This study assesses the cost-effectiveness of adding a sodium-glucose cotransporter 2 inhibitor versus switching to a glucagon-like peptide-1 receptor agonist in patients with diabetes on metformin and a dipeptidyl peptidase-4 inhibitor.
ABSTRACTObjectives: Cost-effectiveness estimates are useful to a health plan when they are specific to a utilization management policy question. To help inform a step therapy policy decision, this study assessed the 3-year cost-effectiveness of adding a sodium-glucose cotransporter 2 (SGLT2) inhibitor versus switching to a glucagon-like peptide-1 receptor agonist (GLP-1 RA) in patients with type 2 diabetes who are on metformin and a dipeptidyl peptidase-4 (DPP-4) inhibitor from both private and public payer perspectives in the United States.
Study Design: Cost-effectiveness analysis.
Methods: A decision-analytic model was built incorporating goal glycated hemoglobin (A1C) achievement as the effectiveness measure, as well as adverse effect and discontinuation rates from clinical trial data. One-way, scenario, and probabilistic sensitivity analyses were performed.
Results: In a cohort of 1000 patients, adding an SGLT2 inhibitor led to $3.9 million more in spending and 93 more patients reaching goal A1C compared with switching from a DPP-4 inhibitor to a GLP-1 RA. This resulted in an incremental cost-effectiveness ratio (ICER) of $42,125 per patient to achieve goal A1C from the private payer perspective. Using a public payer perspective led to an ICER of $103,829. These results were most sensitive to changes in drug costs and the proportion of patients achieving A1C goal or discontinuing.
Conclusions: Assuming a $50,000 willingness-to-pay threshold, adding an SGLT2 inhibitor was cost-effective compared with switching from a DPP-4 inhibitor to a GLP-1 RA from a private payer perspective but not from a public payer perspective. This study highlights how differences in payer reimbursement rates for medications can lead to contrasting results.
Am J Manag Care. 2020;26(3):e76-e83. https://doi.org/10.37765/ajmc.2020.42639
This study assesses the cost-effectiveness of adding a sodium-glucose cotransporter 2 (SGLT2) inhibitor versus switching from a dipeptidyl peptidase-4 (DPP-4) inhibitor to a glucagon-like peptide-1 receptor agonist (GLP-1 RA) in patients with type 2 diabetes already on metformin and a DPP-4 inhibitor.
Type 2 diabetes (T2D) is estimated to affect approximately 27 million Americans and cost approximately $327 billion.1,2 Of this, $237 billion is spent on direct medical care and $90 billion is due to reduced productivity.2 Metformin has increasingly become the first-line agent for T2D; it was prescribed for approximately 60% to 77% of all patients using first-line antidiabetic treatment from 2005 to 2016.3 During this time period, sulfonylureas were the most commonly prescribed second-line agents, but their use has decreased (from 60% to 46%).3 Over the same time frame, the use of dipeptidyl peptidase-4 (DPP-4) inhibitors as second-line agents has increased from 0.4% to 21%.3
In 2013, a new antidiabetic drug class called sodium-glucose cotransporter 2 (SGLT2) inhibitors entered the US market. Canagliflozin was the first drug in the class approved by the FDA, followed by dapagliflozin and empagliflozin in 2014 and ertugliflozin in 2017.4 SGLT2 inhibitors enhance urinary excretion of glucose by blocking transport proteins that help reabsorb glucose systemically.5 SGLT2 inhibitors safely and effectively reduce glycated hemoglobin (A1C) levels by 0.5% to 1.0%,5 reduce body weight by 1 to 3 kg,6 and reduce systolic blood pressure by 3 to 5 mmHg.7,8 Common adverse effects (AEs) include urinary tract infections (UTIs), genital mycotic infections (GMIs), and polyuria.6
In 2018, the American Association of Clinical Endocrinologists guidelines suggested the preferential use of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) before SGLT2 inhibitors as the second-line or third-line agent after metformin.9 GLP-1 RAs are injectables that include exenatide, liraglutide, albiglutide, dulaglutide, lixisenatide, and semaglutide, as well as an oral formulation of semaglutide most recently approved. Whereas exenatide and liraglutide have been on the US market since 2005 and 2010, respectively, albiglutide, dulaglutide, lixisenatide, and semaglutide (injectable) entered the US market more recently, between 2014 and 2017.4 The efficacy of these agents in reducing A1C and body weight has been well established.10-14 Common AEs include gastrointestinal events and hypoglycemia.12
In 2014, several health plans had a step therapy requirement to use metformin and a DPP-4 inhibitor before the initiation of SGLT2 inhibitors.15-19 However, given that GLP-1 RAs are also efficacious in lowering A1C, health plans were considering an alternative step therapy requirement that would switch members from a DPP-4 inhibitor to a GLP-1 RA before use of SGLT2 inhibitors. This is because DPP-4 inhibitors and GLP-1 RAs have similar mechanisms of action, but GLP-1 RAs generally lead to larger A1C reductions. Given that GLP-1 RAs are also more expensive than SGLT2 inhibitors, it would be helpful for health plans to assess the cost-effectiveness of switching from a DPP-4 inhibitor to a GLP-1 RA versus adding on an SGLT2 inhibitor in members on metformin and a DPP-4 inhibitor who need further reduction of A1C. This study aims to assess the cost-effectiveness of these specific treatment sequences using both private and public payer perspectives over a 3-year time horizon.
