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Patient stratification for determining optimal second-line and third-line therapy for type 2 diabetes: the TriMaster study

Nature Medicine volume 29, pages 376–383 (2023)Cite this article

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Abstract

Precision medicine aims to treat an individual based on their clinical characteristics. A differential drug response, critical to using these features for therapy selection, has never been examined directly in type 2 diabetes. In this study, we tested two hypotheses: (1) individuals with body mass index (BMI) > 30 kg/m2, compared to BMI ≤ 30 kg/m2, have greater glucose lowering with thiazolidinediones than with DPP4 inhibitors, and (2) individuals with estimated glomerular filtration rate (eGFR) 60–90 ml/min/1.73 m2, compared to eGFR >90 ml/min/1.73 m2, have greater glucose lowering with DPP4 inhibitors than with SGLT2 inhibitors. The primary endpoint for both hypotheses was the achieved HbA1c difference between strata for the two drugs. In total, 525 people with type 2 diabetes participated in this UK-based randomized, double-blind, three-way crossover trial of 16 weeks of treatment with each of sitagliptin 100 mg once daily, canagliflozin 100 mg once daily and pioglitazone 30 mg once daily added to metformin alone or metformin plus sulfonylurea. Overall, the achieved HbA1c was similar for the three drugs: pioglitazone 59.6 mmol/mol, sitagliptin 60.0 mmol/mol and canagliflozin 60.6 mmol/mol (P = 0.2). Participants with BMI > 30 kg/m2, compared to BMI ≤ 30 kg/m2, had a 2.88 mmol/mol (95% confidence interval (CI): 0.98, 4.79) lower HbA1c on pioglitazone than on sitagliptin (n = 356, P = 0.003). Participants with eGFR 60–90 ml/min/1.73 m2, compared to eGFR >90 ml/min/1.73 m2, had a 2.90 mmol/mol (95% CI: 1.19, 4.61) lower HbA1c on sitagliptin than on canagliflozin (n = 342, P = 0.001). There were 2,201 adverse events reported, and 447/525 (85%) randomized participants experienced an adverse event on at least one of the study drugs. In this precision medicine trial in type 2 diabetes, our findings support the use of simple, routinely available clinical measures to identify the drug class most likely to deliver the greatest glycemic reduction for a given patient. (ClinicalTrials.gov registration: NCT02653209; ISRCTN registration: 12039221.)

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Fig. 1: Study design for the TriMaster three-treatment, three-period crossover trial of pioglitazone, sitagliptin and canagliflozin.
Fig. 2: The two main hypotheses being tested in TriMaster.
Fig. 3: Trial profile (CONSORT diagram): patient flow through the stages of the crossover trial and eligibility for primary analysis.
Fig. 4: Effect of stratification on treatment response.

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Data availability

To minimize the risk of patient re-identification, de-identified individual patient-level clinical data are available under restricted access. Requests for access to anonymized individual participant data and study documents should be made to the corresponding author and will be reviewed by the Peninsula Research Bank Steering Committee. Access to data through the Peninsula Research Bank will be granted for requests with scientifically valid questions by academic teams with the necessary skills appropriate for the research. Data that can be shared will be released with the relevant transfer agreement.

Code availability

Requests for access to code should be made to the corresponding author and will be reviewed by the Peninsula Research Bank Steering Committee. Access to code through the Peninsula Research Bank will be granted for requests with scientifically valid questions by academic teams with the necessary skills appropriate for the research. Code will be released by the lead statistician.

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Acknowledgements

We thank all study participants. We gratefully acknowledge the TriMaster central coordinating team, all members of the TriMaster study group, the MASTERMIND consortium, the Data Monitoring Committee and the Trial Steering Committee (Supplementary Information). In particular, we thank S. Senn for invaluable guidance on the analysis for this trial. In addition, we thank the Exeter NIHR Clinical Research Facility and the Exeter Clinical Trials Unit (CTU), particularly L. Quinn and S. Creanor, for their support with the study, and the CTU Data Team. We thank A. Kerridge and S. Todd of the R&D and Pharmacy Departments at the Royal Devon and Exeter NHS Foundation Trust for support and sponsorship.

This trial is part of the MASTERMIND (MRC APBI Stratification and Extreme Response Mechanism in Diabetes) consortium and is supported by UK Medical Research Council study grant number MR/N00633X/1 (B.M., J.D., C.A., W.H., A.F., N.S., R.H., A.J., E.P. and A.H.). The TriMaster trial was supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre and the National Institute for Health and Care Research Exeter Clinical Research Facility. The funders had no role in study design, data collection, data analysis, data interpretation, decision to publish or preparation of the manuscript. The views expressed are those of the author(s) and not necessarily those of the MRC, the NIHR or the Department of Health and Social Care. For the purpose of open access, the corresponding author has applied a Creative Commons Attribution (CC BY) license to any Author Accepted Manuscript version arising.

