Literature DB >> 32764219

Comparisons of Within-Group Instead of Between-Group Affect the Conclusions. Comment on: "Changes in Weight and Substrate Oxidation in Overweight Adults Following Isomaltulose Intake during a 12-Week Weight Loss Intervention: A Randomized, Double-Blind, Controlled Trial". Nutrients 2019, 11(10), 2367.

Colby J Vorland1, Theodore K Kyle2, Andrew W Brown1.   

Abstract

We read with interest the publication by Lightowler et al [...].

Entities:  

Keywords:  differences in nominal significance; methods; spin

Mesh:

Substances:

Year:  2020        PMID: 32764219      PMCID: PMC7468752          DOI: 10.3390/nu12082335

Source DB:  PubMed          Journal:  Nutrients        ISSN: 2072-6643            Impact factor:   5.717


We read with interest the publication by Lightowler et al., who concluded that the inclusion of isomaltulose in the context of an energy-reduced diet reduced weight and fat mass to a greater extent than sucrose [1]. We praise the authors for their use of blinding, randomization, and power calculation in their study to enhance the rigor of the experiment. Unfortunately, there are errors in the statistical conduct and interpretation that do not support these conclusions. In the abstract, the authors write: “During the 12 weeks, both groups significantly lost weight (p < 0.001), which was more pronounced following [isomaltulose] (−3.2 ± 2.9 vs. −2.1 ± 2.6 kg; )” [1] [emphasis added]. The discussion also notes that “…consumption of [isomaltulose] compared to that of [sucrose] was more effective at promoting weight loss”. The authors stated in their methods that statistical significance was set at p < 0.05, so by the authors’ own designation, the effect on weight loss of isomaltulose was not statistically different from that of sucrose. Highlighting a beneficial effect despite a nonsignificant difference is a reporting strategy that is classified as “spin” [2]. Furthermore, throughout the paper, some conclusions about the differences between groups are made from within-group instead of between-group statistical tests, which is called a differences in nominal significance (DINS) error [3] and results in inflated type 1 error rates [4,5]. An example of this appears in the abstract: “Moreover, for participants in the [isomaltulose] group, this was accompanied by a significant reduction in fat mass ([isomaltulose]: −1.9 ± 2.5, p = 0.005; [sucrose]: −0.9 ± 2.6%, p = 0.224)” [1]. In the results, the between-group p-value is noted as p = 0.169, again not meeting the authors’ declared threshold for the appropriate between-group comparison. Although there is much debate about whether to use a cutoff for statistical significance [6,7], the two examples discussed above do not provide strong evidence that these data are incompatible with the model under the null hypothesis of there being no difference between the groups. It is also inappropriate to solely use the differences between sample means to declare a meaningful difference between groups without accounting for the variability in those estimates [8]. Fortunately, the errors we address herein are not from the structure of the study and can therefore be easily addressed by clarifying the interpretation of the results with a corrigendum.
  7 in total

1.  Reporting and interpretation of randomized controlled trials with statistically nonsignificant results for primary outcomes.

Authors:  Isabelle Boutron; Susan Dutton; Philippe Ravaud; Douglas G Altman
Journal:  JAMA       Date:  2010-05-26       Impact factor: 56.272

2.  Best (but oft forgotten) practices: testing for treatment effects in randomized trials by separate analyses of changes from baseline in each group is a misleading approach.

Authors:  J Martin Bland; Douglas G Altman
Journal:  Am J Clin Nutr       Date:  2015-09-09       Impact factor: 7.045

3.  Scientists rise up against statistical significance.

Authors:  Valentin Amrhein; Sander Greenland; Blake McShane
Journal:  Nature       Date:  2019-03       Impact factor: 49.962

4.  Comparisons against baseline within randomised groups are often used and can be highly misleading.

Authors:  J Martin Bland; Douglas G Altman
Journal:  Trials       Date:  2011-12-22       Impact factor: 2.279

5.  Reproducibility: A tragedy of errors.

Authors:  David B Allison; Andrew W Brown; Brandon J George; Kathryn A Kaiser
Journal:  Nature       Date:  2016-02-04       Impact factor: 49.962

Review 6.  Childhood obesity intervention studies: A narrative review and guide for investigators, authors, editors, reviewers, journalists, and readers to guard against exaggerated effectiveness claims.

Authors:  Andrew W Brown; Douglas G Altman; Tom Baranowski; J Martin Bland; John A Dawson; Nikhil V Dhurandhar; Shima Dowla; Kevin R Fontaine; Andrew Gelman; Steven B Heymsfield; Wasantha Jayawardene; Scott W Keith; Theodore K Kyle; Eric Loken; J Michael Oakes; June Stevens; Diana M Thomas; David B Allison
Journal:  Obes Rev       Date:  2019-08-19       Impact factor: 9.213

7.  Changes in Weight and Substrate Oxidation in Overweight Adults Following Isomaltulose Intake During a 12-Week Weight Loss Intervention: A Randomized, Double-Blind, Controlled Trial.

Authors:  Helen Lightowler; Lisa Schweitzer; Stephan Theis; Christiani Jeyakumar Henry
Journal:  Nutrients       Date:  2019-10-04       Impact factor: 5.717

  7 in total

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