which tools may be most appropriate for their future work.

DESCRIPTION:

We will discuss the well-known problem of reproducibility in economic models, highlighting several critiques of traditional Excel-based modeling approaches, including: 1) missing documentation of formal model tests 2) lack of transparency of code 3) limited ability to scale and extend model structure 4) difficulty to share and verify results, and 5) absence of version control and audit trails. We will offer novel open-source software as a potential solution to these problems.

The next section will introduce several new tools for building models 1) HEEMOD (Markov Models for Health Economics Evaluations) 2) DICE (Discretely Integrated Condition Events) and 3) R-core. Each has distinct advantages and disadvantages which will be discussed. We will then construct a simple Markov cohort cost-effectiveness model on a hypothetical pharmaceutical using all three software. For HEEMOD, this model will be built interactively and parts of the code will be written with audience participation. The other software based models will be run and graphics will be generated in real time.

In the last section, we will show the implementation of a previously published microsimulation model. The Sick-Sicker model incorporates time- and age-dependence. We will evaluate the cost-effectiveness of a treatment that differentially impacts sick and sicker individuals. We will walk through the already constructed model, showing the code required to run the model in both DICE and R-core. The generated outputs will be shown. We will then compare the experiences building the models with each tool and compare the time to build as well as time to run.

1:45 PM - 2:45 PM
BREAKOUT SESSION
Use of Real World Data

1:45 PM - 2:45 PM
Room: 310 (Level 300)

W19: MEDICAL DEVICE REAL-WORLD EVIDENCE FOR BEGINNERS: A PRIMER

Discussion Leaders:

Stephen S Johnston, MA, Director, Johnson & Johnson, Inc., New Brunswick, NJ, USA

Joshua Gagne, PharmD, ScD, Associate Professor of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics; Brigham and Women's Hospital and Harvard Medical School; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA

Frank R. Ernst, PharmD, MS, Executive Director, Real-World Evidence, CTI Clinical Trial and Consulting Services, Covington, KY, USA

Abhishek S Chitnis, MPharm, PhD, Associate Director, Epidemiology, Medical Devices, Real World Analytics and Research, Johnson & Johnson, New Brunswick, NJ, USA

PURPOSE:

Real-world evidence (RWE) is gaining an increasingly important role in the evaluation of medical devices. However, epidemiological, comparative effectiveness, and other varieties of medical device RWE present numerous unique challenges which are often not applicable to such studies on pharmaceuticals. The purpose of this workshop will be to provide participants with a fundamental understanding of these challenges and ways in which they can be addressed in applied research settings.

DESCRIPTION:

The first presenter will review the use cases, strengths, and limitations of available data sources for medical device research – including those commonly used for pharmaceutical research. Such data sources include hospital data, electronic medical records, administrative claims data, registries, the Manufacturer and User Facility Device Experience Database, and publicly-available survey data, among other sources. The second presenter will discuss specific approaches and challenges to medical device identification in databases with examples, followed by an overview of the Unique Device Identifier, its status relative to dissemination in real-world data sources, and its potential to shape the future of medical devices research. The third presenter will discuss the idiosyncrasies of how bias may arise in medical device research – including hospital and provider-level confounding, healthy-user bias, new medical device learning curves, among other issues – along with statistical and study design approaches that may be implemented to address such matters. The final presenter will discuss imminent and emerging sources of nontraditional medical device data, including information collected from ‘smart’ implantable devices, wearables, mobile health platforms, and other ‘internet of things’ platforms. Throughout the workshop, presenters will use a web-based instant audience response system to interactively poll participants on their experiences, opinions, and insights. The workshop will provide practical, specific, and actionable information for those who wish to advance their understanding of the fundamentals and emerging trends of medical device RWE.

