Introduction
This brief abstract defines the challenges of using COAs to incorporate PED intro trial endpoints, and outlines the objectives of the educational series.
EDITORS: Konstantina Skaltsa, Ph.D. and Matt Reaney, Ph.D.
As standardized measures that describe or reflect how a patient feels or functions, clinical outcome assessments (COAs) are the most common method of incorporating patient experience data (PED) into clinical trial endpoints. Although the principle behind COA measurement is sound, COAs are useful to sponsors, reviewers, healthcare professionals and patients only if they generate insights that are meaningful, interpretable and non-misleading.
IQVIA’s Patient Centered Solutions (PCS) team has developed this educational series in an effort to establish an authoritative text on how to robustly analyze COA data. Defining and Analyzing Patient-centric Endpoints Based on COAs and Digital Technologies promotes the basics of COA implementation and analysis in intervention development across the pharmaceutical industry. The series also encourages statisticians and non-statisticians to think beyond the traditional statistical methods to maximize data insights and ask broader questions such as:
- How do you define patient-relevant COA endpoints focused on efficacy, safety and tolerability that will answer meaningful research objectives?
- What are the best ways (traditional and emerging) to analyze different types of COA endpoints, including intensive longitudinal data (ILD) endpoints from digital health technologies?
- What is the estimand framework (in lay person’s terms)? How is it useful in planning COA endpoint development and analysis?
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Explore the series chapters
Consisting of nine chapters, Defining and Analyzing Patient-centric Endpoints Based on COAs and Digital Technologies is being released in installments here ahead of its eventual publication in collected book form. Fill out the form to download the installments as they become available.
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Chapter 1
From objectives to endpoints
This chapter offers guidance on how to define patient-relevant COA endpoints that will answer meaningful research objectives in clinical trials.
Chapter 2
From endpoints to estimands
This chapter provides a gentle introduction to the estimand framework (in lay terms), and its role in planning and analyzing clinical trial endpoints using COAs, with an emphasis on accounting for intercurrent events (ICEs).
Chapter 3
From estimands to estimators: Analyzing continuous endpoints
This chapter outlines how to best analyze continuous COA endpoints using traditional and emerging statistical approaches, while accounting for ICEs.
Chapter 4
From estimands to estimators: Analyzing binary endpoints
This chapter outlines how to best analyze binary COA endpoints using traditional and emerging statistical approaches, while accounting for ICEs.
Chapter 5
From estimands to estimators: Analyzing time-to-event endpoints
This chapter outlines how to best analyze time-to-event COA endpoints using traditional and emerging statistical approaches, while accounting for ICEs.
SPECIAL CHAPTER
Considerations for Creating multi-item scale scores for Clinical Outcome Assessments
This special chapter discusses approaches to scoring COA instruments.
Chapter 6
Diary and intensively collected digital data
This chapter outlines how to obtain more granular insights on patients’ experience by collecting and analyzing diary data and other intensive longitudinal data (ILD).
Chapter 7
On tolerability endpoints
This chapter discusses the emerging role of COA data to assess tolerability from the quantitative point of view, and the specific analytical considerations.
Chapter 8
Structural equation framework: Further understanding COA data
This final chapter synthesizes alternative approaches to analyzing COA data which can offer additional insight and aid interpretation (e.g., by understanding how different aspects measured by COAs impact each other).
About the editors
Konstantina Skaltsa, Ph.D.
Director, Statistics and Psychometrics, Patient Centered Solutions
Dr. Skaltsa is a statistician by training with over 15 years of academic and industry experience in the area of clinical outcome assessments (COA). She serves as a subject-matter expert in psychometrics and statistics for COA endpoint strategy in drug development programs, as well as teaching statistics and clinical trials in BSc and MSc programs. Dr. Skaltsa’s focus is on advancing the science in COA endpoint definitions (efficacy, tolerability, diary or digital), estimands and statistical methodology, including handling of missing data.
Matt Reaney, Ph.D., CPsychol, Csci
Senior Director, Patient Centered Solutions, Global Head of PCS Science and Analytics & Head of the PCS Institute for Thought Leadership
Dr. Reaney has over 20 years of experience in conducting and teaching qualitative and quantitative patient experience research, including the development and validation of COAs, patient preference research and real-world patient experience studies. He has held numerous leadership positions in healthcare consulting and in pharmaceutical companies, published more than 100 research papers, and given more than 120 congress presentations, webinars, workshops, panels and keynote speeches.