Plenary: Cutting Edge Research Plenary
Wednesday, 21 October | 8:00 am – 9:10 am CDT
The Cutting Edge Research plenary session features some of the highest-ranked, innovative research from ISOQOL abstract submissions. In particular, these abstracts reflect research that truly “pushes the ISOQOL envelope” in providing new and different ways to look at quality of life.
Plenary: “Hello, is it me you’re looking for?”: Measuring what matters to us.
Wednesday, 21 October | 9:30 am – 11:00 am CDT
Sponsored by EORTC
A plenary session focused on patient engagement and led by patient advocates. The goal of this plenary is to stimulate discussion regarding theory, methods and application of optimal patient and advocate involvement.
Allyson Berent, DVM DACVIM, Foundation for Angelman Syndrome Therapeutics and GeneTx Biotherapeutics, New York, New York, United States
Dr. Allyson Berent graduated from Cornell University College of Veterinary Medicine in 2002 and completed a residency in veterinary internal medicine at the University of Pennsylvania in 2005, followed by a fellowship in interventional radiology and endourology at the University of Pennsylvania and Thomas Jefferson University. Since 2009, she serves as the director of the Interventional Endoscopy Service at the Animal Medical Center in NYC. Dr. Berent is the CSO of the Foundation for Angelman Syndrome Therapeutics and the Chief Operating Officer for GeneTx Biotherapeutics, developing a novel antisense olignonucleotide for the treatment of Angelman syndrome, as rare neurogenetic disorder.
Kemi Doll, MD MSCR, University of Washington, Seattle, Washington, United States
Dr. Kemi Doll is a gynecologic oncologist and Assistant Professor in the Department of OBGYN and an Adjunct Assistant Professor in the Department of Health Services in the School of Public Health. Her research centers on examining Black-White racial inequity in the care of benign and malignant gynecologic disease in the US. Her research has been funded by the NIH, the Robert Wood Johnson Foundation, and the Patient Centered Outcomes Research Institute (PCORI). She is the co-founder of ECANA, the Endometrial Cancer Action Network for African-Americans (ecanawomen.org) a community-research partnership formed to improve survival among Black women with endometrial cancer.
Elizabeth Unni, PhD MBA Bpharm
Plenary: “It’s not about the money, money, money”: Or is it? The future of value-based healthcare and outcomes-based pricing.
Thursday, 22 October | 8:00 am – 9:30 am CDT
Innovations in healthcare technology are putting increasing pressure on constrained healthcare budgets, and this has led to an emergence of outcomes-based pricing models. The goal of this plenary is to discuss how clinical outcome assessment data are being incorporated into these access systems as well as the benefits and limitations of this model.
Lotte Steuten, PhD, Office of Health Economics, London, United Kingdom
Lotte Steuten, PhD, is Vice-President and Head of Consulting at the Office of Health Economics and Honorary Visiting Professor at City, University of London, UK. Lotte specialises in providing research-based and client-focused analysis and expertise to informing decisions regarding healthcare policy, pricing and regulation of pharmaceuticals, and health technology assessment (HTA). She effectively collaborates with technology assessors, payers and policy makers, (academic) researchers, clinical and patient representatives, pharmaceutical industry and capital investors. Lotte has contributed to the health economics and outcomes research for >15 years in various academic roles and executive functions in the UK, US and the Netherlands.
Paula Williamson, University of Liverpool, Liverpool, United Kingdom
Paula Williamson is Professor of Biostatistics at the University of Liverpool, and was Head of the Department of Biostatistics from 2002 until 2018. Her research has focussed on clinical trials, meta-analysis, and health outcome selection. Paula leads the MRC/NIHR Trials Methodology Research Partnership. She is an NIHR Senior Investigator, a Fellow of the Academy of Medical Sciences, and gave the Bradford Hill Lecture in 2017. Paula co-founded the (Core Outcome Measures in Effectiveness Trials) Initiative in 2010, to improve the quality and relevance of health research to decision makers including patients, health professionals, regulators and policymakers.