A decision-analytic model (Figure 1) was constructed for a hypothetical cohort of 1000 patients with T2D who were currently using metformin and a DPP-4 inhibitor but required additional glycemic control. Patients could then either add an SGLT2 inhibitor or replace the DPP-4 inhibitor with a GLP-1 RA. The model determined whether patients reached a goal of A1C less than 7% at 3 years and whether patients experienced UTIs, GMIs, or hypoglycemia. Due to the short time horizon and specific decision context, this model did not include longer-term complications from diabetes and was focused on the comparison of adding an SGLT2 inhibitor or replacing the DPP-4 inhibitor with a GLP-1 RA in patients on metformin and a DPP-4 inhibitor who need further glycemic control. Patients who discontinued either an SGLT2 inhibitor or a GLP-1 RA were assumed to switch to insulin as fourth-line treatment.
Clinical Input Data
Population. The cost-effectiveness of an SGLT2 inhibitor as an add-on to metformin and a DPP-4 inhibitor versus replacing a DPP-4 inhibitor with a GLP-1 RA was analyzed in adults 18 years or older with T2D uncontrolled on metformin and a DPP-4 inhibitor alone. A literature review was conducted in PubMed to identify phase 3 clinical trials with the sequence of interest (metformin and DPP-4 inhibitor switching to GLP-1 RA or adding SGLT2 inhibitor). Search terms included canagliflozin, dapagliflozin, empagliflozin, ertugliflozin, exenatide, exenatide extended-release, liraglutide, dulaglutide, albiglutide, lixisenatide, semaglutide, metformin, gliptin, efficacy, and safety. Search filters included clinical trial as the article type. References of identified articles were searched through to find other similar articles. We also worked with a formulary manager at a health plan who had recently reviewed the SGLT2 inhibitor and GLP-1 RA drug classes to ensure that we were not missing any clinical trials with the treatment sequence of interest. Baseline characteristics of the model population were based on the characteristics of the patients from those identified clinical trials.20-28 The majority of these clinical trials included adult patients with T2D with a range of baseline A1C levels from 7% to 11% and a baseline body mass index of less than 45 kg/m2. Most trials required previous treatment with at least metformin, and trial durations varied from 24 weeks (short term) to 260 weeks (long term).
Treatment effects and AEs. The primary treatment effect considered in the cost-effectiveness analysis was the percentage of patients achieving goal A1C of less than 7% in either treatment arm (Table 120-22,24-30 [part A and part B]), because many health plans have diabetes quality measures based on A1C. Percentages of patients experiencing AEs, as well as discontinuation rates, were incorporated and determined from the clinical trials (Table 120-22,24-30). When there were estimates for the same treatment arm and time point, we took the average across estimates. If estimates were missing at any time point (24-26 weeks, 1 year, 2 years, or 3 years), we then fit a trend line to the available reported estimate to intrapolate or extrapolate estimates. The eAppendix (available at ajmc.com) provides more details on the reported estimates from the clinical trials and how these were aggregated to estimate the treatment effect, AEs, and discontinuation-rate model inputs in Table 1.20-22,24-30 The AEs, UTI and GMI, were specifically chosen because the health plan we collaborated with to conduct this analysis was mostly interested in costs for the pharmacy benefit, and these AEs are commonly treated with prescription drugs. For example, we did not include rates of nausea or vomiting in our model because these are not commonly treated with prescription drugs. We assumed that all patients were treated for their AEs, GMI was treated with a single dose of fluconazole 150 mg,31 and UTI was treated with either sulfamethoxazole/trimethoprim 800 mg/160 mg twice daily for 3 days or nitrofurantoin 100 mg twice daily for 5 days.32
Costs for antidiabetic drugs and AE treatments were included (Table 120-22,24-30), assuming equal market share distribution of individual drugs within a class. When multiple generic drug products were available, we used those with the lowest cost. We also added pen needle costs if an injectable GLP-1 RA did not include needles as part of the package, because these costs are often covered by the pharmacy benefit. Drug costs were determined using wholesale acquisition cost (WAC) for the private payer perspective.33
Discounting, Time Horizon, and Perspective
A discount rate of 3% was applied to costs and effects.34 The time horizon was set to 3 years based on health plan interests, as this represents the average length of time a patient is covered by a particular health plan. One-year cost-effectiveness estimates were also provided.
