November 17: Causal Inference and Causal Estimands From Target Trial Emulations Using Evidence from Real-World Observational Studies and Clinical Trials - In Person at ISPOR Europe 2024
event-Short-Courses

November 17, 2024

In recent years, real-world evidence (RWE) has been increasingly used to inform regulatory, payer, and health technology assessment (HTA) decisions, as well as clinical guideline development. In addition, it has been recognized that the analysis of hypothetical estimands in clinical trials is necessary when the standard intention-to-treat (ITT) analysis does not answer the decision problem, usually because of treatment switching.

An innovative framework for causal inference methods, target trial emulation, causal estimands and causal modeling guides the design and analysis of observational studies and clinical trials.

Enroll in this in person short course to:

  • Understand causal principles, causal diagrams (directed acyclic graphs; DAGs), and target trial emulation to avoid self-inflicted biases (eg, time-zero bias, immortal time bias).
  • Learn about causal methods for baseline confounding (multivariate regression, propensity scores) and time-varying confounding (eg, g-formula, marginal structural models with inverse probability of treatment weighting, and rank-preserving structural failure-time models with g-estimation).
  • Be able to propose appropriate estimands to ensure decision problems are directly addressed when analyzing observational data or data from clinical trials affected by treatment switching.
  • Discuss lessons learned from applied case examples in HTA, such as single arm-trials with external control arms or trials affected by treatment switching.
  • Identify recommendations regarding the use of causal inference methods and estimands and their application in causal modeling.
  • Discuss acceptance and barriers from an HTA agency perspective.
This short course is offered in-person at the ISPOR Europe 2024 conference.

Register Here

*Conference attendance is not required to attend an ISPOR Short Course. Separate registration is required for conference attendees.


PREREQUISITE: Students are expected to have a basic knowledge in epidemiologic studies and methods (including the concept of confounding).

LEVEL: Experienced
TRACK:
Real World Data & Information Systems
HEOR Key Competency: 5.2 Economic Analysis Alongside Clinical Trials
LENGTH: 4 Hours | Course runs 1 day

FACULTY MEMBERS

Uwe Siebert, MD, MPH, MSc, ScD
Professor & Chair
UMIT - University for Health Sciences
Medical Informatics and Technology
Hall in Tirol, Austria and
Harvard Chan School of Public Health
Harvard University
Boston, MA, USA

Felicitas Kühne, MSc
Manager Outcomes Research
Health & Value Germany
Pfizer Pharma GmbH
Berlin, Germany and
Senior Scientist, Program Causal Inference
UMIT - University for Health Sciences
Medical Informatics and Technology
Innsbruck, Austria

Nicholas Latimer, MSc, PhD
Professor of Health Economics
SCHARR, University of Sheffield
Sheffield, Derbyshire, Great Britain and
Delta Hat Limited
Analyst
Nottingham, UK

Schedule:

Sunday, 17 November 2024 | Course runs 1 Day
08:00-12:00 Central European Time (CET)

Register Here

*Conference attendance is not required to attend an ISPOR Short Course. Separate registration is required for conference attendees.

Visit the ISPOR Europe 2024 Program page to view all short courses offered.

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