Reporting standards for clinical prediction Models (TRIPOD)

NEED

Prediction models are created to assist healthcare providers in estimating the likelihood or risk of a specific disease or condition (diagnostic models) or a specific event in the future (prognostic models) to inform their decision-making process. However, there is overwhelming evidence showing poor reporting quality in prediction model studies. To adequately assess the potential usefulness and risk of bias of prediction models, all aspects of a prediction model must be fully and clearly reported.

Approach to Address Healthcare Challenges:

In both the diagnostic and prognostic settings, estimates of probabilities are usually based on multiple predictors, such as patient characteristics, symptoms, and test results. As a result, prediction models are inherently multivariable and combine multiple predictors by assigning relative weights to each predictor to obtain a risk or probability. Developing or validating multivariable prediction models presents specific challenges for researchers, such as inadequate reporting and insufficient information on all aspects of model development, from patient data descriptions to statistical modeling methods.

Solution:

To address these challenges, the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement was created. The TRIPOD Statement is a 22-item checklist that aims to improve the reporting quality of studies developing, validating, or updating prediction models for diagnostic or prognostic purposes. The checklist provides guidance to ensure transparent reporting of a prediction model study, regardless of the study methods used. Therefore, it is crucial to satisfy external validation via TRIPOD and internal validation to improve usability and transparency when building a predictive model. The TRIPOD checklist can be accessed via this link: https://www.tripod-statement.org/wp-content/uploads/2020/01/Tripod-Checlist-Prediction-Model-Development.pdf