Dataset Information

Clinical and MRI activity as determinants of sample size for pediatric multiple sclerosis trials.

ABSTRACT:

Objective

To estimate sample sizes for pediatric multiple sclerosis (MS) trials using new T2 lesion count, annualized relapse rate (ARR), and time to first relapse (TTFR) endpoints.

Methods

Poisson and negative binomial models were fit to new T2 lesion and relapse count data, and negative binomial time-to-event and exponential models were fit to TTFR data of 42 children with MS enrolled in a national prospective cohort study. Simulations were performed by resampling from the best-fitting model of new T2 lesion count, number of relapses, or TTFR, under various assumptions of the effect size, trial duration, and model parameters.

Results

Assuming a 50% reduction in new T2 lesions over 6 months, 90 patients/arm are required, whereas 165 patients/arm are required for a 40% treatment effect. Sample sizes for 2-year trials using relapse-related endpoints are lower than that for 1-year trials. For 2-year trials and a conservative assumption of overdispersion (?), sample sizes range from 70 patients/arm (using ARR) to 105 patients/arm (TTFR) for a 50% reduction in relapses, and 230 patients/arm (ARR) to 365 patients/arm (TTFR) for a 30% relapse reduction. Assuming a less conservative ?, 2-year trials using ARR require 45 patients/arm (60 patients/arm for TTFR) for a 50% reduction in relapses and 145 patients/arm (200 patients/arm for TTFR) for a 30% reduction.

Conclusion

Six-month phase II trials using new T2 lesion count as an endpoint are feasible in the pediatric MS population; however, trials powered on ARR or TTFR will need to be 2 years in duration and will require multicentered collaboration.

SUBMITTER: Verhey LH

PROVIDER: S-EPMC3795606 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Publications

Clinical and MRI activity as determinants of sample size for pediatric multiple sclerosis trials.

Verhey Leonard H LH Signori Alessio A Arnold Douglas L DL Bar-Or Amit A Sadovnick A Dessa AD Marrie Ruth Ann RA Banwell Brenda B Sormani Maria Pia MP

Neurology 20130821 14

<h4>Objective</h4>To estimate sample sizes for pediatric multiple sclerosis (MS) trials using new T2 lesion count, annualized relapse rate (ARR), and time to first relapse (TTFR) endpoints.<h4>Methods</h4>Poisson and negative binomial models were fit to new T2 lesion and relapse count data, and negative binomial time-to-event and exponential models were fit to TTFR data of 42 children with MS enrolled in a national prospective cohort study. Simulations were performed by resampling from the best- ...[more]

PMID: 23966255

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Project description:BACKGROUND:Multi-centre randomized controlled clinical trials play an important role in modern evidence-based medicine. Advantages of collecting data from more than one site are numerous, including accelerated recruitment and increased generalisability of results. Mixed models can be applied to account for potential clustering in the data, in particular when many small centres contribute patients to the study. Previously proposed methods on sample size calculation for mixed models only considered balanced treatment allocations which is an unlikely outcome in practice if block randomisation with reasonable choices of block length is used. METHODS:We propose a sample size determination procedure for multi-centre trials comparing two treatment groups for a continuous outcome, modelling centre differences using random effects and allowing for arbitrary sample sizes. It is assumed that block randomisation with fixed block length is used at each study site for subject allocation. Simulations are used to assess operation characteristics such as power of the sample size approach. The proposed method is illustrated by an example in disease management systems. RESULTS:A sample size formula as well as a lower and upper boundary for the required overall sample size are given. We demonstrate the superiority of the new sample size formula over the conventional approach of ignoring the multi-centre structure and show the influence of parameters such as block length or centre heterogeneity. The application of the procedure on the example data shows that large blocks require larger sample sizes, if centre heterogeneity is present. CONCLUSION:Unbalanced treatment allocation can result in substantial power loss when centre heterogeneity is present but not considered at the planning stage. When only few patients by centre will be recruited, one has to weigh the risk of imbalance between treatment groups due to large blocks and the risk of unblinding due to small blocks. The proposed approach should be considered when planning multi-centre trials.

Dataset Information

Clinical and MRI activity as determinants of sample size for pediatric multiple sclerosis trials.

Objective

Methods

Results

Conclusion

Publications

Clinical and MRI activity as determinants of sample size for pediatric multiple sclerosis trials.

Similar Datasets

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