- Email: [email protected]
Hyperactivity Disorder (ADHD)
NEW RESEARCH POSTERS 6.23 — 6.25
significant only for the 300-mg group. The most frequent treatment-emergent AEs ( 15.0% of subjects) were somnolence, headache, and decreased appetite, with the incidence increasing with higher SPN-812 ER doses. Conclusions: Treatment with 200, 300, and 400 mg SPN-812 ER resulted in statistically significant improvement in CFB in ADHD RS-IV Total Scores compared to placebo; the primary efficacy results were confirmed by sensitivity analyses and are supported by results from analyses of secondary efficacy measures. All SPN-812 ER doses tested were well tolerated. SPN-812 ER will be further evaluated as a non-stimulant pharmacotherapy for the treatment of ADHD.
PPC, ADHD, RCT Supported by Supernus Pharmaceuticals, Inc. http://dx.doi.org/10.1016/j.jaac.2017.09.367
6.23 PREDICTORS OF LONG-TERM RISKY DRIVING BEHAVIOR IN THE MULTIMODAL TREATMENT STUDY OF CHILDREN WITH ATTENTION-DEFICIT/HYPERACTIVITY DISORDER (ADHD) Jessica A. Johnson, BS, Yale University School of Medicine, [email protected]; Ewgeni Jakubovski, MA, Hannover Medical School, [email protected]; Margot O. Reed, College of the Holy Cross, [email protected]; Michael H. Bloch, MD, MS, Yale University School of Medicine, [email protected] Objectives: The purpose of this study was to examine predictors of later risky driving behavior in children with ADHD. Methods: Stepwise logistic regression and receiver operating characteristic (ROC) analyses were used to explore baseline predictors of risky driving behavior for adolescents that completed the eight-year follow-up assessment in the Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder (MTA). Results: Stepwise logistic regression analysis explained 19 percent of the total variance in risky driving behavior. Increased likelihood of risky driving behavior was associated with parental history of conduct disorder, low parental monitoring and supervision, and increased age. ROC analysis identified discriminative predictors for adolescents older and younger than age 16 years at follow-up. The most discriminative predictors of later risky driving behavior were parental stress at baseline (children 16 years) and increased child-rated parental protectiveness (children < 16 years). Conclusions: Risky driving behavior was significantly predicted by baseline characteristics for the MTA cohort. Aspects of parenting behavior (or the child’s perception of them) including parental stress levels, parental protectiveness, and parental levels of monitoring and supervision were most informative in predicting these outcomes. Our results suggest interventions to reduce high-risk behaviors in these high-risk children with ADHD might involve targeted parenting interventions.
ADHD, EC, PAT http://dx.doi.org/10.1016/j.jaac.2017.09.368
6.24 ROBOT MOTION TRACKING ANALYSIS IN ATTENTION-DEFICIT/HYPERACTIVITY DISORDER (ADHD) Kangryul Kim, MD, Hanyang University Hospital, kangryul@ naver.com; Aran Min, MD, Hanyang University Hospital, [email protected]; Donghyun Ahn, MD, Hanyang University Hospital, [email protected] Objectives: ADHD is a neurodevelopmental disorder characterized by hyperactivity, inattention, and impulsivity. Before 1980, the disease was named attention-deficit disorder (ADD) and then changed to ADHD, with an emphasis on the importance of hyperactivity symptoms. Nonetheless, there are limits to measuring objective activity because the assessments are largely based on observations of therapists and caregivers.
S284
www.jaacap.org
Methods: The participants evaluated in this study were 35 children diagnosed with ADHD and 50 typical development children within the age range of 5 to 12 years. The purpose of this study was to examine behavioral levels using the robot motion-tracking system and to conduct an evaluation and comparative analysis of the results from the Child Behavior Checklist (CBCL) and the Attention-Deficit/Hyperactivity Disorder Diagnostic Scale (ADHD-DS), which are the current standard evaluations for ADHD diagnosis. Results: There were significant average differences between the ADHD group and normal group in attention problems (52.78 3.90 vs. 63.40 7.57, P < 0.001) and ADHD problems (53.64 5.31 vs. 67.77 11.07, P < 0.001) according to the results of the CBCL and the ADHD-DS (25.37 6.30 vs. 12.36 3.39, P < 0.001). There were also significant differences between the movement distance (4,968.64 4,201.53 vs. 830.89 6,324.45, P < 0.001) and movement speed (361.17 133.49 vs. 735.60 1,227.55, P ¼ 0.035) in that the typical developmental group traveled long distances more slowly, whereas the ADHD group traveled short distances more quickly. The results of correlation analysis showed that distance of travel was significantly correlated with attention problems (according to the CBCL) and ADHD problems (according to CBCL and ADHD-DS), whereas movement speed was significantly correlated with the ADHD problems according to the CBCL and ADHD-DS. Conclusions: The children with ADHD were characterized by moving small distances faster than children without ADHD, within the same period of time during the tasks. Moreover, the robot motion-tracking analysis can be used to overcome limitations of previous questionnaires by producing objective information on the children’s activities to determine the effectiveness of diagnosis and treatment.
