A comparative study of restricted randomization procedures for multiarm trials with equal or unequal treatment allocation ratios

Ryeznik, Yevgen; Sverdlov, Oleksandr

doi:10.1002/sim.7817

Cited by 22 publications

(27 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The power of rejecting H 02 in the presence of no trend or a step trend with a magnitude of λ > 0 standard deviation (row-wise); x-axis indicates the value of n 22 and the timing of adding the new arm consistent with the finding of Ryeznik and Sverdlov[17] who compare different randomization procedures in the context of the standard ANOVA F-test.…”

mentioning

confidence: 65%

“…The literature on other trial adaptations such as dropping arms and changing treatment allocation ratio are more comprehensive [6][7][8][9][10][11]. In particular, many have explored the presence of time trends when more complex randomization procedures are recommended/ explored [12][13][14][15][16][17][18][19][20][21]. A trend may be present in a trial when there is a learning curve among the study personnel; a shift in the population baseline characteristics; and/ or the effect of the control treatment may change due to other reasons (e.g.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Including non-concurrent control patients in the analysis of platform trials: is it worth it?

Lee

Wason

2020

BMC Med Res Methodol

View full text Add to dashboard Cite

Background: Platform trials allow adding new experimental treatments to an ongoing trial. This feature is attractive to practitioners due to improved efficiency. Nevertheless, the operating characteristics of a trial that adds arms have not been well-studied. One controversy is whether just the concurrent control data (i.e. of patients who are recruited after a new arm is added) should be used in the analysis of the newly added treatment(s), or all control data (i.e. non-concurrent and concurrent). Methods: We investigate the benefits and drawbacks of using non-concurrent control data within a two-stage setting. We perform simulation studies to explore the impact of a linear and a step trend on the inference of the trial. We compare several analysis approaches when one includes all the control data or only concurrent control data in the analysis of the newly added treatment. Results: When there is a positive trend and all the control data are used, the marginal power of rejecting the corresponding hypothesis and the type one error rate can be higher than the nominal value. A model-based approach adjusting for a stage effect is equivalent to using concurrent control data; an adjustment with a linear term may not guarantee valid inference when there is a non-linear trend. Conclusions: If strict error rate control is required then non-concurrent control data should not be used; otherwise it may be beneficial if the trend is sufficiently small. On the other hand, the root mean squared error of the estimated treatment effect can be improved through using non-concurrent control data.

show abstract

mentioning

confidence: 65%

Section: Introductionmentioning

confidence: 99%

Including non-concurrent control patients in the analysis of platform trials: is it worth it?

Lee

Wason

2020

BMC Med Res Methodol

View full text Add to dashboard Cite

show abstract

“…During the first year of recruitment (2012), programs were randomized using a 1:1 ratio of UC/wave 2 AIM HI to wave 1 AIM HI. Based on an imbalance in the mean number of participants enrolled in UC/wave 2 vs AIM HI wave 1 during the first year, we switched to a restricted randomization approach 34,35 for subsequent years. Specifically, the randomization ratio was recalibrated from 1:1 to 2:1, that is, 2 programs randomized to UC/wave 2 for every program randomized to wave 1 to achieve better balance in the sample size by condition.…”

Section: Methodsmentioning

confidence: 99%

Effectiveness of Training Therapists to Deliver An Individualized Mental Health Intervention for Children With ASD in Publicly Funded Mental Health Services

