Morning Workshops 9:30 am - 12:30 pm
Workshop 1
The International Classification of Function Disability and Health (ICF) and its application in clinical practice and research
Nancy Mayo and Alarcos Cieza
With the approval of the new International Classification of Functioning, Disability and Health (ICF) by the World Health Assembly in May 2001, all WHO member states are now being requested to implement the ICF in the health sector. Besides health, the WHO promotes the use of the ICF in education, insurance, labor, health and disability policy, and health statistics.
The aim of this workshop is to introduce the contents and structure of the ICF, as well as the bio-psycho-social model, which is the basis of the classification. The ICF Core Sets - tools to implement the ICF in clinical practice and research - will be presented in detail. The development process of the ICF Core Sets will be presented on the basis of an exercise in which the participants will have the opportunity to actively implement the ICF.
Since Health Related Quality of Life (HRQoL)- and ICF-based approaches will often be used concurrently in clinical practice, research, and health reporting, it is essential for clinicians and researchers to understand the relationship between HRQOL instruments and the ICF. The process of mapping HRQoL instruments to the ICF, which makes possible the content comparisons among instruments, will be introduced in detail. The usefulness of such a linkage process in identifying the best measures to most efficiently cover the required categories of functioning in studies and how the mapping process can be applied to create Functional Status Indicators (FSI) will also be discussed.
At the completion of the workshop, all participating clinicians or researchers should be familiar with the different components and structure of the ICF, the process of implementing the ICF in clinical practice and research, the relationship between HRQoL measures and the ICF and with the concept of ICF based FSIs.
Level - Basic
Workshop 2
Introduction to Assessing Health-Related Measures in Diverse Populations
Anita Stewart, Anna Nápoles-Springer and Stephen Gregorich
Research to understand the nature of health disparities and the mechanisms by which these occur involves comparing health or determinants of health across racial, ethnic, and language groups. However, most self-reported measures of health and its determinants were developed and tested in mainstream populations without accounting for the perspectives of diverse groups Researchers need to know that the concepts and measures used in health disparities research are culturally appropriate, have adequate reliability and validity, and perform equivalently across groups of interest. We will present three topics: 1) issues in assessing the conceptual and psychometric adequacy and equivalence of self-report measures in studies that compare health across diverse groups, including approaches for reviewing the adequacy and equivalence of existing measures in diverse population groups for use in a specific study, 2) qualitative methods appropriate for pretesting potential measures in diverse groups such as behavioral coding and cognitive interviewing, including a description of how interaction analysis can be used to analyze data and modify measures, and 3) an overview of methods for comparing the psychometric characteristics across diverse groups including steps involved in testing psychometrically that a measure is equally valid and unbiased across groups, defining psychometric invariance in factor analytic terms, and illustrating how confirmatory factor analysis can be used to explore psychometric equivalence (equal validity and unbiased across groups). Examples from our work will be provided.
Level - Advanced
Workshop 3
Utility Approach to the Assessment of Health-Related Quality of Life
David Feeny, William Furlong and George Torrance
The Workshop will be an introductory-level presentation on the utility approach to assessing health-related quality of life. Topics will include the conceptual foundations, practical methods for the direct elicitation of preference scores (visual analogue scale [Feeling Thermometer], time tradeoff, and standard gamble), multi-attribute approaches (EQ-5D, Health Utilities Index [HUI], Short-Form 6D [SF-6D], and Quality of Well-Being Scale [QWB]), a review of evidence on reliability, validity, responsiveness, and the interpretation of utility scores, and examples of applications. The Workshop will include hands on experience in the direct assessment of utility scores and in completing questionnaires from several systems and the analysis and interpretation of the results. Applications will be drawn from diverse settings clinical and population health studies. Guidance on criteria for selecting a utility measure for a study will also be provided.
Outline
- Demonstration of Administration of Selected Utility Measures
- Introduction and Conceptual Foundations
- Direct and Multi-Attribute Approaches for Obtaining Utility Scores
- Reliability, Validity, Responsiveness, and Interpretation of Utility Scores
- Results from Demonstration
- Summary and Synthesis; Criteria for Choosing a Utility Measure
Level - Basic
Workshop 4
Basics of Decision Analysis
Gillian Sanders and Douglas Owens
Introductory Course: This course is intended for individuals new to decision
analysis who which to learn the basic principles of formulating and analyzing
clinical decisions. This is a hands-on course that uses in-class exercises to
teach the building blocks of decision analysis including: Bayes' rule, interpreting
the results of diagnostic tests, formulating a medical decision problem, measuring
utilities and risk attitude, calculating expected utility, and performing sensitivity
analysis. We will also address the following special topics: cost-effectiveness
analysis and using decision analysis in clinical care. Each topic will be introduced
in a series of lectures to the entire group, followed in most cases by a small
workshop.
