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Common Statistical Challenges in Cytokine Studies
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Mohammad Bahrami    , Firouz Amani , Masoud Hassanzadeh Makoui *1 |
| 1- & Department of Immunology, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran , dr.m.makoui@zums.ac.ir |
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Abstract: (51 Views) |
Cytokines are among the most important regulators of immune responses and are widely used as biomarkers in both clinical and experimental immunology studies. Advances in multiplex measurement techniques have enabled the simultaneous assessment of multiple cytokines; however, the statistical analysis and interpretation of these data remain challenging. This letter provides a overview of common statistical challenges encountered in cytokine studies that may affect the validity and interpretation of results. These challenges include the non-normal distribution of cytokine data, the widespread use of inappropriate descriptive measures such as mean ± standard deviation instead of median and interquartile range, and the performance of multiple statistical comparisons without adequate adjustment. In addition, an overemphasis on statistical significance without consideration of effect size or biological relevance may lead to exaggerated interpretations of findings. This letter highlights that many of these issues can be addressed through appropriate study design, more transparent reporting of results, and close collaboration between immunologists and statisticians. Greater attention to these considerations may improve the quality of statistical analyses, enhance the reproducibility of findings, and raise research standards in cytokine studies. |
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| Keywords: Cytokine analysis, Statistical methodology, Multivariate data challenges, Biostatistics in immunology |
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Full-Text [PDF 334 kb]
(15 Downloads)
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Type of Study: Letter to editor |
Subject:
General
Received: 2025/12/27 | Accepted: 2026/01/30 | Published: 2026/03/21
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