Lead Investigator: John Dennis, University of Exeter Medical School
Title of Proposal Research: Stratification of SGLT2 inhibitor glucose lowering therapy in Type 2 diabetes
Vivli Data Request: 5959
Funding Source: Government Funding (Medical Research Council, UK)
Potential Conflicts of Interest: None
Summary of the Proposed Research:
Type 2 diabetes affects over 350 million people. Good control of blood glucose (sugar) with appropriate lifestyle and medication helps patients feel better and reduces the risks of developing diabetes complications. Current guidelines for treating patients with Type 2 diabetes list a large number of drugs without giving clear guidance on which patients should have which drug. This makes it difficult for patients and their health care professionals to know which drugs are likely to suit them best. We know that patients with Type 2 diabetes vary greatly in how well they respond to different diabetes drugs, and whether they develop side effects.
Aim
The aim of this research is to identify clinical characteristics (such as weight or blood test results) that predict HbA1c change and side effects for glucose lowering treatments called sodium–glucose cotransporter 2 inhibitors (SGLT2I). The ultimate aim is to help doctors treat patients with Type 2 diabetes with the drug most likely to work well for them.
Objectives
Our objectives are to:
1. Identify if kidney function is associated with glucose lowering response to SGLT2I treatment
2. Identify whether clinical characteristics and blood tests associated with insulin secretion and insulin resistance are associated with glucose lowering response
3. Determine whether patients with higher glucose, and better glucose lowering response, have more side effects
4. Explore what other characteristics might help predict glucose lowering and side effects with SGLT2I
How will this research be conducted?
This research forms part of a larger national project funded by the UK government Medical Research Council, called MASTERMIND. In this study we will use information from 7 large studies where SGLT2 inhibitor treatment or comparison treatment has been previously tested in over 7000 people with Type 2 diabetes. We will test whether differences between people in these studies (for example their age, weight, or common blood test results such as kidney function) can be used to identify those who are likely to have a large reduction in blood glucose with these treatments and/or have a low risk of side effects.
We will compare results from this study with findings from other studies we are undertaking, for example other drug trials and information from patients taking these tablets as part of their normal care, so that we can be sure our findings are true and accurate. Further work to help us interpret these findings will include assessment of the potential benefits and disadvantages of targeting treatment in this way, through ongoing research in the MASTERMIND project.
How will our findings be communicated to patients and the public?
We will work with the charity Diabetes UK to communicate this research via their website, patient newsletter and social media. We will also communicate findings through presentations to patient groups and for important findings though local and national media.
Statistical Analysis Plan:
Analysis will be predominantly exploratory with replication to be performed in external industry and electronic healthcare record data sets.
1. Clinical predictors of glycaemic response
i. Models of glycaemic response to sodium–glucose cotransporter 2 (SGLT2) inhibitor therapy: We will examine clinical predictors of Haemoglobin A1c [HbA1c] change as a continuous measure using regression analysis, with baseline adjusted change in HbA1c as the outcome and clinical characteristics as the independent variables. Analysis will be adjusted for potential confounders including dose, study & co-therapy. This work will be extended further using more complex analysis taking into account placebo response (Royston Stat Med 2004 [PMID 15287081], Wang Stat Med 2015 [PMID 25736915]). Analysis will be per protocol and restricted to participants with >80% adherence and no change in glucose lowering co-therapy at the time point of interest, with analysis of the intention to treat population as sensitivity analysis. Model fit will be assessed, and variables transformed or categorised where necessary, if model assumptions are not met. Ultimately we will aim to combine independent predictors of response into a multivariable regression model.
ii. Covariates of interest: We will assess the relationships between glycaemic response and the following baseline characteristics, where available. Characteristics may be grouped to create composite variables (e.g. does response differ in individuals exhibiting multiple characteristics associated with insulin resistance?) and in multivariable models (adjusting for multiple characteristics in the same model).
Clinical characteristics:
A. Estimated glomerular filtration rate (Modification of Diet in Renal Disease [MDRD] & Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI] equations)
B. Glycaemia: baseline HbA1c, fasting glucose
C. Markers of beta cell failure: Diabetes duration, age of diagnosis, C-peptide (and/or insulin), insulogenic index, islet autoantibodies, proinsulin insulin ratio, homeostasis model assessment (HOMA) %B
D. Markers of insulin resistance: Body mass index (BMI), fasting triglycerides, High-density lipoprotein cholesterol (HDL-c), Low-density lipoprotein cholesterol (LDL-c), alanine transaminase (ALT) , aspartate aminotransferase (AST), Bilurubin, sex hormone binding globulin (SHBG), HOMA %Insulin Resistance (IR)
E. Sex and ethnicity
F. Measures of volume status: Haematocrit, Haemoglobin, Albumin
G. Other biomarkers: gamma-glutamyl transpeptidase (GGT), platelets, lymphocytes, neutrophils, height, weight
iii. Are characteristics associated with response specific to SGLT2-i: To explore whether a characteristic is specifically associated with response to Empagliflozin (rather than being associated with response to any treatment) we will assess the relationship between characteristics associated with Empagliflozin response and HbA1c change to dipeptidyl peptidase 4 (DPP4) inhibitor therapy, using the same methods described in i. above. This will inform the development of a multivariable regression model of response to DPP4 inhibitor therapy. We will explore the utility of data-driven approaches e.g. causal forests (Wager & Athey 2018 Journal of the American Statistical Association [PMID: 29862536] for detecting heterogeneous treatment effects for SGLT2 inhibitor and DPP4 inhibitor therapy, compared to classical regression based approaches.
