The statistical challenge of analysing changes in dual energy computed tomography (DECT) urate volumes in people with gout.
Semin Arthritis Rheum
; 63: 152303, 2023 12.
Article
em En
| MEDLINE
| ID: mdl-37939600
ABSTRACT
BACKGROUND:
Dual energy computed tomography (DECT) allows direct visualization of monosodium urate crystal deposition in gout. However, DECT urate volume data are often highly skewed (mostly small volumes with the remainder considerably larger), making statistical analyses challenging in longitudinal research. The aim of this study was to explore the ability of various analysis methods to normalise DECT urate volume data and determine change in DECT urate volumes over time.METHODS:
Simulated datasets containing baseline and year 1 DECT urate volumes for 100 people with gout were created from two randomised controlled trials. Five methods were used to transform the DECT urate volume data prior toanalysis:
log-transformation, Box-Cox transformation, log(X-(min(X)-1)) transformation; inverse hyperbolic sine transformation, and rank order. Linear regression analyses were undertaken to determine the change in DECT urate volume between baseline and year 1. Cohen's d were calculated as a measure of effect size for each data treatment method. These analyses were then tested in a validation clinical trial dataset containing baseline and year 1 DECT urate volumes from 91 people with gout.RESULTS:
No data treatment method successfully normalised the distribution of DECT urate volumes. For both simulated and validation data sets, significant reductions in DECT urate volumes were observed between baseline and Year 1 across all data treatment methods and there were no significant differences in Cohen's d effect sizes.CONCLUSIONS:
Normalising highly skewed DECT urate volume data is challenging. Adopting commonly used transformation techniques may not significantly improve the ability to determine differences in measures of central tendency when comparing the change in DECT urate volumes over time.Palavras-chave
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Ácido Úrico
/
Gota
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article