Patient-Reported Outcomes & Patient Preference Research

1:45 PM - 2:45 PM
Room: Ballroom IV (Level 400)

W20: FIXING THE TOWER OF BABEL: ESTABLISHING A COMMON METRIC FOR PATIENT-REPORTED OUTCOME MEASURES

Discussion Leaders:

Jakob B. Bjorner, MD, PhD, CSO, Optum Patient Insights, Johnston, RI, USA

Benjamin D. Schalet, PhD, Research Assistant Professor of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

Felix Fischer, PhD, Researcher, Department for Psychosomatic Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany

Ian Kudel, PhD, Senior Scientist, Optum Patient Insights, Johnston, RI, USA

PURPOSE:

The patient-reported outcomes (PRO) field is replete with instruments measuring the same concepts, but using different questions, response scales, and scoring methods. The large number of different instruments hinders meta-analyses and comparisons of outcomes across studies assessing disease burden, clinical effectiveness, and health systems performance. To overcome these obstacles, methodology from educational testing has recently been adopted to develop common, concept-based metrics (eg, depression, anxiety, fatigue, physical function, and pain interference), allowing results from one PRO measure to be expressed in the metric of another measure using crosswalk tables. Transforming PRO scores to a common metric can potentially bridge gaps between databases and enable broader understanding of patient-centered outcomes. The objectives of this workshop are to educate attendees regarding the methodology, data and statistical requirements, application, and challenges associated with developing and using crosswalks.

DESCRIPTION:

The session will include: a) an outline of the standard statistical assumptions and data requirements for developing crosswalks and how psychometric approaches differ from those used in health economics, b) an overview of the most common designs and analytic methods for developing crosswalks, c) specific examples of projects to develop crosswalks including the National Institutes of Health-funded PROsetta Stone project, which has linked Patient-Reported Outcomes Measurement Information System (PROMIS®) measures and other widely-used instruments, d) introduction to web applications (eg, common-metrics.org) that can be used by researchers and practitioners to put data from different instruments on a common scale using established crosswalks, and e) a discussion of the challenges associated with developing crosswalks in one language/culture and generalizing the results to others. Participants will provide feedback on the strengths, limitations and potential applications of the crosswalk methodology and prioritize domains and instruments for development of new crosswalks.

Use of Real World Data

1:45 PM - 2:45 PM
Room: 309 (Level 300)

W21: PRINCIPLES OF EFFECTIVE MACHINE LEARNING APPLICATIONS IN REAL WORLD EVIDENCE

Discussion Leaders:

Andrew Cox, PhD, Research Scientist, Data Analytics, Evidera, London, UK

Sreeram Ramagopalan, Ph.D, Director, Center for Observational Research and Data Sciences (CORDS), Bristol-Myers Squibb Pharmaceuticals Ltd, Uxbridge, UK

Gorana Capkun-Niggli, PhD, Head of HEOR Innovation, Novartis Pharma AG, Basel, Switzerland

David J. Vanness, PhD, Associate Professor, Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA

PURPOSE:

The aim of this workshop is to illustrate the key challenges faced when planning and executing machine learning (ML) projects and to describe best practices, which help ensure the integrity and validity of Real-World Evidence (RWE) involving ML.

DESCRIPTION:

ML is well adopted by many industries. It is commonly used in the drug discovery process but its application to randomized controlled trials and real-world data is in its infancy. As with any methodologies, it has the potential for incorrect or inappropriate use. This is exacerbated due to the lack of established guidelines concerning the ML best practices and its role and use in a dialogue with regulatory and payer bodies. The background ML expertise within pharmacoeconomics and outcomes research is still at an early stage of its evolution, and such domain expertise is an essential component for high quality rigorous studies. In this workshop, through didactic presentation and interactive review of ML abstracts, we aim to present five key challenges for ML projects, and our suggestions for overcoming them. The challenges include; selection of use cases, understanding and reporting predictive performance, preventing overfitting, overcoming the ‘black box’ criticism and dealing with hyperparameters. Our aim is to help ML practitioners produce rigorous outputs and inform reviewers how to assess ML research critically and effectively.