Stefan Larsson, MD PhD, The Boston Consulting Group, Stockholm, Sweden
Stefan Larsson joined the Boston Consulting Group in 1996 and is a Senior Partner and a BHI Fellow. Stefan has lead strategy assignments and major transformational programs across all sectors of the healthcare industry: Academic medical centers; leading international providers; Biopharma; Biotech and MedTech – from R&D through commercial. He is a cofounder and board member of ICHOM. Stefan has been BCG‘s global sector leader for Healthcare Payers and Providers and later the Healthcare Systems sector. Stefan is an MD, PhD and Associate professor at the Karolinska Institute (KI). Stefan trained at Harvard MS, MRC-HGU, Edinburgh and EMBL Heidelberg.
Patricia Corey-Lisle, PhD MSN
Plenary: “Video killed the radio star”: How technology is changing the way we collect, analyze and interpret patient-relevant data.
Friday, 23 October | 8:00 am – 9:30 am CDT
The goal of this plenary session is to hear how technology is impacting our work. We will hear from innovators working both inside and outside our field as they paint a picture for the future of outcomes measurement and quality of life research.
Marie Deserno, PhD, Max Planck Institute for Human Development, Berlin, Germany
Dr. Marie Deserno is a postdoctoral research fellow at the Formal Methods group of the Max Planck Institute for Human Development in Berlin, Germany. Supported by a NWO Rubicon fellowship her research deals with models of change in developmental psychology and quality of life research in the autistic community. Her work is strongly rooted in the network approach to psychology developed at the Psychosystems group (University of Amsterdam) and sits at the intersection of developmental psychology and psychological methods.
Katarzyna Wac, PhD, University of Geneva, Quality of Life Technologies Lab, Geneva, Switzerland
Katarzyna Wac is a Professor of Health Informatics at the Department of Computer Science, University of Copenhagen, Denmark, and at the University of Geneva, Switzerland, affiliated with Stanford University since 2013. Dr. Wac leads Quality of Life (QoL) Technologies lab researching how mobile and emerging sensor-based technologies can be leveraged for an accurate, longitudinal personalized assessment of the individual’s behavior and QoL, as they unfold naturally over time and in context, and the improvement of the latter. More info at katarzynawac.org.
Kim Oostrom, PhD
Chris Sidey-Gibbons, PhD
Roundtables are informal meetings, with up to nine participants, to network and discuss a select topic related to your work and field. Pre-registration is required and seating is available on a first-come, first-served basis.
Monday, 19 October | 10:00 am – 11:00 am CDT
Roundtable 01: Taking PROs into clinical practice: Implementation vs research- which should we be prioritising?
With increasing evidence supporting the beneficial role PROs can play in clinical practice how should we be advancing the field? Can more progress be achieved through research activity or should implementation and quality improvement projects be given priority? At this roundtable, we will discuss the pros and cons, barriers and facilitators around each approach. Attendees will have the opportunity to share opinions and experiences- so bring along your views and your questions!
Kate Absolom, PhD
University of Leeds
Roundtable 02: What's next for Modern Psychometrics?
Metrology offers a natural framework for the development of psychometrics theory. In this roundtable, we will discuss how quality-assured measurement can be achieved for PRO measures, building on modern psychometrics methods, typically the Rasch measurement theory. We will address challenges and opportunity of using metrological principles for clinical research and clinical practice.
Antoine Regnault, PhD
Roundtable 03: Moving Important Change Threshold Thinking From Minimal to Meaningful Change
The term “minimal clinically important difference” or MCID describes the smallest magnitude of change in a patient-reported outcome score that represents an important patient benefit; yet, in the quest for a minimal threshold may lose sight of what is most meaningful to patients. We will share and discuss methods that provide insights for understanding meaningful change over time.
Kathy Wyrwich, PhD
Tuesday, 20 October | 10:00 am – 11:00 am CDT
Roundtable 04: Big Data in PRO research: What happened and what is next?
Chris Sidey-Gibbons, PhD
MD Anderson Cancer Center
Roundtable 05: The multiple dimensions of Patient Engagement
The phrase ‘Patient Engagement’ takes on different meanings when used in different contexts. Through interactive discussion this roundtable will explore the different ways patient engagement is defined and how it has and continues to evolve.
