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Comparing rates of agreement between different diagnostic criteria for fetal alcohol spectrum disorder: A systematic
Graysen Myers1, Michael Burd1, Marilyn G Klug1
1University of North Dakota School of Medicine and Health Sciences, Grand Forks, North Dakota, USA.
Abstract:
Diagnostic accuracy is important in systems used to diagnose common disorders such as Fetal Alcohol Spectrum Disorder (FASD). Currently, no comprehensive study has examined rates of agreement between different diagnostic criteria for FASD. This study estimates the likelihood that a diagnosis of FASD using one set of diagnostic criteria will result in the same diagnosis when compared to different diagnostic criteria. A systematic review was conducted to identify articles reporting on the comparison of two or more diagnostic criteria for a diagnosis of FASD. Inclusion criteria required that the study present data that estimated agreement for a diagnosis of FASD or no-FASD between two or more FASD criteria using two-by-two tables or presented data that could be used to generate the tables. Meta-analyses with confidence intervals were included to demonstrate variability in the estimates. Standardized measures of agreement were assessed using the kappa statistic with 95% confidence intervals and the phi coefficient as a measure of correlation between binary outcomes. The search identified six studies reporting on eight different FASD diagnostic criteria. The studies compared agreement between 17 different pairings of the criteria. For individual children, agreement ranged from 53.7% to 91%. The agreement between the eight different diagnostic criteria ranged from 59.4% to 89.5%. The kappa statistic found that five associations had a kappa ranging from 0.6 to 0.8. This study illustrates that comparisons of multiple pairs of diagnostic criteria are likely to result in considerable variation in diagnoses of FASD for individual children and between different criteria. The lack of agreement between these commonly used systems is likely to affect clinical care and studies where diagnosis is a key variable. Large-scale multicenter research is needed to examine factors contributing to variation in diagnostic outcomes.
