This podcast delves into survival analysis, a statistical approach for examining time-to-event data, with a particular focus on the Kaplan-Meier method and the Cox proportional hazards model. The speaker illustrates these techniques through a study comparing combination antibiotic therapy to single antibiotics for treating severe bacterial infections. The results revealed that combination therapy significantly lowered 30-day mortality, a conclusion backed by both Kaplan-Meier curves and Cox regression analysis. Additionally, the speaker shares insights on how to perform these analyses using R and SAS software, highlighting the crucial role of understanding and testing the proportional hazards assumption in Cox regression.
