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2016 ; 31
(1
): 38-44
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How to Establish Clinical Prediction Models
#MMPMID26996421
Lee YH
; Bang H
; Kim DJ
Endocrinol Metab (Seoul)
2016[Mar]; 31
(1
): 38-44
PMID26996421
show ga
A clinical prediction model can be applied to several challenging clinical
scenarios: screening high-risk individuals for asymptomatic disease, predicting
future events such as disease or death, and assisting medical decision-making and
health education. Despite the impact of clinical prediction models on practice,
prediction modeling is a complex process requiring careful statistical analyses
and sound clinical judgement. Although there is no definite consensus on the best
methodology for model development and validation, a few recommendations and
checklists have been proposed. In this review, we summarize five steps for
developing and validating a clinical prediction model: preparation for
establishing clinical prediction models; dataset selection; handling variables;
model generation; and model evaluation and validation. We also review several
studies that detail methods for developing clinical prediction models with
comparable examples from real practice. After model development and vigorous
validation in relevant settings, possibly with evaluation of utility/usability
and fine-tuning, good models can be ready for the use in practice. We anticipate
that this framework will revitalize the use of predictive or prognostic research
in endocrinology, leading to active applications in real clinical practice.
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