Quality of reporting of clinical prediction model studies - adherence to TRIPOD

P Heus, JAAG Damen, RJPM Scholten, JB Reitsma, G. S. Collins, D. G. Altman, KGM Moons, L Hooft

Research output: Contribution to conferenceAbstractOther research output


There is a growing number of prediction models, both diagnostic and prognostic, that are published in the medical literature. Systematic reviews are required to deal with this information overload. However, systematic review authors are highly dependent on the quality of the reporting of primary studies. To improve the reporting of prediction models a guideline for Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) was launched in January 2015. The TRIPOD statement is a checklist of 22 main items considered essential for good reporting of studies developing or validating multivariable prediction models.

The objective of our study is to assess the quality of reporting of prediction model studies published before the launch of TRIPOD. In addition, this study could possibly serve as a baseline measurement for future studies evaluating the impact of the introduction of TRIPOD.

For 37 clinical domains we selected 10 journals with the highest impact factors. A PubMed search was performed to identify prediction models published in May 2014. Publications that described the development and/or validation of a prediction model, either diagnostic or prognostic, were eligible. TRIPOD items were carefully translated into a data extraction form, which was piloted extensively. Consensus was reached on when to consider an item “adhered”.

Our search identified 4871 references, of which 347 potentially eligible references were assessed in full text. Eventually 180 references were included. We will present the adherence to TRIPOD, per publication as well as per item across studies, and across clinical domains. Also, diagnostic and prognostic models will be distinguished, and results will be separated for studies addressing model development, model validation, incremental value, or a combination of these.

Our study will provide insight into the current quality of published reports about the development or validation of prediction models across a wide variety of clinical domains. Reporting issues will be identified that might require specific guidance.
Original languageEnglish
Publication statusPublished - 2015
Event23rd Cochrane Colloquium - Vienna, Austria
Duration: 3 Oct 20157 Oct 2015


Conference23rd Cochrane Colloquium


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