Incremental cost-effectiveness ratios (ICERs) were measured in 2017 US$ per patient at goal A1C less than 7%. ICERs less than $50,000 per patient at goal A1C less than 7% were considered cost-effective.
A number of sensitivity analyses were conducted to assess the impact of parameters on the base-case cost-effectiveness results. One-way sensitivity analyses assessed how varying the costs, as well as effectiveness, discontinuation rates, and AE rates of SGLT2 inhibitors and GLP-1 RAs after treatment with metformin and a DPP-4 inhibitor, would affect the ICER. The ranges were calculated by varying the base-case scenario estimates by ±20% of the mean value. In another one-way sensitivity analysis, the base-case scenario estimates were varied by ±40% of the mean value.
One scenario analysis incorporated rebates by estimating drug costs as WAC minus 20%. Another scenario analysis estimated drug costs using the Federal Supply Schedule (FSS)35 from the public payer perspective, instead of the WAC. In general, the FSS price is a better estimate of the maximum price that direct federal purchasers of pharmaceuticals can pay for drugs.36 The 4 largest federal purchasers of pharmaceuticals are the Department of Veterans Affairs, Department of Defense, Public Health Service, and Coast Guard.
A third scenario analysis included the costs of medical visits for AE treatment. These included hospitalizations for severe hypoglycemia and physician visits for the treatment of UTI and GMI. The physician visit cost estimate was based on the Medicare Current Procedural Terminology code 99213, representing a 15-minute office visit.37 The cost estimate for a hospitalization for severe hypoglycemia was derived from a 2008 study30 and then inflation adjusted using the medical care component of the Consumer Price Index.38
A probabilistic sensitivity analysis was done to simultaneously assess uncertainty in model parameters. One thousand Monte Carlo simulations were performed, and beta distributions were assumed for each of the probabilities: achievement of goal A1C, treatment discontinuation, and experience of UTI, GMI, and hypoglycemia.
Base-Case Analysis: Private Payer Perspective
Under base-case assumptions, the SGLT2 inhibitor arm was associated with higher treatment costs ($3,913,108 more) compared with the GLP-1 RA arm (Table 2). However, significant improvements in clinical outcomes, as shown by the number of patients achieving a goal A1C of less than 7.0% (93 more), were seen with the SGLT2 inhibitor arm (Table 2). Adding an SGLT2 inhibitor was associated with an ICER of $42,125 per patient to reach goal A1C versus switching to a GLP-1 RA (Table 2). Assuming a willingness-to-pay threshold of $50,000 per patient to reach goal A1C, adding an SGLT2 inhibitor versus switching to a GLP-1 RA is a more cost-effective option for patients with T2D.
One-way Sensitivity Analyses
Sensitivity analyses using ranges of 20% above and below the base-case value demonstrated that the outcomes from the base-case analysis were most sensitive to changes in the cost of a GLP-1 RA, then effectiveness of adding an SGLT2 inhibitor versus switching to a GLP-1 RA, and then cost of an SGLT2 inhibitor (Figure 2). The base-case ICER of $42,125 per patient reaching goal A1C increased to $80,988 when the GLP-1 RA cost decreased by 20%, to $70,423 when the SGLT2 inhibitor effectiveness decreased by 20%, and to $66,258 when the SGLT2 inhibitor cost increased by 20% (Figure 2). Given a willingness-to-pay threshold of $50,000 per patient reaching goal A1C, none of these scenarios would lead to the SGLT2 inhibitor addition being cost-effective compared with the option of switching to a GLP-1 RA. When ranges were widened to 40% above and below the base-case value, results were similar but potentiated (eAppendix). A GLP-1 RA cost that was 40% above or an SGLT2 inhibitor cost that was 40% below the base-case value led to the SGLT2 inhibitor addition being a dominant strategy (eAppendix).
