Framework outlines how real-world evidence can complement diabetes trials

Randomised controlled trials remain central to evaluating diabetes interventions, but selective enrolment, limited follow-up and trial-specific treatment pathways can constrain their relevance to routine care. This perspective synthesises findings from the Real-world Evidence for Decisions in Diabetes (REDDIE) programme and wider literature. The programme used multiple national diabetes registries and complementary datasets to assess data fitness, regulatory and health technology assessment expectations, and target trial emulations of landmark studies. No new patient sample or pooled effect estimate is reported in the supplied text.

The authors describe how well-designed observational analyses can reproduce major trial findings and extend evidence to populations under-represented in trials, as well as address comparative effectiveness and longer-term outcomes. They emphasise that credibility depends on matching the research question to suitable data, study design and analytical methods. Target trial emulation and modern causal-inference methods may reduce bias, but cannot resolve unmeasured confounding or missing variables in routine datasets.

The article presents real-world evidence and randomised trials as complementary, rather than interchangeable, sources for clinical, regulatory and policy decisions. As a perspective, it offers a methodological framework rather than new comparative treatment results; its discussion does not establish that any particular diabetes therapy should be selected or changed in practice.