3:00 PM - 4:00 PM
BREAKOUT SESSION

3:00 PM - 4:00 PM
Room: Ballroom III (Level 400)

W22: THE MEDIUM IS THE MESSAGE: USING INTERACTIVE GRAPHICS TO EFFECTIVELY COMMUNICATE HEALTH ECONOMICS AND OUTCOMES RESEARCH FINDINGS

Discussion Leaders:

Shelagh M Szabo, MSc, Principal and Scientific Director, Broadstreet Health Economics & Outcomes Research, Vancouver, BC, Canada

Ross Tsuyuki, MSc PharmD, Professor, University of Alberta, Edmonton, AB, Canada

Andrew Lloyd, PhD, Director, Acaster Lloyd Consulting Ltd., London, UK

Bonnie M Donato, PhD, Senior Director, Global Health Outcomes, Alexion Pharmaceuticals, Inc, New Haven, CT, USA

PURPOSE:

The results of HEOR studies can be difficult to understand, interpret, and use effectively. Recent developments in data visualization in other fields can inform novel strategies for effective evidence communication in HEOR. The purpose of this workshop is to: 1) present the scientific theory behind how individuals receive and process complicated information, including graphically; 2) highlight challenges, and innovative developments in, data visualization and evidence communication in HEOR; and 3) identify participants’ preferences for data visualization, and potential solutions for their data challenges.

DESCRIPTION:

First, we will review the latest science on the effective use of data visualization. We will then consider where these techniques have been successful, and less successful, using real-world HEOR data. Ross Tsuyuki will review trends in visualization of economic model output, using a model of a pharmacist-led intervention for hypertension. Andrew Lloyd will discuss the challenges in presenting PRO study findings in a meaningful way; contributed to by the measurement properties of commonly-used instruments, and the extent to which we can interpret differences in scores. Shelagh Szabo will demonstrate the visualization of the results of additional case studies of real-world observational, evidence synthesis, and PRO studies. These examples will illustrate the value of dynamic interfaces in presenting the results of complex analyses; as well as the use of infographics for scientifically-credible storytelling. Bonnie Donato will review considerations from the HEOR industry perspective; including changing needs of key audiences (e.g. HTA and other payers), challenges in ensuring product messages are clearly communicated, and thoughts on how data visualization tools can effectively support healthcare decision-making.

Finally, participants will participate in a real-time survey where their choices on a series of comparisons will reveal their preferences for data visualization output. Participants will then be able to present their own data visualization challenges to workshop members, to brainstorm potential solutions.

Economic Outcomes Research

3:00 PM - 4:00 PM
Room: Ballroom IV (Level 400)

W23: ESTIMATING THE COST OF ADVERSE EVENTS IN ECONOMIC MODELS: A DISCUSSION OF REAL-WORLD DATA VERSUS TREATMENT GUIDELINES BASED METHODOLOGIES

Discussion Leaders:

William Wong, PharmD, MS, Sr. Health Economist, US Medical Affairs, Genentech, Inc., South San Francisco, CA, USA

Martin Cloutier, MSc, Manager, Analysis Group, Inc., Montreal, QC, Canada

Josh J. Carlson, MPH, PhD, Associate Professor, Pharmaceutical Outcomes Research and Policy Program, Department of Pharmacy, University of Washington, Seattle, WA, USA

PURPOSE:

This workshop will introduce some of the issues and methods in estimating adverse event costs and their application to economic modeling, with a focus on oncology.

DESCRIPTION:

Incorporation of adverse events into oncology economic models is important as there are various tolerability profiles across the spectrum of cancer treatments. Furthermore, oncology adverse events are unique in that they are typically graded by severity using the Common Terminology Criteria for Adverse Events (CTCAE). Different methods can be used to estimate the cost per adverse event; however, the varying methodologies have their own strengths and limitations and can result in vastly different estimates. This session will begin by providing an overview of adverse events in oncology and the increasing importance of robust estimates in the context of competent and reliable scientific evidence (CARSE) standards. Next, we will provide an overview of an approach to estimate costs per adverse event from real-world data, including the methods and results of a recent project aimed at estimating costs across a variety of cancer types. Lastly, we will discuss a guidelines-based approach, including a comparison of cost estimates from the two methods. Strengths and limitations of both approaches will be highlighted and recommendations will be discussed. This workshop is appropriate for anyone looking to begin or further his/her understanding and skill set in oncology economic modeling from the U.S. perspective.

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