On the contrary, the base-case ICER of $42,125 per patient reaching goal A1C decreased to $3262 when the GLP-1 RA cost increased by 20% and to $17,992 when the SGLT2 inhibitor cost decreased by 20% (Figure 2). Both of these scenarios would lead to the SGLT2 inhibitor addition being cost-effective compared with the option of switching to a GLP-1 RA.
Scenario Sensitivity Analysis: Incorporating Rebates
When drug costs were estimated as WAC minus 20% to account for potential rebates, the ICER decreased to $11,050 and $33,700 per patient to reach goal A1C over 1 year and 3 years, respectively (Table 2). Assuming a willingness-to-pay threshold of $50,000 per patient to reach goal A1C, adding an SGLT2 inhibitor versus switching to a GLP-1 RA remained cost-effective from a private payer perspective.
Scenario Sensitivity Analysis: Public Payer Perspective
When using FSS as the drug cost estimate to assess cost-effectiveness from a public payer perspective, costs of a GLP-1 RA were significantly lower than the WAC prices ($8.37 vs $20.85; Table 2). As a result, the ICER associated with adding an SGLT2 inhibitor versus switching to a GLP-1 RA was $28,075 per patient to reach goal A1C over 1 year but $103,829 over 3 years. Assuming a willingness-to-pay threshold of $50,000 per patient to reach goal A1C, adding an SGLT2 inhibitor versus switching to a GLP-1 RA would not be a cost-effective option from a public payer perspective over 3 years.
Probabilistic Sensitivity Analysis
The cost-effectiveness analysis curves in Figure 3 show differences in the probabilities of cost-effectiveness depending on type of payer. At a $50,000 willingness-to-pay threshold, private payers are more likely to find that adding an SGLT2 inhibitor instead of switching to a GLP-1 RA is cost-effective (60%) compared with public payers (2%).
Scenario Sensitivity Analysis: Inclusion of Medical Costs
The number of patients who had severe enough hypoglycemia that would require hospitalization was very similar between the SGLT2 inhibitor and GLP-1 RA arms (10 vs 8). As a result, the inclusion of medical costs did not drastically change the ICER ($42,874 vs the base-case value of $42,125 per patient achieving a goal A1C; Table 2).
In a hypothetical cohort of 1000 patients with T2D in our model, payers would expect that over 3 years, adding an SGLT2 inhibitor would result in 93 more patients achieving a goal A1C of less than 7% at an additional cost of $3.9 million (using WAC costs) or $9.6 million (using FSS costs) than if those patients switched to a GLP-1 RA. This means that given a $50,000 willingness-to-pay threshold, adding an SGLT2 inhibitor versus switching to a GLP-1 RA is cost-effective for T2D for private payers that have drug unit costs similar to the WAC but not for public payers that have drug unit costs similar to the FSS (ICERs of $42,125 vs $103,829 per patient at a goal A1C of <7%, respectively). The difference in results was driven mostly by the lower GLP-1 RA unit drug cost when based on the FSS versus the WAC ($8.37 vs $20.85 per unit, respectively). This is an important finding that highlights how differences in medication reimbursement rates can lead to contrasting cost-effectiveness results for the same step therapy policy among different payers.
This study used a 3-year time horizon because the average time that an employee in the United States stays with the same health plan is approximately 3 years.39 When a shorter time horizon was considered (1 year), the SGLT2 inhibitor arm was more cost-effective than the GLP-1 RA arm across all sensitivity analyses. This is because the treatment effect, or achievement of goal A1C, occurred within the first 6 months of treatment and then slightly declined over time based on medication discontinuation rates. Meanwhile, differences in medication treatment costs, the primary cost driver, accumulated over time, leading to the SGLT2 inhibitor arm being less likely to be more cost-effective than the GLP-1 RA arm for longer study time horizons.
When GLP-1 RA costs were increased by 40% or SGLT2 inhibitor costs were decreased by 40%, adding an SGLT2 inhibitor became the dominant strategy, meaning that it was both cost-saving and more effective at achieving goal A1C. Other factors, such as the proportion of the population able to achieve goal A1C, as well as the discontinuation rate, also greatly affected the cost-effectiveness results. Therefore, if GLP-1 RAs or SGLT2 inhibitors were part of value-based payment arrangements, effectiveness and discontinuation should also be considered in addition to cost.
Although other cost-effectiveness analyses have not looked at the initiation of an SGLT2 inhibitor or a GLP-1 RA in patients with T2D specifically on metformin and a DPP-4 inhibitor, existing research on the cost-effectiveness of an SGLT2 inhibitor versus a GLP-1 RA alone suggests that SGLT2 inhibitors are the economically dominant agents as well.23,40 These recent studies corroborate our findings but also exemplify the significance of this particular study, as the cost-effectiveness of the specific treatment sequences in question have not yet been examined.