Danielle Lavalle, PharmD PhD
BC Academic Health Sciences Network
Monday, 19 October | 7:00 am – 10:00 am CDT
Workshop 1: How Patient Engagement and PROMs are Changing Conversations and Care in Complex High-Stakes Chronic Conditions Across the Lifespan: A Roadmap to Routine PROM use in Clinical Practice
Workshop level: Basic
Although major advances allow individuals with formerly life-limiting or life-threatening illnesses to lead full lives, providing timely, responsive care for complex health conditions remains challenging and very costly to patients and society. A compelling example is chronic progressive organ injury leading to failure of vital organs (kidney, lung, heart, and liver) in children and adults. While solid organ transplants can extend life for decades, up to 50% experience ongoing physical symptoms, emotional distress, and social disruptions that impair HRQoL and result in ED visits/hospitalizations. We will provide real world examples of how PROMs greatly impact communication, care, and HRQoL in complex chronic illness programs across the lifespan.
This workshop offers a roadmap for patients, clinicians, administrators, and policy makers seeking to implement PROs for high stakes chronic illnesses. The unique psychosocial challenges of children, teens, and adults living with complex medical illnesses will be highlighted.
Introduction (10 minutes)
Expert Presentations (80 min)
• PROMs are Changing Conversations and Transplant Care
• Multiple Needs, Multicultural Contexts: Ensuring PROMs are Accessible, Responsive, Interpretable, and Actionable to Broad Groups of Users
• Roadmap for Implementing PROs in Adults with Complex Health Conditions
• Measuring What Matters: an eHealth Intervention within a Pediatric Transplant Clinical Practice
Break (10 minutes)
Breakout Session (Activity/Debriefing 60 minutes)
Using a case-study approach, attendees will work in small groups to:
• Identify patient/family/clinician/stakeholder needs
• Review how stakeholder preferences, setting, IT, and psychometric factors impact PROM selection
• Identify potential barriers and strategies to facilitate uptake and sustainability
• Develop learning solutions for patients/families/clinicians/others to enhance value
Q & A (15 minutes)
Wrap-up (5 minutes)
1. Illustrate the potential impact of PROMs on communication and shared decision making in complex, high-stakes health conditions in children and adults using real world examples
2. Provide a roadmap for assessing the needs of patients, families, clinicians and other stakeholders when selecting a core set of PROMs across programs
3. Compare strategies to identify potential barriers, enablers, local champions and increase buy-in for implementation and sustain use of PROMs
Workshop 3: Using Rasch and Classical Test Theory to Assess the Reliability and Validity of Clinical Outcomes Assessments: A Hands-on Workshop
Workshop level: Basic
The goals of the workshop are to discuss Rasch measurement theory and classical test theory and how they can complement one another when evaluating clinical outcome assessments. Specific objectives are to: (1) describe basic concepts of classical test theory and how it can be used to measure reliability and validity; (2) detail introductory concepts and how/when to use Rasch measurement theory to measure reliability and validity; (3) discuss similarities, differences, and limitations of Rasch measurement theory, classical test theory, and item response theory, along with how they can complement one another; (4) detail assumptions, model properties, fit parameters, and recommendations for Rasch analysis using Winsteps software; and (5) provide participants a hands-on experience using the Rasch rating scale model to analyze the validity and reliability of a sample clinical outcomes measure.
Participants interested in learning modern psychometric techniques for measuring validity and reliability of clinical outcome assessments would benefit from this workshop. The level of the workshop is set as introductory.
The workshop outline will be as follows: 1) Overview of clinical outcome assessments including patient reported/centered outcomes; 2) Classical test theory; 3) Rasch measurement theory; 4) How can Rasch, Classical test theory, and Item response theory complement one another?; 5) Rasch model specifications and recommendations; 6) Hands-on Rasch rating scale model analysis in Winsteps software.
1. Participants will be able to discuss clinical outcomes assessments (COAs) including patient-centered outcomes, their components, item generation, biases, reliability and validity, scaling and responses as well as classical test theory. Specifically, discussion will be focused on qualitative and quantitative assessments of each these concepts and providing participants an overview of issues related to measurement. Emphasis will be placed on basic concepts of classical test theory and how it can be used to measure reliability and validity. The presentation format for this objective will be PowerPoint slides. Interaction will be encouraged with Q&A.
