scholarly journals Public availability and adherence to prespecified statistical analysis approaches was low in published randomized trials

2020 ◽  
Vol 128 ◽  
pp. 29-34 ◽  
Author(s):  
Brennan C. Kahan ◽  
Tahania Ahmad ◽  
Gordon Forbes ◽  
Suzie Cro
2001 ◽  
Vol 3 (3) ◽  
pp. 193-202 ◽  
Author(s):  
Sharon M. Hall ◽  
Kevin L. Delucchi ◽  
Wayne F. Velicer ◽  
Christopher W. Kahler ◽  
James Ranger-Moore ◽  
...  

2017 ◽  
Vol 28 (4) ◽  
pp. 1141-1156 ◽  
Author(s):  
Rob Kessels ◽  
Reagan Mozer ◽  
Jos Bloemers

The placebo serves as an indispensable control in many randomized trials. When analyzing the benefit of a new treatment, researchers are often confronted with large placebo effects that diminish the treatment effect. Various alternative methods have been proposed for analyzing placebo and treatment effects in studies where large placebo effects are expected or have already occurred. This paper presents an overview of methodological work that has been proposed for assessing and/or controlling for placebo effects in randomized trials. Throughout this paper, two main approaches are discussed. The first approach considers designs that represent alternatives to the classical placebo-controlled randomized trial design. Separately, the second approach considers adopting new methods for the statistical analysis of placebo and treatment effects to be implemented after the data have been collected using a classical randomized trial design.


2007 ◽  
Vol 25 (15) ◽  
pp. 2122-2126 ◽  
Author(s):  
Boris Freidlin ◽  
Edward L. Korn ◽  
Sally Hunsberger ◽  
Robert Gray ◽  
Scott Saxman ◽  
...  

Progression-free survival is an attractive end point for clinical trials when an overall survival end point may be confounded by additional treatments administered after progression. When a trial is performed in an unblinded manner, however, there is the potential for bias between the treatment arms because of the subjective aspects of the progression end point. We discuss the magnitude of this potential bias and suggest methods for lessening it. We propose the carrying forward of any progression information to two designated time points for the statistical analysis for trials that are not blinded. This proposal, possibly combined with central review of progression scans for these two time points, essentially eliminates any bias, with little risk of major efficiency loss compared with using the reported progression times.


2020 ◽  
Author(s):  
Suzie Cro ◽  
Gordon Forbes ◽  
Nicholas A Johnson ◽  
Brennan C Kahan

AbstractBackgroundChoosing or altering the planned statistical analysis approach after examination of trial data (often referred to as ‘p-hacking’) can bias results of randomized trials. However, the extent of this issue in practice is currently unclear. We conducted a review of published randomized trials to evaluate how often a pre-specified analysis approach is publicly available, and how often the planned analysis is changed.MethodsA review of randomised trials published between January and April 2018 in six leading general medical journals. For each trial we established whether a pre-specified analysis approach was publicly available in a protocol or statistical analysis plan, and compared this to the trial publication.ResultsOverall, 89 of 101 eligible trials (88%) had a publicly available pre-specified analysis approach. Only 22/89 trials (25%) had no unexplained discrepancies between the pre-specified and conducted analysis. Fifty-four trials (61%) had one or more unexplained discrepancies, and in 13 trials (15%) it was impossible to ascertain whether any unexplained discrepancies occurred due to incomplete reporting of the statistical methods. Unexplained discrepancies were most common for the analysis model (n=31, 35%) and analysis population (n=28, 31%), followed by the use of covariates (n=23, 26%) and the approach for handling missing data (n=16, 18%). Many protocols or statistical analysis plans were dated after the trial had begun, so earlier discrepancies may have been missed.ConclusionsUnexplained discrepancies in the statistical methods of randomized trials are common. Increased transparency is required for proper evaluation of results.


2008 ◽  
Vol 18 (4) ◽  
pp. 365-376 ◽  
Author(s):  
Scott A. Baldwin ◽  
Eric Stice ◽  
Paul Rohde

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