Journal
JOURNAL OF THORACIC DISEASE
Volume 11, Issue -, Pages S574-S584Publisher
AME PUBLISHING COMPANY
DOI: 10.21037/jtd.2019.01.25
Keywords
Review; logistic regression; predictive model
Categories
Funding
- Agency for Healthcare Research (AHRQ) [T32 HS026122]
- Department of Veterans Affairs, Veterans Health Administration
Ask authors/readers for more resources
Prediction models help healthcare professionals and patients make clinical decisions. The goal of an accurate prediction model is to provide patient risk stratification to support tailored clinical decision-making with the hope of improving patient outcomes and quality of care. Clinical prediction models use variables selected because they are thought to be associated (either negatively or positively) with the outcome of interest. Building a model requires data that are computer-interpretable and reliably recorded within the time frame of interest for the prediction. Such models are generally defined as either diagnostic, likelihood of disease or disease group classification, or prognostic, likelihood of response or risk of recurrence. We describe a set of guidelines and heuristics for clinicians to use to develop a logistic regression-based prediction model for binary outcomes that is intended to augment clinical decision-making.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available