2. Participants will be introduced to theory and applications of Rasch measurement with specific emphasis on the assumptions of this model in COA development and validation. Introductory concepts and how/when to use Rasch measurement theory to measure reliability and validity will be detailed. Similarities, differences, and limitations of Rasch measurement theory, classical test theory, and item response theory will be discussed, along with how they can complement one another. Assessment will be described in terms of person ability, scale reliability and validity, and item difficulty. Properties and requirements of Rasch models will be explained in detail. For dichotomous and polytomous data, model fit parameters and recommendations will be provided for analysis in WINSTEPS. Further, summaries of Rasch requirements, relevant WINSTEPS tables, and criteria-specific recommendations will be provided. The presentation format will be PowerPoint slides and handouts. Interaction will be encouraged with Q&A, and input on interpretation of example figures and tables.
3. Participants will gain hands-on experience with using a Rasch rating scale model and practice procedures to run the analysis in WINSTEPS, using the guidelines and recommendations learned during the session. Participants will be asked to download the free version of WINSTEPS ahead of time. A sample dataset (for example, sample responses to a questionnaire with a 4-point Likert scale) of less than 75 observations and analysis code will be provided. Instructors will walk through the analysis and highlight key procedures and result output table numbers, where the relevant coefficients and parameters can be found to effectively analyze the validity and reliability of the sample clinical outcomes measure. The presentation format of this learning objective will be analysis demonstration in WINSTEPS software and PowerPoint slides to facilitate discussion of sample results and figures. Interaction will be encouraged with instructors providing assistance with running analyses and group interpretation of findings.
Workshop 4: Stated-preference methods – an alternative method to measure the patient perspective
Workshop level: Basic
There is a growing emphasis on understanding the patient perspective in health research, care, and policy. Patient-centered outcomes and health state utility evidence are one way to incorporate the patient perspective into healthcare decision making. Patient preference studies are starting to gain traction as an alternative or complimentary source of evidence on the patient perspective.
Stated-preference methods are increasingly used to engage patients and to inform decision making in variety of healthcare settings (e.g. clinical trial design, regulatory assessment, value assessment, shared decision making). Identification of the appropriate stated-preference method requires a thorough understanding of the research question and study objective. To ensure valid and reliable results, good research practices in the development, design, conduct, analysis, and interpretation of the methods need to be applied.
This workshop will provide participants with a practical understanding of a variety of stated-preference methods including discrete-choice experiments (DCE), best-worst scaling (BWS), and rating/ranking techniques. We will demonstrate how these methods can be used to engage populations of patients and other stakeholders. Challenges with particular methods will be highlighted with case studies and potential solutions will be identified. Attendees will develop an understanding of the possible applications of stated-preference methods and strategies to overcome practical challenges of conducting stated-preference studies.
Participants interested in learning about patient preference methods to incorporate the patient perspective into health research, care, and policy. No prior knowledge on stated-preference methods is required.
We will identify research questions that can be answered through stated-preference studies. We will discuss good research practices for stated-preference survey development, experimental design, statistical analysis, and interpretation of results.
- Overview of stated-preference methods
- Definitions of stated preferences methods
- How do they differ (PROs, QALYs, MCDA)
- What are common stated-preference methods
- Pros and cons of each method
- Applications of stated-preference studies in healthcare decision making
- Good research practices fro stated-preference methods
- Developing a stated-preference study
- Survey walk-through
- Principles of experimental design
- Different analytical approaches
- Data setup and analysis exercise
- Critical appraisal of stated-preference studies
- Developing a stated-preference study
- Case studies in stated-preference methods
Challenges and solutions
1. Understand the difference between patient-centered outcomes, health state utility, and patient preference studies
2. Identify research questions and study objectives that can be answered through stated-preference methods and discuss how these methods can be used in a variety of therapeutic areas and stakeholder groups.
3. Recognize good research practice for survey development, experimental design, and analysis when designing stated-preference study
Tuesday, 20 October | 7:00 am – 10:00 am CDT
Workshop 5: Interpretation guidelines for clinical relevance of Patient-Reported Outcome (PRO) measures
Workshop level: Basic
To provide participants with comprehensive guidelines outlining the steps involved in establishing a minimal important difference (MID) or clinically important response (CIR) on Patient-Reported Outcome (PRO) measures. Using examples from experience in academia and industry, key challenges and considerations when establishing MID or CIR estimates will be outlined. The workshop will be adapted from successful workshops run at ISOQOL in 2017/2018 to include recent developments in FDA guidance, triangulation, interpretation within clinical practice and item response theory-based approaches.
