Article type
Year
Abstract
Background:
Prediction models are developed to aid healthcare providers in estimating the probability that a specific outcome or disease is present (diagnostic models) or will occur in the future (prognostic models), to inform their decision-making. Clinical prediction models are abundant in medical literature. Some disease areas show an overwhelming number of competing prediction models (sometimes even in excess of 100) for the same outcome or target population. Only when full information on all aspects of a prediction model study are clearly reported can risk of bias and potential usefulness of the prediction model be adequately assessed. Many reviews have shown that the quality of published reports on the development, validation and updating of prediction models, is very poor.
Objectives:
The transparent reporting of a multi-variable prediction model for individual prognosis or diagnosis (TRIPOD) initiative therefore developed a set of consensus-based recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes.
Methods:
The development was based on systematic reviews of the literature, web-based surveys and a 3-day expert meeting among methodologists, healthcare professionals and journal editors.
Results:
The TRIPOD checklist includes 22 items deemed essential for transparent reporting of a prediction model study. The development and contents of the TRIPOD checklist will be presented and illustrated, along with empirical evidence and rationale for their inclusion.
Conclusions:
The TRIPOD statement intends to improve the transparency and completeness of reporting of studies that report the development, validation, or updating of a diagnostic or prognostic prediction model.
Prediction models are developed to aid healthcare providers in estimating the probability that a specific outcome or disease is present (diagnostic models) or will occur in the future (prognostic models), to inform their decision-making. Clinical prediction models are abundant in medical literature. Some disease areas show an overwhelming number of competing prediction models (sometimes even in excess of 100) for the same outcome or target population. Only when full information on all aspects of a prediction model study are clearly reported can risk of bias and potential usefulness of the prediction model be adequately assessed. Many reviews have shown that the quality of published reports on the development, validation and updating of prediction models, is very poor.
Objectives:
The transparent reporting of a multi-variable prediction model for individual prognosis or diagnosis (TRIPOD) initiative therefore developed a set of consensus-based recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes.
Methods:
The development was based on systematic reviews of the literature, web-based surveys and a 3-day expert meeting among methodologists, healthcare professionals and journal editors.
Results:
The TRIPOD checklist includes 22 items deemed essential for transparent reporting of a prediction model study. The development and contents of the TRIPOD checklist will be presented and illustrated, along with empirical evidence and rationale for their inclusion.
Conclusions:
The TRIPOD statement intends to improve the transparency and completeness of reporting of studies that report the development, validation, or updating of a diagnostic or prognostic prediction model.