Logistic Regression: Relating Patient Characteristics to Outcomes

In a recent issue of JAMA, Seymour et al¹ presented a new method for estimating the probability of a patient dying of sepsis using information on the patient’s respiratory rate, systolic blood pressure, and altered mentation. The method used these clinical characteristics—called “predictor” or explanatory or independent variables—to estimate the likelihood of a patient having an outcome of interest, called the dependent variable. To determine the best way to use these clinical characteristics, the authors used logistic regression, a common statistical method for quantifying the relationship between patient characteristics and clinical outcomes.²