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