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

• Authors: Gemma A Bernes, San Diego State University; Natasia S Courchesne-Krak, San Diego State University; Matthew T Hyland, San Diego State University; Miguel T Villodas, San Diego State University; Claire Coles, Emory University; Julie Kable, Emory University; Philip A May, University of North Carolina; Wendy O Kalberg, University of New Mexico; Elizabeth R Sowell, University of Southern California; Jeffrey R Wozniak, University of Minnesota; Kenneth L Jones, University of California San Diego; Edward P Riley, San Diego State University; Sarah N Mattson, San Diego State University
• Journal Title: ALCOHOLISM-CLINICAL AND EXPERIMENTAL RESEARCH
• Volume: Volume 46, Number 1
• Publisher: WILEY | 2021-12-02, Pages 52-65
• Type of Work: Article | Post-print: After Peer Review
• Publisher DOI: http://doi.org/10.1111/acer.14749
• Subjects: Psychology, General; Health Sciences, Mental Health
• Keywords: Science & Technology; Life Sciences & Biomedicine; Substance Abuse; behavior; diagnosis; fetal alcohol spectrum disorders; identification; prenatal alcohol exposure; risk score; SPECTRUM DISORDERS; NEUROBEHAVIORAL PROFILE; PHYSICAL FEATURES; ADAPTIVE-BEHAVIOR; FETAL

Abstract

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.