ArticleBMC medical research methodology2023
Researchers in rheumatology should avoid categorization of continuous predictor variables.
Article in BMC medical research methodology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Efficacy and Safety of Biosimilar CT-P47 Versus Reference Tocilizumab: 1-Year Results of a Randomised, Active-Controlled, Double-Blind, Phase III Study in Patients with Rheumatoid Arthritis.Clinical drug investigation · 2025Trial
- Autoimmune Phenotype Confirmation Intervals and Clinical Indicators in Patients With Latent Autoimmune Diabetes in Adults (LADA) in Southwest China: A Multicenter Retrospective Cross-Sectional Study.Journal of diabetes research · 2026Observational
- Individual and Comorbid Influences of Chronic Stress and a Western Diet on Allostatic Loads and Cardiac Resilience, Adaptation and Proteome Profiles in Male Mice.Comprehensive Physiology · 2025Article
- Association of Weight Loss and Weight Gain With Structural Defects and Pain in Hand Osteoarthritis: Data From the Osteoarthritis Initiative.Arthritis care & research · 2024Article
- Performance of the Models Predicting In-Hospital Mortality in Patients with ST-Segment Elevation Myocardial Infarction with Predictors in Categorical and Continuous Forms.Sovremennye tekhnologii v meditsine · 2024Article
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Authors and funding
3 authors.
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Abstract
backgroundRheumatology researchers often categorize continuous predictor variables. We aimed to show how this practice may alter results from observational studies in rheumatology.
methodsWe conducted and compared the results of two analyses of the association between our predictor variable (percentage change in body mass index [BMI] from baseline to four years) and two outcome variable domains of structure and pain in knee and hip osteoarthritis. These two outcome variable domains covered 26 different outcomes for knee and hip combined. In the first analysis (categorical analysis), percentage change in BMI was categorized as ≥ 5% decrease in BMI, < 5% change in BMI, and ≥ 5% increase in BMI, while in the second analysis (continuous analysis), it was left as a continuous variable. In both analyses (categorical and continuous), we used generalized estimating equations with a logistic link function to investigate the association between the percentage change in BMI and the outcomes.
resultsFor eight of the 26 investigated outcomes (31%), the results from the categorical analyses were different from the results from the continuous analyses. These differences were of three types: 1) for six of these eight outcomes, while the continuous analyses revealed associations in both directions (i.e., a decrease in BMI had one effect, while an increase in BMI had the opposite effect), the categorical analyses showed associations only in one direction of BMI change, not both; 2) for another one of these eight outcomes, the categorical analyses suggested an association with change in BMI, while this association was not shown in the continuous analyses (this is potentially a false positive association); 3) for the last of the eight outcomes, the continuous analyses suggested an association of change in BMI, while this association was not shown in the categorical analyses (this is potentially a false negative association).
conclusionsCategorization of continuous predictor variables alters the results of analyses and could lead to different conclusions; therefore, researchers in rheumatology should avoid it.
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