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Applicability of extracellular vesicles in clinical studies
Author(s) -
Vozel Domen,
Uršič Bojana,
Krek Judita Lea,
Štukelj Roman,
KraljIglič Veronika
Publication year - 2017
Publication title -
european journal of clinical investigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.164
H-Index - 107
eISSN - 1365-2362
pISSN - 0014-2972
DOI - 10.1111/eci.12733
Subject(s) - extracellular vesicles , repeatability , clinical significance , clinical practice , statistical significance , statistical power , sample size determination , flow cytometry , medicine , pathology , biology , statistics , mathematics , immunology , physical therapy , microbiology and biotechnology
Abstract Background Extracellular vesicles ( EV s) are submicron cellular fragments that mediate intercellular communication. EV s have in the last decade attracted major interest as biomarkers or platforms for biomarkers of health and disease. To better understand the reasons why despite great expectations and considerable effort, EV ‐based methods have not yet been introduced into clinical practice, we present a systematic analysis of published results of clinical studies. Materials and methods Clinical studies on populations of body fluid samples, published from 2010 to including 2015, applying centrifugation of fluid human samples with centrifuge accelerations up to about 25 000 g and flow cytometry for detection of EV s were analysed with respect to statistical significance ( p ), statistical power ( P ), clinical significance ( CS ), defined as the difference between the means divided by the sum of standard deviations, and size of the populations ( N min ), defined as the number of samples in the smaller group. Results Final analysis included 65 publications with 716 comparisons reporting 308 (43%) statistically significant differences ( P < 0·05), 242 (34%) had statistical power P > 0·8 and 88 (12%) had clinical importance CS > 1·96. None of comparison with CS > 1·96 included populations in which the smaller group consisted of 50 or more samples. Conclusions To fulfil claimed expectations for EV ‐based methods as promising diagnostic tools, more evidence on EV ‐based mechanisms of diseases should be gathered. Also, the methods of EV harvesting and assessment should be improved to yield better repeatability and thus allow clinical studies with larger number of samples.