Level - Basic
Workshop 5
Analysis, Interpretation and Reporting of HRQOL Data: An Approach of the
Clinical Trials Group (CTG) of the National Cancer Institute of Canada (NCIC)
David Osoba, Andrea Bezjak and Michael Brundage
Clinicians are being confronted with increasing amounts of health-related
quality of life (HRQOL) data. However, most of them have received very little
training in how to interpret the results in the literature they read. Furthermore,
HRQOL researchers present their data in many different ways, some of which
are not easily interpretable by clinicians. Thus, there is a need for researchers
and clinical trials investigators to analyze and present their data in ways
that make clinical sense, and lead to easier decision making about the value
of new therapies.
The approach of the NCIC CTG emphasizes the clinical meaning of the results,
while avoiding complex statistical modeling. It consists of four steps: calculating
the questionnaire completion rates, calculating the baseline scores, determining
the individual change in scores over time for the domains specified in the
trial hypothesis, and culminates in determining the proportions of patients
who have reported clinically meaningful changes in scores since baseline.
A rationale supporting each step will be given. Complete reporting should
contain the data generated by the above four steps. This approach is a simple
and practical aid to the analysis, interpretation and reporting of HRQOL
results.
Level - Basic
Workshop 6
Applications of Item Response Theory Modeling for Improving Health Outcomes
Measurement
Bryce Reeve and Chih-Hung Chang
There is a great need in health outcomes research to develop instruments
that accurately measure a person s health status with minimal response burden.
This need for psychometrically sound and clinically meaningful measures calls
for better analytical tools beyond the methods available from traditional
measurement theory. Applications of item response theory (IRT) modeling have
increased considerably because of its utility for instrument development
and evaluation, assessment of measurement equivalence, instrument linking,
and computerized adaptive testing. IRT models the relationship, in probabilistic
terms, between a person s response to a survey question and their standing
on a health construct such as fatigue or depression. This introductory workshop
will discuss the basics of IRT models and applications of these models to
improve health outcomes measurement. Illustrations will be used throughout
the presentation that focuses on measuring key health-related quality of
life domains in cancer populations.
Level - Basic
Workshop 7
Introduction to Bayesian Data Analysis in Health and Medicine
Dennis Fryback
Bayesian data analyses are becoming more common with availability of general
purpose software to support Markov Chain Monte Carlo (MCMC) computational methods.
The purpose of this workshop is to provide a didactic introductory overview of
modern Bayesian statistical data analysis methods with rudimentary explanation
of MCMC methods. Although we will cover basic theory and attendees should be
comfortable with algebraic descriptions of statistical distributions, the emphasis
will be understanding and illustration of methods and not on theoretical derivations.
Part 1 of the workshop covers the basics of Bayesian analysis and MCMC computations.
Part 2 illustrates analyses using very simple examples and introduces WinBUGS,
the most widely used software. Part 3 presents a more advanced example to demonstrate
more sophisiticated Bayesian data modeling. Although this is not a hands-on workshop,
Part 4 provides pointers to resources in print and on the web, and other training
opportunities for those who wish to learn more about Bayesian techniques and
to gain hands-on skills.
Level - Advanced
Workshop 8
Imputation for non-randomly missing HRQOL data in longitudinal studies
Diane Farclough
This course will examine methods of imputation for longitudinal studies when
the missing HRQOL assessments are believed to be non-ignorable. It includes a
brief review of simple imputation methods (e.g. mean substitution, LVCF) and
their limitations. The focus of the course will be on multiple imputation methods
such as Approximate Bayesian Bootstrap (ABB), explicit regression, closest predictor
and MCMC (Multiple Chain Monte Carlo) for multivariate normal data. We will discuss
the strengths and weaknesses of these methods in the context of longitudinal
studies with non-ignorable (NMAR) missing data. Handouts will include all slides
and SAS code for examples. The workshop will include discussion (20% of time)
and hands-on experience with selected techniques (20% of time). After completing
this workshop, participants will be able to:
- Understand the limitations of simple imputation and the motivation for multiple imputation techniques,
- Identify settings where multiple imputation is appropriate and will facilitate the analysis of longitudinal studies with missing HRQOL data,
- Identify which imputation techniques that are suitable for missing data in longitudinal studies, and
- Perform analyses of multiply imputed data. Participants should have some experience with multivariate analysis for longitudinal data or repeated measures including MANOVA and mixed-effects models.
