Methods for Metabolic Measurement in Cancer Populations: A Systematic Review
Jay Calder, Kellie Toohey, Jodie Cochrane Wilkie, Andrew McKune
University of Canberra Southern Cross University Edith Cowan University
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Background: Cancer is increasingly recognized as a metabolic disease, with mounting evidence to implicate metabolic dysfunction in the process of tumorigenesis. Accurate metabolism measurement in cancer populations is pivotal to validating this hypothesis; however, consistency is lacking in the protocols currently used, which influences the validity, reliability, and comparability of results. Methods: In this systematic review of methodologies, we aimed at evaluating methods and protocols used to measure resting energy metabolism and substrate use among cancer populations. Five electronic databases (CINHAL Plus, Medline, Sport Discus, Cochrane Central, and Web of Science Core Collection) were searched from their inception until September 11, 2024. Results: Twenty articles met inclusions criteria and were methodologically reviewed. Articles encompassed the metabolic measurement of 669 participants with diverse demographics and cancer characteristics. Synthesis of measurement protocols highlighted clear noncompliance with best practice recommendations and/or significant gaps in reporting. This was particularly evident in criteria relating to fasting durations, physical activity restrictions, and environmental control during measurement. Conclusion: The lack of standardization and transparency in the reporting of protocols introduces errors that limit the comparability and ascertainment of metabolic function from resting energy metabolism assessment in cancer populations. Authors of future studies should apply guidelines for metabolic measurement with rigor. This includes prioritizing standardizations with other protocols in similar populations and ensuring complete transparency in reporting of protocols and results. These practices will ensure that accurate and reliable measures of resting energy metabolism measures inform future researchers who investigate metabolic dysfunction in cancer populations.
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生物医学Cancer Risks and Factors
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