Thomas Lampeter, Charles Love, T. T. Tang, Aditi Marella, H. Y. Lee, Armani K Oganyan, Devin Moffat, Anisha Kareem, Matthew Rusling, Aubrey Massmann, Melanie Orr, C. Bongiorno, Lilian Yuan
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Abstract
Abstract Risk of bias assessment is a critical step of any meta-analysis or systematic review. Given the low sample count of many microbiome studies, especially observational or cohort studies involving human subjects, many microbiome studies have low power. This increases the importance of performing meta-analysis and systematic review for microbiome research in order to enhance the relevance and applicability of microbiome results. This work proposes a method based on the ROBINS-I tool to systematically consider sources of bias in microbiome research seeking to perform meta-analysis or systematic review for microbiome studies.
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