Sodium-Glucose Co-transporter 2 (SGLT2) Inhibitor: Comparing Trial Data and Real-World Use

The cardiovascular benefits identified by the EMPA-REG trial were a surprising but very welcome finding. However, it is important to be clear that the trial’s participants were selected on the basis of very high cardiovascular risk. We can therefore only expect similar cardiovascular benefits in the same high risk group in the real world. Our data suggest that this makes up only a small but not insubstantial proportion of those with T2DM. It also suggests that current SGLT2 inhibitor use occurs in a subgroup of people with T2DM who are of a younger age and have a lower cardiovascular risk than most people with T2DM. Any cardiovascular benefit in these people is uncertain. There are also a large proportion of people with high cardiovascular risk who are not currently treated with an SGLT2 inhibitor. Therefore, there is some scope to consider extending the use of empagliflozin in people with high cardiovascular risk if clinically appropriate.

The presence of cardiovascular risk factors was found, unsurprisingly, to be highest in the oldest age groups. It is therefore likely that this group is most likely to gain the largest cardiovascular risk reduction from SGLT2 inhibitor use. However, the use of SGLT2 inhibitors in this group can be problematic as the elderly are more likely to experience volume depletion, more likely to have baseline renal impairment, and have more significant sequelae from urinary tract infections [23, 24, 25, 26, 27].

Other cardiovascular safety trials are still ongoing and will help to explore questions around whether these benefits are a class effect and whether they can also be seen in lower cardiovascular risk groups. The Multicenter Trial to Evaluate the Effect of Dapagliflozin on the Incidence of Cardiovascular Events (DECLARE-TIMI 58) and CANagliflozin cardioVascular Assessment Study (CANVAS) trials with dapagliflozin and canagliflozin, respectively, are the two major ongoing trials with currently approved SGLT2 inhibitors [28, 29]. Their inclusion criteria are somewhat broader than those of the EMPA-REG trial, with lower cardiovascular risk participants enrolled. Whilst these trial results are awaited, a comparison of the characteristics of people treated with T2DM in clinical practice with those of the EMPA-REG trial is important to enable an understanding of how the existing data can be applied in practice. We provide a description of the cardiovascular risk profile of a large national sample of people with T2DM treated with SGLT2 inhibitors in England and compare this to the EMPA-REG trial inclusion criteria. We also provide a comparison with the complete denominator group (all people with identified T2DM).

It should be clearly stated that SGLT2 inhibitors have benefits beyond cardiovascular risk reduction: predominantly improved glycemic control and weight loss [30]. Our real-world data demonstrate that people prescribed SGLT2 inhibitors have a higher BMI than others with T2DM. This trend suggests that the weight loss benefits of the class are a key consideration in prescribing. Whilst our analysis demonstrates that the cardiovascular benefit identified in the EMPA-REG trial can only be extrapolated to a small proportion of those currently prescribed SGLT2 inhibitors, this group will still experience glycemic and weight loss benefits.

The SGLT2 inhibitor class of medication is costlier than older therapies. The National Institute for Health and Care Excellence (NICE) in the UK has previously undertaken an economic analysis of the use of SGLT2 inhibitors and considers their use to be below the cost-effectiveness thresholds [31, 32, 33]. Otherwise analyses also suggest SGLT2 inhibitors provide cost-effective benefit [34, 35, 36]. The benefits in these analyses are based on the glucose-lowering potential and do not consider the additional cardiovascular benefits seen in the EMPA-REG trial. Although we show that the trial findings can be only applied directly to a small proportion of those with T2DM, incorporation of the additional cardiovascular risk reduction into existing economic models is still likely to improve the cost–benefit estimates.

Our data highlight the importance of further research to identify any cardiovascular benefit from SGLT2 inhibitors in lower-risk groups which make up the majority of SGLT2 inhibitor use currently. This leads to several important clinically relevant questions: Are there any cardiovascular benefits with canagliflozin and dapagliflozin (which makes up the majority of SGLT2 inhibitor prescriptions currently)? What, if any, is the degree of cardiovascular benefit afforded in the lower cardiovascular risk groups? The ongoing cardiovascular safety trials with canagliflozin (CANVAS) and dapagliflozin (DECLARE-TIMI 58) will go some way to answering these questions [28, 29]. The CANVAS trial is estimated to complete in 2017 and DECLARE-TIMI 58 in 2019. These trials should be supported by real-world analyses of cardiovascular outcomes in people currently treated with SGLT2 inhibitors.

The EMPA-REG, CANVAS, and DECLARE-TIMI 58 trials also exclude people with certain comorbidities. Many of those excluded may have had significant cardiovascular risk. Additional real-world evidence may also be needed to clarify whether the use of SGLT2 inhibitors in those with multimorbidity confers cardiovascular benefit.

Only one other similar study comparing the EMPA-REG trial inclusion criteria against a large sample of people with diabetes has been performed. The study in initial reporting, and not yet published in a complete manuscript, compared the criteria against a large registry-based population in the USA (the Diabetes Collaborative Registry) [37]. The authors used prior myocardial infarction, any coronary artery disease, any coronary revascularization, or peripheral artery disease to approximate the EMPA-REG criteria. They found that only 16% of those with T2DM met these approximate criteria. These results agree closely with those presented here. Our present study may provide a more representative sample of the general population with T2DM than this registry-based analysis. We were also able to provide a closer mapping of disease codes to the EMPA-REG inclusion criteria than was possible for this study.

The key strengths and limitations of the data source used for the study (RCGP RSC network of practices) have previously been described [21, 38] in accordance with European Federation for Medical Informatics Primary Care Informatics Working Group consensus recommendations [39]. Key strengths include the large sample size, high level of data completeness, and the broadly representative nature of the population sample. However, the RCGP RSC group of practices are a somewhat self-selecting group of GP practices with a slightly more affluent population than the UK average [38]. Despite this, given the size of the population analyzed (ca. 1.7% of the English population), we feel that these data provide a reasonable approximation of the UK population.

Identification of the EMPA-REG inclusion criteria risk factors from routine primary care data may be limited by a number of factors. Firstly, the possibility of missing data (either because of failure to record known diagnoses or failure to identify risk factors in clinical practice) may have led us to underestimate the number of people who meet these criteria. As mentioned, our previous analyses of this dataset have demonstrated a high level of data completeness, particularly in those with diabetes which somewhat mitigates this limitation [21, 38]. Identification of specific inclusion criteria is limited by the clinical coding system used in UK primary care (Read codes) which does not have a code which mapped directly onto each EMPA-REG criterion. We have therefore used non-specific/broader clinical codes where no more specific code was available. This approach may have slightly overestimated the number of people meeting each inclusion criteria. Generally the Read coding system is an extensive system which facilitates very detailed coding of diagnoses and other code domains [19] such that this mapping mismatch is limited. Additional limitations of using routinely collected primary care data in research have also previously been described and include the loss of information recorded in the record as free text [40] which may have led to some missing cases in our data.