Statistical issues in the use of dynamic allocation methods for balancing baseline covariates

Pond, Gregory R.

doi:10.1038/bjc.2011.157

Cited by 12 publications

(12 citation statements)

References 39 publications

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“…Third, we used minimization, a dynamic allocation method that can balance known prognostic factors between treatment groups. The minimization method is gaining popularity, however, considerable controversy exists over its proper application because it might not be taken as a truly random method . Therefore, we confirmed the robustness of the primary analysis by the sensitivity analysis.…”

Section: Discussionsupporting

confidence: 64%

Clarithromycin Plus Intravenous Immunoglobulin Therapy Can Reduce the Relapse Rate of Kawasaki Disease: A Phase 2, Open‐Label, Randomized Control Study

Nanishi

Nishio

Takada

et al. 2017

JAHA

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BackgroundWe previously reported that biofilms and innate immunity contribute to the pathogenesis of Kawasaki disease. Therefore, we aimed to assess the efficacy of clarithromycin, an antibiofilm agent, in patients with Kawasaki disease.Methods and ResultsWe conducted an open‐label, multicenter, randomized, phase 2 trial at 8 hospitals in Japan. Eligible patients included children aged between 4 months and 5 years who were enrolled between days 4 and 8 of illness. Participants were randomly allocated to receive either intravenous immunoglobulin (IVIG) or IVIG plus clarithromycin. The primary end point was the duration of fever after the initiation of IVIG treatment. Eighty‐one eligible patients were randomized. The duration of the fever did not differ between the 2 groups (mean±SD, 34.3±32.4 and 31.1±31.1 hours in the IVIG plus clarithromycin group and the IVIG group, respectively [P=0.66]). The relapse rate of patients in the IVIG plus clarithromycin group was significantly lower than that in the IVIG group (12.5% versus 30.8%, P=0.046). No serious adverse events occurred during the study period. In a post hoc analysis, the patients in the IVIG plus clarithromycin group required significantly shorter mean lengths of hospital stays than those in the IVIG group (8.9 days versus 10.3 days, P=0.049).ConclusionsAlthough IVIG plus clarithromycin therapy failed to shorten the duration of fever, it reduced the relapse rate and shortened the duration of hospitalization in patients with Kawasaki disease.Clinical Trial RegistrationURL: http://www.umin.ac.jp/ctr/index.htm. Unique identifier: UMIN000015437.

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Section: Discussionsupporting

confidence: 64%

Clarithromycin Plus Intravenous Immunoglobulin Therapy Can Reduce the Relapse Rate of Kawasaki Disease: A Phase 2, Open‐Label, Randomized Control Study

Nanishi

Nishio

Takada

et al. 2017

JAHA

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“…Consequently, it is difficult to verify that the ANCOVA model is correctly specified. Re‐randomization‐based inference that follows the ‘analyze as you randomize’ principle provides an attractive alternative to standard analysis and protects against model mis‐specification . Simon first proposed the re‐randomization test for inference under minimization.…”

Section: Continuous Endpointsmentioning

confidence: 99%

Validity and power considerations on hypothesis testing under minimization

Proschan

Lee

2016

Statist. Med.

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Minimization, a dynamic allocation method, is gaining popularity especially in cancer clinical trials. Aiming to achieve balance on all important prognostic factors simultaneously, this procedure can lead to a substantial reduction in covariate imbalance compared with conventional randomization in small clinical trials. While minimization has generated enthusiasm, some controversy exists over the proper analysis of such a trial. Critics argue that standard testing methods that do not account for the dynamic allocation algorithm can lead to invalid statistical inference. Acknowledging this limitation, the International Conference on Harmonization E9 guideline suggests that 'the complexity of the logistics and potential impact on analyses be carefully evaluated when considering dynamic allocation'. In this article, we investigate the proper analysis approaches to inference in a minimization design for both continuous and time-to-event endpoints and evaluate the validity and power of these approaches under a variety of scenarios both theoretically and empirically. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

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“…In theory, matching should not introduce loss of statistical power even when performed on irrelevant covariates 34 . Since purely deterministic allocation methods have been criticized for the risk of introducing experimental biases due to, for instance, the lack of masking 36 , our constrained randomization procedure incorporated also a stochastic component, making it fully compatible with the current clinical recommendations of random allocation and balancing at baseline. The matching-based randomization approach refines all possible allocations from a single pool of individuals, and then randomly picks one of these most feasible allocation solutions.…”

Section: Methodsmentioning

confidence: 99%

Optimized design and analysis of preclinical intervention studies in vivo

Laajala

Jumppanen

Huhtaniemi

et al. 2016

Sci Rep

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Recent reports have called into question the reproducibility, validity and translatability of the preclinical animal studies due to limitations in their experimental design and statistical analysis. To this end, we implemented a matching-based modelling approach for optimal intervention group allocation, randomization and power calculations, which takes full account of the complex animal characteristics at baseline prior to interventions. In prostate cancer xenograft studies, the method effectively normalized the confounding baseline variability, and resulted in animal allocations which were supported by RNA-seq profiling of the individual tumours. The matching information increased the statistical power to detect true treatment effects at smaller sample sizes in two castration-resistant prostate cancer models, thereby leading to saving of both animal lives and research costs. The novel modelling approach and its open-source and web-based software implementations enable the researchers to conduct adequately-powered and fully-blinded preclinical intervention studies, with the aim to accelerate the discovery of new therapeutic interventions.

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Statistical issues in the use of dynamic allocation methods for balancing baseline covariates

Cited by 12 publications

References 39 publications

Clarithromycin Plus Intravenous Immunoglobulin Therapy Can Reduce the Relapse Rate of Kawasaki Disease: A Phase 2, Open‐Label, Randomized Control Study

Clarithromycin Plus Intravenous Immunoglobulin Therapy Can Reduce the Relapse Rate of Kawasaki Disease: A Phase 2, Open‐Label, Randomized Control Study

Validity and power considerations on hypothesis testing under minimization

Optimized design and analysis of preclinical intervention studies in vivo

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