Abstract
BackgroundBiomarker-based analyses are commonly reported in observational epidemiological studies; however currently there are no specific study quality assessment tools to assist evaluation of conducted research. Accounting for study design and biomarker measurement would be important for deriving valid conclusions when conducting systematic data evaluation.MethodsWe developed a study quality assessment tool designed specifically to assess biomarker-based cross-sectional studies (BIOCROSS) and evaluated its inter-rater reliability. The tool includes 10-items covering 5 domains: ‘Study rational’, ‘Design/Methods’, ‘Data analysis’, ‘Data interpretation’ and ‘Biomarker measurement’, aiming to assess different quality features of biomarker cross-sectional studies. To evaluate the inter-rater reliability, 30 studies were distributed among 5 raters and intraclass correlation coefficients (ICC-s) were derived from respective ratings.ResultsThe estimated overall ICC between the 5 raters was 0.57 (95% Confidence Interval (CI): 0.38–0.74) indicating a good inter-rater reliability. The ICC-s ranged from 0.11 (95% CI: 0.01–0.27) for the domain ‘Study rational’ to 0.56 (95% CI: 0.40–0.72) for the domain ‘Data interpretation’.ConclusionBIOCROSS is a new study quality assessment tool suitable for evaluation of reporting quality from cross-sectional epidemiological studies employing biomarker data. The tool proved to be reliable for use by biomedical scientists with diverse backgrounds and could facilitate comprehensive review of biomarker studies in human research.
Highlights
Biomarker-based analyses are commonly reported in observational epidemiological studies; currently there are no specific study quality assessment tools to assist evaluation of conducted research
BIOCROSS evaluation tool The tool has been divided into 5 domains (‘Study rational’, Design/Methods’, ‘Data analysis’, ‘Data interpretation’ and ‘Biomarker measurement’), aiming to assess different quality features of biomarker cross-sectional studies
The first item assesses how the study population selection was performed and how information about the selection process is presented in the publication
Summary
Biomarker-based analyses are commonly reported in observational epidemiological studies; currently there are no specific study quality assessment tools to assist evaluation of conducted research. Accounting for study design and biomarker measurement would be important for deriving valid conclusions when conducting systematic data evaluation. Biomarkers have been broadly defined as any measurable characteristic of an organism that reflects a particular physiological state. These are molecules isolated from serum, urine, or other fluids that can have multifaceted application (i) indicating. Among different study designs in epidemiology, crosssectional studies have gained much application in utilizing biomarker data due to their high feasibility. Even though no inferences on causality can be drawn, cross-sectional studies have proven helpful in gaining insights into potential correlations between biomarkers and other factors [5]
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