Statisticians, Outcomes researchers, Instrument developers, Industry attendees. No prior knowledge of interpretation guidelines is assumed.
Establishing clinical relevance is important to numerous key stakeholders. Interpretation based on statistical significance alone isn’t recommended, as any observed difference can be significant depending on sample size. From a clinician perspective, benefits of a new treatment and its implications for clinical management of the patient are key considerations in judging the value of a treatment. The clinical relevance of differences in scores on a PRO instrument may need to be interpreted at the group-level, e.g. when assessing the average benefit of two treatments in a clinical trial, or at the individual-level, e.g. when determining whether a patient has improved or deteriorated significantly over a specified period of treatment.
Various techniques will be introduced, using examples to highlight their practical application in deriving thresholds, and the contexts that each is best suited for.
Key challenges will be discussed:
- Thresholds for group change (e.g. average of a sample of individuals) compared to thresholds for change within an individual (responder definition): why different methods may be required to establish these and why thresholds obtained may not be the same
- The role of distribution-based estimates, anchor-based estimates, and qualitative approaches (e.g. patient interviews)
- The process of triangulation to combine multiple estimates and a standardized approach.
- Anchor selection and the difficulties identifying good anchors plus the impact on the resulting threshold estimates
The workshop will aim to clarify the methodology in the field leading to a more standardized approach for derivation of MID/CIR.
1. Introduction to clinical relevance and methodological overview. Participants will gain an understanding of what clinical relevance means in the context of PRO COAs and why it is important for interpretation of PRO data. Participants will be introduced to the different terminology used in the field and a framework for interpreting PRO measures at group and individual levels, distinguishing between applications that require interpretation of PRO scores between groups/individuals versus within groups/individuals. Participants will learn about the various methods available to judge whether the degree of change (within a group or individual) or difference (between groups or individuals) is clinically meaningful, including novel emerging methodology in the field. They will learn that different techniques are required for each different type of interpretation within the above framework. There will be a discussion around the use of historical thresholds and how these may need updating in the light of new methodology.
2. Practical examples of deriving and using interpretation guidelines. A real world example will be used to show how estimates from anchor-based and distribution-based methods can be combined, and how qualitative data can be utilized. Participants will learn about triangulation and how to plan this stage of establishing interpretation guidelines; a systematic approach to triangulation will be presented. In addition, the AURELIA trial will be used to illustrate how some of the methodology discussed can be used in practice. This example includes the use of cumulative distribution functions to highlight interpretation across a range of possible thresholds for clinical relevance.
3. Challenges, limitations and future direction. Participants will develop an awareness of key considerations and challenges associated with deriving interpretation guidelines. Topics covered include finding suitable anchors that correlate well with PRO scores and the impact of this correlation on estimation of clinically relevant differences using ROC methods as an example and the limitations of underlying categorical scales in determining the appropriate level of individual response. Participants will hear about the latest developments and solutions for interpreting PRO data.
Workshop 6: Bayesian Nonparametric Mixture Modeling and Patient Reported Outcomes Research
Workshop level: Advanced
This tutorial will: 1) show you what the BNP look like using a lot of visual explanations; 2) explain the essential mathematical derivations often omitted in existing expositions you find online; and 3) demonstrate how to fit a simple BNP model. The R code will be explained line-by-line to make the equations concrete and explicit, so that you know precisely how the computation algorithm works. I hope you will take home with a fundamental intuition to continue to learn more on your own.
The intended audience is researchers who want to know BNP but find existing tutorials too technical or too simple.
The prerequisites are:
- Familiarity with R programming (e.g., how to simulate data from standard distributions). However, the programming skills required are no more complicated than writing simple functions or sampling data from standard distributions.
- Familiarity with basic Bayesian statistics at an introductory level (e.g., conditional probability and familiarity with why conjugate priors make Bayesian computation easier)
- Consider bringing a laptop with R already installed so that you can run the R program right away
Machine Learning analytic techniques are gaining popularity at ISOQOL in recent years, e.g., in the Cutting-Edge Research sessions in the 2019 meeting in San Diego. However, exiting applications are primarily based on well-established off-the-shelf methods. There is a need to help ISOQOL members to go beyond these basic methods. Bayesian nonparametric (BNP) models are part of Machine Learning and AI in the internet era. However, tutorials found online tend to be abstract and complex. Key ideas are assumed understood or explained at a level not easily accessible to non-technicians. This tutorial’s primary aim is to make BNP accessible to a broad audience of non-experts, using the Dirichlet Process (DP) mixture model as an illustrative example. I hope that this workshop will also be useful to more experienced analysts and psychometricians, perhaps as a refresher course.
