Controlling Bias in Randomized Clinical Trials

Bruce A. Barton ()
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Bruce A. Barton: University of Massachusetts Medical School, Department of Population and Quantitative Health Sciences

Chapter 42 in Principles and Practice of Clinical Trials, 2022, pp 787-803 from Springer

Abstract: Abstract Clinical trials are considered to be the gold standard of research designs at the top of the evidence chain. This reputation is due to the ability to randomly allocate subjects to treatments and to mask the treatment assignment at various levels, including subject, observers taking measurements or administering questionnaires, and investigators who are overseeing the performance of the study. This chapter section deals with the five major causes of bias in clinical trials: (1) selection bias, or the biased assignment of subjects to treatment groups; (2) performance bias, or the collection of data in a way that favors one treatment group over another; (3) detection bias, or the biased detection of study outcomes (including both safety and efficacy) to favor one treatment group over another; (4) attrition bias, or differential dropout from the study in one treatment group compared to the other; and (5) reporting and publication bias, or the tendency of investigators to include only the positive results in the main results paper (regardless of what is specified in the study protocol) and the tendency of journals to publish only papers with positive results. While other biases can (and do) occur and are also described here, they tend to have lower impact on the integrity of the study. The definitions of these biases will be presented, along with how to proactively prevent them through study design and procedures.

Keywords: Treatment randomization; Treatment masking; Selection bias; Performance bias; Detection bias; Attrition bias; Reporting bias (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-3-319-52636-2_214

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