TRIPOD Statement

1Detailed Explanation

TRIPOD was published in 2015 and provides a 22-item checklist for prediction model studies, whether for diagnostic (prognostic) or predictive purposes. Key elements include: title identifying the study as development/validation/both, abstract with key items, introduction (background, objectives), methods (participants, outcomes, predictors, sample size, missing data, statistical analysis), results (participants, model performance, model specifications), discussion (limitations, comparison with other studies, clinical applicability), and supplementary. The checklist applies to both development and validation studies, with separate items for each. Extensions exist for specific types of models, including TRIPOD-AI for AI/ML prediction models.

2Examples

• A.A TRIPOD-compliant study developing and validating a risk score for cardiovascular disease using Cox regression
• B.A machine learning model for predicting sepsis following TRIPOD-AI extension

3Why It Matters in Research

TRIPOD is increasingly required for prediction model studies, including those using machine learning and AI approaches. It improves transparency and facilitates external validation.

Related Journal Format Guides

Journals that commonly use TRIPOD Statement in their manuscripts