1. Treatment heterogeneity. It is well known that different people respond to interventions differently. Examples of behavioral interventions are programs to encourage smokers to quit, hypertensives to take medications, diabetics to exercise, or individuals with a high risk of a disease to engage in more frequent screening. They may also involve adhering to a daily medication. Scientists always look for newer and more precise person profiling methods to find out the how, when, under what circumstances and for whom the intervention would work best. Bayesian nonparametric methods may be used to discover subgroups of patients with unique PRO profiles. These unique PRO profiles may be linked to differential treatment responses. Our first aim is to understand why we need to discover these PRO profiles.
2. BNP is flexible and adaptive. The main strength of a Bayesian nonparametric (BNP) analytic technique is that BNP models can grow in complexity as it encounters more data. This is accomplished by a unique analytic approach called the “Stick Breaking” algorithm. For example, researchers at Microsoft use BNP methods to predict online fraud based on user characteristics in digital experiments. We will go over the “stick breaking” algorithm and its flexibility and discuss how we can capitalize on this feature in the discovery of PRO profiles. We will go over the stick-breaking algorithm step by step and explain why it works and how to use it. Hypothetical data will be used to help attendees grasp the fundamental ideas of BNP.
3. Real-world data analysis. We will use real-world data collected in a grant (NIH R01 CA128134, PI: Breitbart), a randomized controlled trial comparing Individual Meaning Centered Psychotherapy (IMCP, n=109), Supportive Psychotherapy (SP, n=108) and Enhanced Usual Care (EUC, n=104), in reducing psychological distress and improving meaning making in patients with advanced and terminal cancer. I will show you, step by step, how to use BNP to discover treatment heterogeneity in baseline patient-reported anxiety and depression. Briefly, a BNP cluster analysis identified 5 subgroups of patients with unique profiles of anxiety and depression scores before psychotherapy. BNP shows that cancer patients who report mild symptoms in both anxiety and depression are most likely to respond to IMCP as compared to EUC. BNP cluster analysis in IMPC psychotherapy is just an illustrative example. The techniques can be applied in any other mediation/moderation analysis.
Workshop 7: Patient-focused endpoints: Developing and analyzing PRO endpoints with considerations for missing data for optimal interpretability
Workshop level: Advanced
The goals of this workshop are to:
1. Provide the context for patient-reported endpoints in clinical trials and real-world prospective studies,
2. Learn how to define appropriate endpoints from patient-reported outcome (PRO) measures,
3. Learn techniques for statistically evaluating PRO endpoints while considering missing data, and
4. Presenting PRO endpoints for optimum interpretability.
The workshop is intended for academics, outcomes researchers, and clinical trialists who design clinical trials and real-world prospective studies with patient-reported endpoints and/or who analyze PRO data.
- Importance of PRO endpoints:
- It is now mandated in the US that patients are active participants in drug development.
- Regulatory and reimbursement authorities in European countries have moved from considering PRO information supportive to required.
- As such, the ability to define and interpret these endpoints is increasingly critical.
- Considerations for PRO endpoints:
- PROs directly measure a patient’s symptoms, functional status, and health-related quality of life.
- These complex constructs require careful consideration to capture temporal relationships and severity of response.
- Variability in the scoring methodologies and recall periods makes interpretation of results is complex.
- Analytic approaches must address complexities to interpret conclusions for non-statistical stakeholders.
- Importance of PRO endpoints:
- Defining interpretable patient-focused endpoints
- A patient-centered endpoint quantifies patient experience in a meaningful way.