This cost-effectiveness study provides results that directly inform step therapy requirements that US health plans have been placing on antidiabetic drugs. Many health plans require step therapy or prior authorization before initiating the use of SGLT2 inhibitors, but if SGLT2 inhibitors are a more cost-effective option with greater health outcomes, payers may need to reconsider. However, payers need to consider their own drug unit costs, which, in our example, could change whether one treatment sequence was more cost-effective than the other. Payers can also use this study to inform negotiations on rebates to ensure that their step therapy and prior authorization policies are encouraging cost-effective treatment sequences in T2D.
Another strength of this study is its utilization of available clinical trials comparing treatment sequences of antidiabetic drugs that provided estimates of A1C reduction, as well as AE and discontinuation rates, specific to the treatment sequences of interest.
Limitations and Future Directions
One limitation of our study was that we did not use previous comprehensive diabetes models due to our need to keep the model simple and transparent for our payer end user, which was interested in a short time horizon and the immediate effects of drug treatment. Also, limited clinical trials were available for this specific decision context. Another limitation was that because GMI and UTI are not necessarily AEs of interest for non—SGLT2 inhibitor drug classes, the adjudication for these AEs may not be as robust as in SGLT2 inhibitor clinical trials. Therefore, a wide variety of sensitivity analyses were conducted to assess the impact of varying model inputs. Additionally, all estimates of treatment effect, or patients achieving goal A1C, came from clinical trials. Although the internal validity of clinical trial data is generally strong, it is unknown whether the treatment effect estimates are representative of real-world settings. At the time of the study, we were unable to find observational studies from real-world settings providing estimates for the specific treatment sequences of interest. If future estimates from real-world settings become available, it would be of interest to conduct sensitivity analyses using estimates from such studies. Furthermore, subgroup analyses to identify if cost-effectiveness estimates vary across age or comorbidities is another area of future research, when data become available.
Attention has focused recently on the cardiovascular (CV) outcomes of antidiabetic agents, GLP-1 RAs and SGLT2 inhibitors in particular. For example, clinical trials have demonstrated that the use of SGLT2 inhibitors in patients with T2D with high CV event risk had substantially lower CV event—related deaths, lower hospitalizations for heart failure, and lower deaths in general.41-44 GLP-1 RAs have also demonstrated fewer CV-related deaths, but to varying extents across the various GLP-1 RA agents.45-48 Meanwhile, CV outcomes trials have not shown that DPP-4 inhibitors improve CV outcomes in patients with T2D.49-51 Nonetheless, no trials provide CV outcome data for the specific treatment sequences of interest examined here—adding an SGLT2 inhibitor versus replacing a DPP-4 inhibitor with a GLP-1 RA. In the future, if evidence becomes available, it would be of interest to use CV outcomes as the primary outcome instead of achievement of target A1C goals.
Assuming a $50,000 willingness-to-pay threshold, adding an SGLT2 inhibitor versus switching to a GLP-1 RA is cost-effective for T2D for private payers that have drug unit costs similar to the WAC but not for public payers that have drug unit costs similar to the FSS (ICERs of $42,125 vs $103,829 per patient at a goal A1C of <7%, respectively). This important finding highlights how differences in medication reimbursement rates can lead to contrasting cost-effectiveness results for the same step therapy policy among different payers.Author Affiliations: Duke Clinical Research Institute (AH), Durham, NC; University of Maryland School of Pharmacy (BJ, JFS), Baltimore, MD; Defense Health Agency Pharmacy Operations Division (AL), San Antonio, TX.
Source of Funding: None.
Author Disclosures: Dr Hung has received a grant from Pharmaceutical Research and Manufacturers of America (PhRMA). Dr Slejko has received grants from PhRMA and PhRMA Foundation. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design (AH, AL, JFS); acquisition of data (AH, BJ); analysis and interpretation of data (AH, BJ, AL); drafting of the manuscript (AH, BJ); critical revision of the manuscript for important intellectual content (AH, AL, JFS); statistical analysis (AH); provision of patients or study materials (AH, BJ); administrative, technical, or logistic support (AH, AL); and supervision (AH, AL, JFS).
Address Correspondence to: Anna Hung, PharmD, PhD, Duke Clinical Research Institute, 200 Morris St, Durham, NC 27701. Email: firstname.lastname@example.org.REFERENCES
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