Author information

Authors and Affiliations

  1. Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK

    Beverley M. Shields, John M. Dennis, Catherine D. Angwin, Angus G. Jones & Andrew T. Hattersley

  2. Clinical Trials Unit, University of Exeter Medical School, Exeter, UK

    Fiona Warren

  3. Institute of Health Research, University of Exeter Medical School, Exeter, UK

    Fiona Warren & William E. Henley

  4. Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK

    Andrew J. Farmer

  5. School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, UK

    Naveed Sattar

  6. Diabetes Trials Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, UK

    Rury R. Holman

  7. Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK

    Ewan R. Pearson

Authors
  1. Beverley M. Shields
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Consortia

TriMaster Study group

  • Beverley M. Shields
  • , John M. Dennis
  • , Catherine D. Angwin
  • , Fiona Warren
  • , William E. Henley
  • , Andrew J. Farmer
  • , Naveed Sattar
  • , Rury R. Holman
  • , Angus G. Jones
  • , Ewan R. Pearson
  •  & Andrew T. Hattersley

Contributions

B.S. helped design the study, wrote the Statistical Analysis Plan, performed analysis and drafted the manuscript. J.D. discussed the results and helped write the manuscript. C.A. was the trial manager and helped design the study and edited the manuscript. F.W. was the second analyst for the trial and edited the manuscript. W.H. helped design the study, advised on the Statistical Analysis Plan and edited the manuscript. N.B. advised on design of the patient preference questionnaires and edited the manuscript. A.J.F. advised on study design and edited the manuscript. N.S. advised on study design and edited the manuscript. R.H. advised on study design and statistical analysis and edited the manuscript. A.J. advised on study design and edited the manuscript. E.P. helped design the study and edited the manuscript. A.H. was Chief Investigator on the study, led the study design, advised on analysis and edited the manuscript.

Corresponding author

Correspondence to Andrew T. Hattersley.

Ethics declarations

Competing interests

N.S. is supported by a BHF Centre of Excellence Award (RE/18/6/34217). R.H. is an Emeritus National Institute for Health Research Senior Investigator. A.H. is a Wellcome Senior Investigator (098395/Z/12/Z) and a Senior Investigator at the NIHR. A.H., B.S., A.J. and C.A. are supported by the NIHR Exeter Clinical Research Facility. A.H., B.S., J.D., A.G. and C.A. are supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre. A.F. receives support from the NIHR Oxford Biomedical Research Centre. E.P. has received honoraria from Eli Lilly, Sanofi and Illumina. N.S. has consulted for and/or received speaker honoraria from Abbott Laboratories, Afimmune, Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Hanmi Pharmaceuticals, Janssen, Merck Sharp & Dohme, Novo Nordisk, Novartis, Sanofi and Pfizer and received grant funding paid to his university from AstraZeneca, Boehringer Ingelheim, Novartis and Roche Diagnostics. R.R.H. reports research support from AstraZeneca, Bayer and Merck Sharp & Dohme and personal fees from Anji Pharmaceuticals, AstraZeneca, Novartis and Novo Nordisk. W.H. has received grant funding from IQVIA and travel funds from Eisai. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Medicine thanks Ronald Ma, Victor Volovici, Nisa Maruthur and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary handling editor: Jennifer Sargent, in collaboration with the Nature Medicine team.

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Extended data

Extended Data Fig. 1

Distribution of side effects experienced on each of the three study drugs (pioglitazone represented by blue bars, sitagliptin by yellow bars, and canagliflozin by red bars) for all instances where people tried the therapy (n = 469 pioglitazone, n = 474 sitagliptin, n = 474 canagliflozin). Proportions experiencing the side effects at baseline shown by black bars.

Extended Data Fig. 2

Scatterplots showing a) difference in on-treatment HbA1c between pioglitazone and sitagliptin (negative values favour pioglitazone, positive values favour sitagliptin) against BMI, and b) difference in on-treatment HbA1c between sitagliptin and canagliflozin (negative values favour sitagliptin, positive values favour canagliflozin) against eGFR. Line of best fit shown for each plot.

Extended Data Table 1 Five components of the estimand for both study hypotheses
Full size table
Extended Data Table 2 Primary analysis hypothesis 1. Absolute unadjusted values for HbA1c on pioglitazone and sitagliptin split by BMI strata and the corresponding mean difference between drugs, and between strata. P value assessed by a t test comparing the difference between drugs between strata. *negative values favour pioglitazone
Full size table
Extended Data Table 3 Primary analysis hypothesis 2. Absolute unadjusted values for HbA1c on sitagliptin and canagliflozin split by eGFR strata and the corresponding mean difference between drugs, and between strata. P value assessed by a t test comparing the difference between drugs between strata. *negative values favour sitagliptin
Full size table
Extended Data Table 4 Tolerability by Hypothesised Drug/Strata combinations. Proportions tolerating therapy (remaining on therapy for at least 12 weeks) for each of the drug/strata combinations
Full size table
Extended Data Table 5 Side effects by Hypothesised Drug/Strata Combinations. Proportions experiencing at least one side effect for each of the hypothesised drug/strata combinations
Full size table
Extended Data Table 6 Weight difference by drug and strata. P value assessed by a t test comparing the difference between drugs between strata
Full size table
Extended Data Table 7 Hypoglycemia by hypothesised drug/strata combinations. Proportions experiencing hypoglycemia for each of the hypothesised drug/strata combinations
Full size table
Extended Data Table 8 Protocol Amendments in the TriMaster randomised three way crossover trial
Full size table

Supplementary information

Supplementary Information

Supplementary Tables 1–21 and Supplementary Information

Reporting Summary

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Shields, B.M., Dennis, J.M., Angwin, C.D. et al. Patient stratification for determining optimal second-line and third-line therapy for type 2 diabetes: the TriMaster study. Nat Med 29, 376–383 (2023). https://doi.org/10.1038/s41591-022-02120-7

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