iv. Exploration of confounding: The distribution of baseline characteristics will depend on the study of origin, which could confound results if variation in characteristics potentially predictive of response are not sufficiently represented in those treated with a particular agent. To ensure this is not confounding results we will explore the relationship between characteristics associated with response against placebo in the whole group (pooled results) and response within the individual studies.
v. Validation of findings: It will be important to validate findings from these trial datasets in other datasets, and to validate findings from other datasets in these trial datasets. We have access to the GoDARTS, a Tayside-based population dataset of treatment response, and observational primary care response data for >150000 patients with diabetes from the UK Clinical Practice Research Datalink (CPRD) which will provide a cohort of observational data for replication. In addition we are undertaking a randomised double blind crossover study directly comparing SGLT2 inhibitor, DPP4 inhibitor and Pioglitazone therapy to test stratification hypotheses derived from other trial data, this will allow us to replicate findings in the setting of comparative within individual response against other treatment classes.
2. Side effects
i. Analysis: We will assess the relationship between any characteristics associated with SGLT2 inhibitor response as a continuous variable and incidence of specific side effects (Urinary tract infection, genital infection, hypoglycaemia, event consistent with volume depletion, polyuria, acute renal failure) and treatment discontinuation using survival based methods, such as cox regression, with adjustment for clinical characteristics (depending on outcome of interest) age, gender, duration of diabetes, renal function, baseline glycaemia and liver function, study allocation, dose and co-therapy. We will explore the use of more complex joint modelling to evaluate the association between disease progression (longitudinal outcome) and risk of side-effects or treatment discontinuation (time-to-event outcomes).
We will test two specific hypotheses:
A. That participants with high baseline glycaemia will have a higher incidence of glycosuria related side effects and treatment discontinuation with SGLT2 in comparison to placebo and comparator therapies at the same level of baseline glycaemia.
B. That glycosuria related side effects will be more common in those with increased glucose lowering response at a given level of baseline glycaemia
ii. Confounding: the covariates of interest above may simply be prognostic factors of occurrence of these factors in the population, and unrelated to treatment allocation, rather than predictors of occurrence with SGLT2 treatment. The analysis in 2i above is therefore exploratory and methods adjusting for occurrence of these in a comparison group (such as that described above) will therefore be required to validate findings.
iii. Validation of findings: as outlined in 1v above findings will be validated in the additional observational and trial datasets available to the MASTERMIND consortium.
3. Precision estimate
Based on response data from the GoDarts study and assuming at least 3000 participants allocated to Empagliflozin/DPP4I (of 3900/4500 randomised to these therapies) are eligible for inclusion in the analysis conventional regression analyses will have 90% power to detect a covariate that explains <1% of variance in HbA1c reduction with an alpha <0.05.
Requested Studies:
A 78 Week Open Label Extension to Trials Assessing the Safety and Efficacy of BI 1356 (5 mg) as Monotherapy or in Combination With Other Antidiabetic Medications in Type 2 Diabetic Patients.
Sponsor: Boehringer Ingelheim
Study ID: NCT00736099
Sponsor ID: 1218.40
A Phase III Randomised, Double-blind, Placebo-controlled, Parallel Group, Efficacy and Safety Study of BI 10773 (10 mg, 25 mg) Administered Orally, Once Daily Over 24 Weeks in Patients With Type 2 Diabetes Mellitus With Insufficient Glycaemic Control Despite Treatment With Metformin Alone or Metformin in Combination With a Sulfonylurea
Sponsor: Boehringer Ingelheim
Study ID: NCT01159600
Sponsor ID: 1245.23
A Phase III, Randomised, Double-blind, Placebo-controlled, Parallel Group, Efficacy and Safety Study of BI 10773 (10 mg and 25 mg Administered Once Daily) as Add on to Pre-existing Antidiabetic Therapy Over 52 Weeks in Patients With Type 2 Diabetes Mellitus and Renal Impairment and Insufficient Glycaemic Control
Sponsor: Boehringer Ingelheim
Study ID: NCT01164501
Sponsor ID: 1245.36
A Randomised, Double-blind, Placebo-controlled Parallel Group Efficacy and Safety Trial of BI 10773 (10 and 25 mg Administered Orally Once Daily) Over 24 Weeks in Patients With Type 2 Diabetes Mellitus With Insufficient Glycaemic Control Despite a Background Therapy of Pioglitazone Alone or in Combination With Metformin
Sponsor: Boehringer Ingelheim
Study ID: NCT01210001
Sponsor ID: 1245.19
A Phase III Randomised, Double-blind, Placebo-controlled Parallel Group Efficacy and Safety Study of BI 10773 and Sitagliptin Administered Orally Over 24 Weeks, in Drug naïve Patients With Type 2 Diabetes Mellitus and Insufficient Glycaemic Control Despite Diet and Exercise
Sponsor: Boehringer Ingelheim
Study ID: NCT01177813
Sponsor ID: 1245.20
A Randomised, Double-blind, Placebo Controlled, Parallel Group 24 Week Study to Assess the Efficacy and Safety of BI 1356 (5 mg) in Combination With 30 mg Pioglitazone (Both Administered Orally Once Daily), Compared to 30 mg Pioglitazone Plus Placebo in Drug Naive or Previously Treated Type 2 Diabetic Patients With Insufficient Glycaemic Control.
