| Literature DB >> 25355828 |
Karen Anthony1, Virginia Arechavala-Gomeza1, Laura E Taylor1, Adeline Vulin1, Yuuki Kaminoh1, Silvia Torelli1, Lucy Feng1, Narinder Janghra1, Gisèle Bonne1, Maud Beuvin1, Rita Barresi1, Matt Henderson1, Steven Laval1, Afrodite Lourbakos1, Giles Campion1, Volker Straub1, Thomas Voit1, Caroline A Sewry1, Jennifer E Morgan1, Kevin M Flanigan1, Francesco Muntoni2.
Abstract
OBJECTIVE: We formed a multi-institution collaboration in order to compare dystrophin quantification methods, reach a consensus on the most reliable method, and report its biological significance in the context of clinical trials.Entities:
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Year: 2014 PMID: 25355828 PMCID: PMC4248450 DOI: 10.1212/WNL.0000000000001025
Source DB: PubMed Journal: Neurology ISSN: 0028-3878 Impact factor: 9.910
Sample ranking order by laboratory
Figure 1Inter- and intralaboratory variability of dystrophin quantification using immunohistochemistry
Five laboratories each quantified the level of dystrophin expression in the same 6 biopsies using a standardized immunohistochemistry protocol; data were analyzed using the Arechavala-Gomeza method.[19] To assess interlaboratory variability, the mean ± SD for each biopsy was calculated as well as the coefficient of variation (CV). Note how this variation is higher for those samples containing less dystrophin (E and B). To assess intraassay precision within each laboratory, the mean ± SD for each laboratory per sample was calculated as well as the average CV per laboratory. Laboratories are unidentified.
Figure 2Assessing the agreement between different methods of immunohistochemical dystrophin measurement
The mean data from each method were compared in a bar chart ± SD (A) and plotted with a regression line (B). The difference between the Arechavala-Gomeza and Taylor methods was plotted against their mean in a Bland-Altman plot (C) where the mean of the differences between the methods represents the bias (i.e., the value determined by one method minus the value determined by the other method) and the upper and lower 95% confidence limits represent the upper and lower limits of agreement, respectively (the difference between the 2 methods should lie within these bounds on 95% of occasions).
Figure 3Inter- and intralaboratory variability of dystrophin quantification using Western blotting
Five laboratories each quantified the level of dystrophin expression in the same 6 biopsies using a standardized Western blotting protocol. To assess interlaboratory variability, the mean ± SD for each laboratory and biopsy was plotted on a bar chart and the average coefficient of variation (CV) per laboratory calculated. To assess intralaboratory variation, the mean ± SD for each laboratory per sample was calculated as well as the average CV per laboratory. Laboratories are unidentified.
Figure 4Assessing the agreement between immunohistochemistry and Western blotting for dystrophin quantification
The mean immunohistochemistry and Western blotting data for each biopsy were compared in a bar chart ± SD (A) and plotted with a regression line (B). The difference between the methods was plotted against their mean in a Bland-Altman plot (C) where the mean of the differences between the methods represents the bias (i.e., the value determined by one method minus the value determined by the other method) and the upper and lower 95% confidence limits represent the upper and lower limits of agreement, respectively (the difference between the 2 methods should lie within these bounds on 95% of occasions).