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Rain dance: the role of randomization in clinical trials

Authors Diniz JB, Fossaluza V, Pereira CAB, Wechsler S

Received 12 November 2015

Accepted for publication 26 January 2016

Published 13 July 2016 Volume 2016:8 Pages 21—32


Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr RaghunadhaReddy Seelam

Peer reviewer comments 2

Editor who approved publication: Professor Greg Martin

Video abstract presented by Juliana Belo Diniz.

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Juliana Belo Diniz,1 Victor Fossaluza,2 Carlos Alberto de Bragança Pereira,1,2 Sergio Wechsler2

1Institute of Psychiatry, Clinics Hospital University of São Paulo Medical School, 2Department of Statistics, Institute of Mathematics and Statistics, University of São Paulo, São Paulo, Brazil

Abstract: Randomized clinical trials are the gold standard for testing efficacy of treatment interventions. However, although randomization protects against deliberately biased samples, it does not guarantee random imbalances will not occur. Methods of intentional allocation that can overcome such deficiency of randomization have been developed, but are less frequently applied than randomization. Initially, we introduce a fictitious case example to revise and discuss the reasons of researchers' resistance to intentionally allocate instead of simply randomizing. We then introduce a real case example to evaluate the performance of an intentional protocol for allocation based on compositional data balance. A real case of allocation of 50 patients in two arms was compared with an optimal allocation of global instead of sequential arrivals. Performance was measured by a weighted average of Aitchison distances, between arms, of prognostic factors. To compare the intentional allocation with simple random allocation, 50,000 arrival orderings of 50 patients were simulated. To each one of the orders, both kinds of allocations into two arms were considered. Intentional allocation performed as well as optimal allocation in the case considered. In addition, out of the 50,000 simulated orders, 61% of them performed better with intentional allocation than random allocation. Hence, we conclude that intentional allocation should be encouraged in the design of future interventional clinical trials as a way to prevent unbalanced samples. Our sequential method is a viable alternative to overcome technical difficulties for study designs that require sequential inclusion of patients as it does not require prior knowledge about the total sample composition.

Keywords: randomization, intentional allocation, clinical trials, current trends, biostatistics

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