- Interpretation of patient-focused endpoints. Specifically:
- Evaluating meaningful change through responder analyses, including:
- Comparing proportions of responders at specific endpoints
- Evaluating clinical and symptomatic response jointly
- Cumulative likelihood of meaningful response
- Time to improvement or deterioration of symptoms or function, including:
- When to measure improvement versus deterioration
- Defining meaningful improvement/deterioration
- Inclusion of death in the event definition
- Single item analysis. Specifically:
- Why it is important to evaluate item-level response
- Heterogeneity of scales
- Analytic approaches to:
- describe distribution of responses
- estimate the likelihood of 1- or 2-grade change
- estimate time to 1- or 2-grade change.
- Missing PRO data
- How can we mitigate the impact of missing PRO response?
- Analytic methods for handling missing data
- Sensitivity analyses for PROs
- Evaluating meaningful change through responder analyses, including:
Estimands for PRO endpoints
1. Given a PRO measure, design three interpretable patient-focused endpoints for a clinical trial or real-world study
2. Articulate the importance of evaluating meaningful change and describe four ways in which to analyze within-person change while accounting for missing data
3. Describe the value of analyzing single items within a PRO scale including the concepts of item construct heterogeneity, temporal relationships to the endpoint and severity variability
Workshop 8: Measuring Latent States in Medical Research: from Theory to Practice
Workshop level: Advanced
To review measurement theory, connections between theory and various scoring alternatives, and ramifications for how these different scoring alternatives impact the assessment of change in the measurement of health-related states.
After attending, participants should understand:
- The fundamental role that a theory of a latent state plays in determining a measurement strategy of that latent state. By showing how to ground measurement approaches in theory, the content and construct validity concepts can be effectively bridged and coherently capture patient experiences.
- The different approaches and mathematics that underpin scoring for classical and modern psychometrics–specifically the differences between sum scores and model-based scores. By evaluating the different approaches, participants will understand how the approaches to scoring items rated by individuals capture similar and different aspects of latent stats and how the differences can be expected to manifest in real-world situations.
- Different alternative approaches to analyzing changes in scores in terms of individual differences versus group comparisons. Participants will understand the merits of different techniques such as raw changes, residual changes, and regression methods as well as modeling methods. Further the participants will explore the important concept of within-individual versus between-group change assessments and how this dichotomy relates to the different approaches to analyzing change scores.
Practitioners of classical and modern psychometric methods for measurement of health states within clinical research settings.
- Introduction and overview
- Measurement and measurement theory
- Measurement across different fields such as physical and social sciences
- Psychometrics and clinical/medical research
- Psychometric scoring
- Classical methods—scores assuming tau-equivalency
- Modern methods—model-based scoring
- Analysis of scores
- Group methods
- Raw change scores
- Alternative methods such as residual scores and regression estimates
- Individual differences—accounting for within-person change
- Implications for practice: Considering the importance of linking within-person change to scores
- Group methods
1. For participants to understand the fundamental role that a theory of a latent state plays in determining a measurement strategy of that latent state. Therefore, by grounding measurement approaches in theory, the content and construct validity concepts are bridged and coherently capture patient experiences. To illustrate the relationship between the theories and practices of measurement, examples from across different fields of study, e.g., physical, social, and medical sciences, will be compared and contrasted.
2. The different approaches and mathematics that underpin scoring for classical and modern psychometrics will be compared including sum scores and model-based scores, e.g., homogeneous expected a priori scores such as those from a Rasch model, and expected a priori scores from heterogeneous graded response models. By presenting the different approaches, participants will gain an understanding of how the approaches to scoring items rated by individuals are similar and different and how the differences can be expected to manifest in real-world situations.
3. Different alternative approaches to analyzing changes in scores in terms of individual differences versus group comparisons will be presented, such as raw changes, residual changes, and regression methods as well as modeling methods will be presented. The merits of these different techniques will be explored. The important concept of within-individual versus between-group change assessments will be used to juxtapose the different approaches to analyzing change scores.
Awards and Member Business Meeting
Friday, 23 October | 10:00 AM – 11:00 AM CDT
The Awards and Member Business Meeting includes presentation of annual awards, leadership transition, and official ISOQOL business. Since membership dues are included in the conference registration, all Annual Conference attendees are members and and encouraged to attend this session.
The International Society for Quality of Life Research (ISOQOL) is a global community of researchers, clinicians, health care professionals, industry professionals, consultants, and patient research partners advancing health related quality of life research (HRQL).
Together, we are creating a future in which patient perspective is integral to health research, care and policy.