A Validation Study of the Alcohol Related Neurodevelopmental Disorders Behavioral Checklist

Identifying Prenatal Alcohol Exposure and Children Affected by It: A Review of Biomarkers and Screening Tools

PURPOSE

Early identification of prenatal alcohol exposure (PAE) and of those in need of services resulting from this exposure is an important public health concern. This study reviewed the existing literature on potential biomarkers and screening tools of PAE and its impact.

SEARCH METHODS

Electronic databases were searched for articles published between January 1, 1996, and November 30, 2021, using the following search terms: ("fetal alcohol" or "prenatal alcohol" or "FASD" or "alcohol-related neurodevelopmental disorder" or "ARND" or "ND-PAE") and ("screening" or "identification" or "biomarker"). Duplicate articles were electronically eliminated. Titles and abstracts were reviewed for appropriateness, and selected articles were retrieved for further analysis. Additional articles were added that were referenced in the reviewed articles or identified from expert knowledge. Information about the characteristics of the sample, the biomarker or screening tool, and the predictive validity outcome data were abstracted. A narrative analysis of the studies was then performed on the data.

SEARCH RESULTS

A total of 3,813 articles were initially identified, and 1,215 were removed as duplicates. Of the remaining articles, 182 were identified as being within the scope of the review based on title and abstract inspection, and 181 articles were successfully retrieved. Of these, additional articles were removed because they were preclinical (3), were descriptive only (13), included only self-report of PAE (42), included only mean group comparison (17), were additional duplicates (2), focused on cost analysis (9), missed predictive validity data (24), or for other reasons (23). The remaining articles (n = 48) were abstracted. An additional 13 manuscripts were identified from these articles, and two more from expert knowledge. A total of 63 articles contributed to the review.

DISCUSSION AND CONCLUSIONS

Biomarkers and screening tools of PAE and its impact fall short of ideal predictive validity characteristics. Higher specificity than sensitivity was found for many of the biomarkers and screening tools used to identify PAE and its impact, suggesting that current methods continue to under-identify the full range of individuals impacted by PAE. Exceptions to this were found in recent investigations using microRNAs related to growth and vascular development, proteomic changes associated with PAE, and combinations of markers estimating levels of various cytokines. Replications of these findings are needed across other samples to confirm the limited data available. Future research on biomarkers and screening tools should attend to feasibility and scalability of implementation. This article also recommends a systematic process of evaluation to improve early identification of individuals impacted by PAE so that harm reduction and habilitative care efforts can be implemented.

Fetal alcohol spectrum disorders

Alcohol readily crosses the placenta and may disrupt fetal development. Harm from prenatal alcohol exposure (PAE) is determined by the dose, pattern, timing and duration of exposure, fetal and maternal genetics, maternal nutrition, concurrent substance use, and epigenetic responses. A safe dose of alcohol use during pregnancy has not been established. PAE can cause fetal alcohol spectrum disorders (FASD), which are characterized by neurodevelopmental impairment with or without facial dysmorphology, congenital anomalies and poor growth. FASD are a leading preventable cause of birth defects and developmental disability. The prevalence of FASD in 76 countries is >1% and is high in individuals living in out-of-home care or engaged in justice and mental health systems. The social and economic effects of FASD are profound, but the diagnosis is often missed or delayed and receives little public recognition. Future research should be informed by people living with FASD and be guided by cultural context, seek consensus on diagnostic criteria and evidence-based treatments, and describe the pathophysiology and lifelong effects of FASD. Imperatives include reducing stigma, equitable access to services, improved quality of life for people with FASD and FASD prevention in future generations.

Validation of the FASD-Tree as a screening tool for fetal alcohol spectrum disorders

BACKGROUND

As many as 80% of individuals with fetal alcohol spectrum disorders (FASD) are misdiagnosed or not diagnosed. This study tests the accuracy and validity of a web-based screening tool (the FASD-Tree) for identifying children and adolescents with FASD.

METHODS

Children with histories of prenatal alcohol exposure (PAE) and controls (N = 302, including 224 with PAE and 78 controls) were examined for physical signs of fetal alcohol syndrome (FAS), and parents completed behavioral questionnaires. Data were entered into the FASD-Tree, a web-based decision tree application. The FASD-Tree provided two outcomes: a dichotomous indicator (yes/no) and a numeric risk score (0 to 5), which have been shown separately to identify children with PAE and neurobehavioral impairment and to correlate with neurobehavioral outcomes. Overall accuracy (ACC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for the decision tree, risk score, and their combination. Misclassified cases were examined for systematic bias.

RESULTS

The FASD-Tree was successful in accurately identifying youth with histories of PAE and the subgroup of individuals with FASD, indicating its validity as an FASD screening tool. Overall accuracy rates for FASD-Tree components ranged from 75.0% to 84.1%, and both the decision tree outcome and risk score, and their combination, resulted in fair to good discrimination (area under the curve = 0.722 to 0.862) of youth with histories of PAE or FASD. While most participants were correctly classified, those who were misclassified differed in IQ and attention. Race, ethnicity, and sex did not affect the results.

CONCLUSION

The FASD-Tree is not a biomarker of PAE and does not provide definitive evidence of prenatal alcohol exposure. Rather it is an accurate and valid screening tool for FASD and can be used by clinicians who suspect that a patient has a history of PAE, even if the exposure is unknown.

Development and validation of a postnatal risk score that identifies children with prenatal alcohol exposure

BACKGROUND

This study aimed to develop an efficient and easily calculable risk score that can be used to identify an individual's risk of having been exposed to alcohol prenatally.

METHODS

Data for this study were collected as part of the Collaborative Initiative on Fetal Alcohol Spectrum Disorders, Phases 2 and 3. Two cohorts (ages 5 to 17 years) completed a comprehensive neurobehavioral battery and a standard dysmorphology exam: a development cohort (DC; n = 325) and a comparative cohort (CC; n = 523). Both cohorts included two groups: those with histories of heavy prenatal alcohol exposure (AE-DC, n = 121; AE-CC, n = 177) and a control group that included subjects with minimal or no prenatal alcohol exposure (CON-DC, n = 204; CON-CC, n = 346). Behavioral assessments and physical exam data were combined using regression techniques to derive a risk score indicating the likelihood of prenatal alcohol exposure. Subjects were then divided into two subgroups: (1) low risk and (2) high risk. Chi-square (χ² ) determined classification accuracy and ROC curves were produced to assess the predictive accuracy. Correlations between risk scores and intelligence quotient and executive function scores were calculated.

RESULTS

Subjects were accurately classified in the DC (χ²  = 78.61, p < 0.001) and CC (χ²  = 86.63, p < 0.001). The classification model also performed well in the DC (ROC = 0.835 [SE = 0.024, p < 0.001]) and CC (ROC = 0.786 [SE = 0.021, p < 0.001]). In the AE-CC and CON-CC, there were modest but significant associations between the risk score and executive function (AE-CC: r = -0.20, p = 0.034; CON-CC: r = -0.28, p < 0.001) and intelligence quotient (AE-CC: r = -0.20, p = 0.034; CON-CC: r = -0.28, p < 0.001).

CONCLUSION(S)

The risk score significantly distinguished alcohol-exposed from control subjects and correlated with important cognitive outcomes. It has significant clinical potential and could be easily deployed in clinical settings.