Orthogonal array composite designs for drug combination experiments with applications for tuberculosis

Luna, José Manuel Cabra De; Jaynes, Jessica; Xu, Hongquan; Wong, Weng Kee

doi:10.1002/sim.9423

Cited by 4 publications

(3 citation statements)

References 37 publications

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“… 8 Finally, factorial randomisation without factorial analysis can be used where the aim is to determine which intervention combination is the best. 9 – 11 …”

Section: Introductionmentioning

confidence: 99%

“…8 Finally, factorial randomisation without factorial analysis can be used where the aim is to determine which intervention combination is the best. [9][10][11] Factorial trials have started to be used more, particularly in the field of infections where the different interventions are typically in different 'domains' of intervention. 12,13 However, we believe that factorial designs may be an under-used tool for addressing multiple questions at little extra difficulty or cost.…”

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confidence: 99%

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When should factorial designs be used for late-phase randomised controlled trials?

White,

Szubert,

Choodari-Oskooei

et al. 2023

Clinical Trials

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Background A 2×2 factorial design evaluates two interventions (A versus control and B versus control) by randomising to control, A-only, B-only or both A and B together. Extended factorial designs are also possible (e.g. 3×3 or 2×2×2). Factorial designs often require fewer resources and participants than alternative randomised controlled trials, but they are not widely used. We identified several issues that investigators considering this design need to address, before they use it in a late-phase setting. Methods We surveyed journal articles published in 2000–2022 relating to designing factorial randomised controlled trials. We identified issues to consider based on these and our personal experiences. Results We identified clinical, practical, statistical and external issues that make factorial randomised controlled trials more desirable. Clinical issues are (1) interventions can be easily co-administered; (2) risk of safety issues from co-administration above individual risks of the separate interventions is low; (3) safety or efficacy data are wanted on the combination intervention; (4) potential for interaction (e.g. effect of A differing when B administered) is low; (5) it is important to compare interventions with other interventions balanced, rather than allowing randomised interventions to affect the choice of other interventions; (6) eligibility criteria for different interventions are similar. Practical issues are (7) recruitment is not harmed by testing many interventions; (8) each intervention and associated toxicities is unlikely to reduce either adherence to the other intervention or overall follow-up; (9) blinding is easy to implement or not required. Statistical issues are (10) a suitable scale of analysis can be identified; (11) adjustment for multiplicity is not required; (12) early stopping for efficacy or lack of benefit can be done effectively. External issues are (13) adequate funding is available and (14) the trial is not intended for licensing purposes. An overarching issue (15) is that factorial design should give a lower sample size requirement than alternative designs. Across designs with varying non-adherence, retention, intervention effects and interaction effects, 2×2 factorial designs require lower sample size than a three-arm alternative when one intervention effect is reduced by no more than 24%–48% in the presence of the other intervention compared with in the absence of the other intervention. Conclusions Factorial designs are not widely used and should be considered more often using our issues to consider. Low potential for at most small to modest interaction is key, for example, where the interventions have different mechanisms of action or target different aspects of the disease being studied.

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“… 8 Finally, factorial randomisation without factorial analysis can be used where the aim is to determine which intervention combination is the best. 9 – 11 …”

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

When should factorial designs be used for late-phase randomised controlled trials?

White,

Szubert,

Choodari-Oskooei

et al. 2023

Clinical Trials

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show abstract

“…Under this setup, various design layouts has been constructed Bailey and Cameron, (2019). Luna et al, (2022) utilized 2-part design to compared the efficiencies of Orthogonal array composite designs relative to the central composite design when there are a few missing observations from one factorial point and one additional point. Karmakar et al (2023) used twopart designs in selecting the best possible components in integrated farming system that involve two groups of treatment arranged in incomplete blocks with respect to both groups, and the concurrence of treatment pairs within and between groups is constant.…”

Section: Introductionmentioning

confidence: 99%

A Study on 2-Part Balanced Incomplete Block Design

Muhammad

Garba

Muhammad

2023

USci

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Multi-part Balanced Incomplete Block Designs is a combination of many orthogonal balanced incomplete block designs in the same block. The design has been used to study cancer trials with medical centers as blocks. Various design layouts has been constructed for a restricted number of cancer types and drugs. However, parameter estimation, hypothesis testing, and model building for the constructed design layouts have not being considered. Based on the foregoing, we proposed additive model for the design (2-part Balanced Incomplete Block Designs) and estimated its parameters using the least square method. The parameter estimation precipitated to the formation of ANOVA table which paved way for the hypothesis testing procedure.

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On efficiency of locally D -optimal designs under heteroscedasticity and non-Gaussianity

Zhang,

Shen

2024

Journal of Applied Statistics

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Orthogonal array composite designs for drug combination experiments with applications for tuberculosis

Cited by 4 publications

References 37 publications

When should factorial designs be used for late-phase randomised controlled trials?

When should factorial designs be used for late-phase randomised controlled trials?

A Study on 2-Part Balanced Incomplete Block Design

On efficiency of locally D -optimal designs under heteroscedasticity and non-Gaussianity

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