Afternoon Workshops 1:30 - 4:30 pm
Workshop 9
Use of Theoretical Models in the Design, Conduct and Analysis of Clinical Trials Assessing Health-Related Quality of Life
Michelle Naughton and Roger Anderson
Assessment of health-related quality of life (HRQL) has become an integral part of many clinical trials, especially those directed at the primary or secondary prevention of chronic diseases. It is now well accepted that conventional clinical and functional measures of disease status do not fully measure the impact of the interventions on patients. Assessment of HRQL is especially important when the tested interventions do not result in an obvious clinical benefit, such as a reduction in mortality or major morbidity, or when two interventions may result in similar clinical outcomes, but have very different impacts on various aspects of the patients' quality of life.
Although a great deal of progress has been made in the last two decades in the measurement of HRQL the under-application of theory remains an important limitation. HRQL variables are most often used as primary or secondary outcome measures to assess the impact of some form of intervention (i.e., pharmaceutical, surgical, behavioral) or health condition/disease process on patients' daily lives. The development of HRQL research studies to test specific social and/or behavioral theories, however, are more rare. These theoretical frameworks can be used to examine such topics as specifying and testing the direction, temporal sequence and effects of a condition or intervention on domains of HRQL, and/or to investigate physical/clinical, social and behavioral mechanisms by which decrements or improvements in HRQL might occur. In this way, HRQL can play a more integral role in testing hypotheses and elaborating theory on patient outcomes.
This workshop will be of interest to behavioral and social scientists, new or more experienced, who are interested in the design, conduct, and analysis of HRQL studies.
The topics to be presented and discussed will include:
- Definition of HRQL and a review of the different dimensions of HRQL that can be measured in clinical trials
- A historical perspective of clinical trials assessing HRQL: what have we learned? What are the current perspectives?
- Discussion of the use of HRQL in outcome studies versus testing specific social and behavioral theories examining individuals' HRQL. Examples of these types of studies will be drawn from various fields, including cancer, diabetes, and cardiovascular disease.
- Selection of instruments for use in HRQL assessments.
- Methodological and statistical considerations in the design, conduct, and analysis of theoretical models assessing HRQL.
Level - Basic
Workshop 10
Using Health Related Quality of Life Measures in Economic Evaluation
John Brazier
Instruments for assessing health related quality of life (HRQoL) are increasingly
being used as end points in clinical trials. An important stimulus for the use
of HRQoL instruments has been the increasing pressure on health care budgets
throughout the world. These same pressures have also lead Governments and other
health funders to examine the cost-effectiveness of new developments (for example
though agencies such as NICE in the UK). Whilst enhancements to HRQoL is an important
benefit of health, many of the instruments used to assess these and related concepts
have not been designed for use in economic evaluation and are not able to address
the question cost-effectiveness. At the same there has been the development in
health economics of a single measure of health benefit called the quality adjusted
life year (QALY).
This workshop is concerned with the use of HRQoL measures in economic evaluation,
including their use in deriving the health state values required to calculate
QALYs. It is designed to provide a practical introduction.
Level - Advanced
Workshop 11
Advanced Psychometric Methods: Application in Pro Instrument Development and
Evaluation
Dennis Revicki and Donald Stull
The development and psychometric evaluation of PRO instruments requires the application
of a number of different techniques, including exploratory and confirmatory factor
analysis (FA), item response theory analysis, and structural equation modeling
(SEM). We will provide a brief overview of psychometric analyses and will then
focus on the application of (1) exploratory and confirmatory factor analysis
for understanding of new measures and (2) use of SEM for testing construct validity.
Exploratory and confirmatory FA can be used to examine the relationships among
items with a PRO measure or among different domains or multiple PRO measures.
These technicaues are useful for understanding the internal structure of PRO
instruments and for understanding construct validity. The workshop will describe
the main methods of FA and illustrate these methods with examples from the instrument
development literature.
