Patient preference for second- and third-line therapies in type 2 diabetes: a prespecified secondary endpoint of the TriMaster study

Beverley M. Shields, Catherine D. Angwin, Maggie H. Shepherd, Nicky Britten, Angus G. Jones, Naveed Sattar, Rury Holman, Ewan R. Pearson, Andrew T. Hattersley (Lead / Corresponding author)

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)
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Patient preference is very important for medication selection in chronic medical conditions, like type 2 diabetes, where there are many different drugs available. Patient preference balances potential efficacy with potential side effects. As both aspects of drug response can vary markedly between individuals, this decision could be informed by the patient personally experiencing the alternative medications, as occurs in a crossover trial. In the TriMaster (NCT02653209, ISRCTN12039221), randomized double-blind, three-way crossover trial patients received three different second- or third-line once-daily type 2 diabetes glucose-lowering drugs (pioglitazone 30 mg, sitagliptin 100 mg and canagliflozin 100 mg). As part of a prespecified secondary endpoint, we examined patients’ drug preference after they had tried all three drugs. In total, 448 participants were treated with all three drugs which overall showed similar glycemic control (HbA1c on pioglitazone 59.5 sitagliptin 59.9, canagliflozin 60.5 mmol mol−1, P = 0.19). In total, 115 patients (25%) preferred pioglitazone, 158 patients (35%) sitagliptin and 175 patients (38%) canagliflozin. The drug preferred by individual patients was associated with a lower HbA1c (mean: 4.6; 95% CI: 3.9, 5.3) mmol mol−1 lower versus nonpreferred) and fewer side effects (mean: 0.50; 95% CI: 0.35, 0.64) fewer side effects versus nonpreferred). Allocating therapy based on the individually preferred drugs, rather than allocating all patients the overall most preferred drug (canagliflozin), would result in more patients achieving the lowest HbA1c for them (70% versus 30%) and the fewest side effects (67% versus 50%). When precision approaches do not predict a clear optimal therapy for an individual, allowing patients to try potential suitable medications before they choose long-term therapy could be a practical alternative to optimizing treatment for type 2 diabetes.
Original languageEnglish
Pages (from-to)384–391
Number of pages8
JournalNature Medicine
Early online date7 Dec 2022
Publication statusPublished - Feb 2023


  • Randomized controlled trials
  • Type 2 diabetes

ASJC Scopus subject areas

  • General Biochemistry,Genetics and Molecular Biology


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