Validate study variables to reduce misclassification bias: recent tools and research needs
In this interactive workshop, we will identify key barriers, explore recent tools, and highlight critical research needs. Our ultimate goal is to bridge the gap between methodology and application—developing an agenda to improve validation practices, facilitate adoption, and effectively reduce misclassification bias in study results.
Consult and download the slides:
- Gini R. Introduction: towards an agenda to reduce misclassification bias using validation.
- Lo Re V. Recommendations and practice in validation studies and their use in studies.
- Ehrenstein V. An ISPE guideline.
- Tarazjani A D. The VAC4EU validation pipeline.
- Thurin N. Interrelation between validity indices and validation in French administrative data.
- Limocella G. Screening algorithms to reduce underestimation and test for differential misclassification.
- Hyeraci G. The SeValid project.
- Lippi M. Contribution of Artificial Intelligence to validation.
- Roberto G. Ablation of prompts to estimate sensitivity of algorithms in a data source.
- Schultze A. Quantitative bias analysis in practice.
- Martin Merino E. Validation in BIFAP and application in studies: experience and challenges.
- de Albeniz Martinez X G. Validate study variables to reduce misclassification bias: recent tools and research needs. Discussion.
Hybrid workshop
27 March 2025 - 14.30 - 18.30
ARS Toscana - Villa La Quiete, via Pietro Dazzi 1 - Florence, Italy
Validation of study variables derived from Real World Data is recommended, and quantitative bias analysis methods exist to address misclassification bias. However, validation studies remain rare, and their findings are seldom integrated into Real World Evidence used for regulatory decisions.
What prevents more widespread validation? What challenges hinder the reduction of misclassification bias?
In this interactive workshop, we will identify key barriers, explore recent tools, and highlight critical research needs. Our ultimate goal is to bridge the gap between methodology and application—developing an agenda to improve validation practices, facilitate adoption, and effectively reduce misclassification bias in study results.
View and download the agenda
Organizing Secretariat ARS Toscana
Jessica Fissi, Lucia Paone
347 8888418 - 055 4624325