Sponsor: Boehringer Ingelheim
Study ID: NCT00641043
Sponsor ID: 1218.15
A Randomised, Double-blind, Placebo-controled Parallel Group Efficacy and Safety Study of BI 1356 (5 mg Administered Orally Once Daily) Over 24 Weeks, in Drug Naive or Previously Treated (6 Weeks Washout) Type 2 Diabetic Patients With Insufficient Glycemic Control
Sponsor: Boehringer Ingelheim
Study ID: NCT00621140
Sponsor ID: 1218.16
A Randomised, Double-blind, Placebo-controlled Parallel Group Efficacy and Safety Study of BI 1356 (One Dose, e.g. 5 mg), Administered Orally Once Daily Over 24 Weeks, With an Open Label Extension to 80 Weeks (Placebo Patients Switched to BI 1356), in Type 2 Diabetic Patients With Insufficient Glycaemic Control Despite Metformin Therapy
Sponsor: Boehringer Ingelheim
Study ID: NCT00601250
Sponsor ID: 1218.17
A Randomised, Double-blind, Placebo-controlled Parallel Group Efficacy and Safety Study of BI 1356 (5 mg) Administered Orally Once Daily Over 24 Weeks, With an Open-label Extension to One Year (Placebo Patients Switched to BI 1356), in Type 2 Diabetic Patients With Insufficient Glycaemic Control Despite a Therapy of Metformin in Combination With a Sulphonylurea
Sponsor: Boehringer Ingelheim
Study ID: NCT00602472
Sponsor ID: 1218.18
A Phase III Double-blind, Extension, Placebo-controlled Parallel Group Safety and Efficacy Trial of BI 10773 (10 and 25mg Once Daily) and Sitagliptin (100mg Once Daily) Given for Minimum 76 Weeks (Incl. 24 Weeks of Preceding Trial) as Monotherapy or With Different Back-ground Therapies in Patients With Type 2 Diabetes Mellitus Previously Completing Trial 1245.19, 1245.20 or 1245.23
Sponsor: Boehringer Ingelheim
Study ID: NCT01289990
Sponsor ID: 1245.31
A Phase III Randomised, Double-blind, Active-controlled Parallel Group Efficacy and Safety Study of BI 10773 Compared to Glimepiride Administered Orally During 104 Weeks With a 104 Week Extension Period in Patients With Type 2 Diabetes Mellitus and Insufficient Glycaemic Control Despite Metformin Treatment
Sponsor: Boehringer Ingelheim
Study ID: NCT01167881
Sponsor ID: 1245.28
A Randomised Double-blind, Active-controlled Parallel Group Efficacy and Safety Study of BI 1356 ( 5.0 mg, Administered Orally Once Daily) Compared to Glimepiride Over Two Years in Type 2 Diabetic Patients With Insufficient Glycaemic Control Despite Metformin Therapy
Sponsor: Boehringer Ingelheim
Study ID: NCT00622284
Sponsor ID: 1218.20
A Multicenter, Randomized, Double-Blind, Placebo-Controlled Study to Evaluate Cardiovascular Outcomes Following Treatment With Alogliptin in Addition to Standard of Care in Subjects With Type 2 Diabetes and Acute Coronary Syndrome (EXAMINE)
Sponsor: Takeda
Study ID: NCT00968708
Sponsor ID: SYR-322_402
A Multicenter, Randomized, Double-Blind, Active-Controlled Study to Evaluate the Durability of the Efficacy and Safety of Alogliptin Compared to Glipizide When Used in Combination With Metformin in Subjects With Type 2 Diabetes (ENDURE)
Sponsor: Takeda
Study ID: NCT00856284
Sponsor ID: SYR-322_305
Public Disclosures:
Dennis, J.M., Young, K.G., McGovern, A.P., Mateen, B.A., Vollmer, S.J., Simpson, M.D., Henley, W.E., Holman, R.R., Sattar, N., Pearson, E.R. and Hattersley, A.T., 2022. Development of a treatment selection algorithm for SGLT2 and DPP-4 inhibitor therapies in people with type 2 diabetes: a retrospective cohort study. The Lancet Digital Health, 4(12), pp.e873-e883. doi: 10.1016/S2589-7500(22)00174-1