• Implementing stakeholder engagement to explore alternative models of consent: An example from the PREP-IT trials

      Pechero, Guillermo; Pfaff, Branden; Rao, Mayank; Pogorzelski, David; McKay, Paula; Spicer, Ella; Howe, Andrea; Demyanovich, Haley K; Sietsema, Debra L; McTague, Michael F; et al. (Elsevier Ltd., 2021-06-14)
      Introduction: Cluster randomized crossover trials are often faced with a dilemma when selecting an optimal model of consent, as the traditional model of obtaining informed consent from participant's before initiating any trial related activities may not be suitable. We describe our experience of engaging patient advisors to identify an optimal model of consent for the PREP-IT trials. This paper also examines surrogate measures of success for the selected model of consent. Methods: The PREP-IT program consists of two multi-center cluster randomized crossover trials that engaged patient advisors to determine an optimal model of consent. Patient advisors and stakeholders met regularly and reached consensus on decisions related to the trial design including the model for consent. Patient advisors provided valuable insight on how key decisions on trial design and conduct would be received by participants and the impact these decisions will have. Results: Patient advisors, together with stakeholders, reviewed the pros and cons and the requirements for the traditional model of consent, deferred consent, and waiver of consent. Collectively, they agreed upon a deferred consent model, in which patients may be approached for consent after their fracture surgery and prior to data collection. The consent rate in PREP-IT is 80.7%, and 0.67% of participants have withdrawn consent for participation. Discussion: Involvement of patient advisors in the development of an optimal model of consent has been successful. Engagement of patient advisors is recommended for other large trials where the traditional model of consent may not be optimal.
    • Patiromer for the management of hyperkalaemia in patients receiving renin-angiotensin-aldosterone system inhibitors for heart failure: design and rationale of the DIAMOND trial.

      Butler, Javed; Anker, Stefan D; Siddiqi, Tariq Jamal; Coats, Andrew J S; Dorigotti, Fabio; Filippatos, Gerasimos; Friede, Tim; Göhring, Udo-Michael; Kosiborod, Mikhail N; Lund, Lars H; et al. (John Wiley and Sons Inc., 2021-11-20)
      Aims: In patients with current or a history of hyperkalaemia, treatment with renin–angiotensin–aldosterone system inhibitors (RAASi) is often compromised. Patiromer, a novel potassium (K+) binder, may improve serum K+ levels and adherence to RAASi. Methods: The DIAMOND trial will enroll ∼820 patients with heart failure with reduced ejection fraction (HFrEF; ejection fraction ≤40%). Patients meeting the screening criteria will enter a single-blinded run-in phase where they will be started or continued on a mineralocorticoid receptor antagonist (MRA) titrated to 50 mg/day and other RAASi therapy to ≥50% target dose, and patiromer. Patiromer will be titrated up to a maximum three packs/day (8.4 g/pack) to achieve optimal doses of RAASi without hyperkalaemia. The run-in phase will last up to 12 weeks, following which patients will undergo double-blind randomization in a 1:1 ratio to receive either continued patiromer or placebo (patiromer withdrawal). The primary endpoint is the mean difference in serum K+ from randomization between patiromer and placebo arms. Secondary endpoints will include hyperkalaemia events with K+ value >5.5 mEq/L, durable enablement of MRA at target dose, investigator-reported adverse events of hyperkalaemia, hyperkalaemia-related clinical endpoints and an overall RAASi use score (using a 0–8-point scale) comprising all-cause death, occurrence of cardiovascular hospitalization or usage of comprehensive heart failure medication. Conclusion: The DIAMOND trial is designed to determine if patiromer can favourably impact K+ control in patients with HFrEF with hyperkalaemia or a history of hyperkalaemia leading to RAASi therapy compromise, and in turn improve RAASi use. © 2021 The Authors.