Intention-to-Treat Analysis in Clinical Research: Basic Concepts for Clinicians.
Susan Armijo-OlivoJordana Barbosa-SilvaEster Moreira de Castro-CarlettiAna Izabela Sobral de Oliveira-SouzaElisa Bizetti PelaiNorazlin MohamadFatemeh BaghbaninaghadehiLiz DennettJeremy P SteenDinesh KumbhareNikolaus BallenbergerPublished in: American journal of physical medicine & rehabilitation (2024)
This review presents a comprehensive summary and critical evaluation of intention-to-treat analysis, with a particular focus on its application to randomized controlled trials within the field of rehabilitation. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we conducted a methodological review that encompassed electronic and manual search strategies to identify relevant studies. Our selection process involved two independent reviewers who initially screened titles and abstracts and subsequently performed full-text screening based on established eligibility criteria. In addition, we included studies from manual searches that were already cataloged within the first author's personal database. The findings are synthesized through a narrative approach, covering fundamental aspects of intention to treat, including its definition, common misconceptions, advantages, disadvantages, and key recommendations. Notably, the health literature offers a variety of definitions for intention to treat, which can lead to misinterpretations and inappropriate application when analyzing randomized controlled trial results, potentially resulting in misleading findings with significant implications for healthcare decision making. Authors should clearly report the specific intention-to-treat definition used in their analysis, provide details on participant dropouts, and explain upon their approach to managing missing data. Adherence to reporting guidelines, such as the Consolidated Standards of Reporting Trials for randomized controlled trials, is essential to standardize intention-to-treat information, ensuring the delivery of accurate and informative results for healthcare decision making.
Keyphrases
- randomized controlled trial
- healthcare
- meta analyses
- decision making
- systematic review
- public health
- clinical practice
- adverse drug
- clinical trial
- emergency department
- type diabetes
- machine learning
- risk assessment
- metabolic syndrome
- climate change
- weight loss
- electronic health record
- mass spectrometry
- insulin resistance
- drug induced
- case control