2 research outputs found
PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies
Development and application of statistical models for medical scientific researc
PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies
Prediction models in health care use predictors to estimate for an
individual the probability that a condition or disease is already present
(diagnostic model) or will occur in the future (prognostic model).
Publications on prediction models have become more common
in recent years, and competing prediction models frequently
exist for the same outcome or target population. Health
care providers, guideline developers, and policymakers are often
unsure which model to use or recommend, and in which
persons or settings. Hence, systematic reviews of these studies
are increasingly demanded, required, and performed.
A key part of a systematic review of prediction models is examination
of risk of bias and applicability to the intended population
and setting. To help reviewers with this process, the authors developed
PROBAST (Prediction model Risk Of Bias ASsessment Tool)
for studies developing, validating, or updating (for example, extending)
prediction models, both diagnostic and prognostic.
PROBAST was developed through a consensus process involving
a group of experts in the field. It includes 20 signaling
questions across 4 domains (participants, predictors, outcome,
and analysis). This explanation and elaboration document describes
the rationale for including each domain and signaling
question and guides researchers, reviewers, readers, and guideline
developers in how to use them to assess risk of bias and
applicability concerns. All concepts are illustrated with published
examples across different topics. The latest version of the
PROBAST checklist, accompanying documents, and filled-in examples
can be downloaded from www.probast.org.Drs. Moons and Reitsma received financial support from the Netherlands Organisation for Scientific Research (ZONMW 918.10.615 and 91208004). Dr. Riley is a member of the Evidence Synthesis Working Group funded by the NIHR School for Primary Care Research (project 390). Dr. Whiting (time) was supported by the NIHR Collaboration for Leadership in Applied Health Research and Care West at University Hospitals Bristol NHS Foundation Trust. Dr. Collins was supported by the NIHR Biomedical Research Centre, Oxford. Dr. Mallett is supported by NIHR Birmingham Biomedical Research Centre at the University Hospitals Birmingham NHS Foundation Trust and the University of Birmingham