「Beyond Evidence: Navigating Decision-Making in Universal SGLT2 Treatment」

A recent meta-analysis confirms that SGLT2 inhibitors offer broad renal benefits across diverse patient groups, yet this very success complicates clinical choices by encouraging the over-prescription of multiple medications. While traditional statistical averages prove a drug’s general efficacy, they often obscure individual risks and the specific boundaries where a treatment might become counterproductive. To address this, the text proposes integrating Distributional Structural Analysis (DSA) to visualize how treatment responses vary across a population beyond a simple mean. Furthermore, using Directed Acyclic Graphs (DAGs) can map the causal pathways behind these variations, transforming intuitive clinical judgment into a rigorous, explainable framework. This combined approach allows doctors to prioritize treatments effectively and identify when to withhold therapy, moving past generic guidelines toward a more transparent and individualized decision-making process.