The analytical procedures can produce p-values and confidence intervals, allowing you to determine statistical significance. Hazard ratios are an excellent way to quantify relative probabilities for any point in time during the study. That’s not good because patients are dying more quickly (i.e., survival times are shorter)! Interpretation Cautions In that case, a hazard ratio of two indicates that the probability of dying is double in the treatment group relative to the control group at any point. Patients feel better more quickly.Ĭonversely, suppose the event is patient death. A subject in the treatment group has twice the probability of symptom resolution than someone in the control group at any given point. If you’re studying a new medicine and the endpoint event is the resolution of symptoms, then an HR of two is good. This result indicates that the event happens more frequently in the treatment group per unit of time, which equates to shorter times to events. Is a hazard ratio of 2 good or bad? As I mentioned in a previous section, that depends on the nature of the event and whether you want shorter or longer times to the event. In a medical study, HR = 2 indicates that an unaffected subject in the treatment group has twice the probability of experiencing the event within a time span than someone in the control group. Let’s interpret an example hazard ratio of 2. Consequently, the treatment group experiences a lower event probability during a unit of time than the control group. Hazard Ratio < 1: The numerator is less than the denominator in the HR. Therefore, the treatment group experiences a higher event probability within any given period than the control group. Hazard Ratio > 1: The numerator is greater than the denominator in the hazard ratio. This equivalence occurs when both groups experience the same number of events in a period. Hazard Ratio = 1: An HR equals one when the numerator and denominator are equal. As the ratio moves away from one in either direction, the difference between the control and treatment groups increases.
ENGAUGE DIGITIZER HAZARD RATIO HOW TO
That depiction clarifies how to interpret hazard ratios.Ī hazard ratio tells us whether a subject in the treatment group who is unaffected at any given time has a greater, equal, or lower probability (i.e., hazard rate) of experiencing the event during the next unit of time than an unaffected subject in the control group.īecause we’re dealing with a ratio, the value of 1 becomes critical to interpreting hazard ratios because it indicates that the treatment and control groups have equal hazard rates. Keep in mind how Kaplan-Meier curves depict the proportion of subjects who have not experienced the event (i.e., unaffected subjects) at various time points. Read my report about a COVID vaccine analysis that used a Cox proportional hazards model. In medical settings, these models can evaluate the change in risk associated with a treatment while incorporating patient attributes and risk factors. Statisticians frequently use a stratified Cox proportional hazard regression model to estimate hazard ratios and their confidence intervals.
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