SEM is a powerful analytic technique that combines FA and path analysis in a
simultaneous, confirmatory approach. Using SEM, the researcher can specify and
evaluate hypothesized relationships between observed and latent (unobserved)
constructs as well as relationships among the latent variables. SEM can also
estimate the reliability and validity of measurement models while explicitly
modeling measuremnt error. A researcher specifies a measurement model and a structural
model which specifies relationships among the latent variables to examine construct
and criterion-related validity. If the observed covariances are consistent with
the model-implied covariances, the researcher has evidence supporting the construct
validity of the PRO measure. This workshop will demonstrate the main methods,
testing assumptions and criteria, and provide examples to illustrate the methods
of SEM.
Level - Advanced
Workshop 12
The Language of Quality of Life
Ivan Barofsky
Recently, quality of life (QOL) and health-related quality of life (HRQOL) researchers
have come to appreciate the role that information presented as a narrative can
play in their research. A number of quantitative techniques have been discussed
at previous ISOQOL sessions (e.g., discourse analysis, or text analysis). However,
little discussion has has taken placed concerning what is the optimal form of
expressing QOL or HRQOL information, nor has any systematic approach been presented
concerning how the language of QOL or HRQOL can be analyzed.
This Workshop will present an approach to this task, by first defining and
distinguishing literal and figurative language. It will be proposed that QOL
or HRQOL statements
are a form of figurative language, which raises the question of how to determine
that what is stated is true and real. This will lead to a discussion of the
role of logical positivism and empirical constructionism as alternatives methods
of "how we come to know".
As a form of figurative language the presenter will consider if QOL or HRQOL
information (e.g., various definitions of QOL or HRQOL) contains linguistic or
conceptual metaphors. It will be proposed that definitions of QOL or HRQOL are
best seen as a form of conceptual metaphor.
With this background, the presenter will review available studies that examine
changes in figurative and literal language as a function of various medical or
treatment conditions. Particular emphasis will be placed on how the distinction
between literal and figurative language can be used to study the QOL or HRQOL
of the compromised person.
Level - Basic
Workshop 13
Evaluating Change in Health-Related Quality of Life Measures
Kathleen Wyrwich
Although numerous measures have been developed for the evaluation of health-related
quality of life (HRQoL), strategies for identifying meaningful intra-individual
and group change in these measures have not kept pace with instrument development.
As a result, clinical trial researchers, quality assurance assessment teams,
practicing clinicians, and patients are without established standards to evaluate
change in HRQoL measures. This course will review, critique and compare the methods
that have been applied to establish intra-individual and group HRQoL change standards,
which include anchor- and distribution-based techniques. Practical approaches
to improving and advancing HRQoL change evaluations that enhance the interpretation
of intra-individual and group change, as well as a review of controversies that
have developed will be provided. In addition, the course will explore future
qualitative and quantitative challenges in this area of HRQoL research. The workshop
outline includes: 1. Who are the stakeholders in HRQoL change evaluations?; 2.
Review and critique of evaluation methods to date (Anchor-based and Distribution-based);
3. Relationships between evaluation methods; 4. Controversies associated with
these methods; 5. Practical approaches; 6. Challenges ahead; and 7. Additional
questions and discussion. The workshop will be divided between 70% lecture, 10%
class exercises, and 20% discussion and answer periods. Participants are strongly
encourages to bring a hand calculator.
Level - Advanced
Workshop
14
Cross-cultural HRQL Instrument Development in Children with and without a Chronic
Health Condition
Ulrike Ravens-Sieberer, Silke Schmidt and Monika Bullinger
While quality of life research in adults has progressed substantially over the past 15 years, health-related quality of life of children has only recently been addressed. QOL research in children is important because children can be confronted with disease and treatment as patients. It is important to know how children feel and how treatment can be optimised. Also, children can suffer substantial strain from diseases in other family members. Lastly, epidemiological research has so far neglected living conditions that might be detrimental to the health-related quality of life of children; exceptions are a few studies published in the area of public health and clinical psychology.