ADHD, ND http://dx.doi.org/10.1016/j.jaac.2017.09.369
6.25 MEDICATION ADHERENCE MONITORING IN PEDIATRIC AND YOUNG ADULT POPULATIONS ON ATTENTION-DEFICIT/HYPERACTIVITY DISORDER (ADHD) STIMULANT MEDICATIONS Mancia Ko, PharmD, Ameritox, [email protected] Objectives: The goals of this presentation are to identify potential nonadherence among pediatric, adolescent, and young adult patients who were prescribed ADHD stimulant medications and assess the differences in illicit substance and/or nonprescribed medication use in patients testing positive versus negative for the ADHD medication. Methods: Urine samples submitted to the laboratory between 2014 and 2016 from patients (ages 6–25 years inclusive), who were documented on the laboratory requisition to have been prescribed an amphetamine or methylphenidate medication for the treatment of ADHD, were included in the analysis. The first urine sample obtained from each patient was analyzed for the presence of the prescribed ADHD medication, illicit substances [marijuana metabolite (tetrahydrocannabinol, THC) and cocaine metabolite (benzoylecgonine)], and nonprescribed opioid or benzodiazepine medications. Results: Samples were analyzed from 4,449 patients; 66.4 percent of patients were male, and the mean age was 14.1 5.5 years. Overall, 30.2 percent of patients tested negative for their prescribed ADHD medication. Patients aged 6 to 10 years had the lowest rate of negative test results (21.0%) and patients aged 18 to 21 years had the highest rate [45.5%; adjusted OR (aOR) 3.2 (95% CI 2.5–4.1)]. Illicit substances, primarily THC, were rarely detected for patients under age 14 years but were detected in 11.8, 20.8, and 20.0 percent of patients ages 14 to 17, 18 to 21, and 22 to 25 years, respectively. Detection of nonprescribed opioid medications was rare in patients <18 years of age but were found in 7.7 and 11.4 percent of patients ages 18 to 21 and 22 to 25 years, respectively. Patients who tested negative for prescribed ADHD medication were significantly more likely than patients who tested positive to have THC detected in the urine sample [17.3 vs. 7.1%; aOR 1.9 (95% CI 1.5–2.4)]. Conclusions: Urine drug monitoring in patients prescribed stimulant ADHD medication can be of value both for evaluating adherence to ADHD therapy and identifying the inappropriate use of illicit substances and/or nonprescribed medications. The data suggest that potential nonadherence to
J OURNAL
OF THE
AMERICAN A CADEMY OF CHILD & ADOLESCENT P SYCHIATRY VOLUME 56 NUMBER 10S OCTOBER 2017
significant only for the 300-mg group. The most frequent treatment-emergent AEs ( 15.0% of subjects) were somnolence, headache, and decreased appetite, with the incidence increasing with higher SPN-812 ER doses. Conclusions: Treatment with 200, 300, and 400 mg SPN-812 ER resulted in statistically significant improvement in CFB in ADHD RS-IV Total Scores compared to placebo; the primary efficacy results were confirmed by sensitivity analyses and are supported by results from analyses of secondary efficacy measures. All SPN-812 ER doses tested were well tolerated. SPN-812 ER will be further evaluated as a non-stimulant pharmacotherapy for the treatment of ADHD.
PPC, ADHD, RCT Supported by Supernus Pharmaceuticals, Inc. http://dx.doi.org/10.1016/j.jaac.2017.09.367
6.23 PREDICTORS OF LONG-TERM RISKY DRIVING BEHAVIOR IN THE MULTIMODAL TREATMENT STUDY OF CHILDREN WITH ATTENTION-DEFICIT/HYPERACTIVITY DISORDER (ADHD) Jessica A. Johnson, BS, Yale University School of Medicine, [email protected]; Ewgeni Jakubovski, MA, Hannover Medical School, [email protected]; Margot O. Reed, College of the Holy Cross, [email protected]; Michael H. Bloch, MD, MS, Yale University School of Medicine, [email protected] Objectives: The purpose of this study was to examine predictors of later risky driving behavior in children with ADHD. Methods: Stepwise logistic regression and receiver operating characteristic (ROC) analyses were used to explore baseline predictors of risky driving behavior for adolescents that completed the eight-year follow-up assessment in the Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder (MTA). Results: Stepwise logistic regression analysis explained 19 percent of the total variance in risky driving behavior. Increased likelihood of risky driving behavior was associated with parental history of conduct disorder, low parental monitoring and supervision, and increased age. ROC analysis identified discriminative predictors for adolescents older and younger than age 16 years at follow-up. The most discriminative predictors of later risky driving behavior were parental stress at baseline (children 16 years) and increased child-rated parental protectiveness (children < 16 years). Conclusions: Risky driving behavior was significantly predicted by baseline characteristics for the MTA cohort. Aspects of parenting behavior (or the child’s perception of them) including parental stress levels, parental protectiveness, and parental levels of monitoring and supervision were most informative in predicting these outcomes. Our results suggest interventions to reduce high-risk behaviors in these high-risk children with ADHD might involve targeted parenting interventions.