et al. 2019

View full text Add to dashboard Cite

IMPORTANCE Publicly funded mental health services play an important role in addressing co-occurring mental health problems in children with autism spectrum disorder (ASD); however, therapists report lacking training to effectively serve this complex population. OBJECTIVE To test the effectiveness of training community therapists in An Individualized Mental Health Intervention for ASD (AIM HI) on challenging behaviors across 18 months among children with ASD and identify moderators and mediators of any intervention effects. DESIGN, SETTING, AND PARTICIPANTS Cluster randomized trial conducted in 29 publicly funded outpatient and school-based mental health programs in southern California from 2012 to 2017. Programs were randomized to receive immediate AIM HI training or provide usual care followed by receipt of AIM HI training. Therapist participants were recruited from enrolled programs, and child participants were recruited from participant therapists' caseloads. Data were analyzed from 202 children with ASD who were aged 5 to 13 years. INTERVENTIONS The AIM HI protocol is a package of parent-mediated and child-focused strategies aimed to reduce challenging behaviors in children with ASD who are 5 to 13 years old. It was designed for delivery in publicly funded mental health services based on a systematic assessment of therapist training needs and child clinical needs. The therapist training and consultation process takes approximately 6 months and includes an introductory workshop, 11 structured consultation meetings as the therapist delivers AIM HI with a current client, and case-specific performance feedback from trainers. MAIN OUTCOMES AND MEASURES Child participants were assessed for challenging behaviors using the Eyberg Child Behavior Inventory (ECBI) and Social Skills Improvement System (SSIS) Competing Problem Behaviors scales based on parent report at baseline and at 6-month intervals for 18 months. Outcomes were analyzed using intent-to-treat models. RESULTS In total, 202 children with ASD (mean [SD] age, 9.1 [2.4] years; 170 [84.2%] male; 121 [59.9%] Latinx) were eligible, enrolled, and included in the analyses. Statistically significant group by time interactions for the ECBI Intensity (B = −0.38; P = .02) and ECBI Problem (B = −1.00; P = .005) scales were observed, with significantly larger decreases in ECBI Intensity scores in the AIM HI group (B = −1.36; P < .001) relative to the usual care group (B = −0.98; P < .001) and a significantly larger decrease in ECBI Problem scores in the AIM HI group (B = −1.22; P < .001) relative to the usual care group (B = −0.20; P = .29). Therapist fidelity moderated these intervention effects. CONCLUSIONS AND RELEVANCE The present findings support the effectiveness of training therapists to deliver the AIM HI model to children with ASD receiving publicly funded mental health services.

show abstract

“…Maximum entropy constrained balance randomization (MaxEnt): The MaxEnt procedure is an extension of Efron's biased coin design (38) to a multi-arm setting with unequal allocation (39,40). Dose assignments for eligible subjects are made sequentially.…”

Section: Doubly Adaptive Biased Coin Design (Dbcd)mentioning

confidence: 99%

“…The explicit solution to problem in Eq. (6) can be found in (40). The six described randomization procedures can be used as building blocks for constructing adaptive randomization designs.…”

Section: Doubly Adaptive Biased Coin Design (Dbcd)mentioning

confidence: 99%

Implementing Optimal Designs for Dose–Response Studies Through Adaptive Randomization for a Small Population Group

Ryeznik

Sverdlov²,

Hooker

2018

AAPS J

Self Cite

View full text Add to dashboard Cite

In dose-response studies with censored time-to-event outcomes, D-optimal designs depend on the true model and the amount of censored data. In practice, such designs can be implemented adaptively, by performing dose assignments according to updated knowledge of the dose-response curve at interim analysis. It is also essential that treatment allocation involves randomization-to mitigate various experimental biases and enable valid statistical inference at the end of the trial. In this work, we perform a comparison of several adaptive randomization procedures that can be used for implementing D-optimal designs for dose-response studies with time-to-event outcomes with small to moderate sample sizes. We consider single-stage, two-stage, and multi-stage adaptive designs. We also explore robustness of the designs to experimental (chronological and selection) biases. Simulation studies provide evidence that both the choice of an allocation design and a randomization procedure to implement the target allocation impact the quality of dose-response estimation, especially for small samples. For best performance, a multi-stage adaptive design with small cohort sizes should be implemented using a randomization procedure that closely attains the targeted D-optimal design at each stage. The results of the current work should help clinical investigators select an appropriate randomization procedure for their dose-response study.

show abstract

A comparative study of restricted randomization procedures for multiarm trials with equal or unequal treatment allocation ratios

Cited by 22 publications

References 54 publications

Including non-concurrent control patients in the analysis of platform trials: is it worth it?

Including non-concurrent control patients in the analysis of platform trials: is it worth it?

Effectiveness of Training Therapists to Deliver An Individualized Mental Health Intervention for Children With ASD in Publicly Funded Mental Health Services

Implementing Optimal Designs for Dose–Response Studies Through Adaptive Randomization for a Small Population Group

Contact Info

Product

Resources

About