Interpreting real-world evidence | ACROSS T2D

Interpreting real-world evidence

Numerous sources of clinical data are used to inform clinical practice. This module compares real-world evidence, randomised controlled trials and meta-analyses, summarising their key differences and how their findings can be interpreted appropriately.

Interpreting real-world evidence

Interpreting real-world evidence
Interpreting real-world evidence
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What does ‘real-world evidence’ mean?
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Many different sources of data derived from routine clinical care can be used to generate evidence and inform clinical practice
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RCTs and RWE studies measure the effects of a treatment in different settings
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Interpreting real-world evidence
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How can real-world data be used?
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RWE studies provide further insights to those gained from RCTs
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Findings from RCTs and RWE studies can differ for a number of reasons
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There are several important differences between RCTs, meta-analyses of RCTs and RWE studies
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Each type of study has strengths and limitations
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Time-related biases can occur in RWE studies
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What conclusions can be drawn from RCTs versus RWE studies?
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Interpreting real-world evidence
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EMPRISE: comprehensive clinical picture of empagliflozin
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EMPRISE: study design
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The EMPRISE study design uses a best-practice approach to minimise confounding and avoid bias
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Empagliflozin was associated with a reduced risk of HHF in routine clinical practice compared with DPP-4 inhibitors
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EMPRISE heart failure outcomes complement the results from EMPA‑REG OUTCOME
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How should the available results from the EMPRISE study be interpreted?
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Summary of interim analysis from the EMPRISE study
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Interpreting real-world evidence
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OBSERVE-4D: US real‑world analysis of canagliflozin versus other SGLT2 inhibitors and non-SGLT2 inhibitors
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OBSERVE-4D: study design
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In the OBSERVE-4D study, canagliflozin and other SGLT2 inhibitors were associated with a lower risk of HHF versus other antihyperglycaemic agents
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How should the results from the OBSERVE-4D observational study be interpreted?
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What conclusions can be drawn from the OBSERVE-4D study?
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Interpreting real-world evidence
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EASEL: real‑world analysis of US Department of Defense Military Health System (SGLT2 inhibitors versus non-SGLT2 inhibitors)
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EASEL: study design
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In EASEL, SGLT2 inhibitors were associated with a lower risk of all-cause mortality, HHF and MACE, and a higher risk of BKA versus non-SGLT2 inhibitors
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How should the results from EASEL be interpreted?
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What conclusions can be drawn from the EASEL study?
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Interpreting real-world evidence
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The CVD-REAL observational studies
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In the CVD-REAL studies, SGLT2 inhibitors were associated with lower rates of CV outcomes versus other glucose-lowering drugs
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EMPA-REG OUTCOME, DECLARE-TIMI 58, CANVAS Program and CVD-REAL: baseline characteristics and key outcomes
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Heart failure outcomes seen in the DECLARE and CANVAS Program trials were complemented by CVD-REAL
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Mortality outcomes seen in CVD-REAL were not complemented by the DECLARE and CANVAS Program trials
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How should the results from the CVD-REAL observational studies be interpreted?
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What conclusions can be drawn from the CVD-REAL studies?
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Interpreting real-world evidence
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Summary: interpreting different levels of evidence
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Back-up slides
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Immortal time bias in CVD-REAL may lead to overestimation of the effect on mortality
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There are several important differences between each type of study (1)
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There are several important differences between each type of study (2)