Reflections on how to assess quality of life of children also bear on the focus of such assessment. Basically, there are three dimensions to quality of life assessment in children. The first concerns the specificity of assessment intended. Disease specific assessments aim at substantial and comprehensive analyses of the health-related quality of life of children suffering from specific chronic conditions. In contrast, generic assessment focuses on relevant aspects of children's perceived health independent of the actual medical condition of the child. A second dimension concerns the type of assessment intended, i.e. the use of questionnaires or interviews, of observational methods or computer assisted programs. The questionnaire method is usually favored for the economy of its use, as well as the psychometric quality criteria, which include reliability, validity and sensitivity. Finally, and most critically, is the dimension of who assesses the quality of life of children. In general, expert ratings, that is external observation of children's quality of life, have been favored; however, the essence of quality of life assessment is the self rating method. The question of whether and at which age children are able to report on their feelings has been intensively discussed, and principally deemed realizable under the condition that an instrument corresponding to the child's abilities can be chosen.
This workshop reviews the state of the art of quality of life assessment in children/adolescents as it relates to the underlying concepts the instruments available, and application in research and practice. Generic as well as disease-specific measures (e.g. asthma, diabetes, epilepsy, rheumatoid arthritis) will be focused on. The material presented will include results of recent of two large EC funded projects on "Quality of Life of Children with Disabilities (DISABKIDS)" and "Assessing Health Related Quality of Life in Representative Samples of European Children (KIDSCREEN)." The presentation will include an overview over instrument development, cross-cultural testing and practical use, demonstration of instruments as well as their computer assisted versions, and a thorough evaluation of the evidence of their use in clinical studies and patient care
Level - Basic
Workshop 15
Computerized Dynamic Assessment of Health-Related Quality of Life
John E. Ware, Jr., and Jakob B. Bjorner
This workshop begins with an overview of the advantages and problems involved in standardizing health status metrics for purposes of general population surveys, clinical trials and individual patient assessments. Applications of item response theory (IRT) focusing on the measurement of generic and disease-specific health-related quality of life outcomes are explained along with how IRT differs from the “classical” psychometric approach. Methods and results from specific analyses and software packages used at each step in applying IRT are presented to illustrate item trace line exploration (Testgraf software), the factor analysis of categorical data to test for multidimensionality (Mplus software), Rasch item response model estimation (OPLM software), and IRT modeling (Parscale software). The use of IRT in the cross-calibration of widely-used measures, enabling comparisons of results, is also explained. The logic and advantages of computerized adaptive testing (CAT) is illustrated using dynamic health assessment (DYNHA software). Results from both “real data simulations” and evaluations of actual CAT administrations are demonstrated. Other advanced topics covered include: (a) how item and test “information functions” are used by CAT for individual patients at specific levels throughout the score range; (b) how IRT and CAT can be used to develop better “static” short forms; (c) strategies for using IRT models for missing date estimation; and, (d) the practical implications of CAT in terms of reducing respondent burden and achieving the score precision necessary for monitoring individual patient health outcomes.
Workshop participants will receive a printed copy of the information presented, copies of various articles and reference materials.
Level - Advanced
Workshop 16
Symptom Measurement: Methods & Utilization
Charles Cleeland, Andrei Novik, Shelley Wang and Tatyana Ionova
Patients with serious illness exhibit pronounced symptom burden and impairment
of QoL caused by disease and treatment. In this workshop we focus on
the symptoms of cancer and its treatment. Pain, fatigue and depression
are recognized as major
sources of symptom burden in this patient group. Better symptom control
can produce significant QoL improvement. Effective control is possible
if symptoms are assessed
with tools that adequately evaluate their prevalence and severity. Implementing
symptom assessment in routine cancer practice is a first step toward
improving quality of care for advanced cancer patients. Trials and clinical
studies are
now done in many countries, making it critical to develop symptom measures
in multiple languages and evaluate their equivalence. Such measures can
also improve
the implementation of symptom control guidelines in many countries. In
the workshop we will:
- Discuss progress in symptom assessment
- Review principles that guided the development of the Brief Pain Inventory, Brief Fatigue Inventory and M. D. Anderson Symptom Inventory
- Present results of QoL and specific symptom assessment in the United States, Russia, China, Japan
- Discuss cross-cultural issues in symptom assessment
- Discuss the role of symptom assessment in the clinical management of patients.
- Symptom assessment: background, methods, assessment tools
- Psychometric properties: cross-cultural data
- QoL impairment and symptoms in advanced cancer
- QoL in advanced cancer compared to population norms
- Comparative analysis of symptom prevalence and severity in hematologic malignancies and solid tumors
- Application to clinical practice.
TOPICS:
Scale development and evaluation (reliability, and validity including responsiveness, scale equivalence)
Cancer/oncology
Symptom assessment
Level - Basic