Article Title
Precision Prescribing of SGLT2 Inhibitors in People With Type 2 Diabetes for Primary Prevention of Heart Failure: A Model Development and Validation Study
Summary
This study developed and validated a tool called SABRE to estimate which people with type 2 diabetes, but without existing heart failure, kidney disease, or atherosclerotic cardiovascular disease, are most likely to benefit from SGLT2 inhibitors for preventing heart failure.
Background
Heart failure is a serious condition in which the heart cannot pump blood as well as it should. People with type 2 diabetes have a higher risk of developing heart failure, even if they have not yet had a heart attack, stroke, kidney disease, or diagnosed heart failure. Sodium-glucose cotransporter 2 inhibitors, commonly called SGLT2 inhibitors, are diabetes medicines that help lower blood sugar by increasing glucose loss in urine. Over the past several years, they have also been shown to reduce the risk of heart failure and kidney complications.
Current guidelines already recommend SGLT2 inhibitors for many patients with type 2 diabetes who also have established atherosclerotic cardiovascular disease, heart failure, or chronic kidney disease. However, most people with type 2 diabetes do not have these conditions. For that broader group, clinicians still lack a simple way to identify who will gain the greatest heart failure prevention benefit from starting an SGLT2 inhibitor.
Why This Study Was Done
The research team wanted to move beyond a one-size-fits-all approach. Their goal was to build a clinical prediction model that could estimate each person’s absolute heart failure benefit from SGLT2 inhibitor treatment over 5 years. In other words, instead of asking only whether the drug works in general, the model asks how much an individual patient is likely to benefit.
This kind of precision prescribing may help clinicians choose the right preventive therapy for the right patient, while also supporting shared decision-making and efficient use of medicines.
How the SABRE Model Works
The investigators created the SGLT2i Absolute Benefit Response, or SABRE, model. It combines two pieces of information:
1. A person’s baseline absolute risk of developing heart failure, estimated using the validated QDiabetes-HF model.
2. The relative treatment effect of SGLT2 inhibitors on heart failure hospitalization, derived from a meta-analysis of randomized clinical trials, which showed a hazard ratio of 0.63.
By combining these two elements, the model estimates how many heart failure events might be prevented over 5 years for a given individual. People at higher baseline risk generally have more to gain in absolute terms, even if the relative risk reduction is similar across patients.
Study Design and Validation
The researchers used linked United Kingdom primary care, hospital, and death registry data from 2013 to 2020. They examined two large groups of adults with type 2 diabetes who did not have a prior diagnosis of atherosclerotic cardiovascular disease, heart failure, or chronic kidney disease.
The study included:
– 57,368 people who started an SGLT2 inhibitor
– 111,673 people who started a comparator drug, either a dipeptidyl peptidase 4 inhibitor or a sulfonylurea
The investigators then assessed whether the SABRE model’s predictions matched observed real-world outcomes. They also checked whether the treatment effect appeared to differ by baseline heart failure risk.
Main Findings
Among people starting an SGLT2 inhibitor, the risk of new-onset heart failure was about 30% lower than in the comparator group, with a hazard ratio of 0.70 (95% confidence interval 0.63 to 0.78). This result was consistent with the benefits seen in randomized trials.
Importantly, the relative heart failure benefit did not vary meaningfully according to a person’s starting heart failure risk. This means the proportional reduction in risk was fairly similar across risk groups, but the absolute number of heart failure events prevented was larger in those with higher baseline risk.
The SABRE model estimated a wide range of 5-year absolute heart failure benefit:
– less than 0.1% in some individuals
– up to 14.1% in others
– median benefit: 1.0%
– interquartile range: 0.6% to 1.8%
The model was well calibrated, meaning its predicted benefits aligned closely with what was seen in real-world outcome data.
Clinical Meaning
This study is important because it provides a practical way to identify which patients with type 2 diabetes may benefit most from an SGLT2 inhibitor for preventing heart failure before any cardiovascular or kidney disease has appeared.
In everyday practice, this could help clinicians answer questions such as:
– Is this patient likely to benefit enough to justify starting an SGLT2 inhibitor now?
– Should prevention of heart failure be a major reason for choosing this drug?
– How can we discuss expected benefit in a more personalized way?
A key strength of the SABRE approach is that it translates trial evidence into an individualized absolute benefit estimate. Absolute benefit is often easier to discuss with patients than relative risk reduction because it reflects the real-world chance of avoiding a future event.
How This Fits With Current Treatment Options
SGLT2 inhibitors are now widely used in type 2 diabetes management, and common drugs in this class include empagliflozin, dapagliflozin, canagliflozin, and ertugliflozin. Their benefits extend beyond glucose lowering. They can also reduce hospitalization for heart failure and slow progression of kidney disease in many patients.
That said, these medicines are not appropriate for every person. Factors such as low blood pressure, recurrent genital infections, dehydration risk, diabetic ketoacidosis risk, cost, and kidney function should still be considered. The SABRE model does not replace clinical judgment; rather, it adds a data-driven way to estimate who is most likely to gain preventive heart failure benefit.
For people with established atherosclerotic cardiovascular disease, heart failure, or chronic kidney disease, guidelines already support SGLT2 inhibitor use. The more challenging group is the much larger population with type 2 diabetes who have none of these conditions yet. This study directly addresses that gap.
Strengths and Limitations
One major strength of the study is that it combined high-quality randomized trial evidence with large-scale real-world data, allowing both scientific rigor and practical validation. The sample size was large, and the model performed well in routine care settings.
However, there are some limitations to keep in mind. As with all observational validation studies, treatment choice in real-world practice may be influenced by factors that are difficult to fully measure. The model was built using data from the United Kingdom, so performance may vary in other healthcare systems or populations. Also, the study focused on prevention of heart failure, not on every possible benefit or adverse effect of SGLT2 inhibitors.
Practical Takeaway
For people with type 2 diabetes who do not yet have heart failure, chronic kidney disease, or known atherosclerotic cardiovascular disease, the SABRE model may help identify who stands to gain the most from starting an SGLT2 inhibitor for primary heart failure prevention. Rather than treating all patients the same, this approach supports more precise, personalized prescribing.
Conclusion
The SABRE model is an easy-to-use clinical prediction tool that combines a person’s baseline heart failure risk with the proven relative benefit of SGLT2 inhibitors. In validation using routine U.K. health data, it estimated individualized 5-year heart failure prevention benefit accurately and suggested it can improve targeting beyond current guideline-based prescribing. This represents an important step toward precision medicine in type 2 diabetes care.