ADHD, EC, PAT http://dx.doi.org/10.1016/j.jaac.2017.09.368
6.24 ROBOT MOTION TRACKING ANALYSIS IN ATTENTION-DEFICIT/HYPERACTIVITY DISORDER (ADHD) Kangryul Kim, MD, Hanyang University Hospital, kangryul@ naver.com; Aran Min, MD, Hanyang University Hospital, [email protected]; Donghyun Ahn, MD, Hanyang University Hospital, [email protected] Objectives: ADHD is a neurodevelopmental disorder characterized by hyperactivity, inattention, and impulsivity. Before 1980, the disease was named attention-deficit disorder (ADD) and then changed to ADHD, with an emphasis on the importance of hyperactivity symptoms. Nonetheless, there are limits to measuring objective activity because the assessments are largely based on observations of therapists and caregivers.
S284
www.jaacap.org
Methods: The participants evaluated in this study were 35 children diagnosed with ADHD and 50 typical development children within the age range of 5 to 12 years. The purpose of this study was to examine behavioral levels using the robot motion-tracking system and to conduct an evaluation and comparative analysis of the results from the Child Behavior Checklist (CBCL) and the Attention-Deficit/Hyperactivity Disorder Diagnostic Scale (ADHD-DS), which are the current standard evaluations for ADHD diagnosis. Results: There were significant average differences between the ADHD group and normal group in attention problems (52.78 3.90 vs. 63.40 7.57, P < 0.001) and ADHD problems (53.64 5.31 vs. 67.77 11.07, P < 0.001) according to the results of the CBCL and the ADHD-DS (25.37 6.30 vs. 12.36 3.39, P < 0.001). There were also significant differences between the movement distance (4,968.64 4,201.53 vs. 830.89 6,324.45, P < 0.001) and movement speed (361.17 133.49 vs. 735.60 1,227.55, P ¼ 0.035) in that the typical developmental group traveled long distances more slowly, whereas the ADHD group traveled short distances more quickly. The results of correlation analysis showed that distance of travel was significantly correlated with attention problems (according to the CBCL) and ADHD problems (according to CBCL and ADHD-DS), whereas movement speed was significantly correlated with the ADHD problems according to the CBCL and ADHD-DS. Conclusions: The children with ADHD were characterized by moving small distances faster than children without ADHD, within the same period of time during the tasks. Moreover, the robot motion-tracking analysis can be used to overcome limitations of previous questionnaires by producing objective information on the children’s activities to determine the effectiveness of diagnosis and treatment.
ADHD, ND http://dx.doi.org/10.1016/j.jaac.2017.09.369
6.25 MEDICATION ADHERENCE MONITORING IN PEDIATRIC AND YOUNG ADULT POPULATIONS ON ATTENTION-DEFICIT/HYPERACTIVITY DISORDER (ADHD) STIMULANT MEDICATIONS Mancia Ko, PharmD, Ameritox, [email protected] Objectives: The goals of this presentation are to identify potential nonadherence among pediatric, adolescent, and young adult patients who were prescribed ADHD stimulant medications and assess the differences in illicit substance and/or nonprescribed medication use in patients testing positive versus negative for the ADHD medication. Methods: Urine samples submitted to the laboratory between 2014 and 2016 from patients (ages 6–25 years inclusive), who were documented on the laboratory requisition to have been prescribed an amphetamine or methylphenidate medication for the treatment of ADHD, were included in the analysis. The first urine sample obtained from each patient was analyzed for the presence of the prescribed ADHD medication, illicit substances [marijuana metabolite (tetrahydrocannabinol, THC) and cocaine metabolite (benzoylecgonine)], and nonprescribed opioid or benzodiazepine medications. Results: Samples were analyzed from 4,449 patients; 66.4 percent of patients were male, and the mean age was 14.1 5.5 years. Overall, 30.2 percent of patients tested negative for their prescribed ADHD medication. Patients aged 6 to 10 years had the lowest rate of negative test results (21.0%) and patients aged 18 to 21 years had the highest rate [45.5%; adjusted OR (aOR) 3.2 (95% CI 2.5–4.1)]. Illicit substances, primarily THC, were rarely detected for patients under age 14 years but were detected in 11.8, 20.8, and 20.0 percent of patients ages 14 to 17, 18 to 21, and 22 to 25 years, respectively. Detection of nonprescribed opioid medications was rare in patients <18 years of age but were found in 7.7 and 11.4 percent of patients ages 18 to 21 and 22 to 25 years, respectively. Patients who tested negative for prescribed ADHD medication were significantly more likely than patients who tested positive to have THC detected in the urine sample [17.3 vs. 7.1%; aOR 1.9 (95% CI 1.5–2.4)]. Conclusions: Urine drug monitoring in patients prescribed stimulant ADHD medication can be of value both for evaluating adherence to ADHD therapy and identifying the inappropriate use of illicit substances and/or nonprescribed medications. The data suggest that potential nonadherence to
J OURNAL
OF THE
AMERICAN A CADEMY OF CHILD & ADOLESCENT P SYCHIATRY VOLUME 56 NUMBER 10S OCTOBER 2017