The REFRACT trial: implementation of Bayesian power priors in a randomised, sequential phase II adaptive platform trial
Abstract Background REFRACT is a randomised trial aimed at rapidly evaluating multiple novel therapies against standard treatment for relapsed or refractory follicular lymphoma (rrFL) using a minimal number of patients. To this end, we designed a prospective, adaptive, sequentially randomised clinic...
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2025-05-01
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| Online Access: | https://doi.org/10.1186/s12874-025-02575-5 |
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| author | Charlotte Gaskell Kim Linton Mark Bishton Graham McIlroy Siân Lax Sonia Fox Louise Hopkins Rebecca Collings Malcolm Rhodes Tania Seale Aimee Jackson |
| author_facet | Charlotte Gaskell Kim Linton Mark Bishton Graham McIlroy Siân Lax Sonia Fox Louise Hopkins Rebecca Collings Malcolm Rhodes Tania Seale Aimee Jackson |
| author_sort | Charlotte Gaskell |
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| description | Abstract Background REFRACT is a randomised trial aimed at rapidly evaluating multiple novel therapies against standard treatment for relapsed or refractory follicular lymphoma (rrFL) using a minimal number of patients. To this end, we designed a prospective, adaptive, sequentially randomised clinical trial to allow multiple novel therapies to be assessed sequentially against a control arm of investigator choice standard therapy (ICT). Methods REFRACT uses a Bayesian power priors approach enabling the sharing of control arm data from previous treatment rounds. The design allows for the randomisation ratio to be changed and fixed to 1:4 in later treatment rounds resulting in fewer patients being recruited to the control arm. Results Following extensive simulations, we arrived at the selected design of three sequential treatment rounds, each with a control group and a novel experimental arm assessed for the primary outcome of complete metabolic response (CMR) at 24 weeks. Patients in Round 1 are randomised using a 1:1 allocation, with Rounds 2 and 3 randomised using a 1:4 allocation, in favour of experimental treatment. Using Bayesian power priors, data from control patients in earlier rounds will be shared to improve the operating characteristics in the current round. Previous control arm patients will be weighted at 75% of an active control patient within the prior, with opportunities for adjustment should control treatments change over time. Conclusions With the use of power priors and an adaptive design this trial will sequentially evaluate three novel treatment regimens in a disease that urgently requires additional treatment options. REFRACT opened to recruitment in July 2023. Trial registration EudraCT: 2022–000677-75; 10-Feb-2022. ClinicalTrials.gov: NCT05848765; 08-May-2023. |
| format | Article |
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| language | English |
| publishDate | 2025-05-01 |
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| series | BMC Medical Research Methodology |
| spelling | doaj-art-e36f545192ac487fae099d043a983e562025-08-20T02:10:56ZengBMCBMC Medical Research Methodology1471-22882025-05-012511810.1186/s12874-025-02575-5The REFRACT trial: implementation of Bayesian power priors in a randomised, sequential phase II adaptive platform trialCharlotte Gaskell0Kim Linton1Mark Bishton2Graham McIlroy3Siân Lax4Sonia Fox5Louise Hopkins6Rebecca Collings7Malcolm Rhodes8Tania Seale9Aimee Jackson10Cancer Research UK Clinical Trials Unit, University of BirminghamDepartment of Medical Oncology, The Christie NHS Foundation TrustTranslational Medical Sciences, University of NottinghamCancer Research UK Clinical Trials Unit, University of BirminghamCancer Research UK Clinical Trials Unit, University of BirminghamCancer Research UK Clinical Trials Unit, University of BirminghamCancer Research UK Clinical Trials Unit, University of BirminghamCancer Research UK Clinical Trials Unit, University of BirminghamPatient advocate, National Cancer Research InstituteDivision of Cancer Sciences, Wolfson Molecular Imaging Centre, The University of ManchesterCancer Research UK Clinical Trials Unit, University of BirminghamAbstract Background REFRACT is a randomised trial aimed at rapidly evaluating multiple novel therapies against standard treatment for relapsed or refractory follicular lymphoma (rrFL) using a minimal number of patients. To this end, we designed a prospective, adaptive, sequentially randomised clinical trial to allow multiple novel therapies to be assessed sequentially against a control arm of investigator choice standard therapy (ICT). Methods REFRACT uses a Bayesian power priors approach enabling the sharing of control arm data from previous treatment rounds. The design allows for the randomisation ratio to be changed and fixed to 1:4 in later treatment rounds resulting in fewer patients being recruited to the control arm. Results Following extensive simulations, we arrived at the selected design of three sequential treatment rounds, each with a control group and a novel experimental arm assessed for the primary outcome of complete metabolic response (CMR) at 24 weeks. Patients in Round 1 are randomised using a 1:1 allocation, with Rounds 2 and 3 randomised using a 1:4 allocation, in favour of experimental treatment. Using Bayesian power priors, data from control patients in earlier rounds will be shared to improve the operating characteristics in the current round. Previous control arm patients will be weighted at 75% of an active control patient within the prior, with opportunities for adjustment should control treatments change over time. Conclusions With the use of power priors and an adaptive design this trial will sequentially evaluate three novel treatment regimens in a disease that urgently requires additional treatment options. REFRACT opened to recruitment in July 2023. Trial registration EudraCT: 2022–000677-75; 10-Feb-2022. ClinicalTrials.gov: NCT05848765; 08-May-2023.https://doi.org/10.1186/s12874-025-02575-5BayesianPower priorsTrial designNovel therapiesFollicular lymphoma |
| spellingShingle | Charlotte Gaskell Kim Linton Mark Bishton Graham McIlroy Siân Lax Sonia Fox Louise Hopkins Rebecca Collings Malcolm Rhodes Tania Seale Aimee Jackson The REFRACT trial: implementation of Bayesian power priors in a randomised, sequential phase II adaptive platform trial BMC Medical Research Methodology Bayesian Power priors Trial design Novel therapies Follicular lymphoma |
| title | The REFRACT trial: implementation of Bayesian power priors in a randomised, sequential phase II adaptive platform trial |
| title_full | The REFRACT trial: implementation of Bayesian power priors in a randomised, sequential phase II adaptive platform trial |
| title_fullStr | The REFRACT trial: implementation of Bayesian power priors in a randomised, sequential phase II adaptive platform trial |
| title_full_unstemmed | The REFRACT trial: implementation of Bayesian power priors in a randomised, sequential phase II adaptive platform trial |
| title_short | The REFRACT trial: implementation of Bayesian power priors in a randomised, sequential phase II adaptive platform trial |
| title_sort | refract trial implementation of bayesian power priors in a randomised sequential phase ii adaptive platform trial |
| topic | Bayesian Power priors Trial design Novel therapies Follicular lymphoma |
| url | https://doi.org/10.1186/s12874-025-02575-5 |
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