Thomas Lampeter, Charles Love, Trien T Tang, Aditi S Marella, Hayden Y Lee, Armani Oganyan, Devin Moffat, Anisha Kareem, Matthew Rusling, Aubrey Massmann, Melanie Orr, Christian Bongiorno, Li-Lian Yuan
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引用次数: 0
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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