Erica Kovacs

Health-Related Quality of Life in Children with Autism Spectrum Disorders: Results from the Autism Treatment Network

We examined data collected as a part of the Autism Treatment Network, a group of 15 autism centers across the United States and Canada. Mean Health-Related Quality of Life (HRQoL) scores of the 286 children assessed were significantly lower than those of healthy populations (according to published norms). When compared to normative data from children with chronic conditions, children with ASD demonstrated worse HRQoL for total, psychosocial, emotional and social functioning, but did not demonstrate differing scores for physical and school functioning. HRQoL was not consistently related to ASD diagnosis or intellectual ability. However, it was consistently related to internalizing and externalizing problems as well as repetitive behaviors, social responsiveness, and adaptive behaviors. Associations among HRQoL and behavioral characteristics suggest that treatments aimed at improvements in these behaviors may improve HRQoL.

PREFERENCE-BASED HEALTH-RELATED QUALITY OF LIFE OUTCOMES IN CHILDREN WITH AUTISM SPECTRUM DISORDERS: A COMPARISON OF GENERIC INSTRUMENTS

BackgroundCost-effectiveness analysis of pharmaceutical and other treatments for children with autism spectrum disorders (ASDs) has the potential to improve access to services by demonstrating the value of treatment to public and private payers, but methods for measuring QALYs in children are under-studied. No cost-effectiveness analyses have been undertaken in this population using the cost-per-QALY metric.ObjectiveThis study describes health-related quality-of-life (HR-QOL) outcomes in children with ASDs and compares the sensitivity of two generic preference-based instruments relative to ASD-related conditions and symptoms.MethodsThe study design was cross-sectional with prospectively collected outcome data that were correlated with retrospectively assessed clinical information. Subjects were recruited from two sites of the Autism Treatment Network (ATN) in the US: a developmental centre in Little Rock, Arkansas, and an outpatient psychiatric clinic at Columbia University Medical Center in New York. Children that met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for an ASD by a multidisciplinary team evaluation were asked to participate in a clinical registry. Families of children with an ASD that agreed to be contacted about participation in future research studies as part of the ATN formed the sampling frame for the study. Families were included if the child with the ASD was between 4 and 17 years of age and the family caregiver spoke English. Eligible families were contacted by mail to see if they would be interested in participating in the study with 150 completing surveys. HR-QOL outcomes were described using the Health Utilities Index (HUI) 3 and the Quality of Well-Being Self-Administered (QWB-SA) scale obtained by proxy via the family caregiver.ResultsChildren were diagnosed as having autistic disorder (76%), pervasive developmental disorder-not otherwise specified [PDD-NOS] (15%), and Asperger’s disorder (9%). Average HUI3 and QWB-SA scores were 0.68 (SD 0.21, range 0.07–1) and 0.59 (SD 0.16, range 0.18–1), respectively. The HUI3 score was significantly correlated with clinical variables including adaptive behaviour (ρ=0.52;p<0.001) and cognitive functioning (ρ=0.36;p<0.001). The QWB-SA score had weak correlation with adaptive behaviour (ρ=0.25;p<0.001) and cognitive functioning (ρ=0.17;p<0.005). Change scores for the HUI3 were larger than the QWB-SA for all clinical measures. Scores for the HUI3 increased 0.21 points (95% CI 0.14, 0.29) across the first to the third quartile of the cognitive functioning measure compared with 0.05 (95% CI −0.01, 0.11) for the QWB-SA. Adjusted R2 values also were higher for the HUI3 compared with the QWB-SA across all clinical measures.ConclusionsThe HUI3 was more sensitive to clinical measures used to characterize children with autism compared with the QWB-SA score. The findings provide a benchmark to compare scores obtained by alternative methods and instruments. Researchers should consider incorporating the HUI3 in clinical trials and other longitudinal research studies to build the evidence base for describing the cost effectiveness of services provided to this important population.

Autism spectrum disorders: a review of measures for clinical, health services and cost-effectiveness applications.

Autism spectrum disorders (ASDs) are characterized by impairments in social interaction, communication and behavioral functioning that can affect the health-related quality-of-life outcomes of the affected child and the family. ASDs have increased in prevalence, leading to a demand for improved understanding of the comparative effectiveness of different pharmacologic, behavioral, medical and alternative treatments for children as well as systems for providing services. This review describes outcome instruments that can be used for clinical, health services and cost–effectiveness applications. There is a pressing need to identify the most appropriate instruments for measuring health-related quality-of-life outcomes in this population. Studies evaluating the cost–effectiveness of interventions or treatments for children with ASDs using the cost per quality-adjusted life year metric are lacking. Researchers have the potential to contribute greatly to the field of autism by quantifying outcomes that can inform optimal treatment strategies.

Caring for a Child with Autism Spectrum Disorder and Parents’ Quality of Life: Application of the CarerQol

This study describes the impact of caregiving on parents of children with autism spectrum disorders (ASDs). Secondly, we investigate construct validation of the care-related quality of life instrument (CarerQol) measuring impact of caregiving. Primary caregivers of children with ASDs were included. Many parents experienced considerable problems combining daily activities with care, had financial problems or suffered from depressive mood. Validity tests showed that a higher impact of caring on the CarerQol was positively associated with higher subjective burden and lower family quality of life. Most of the associations between CarerQol scores and background characteristics confirmed previous research. The CarerQol validly measures the impact of caregiving for children with ASDs on caregivers in our sample. The CarerQol may therefore be useful for including parent outcomes in research on ASDs.

Predicting Health Utilities for Children with Autism Spectrum Disorders

Comparative effectiveness of interventions for children with autism spectrum disorders (ASDs) that incorporates costs is lacking due to the scarcity of information on health utility scores or preference‐weighted outcomes typically used for calculating quality‐adjusted life years (QALYs). This study created algorithms for mapping clinical and behavioral measures for children with ASDs to health utility scores. The algorithms could be useful for estimating the value of different interventions and treatments used in the care of children with ASDs. Participants were recruited from two Autism Treatment Network sites. Health utility data based on the Health Utilities Index Mark 3 (HUI3) for the child were obtained from the primary caregiver (proxy‐reported) through a survey (N = 224). During the initial clinic visit, proxy‐reported measures of the Child Behavior Checklist, Vineland II Adaptive Behavior Scales, and the Pediatric Quality of Life Inventory 4.0 (start measures) were obtained and then merged with the survey data. Nine mapping algorithms were developed using the HUI3 scores as dependent variables in ordinary least squares regressions along with the start measures, the Autism Diagnostic Observation Schedule, to measure severity, child age, and cognitive ability as independent predictors. In‐sample cross‐validation was conducted to evaluate predictive accuracy. Multiple imputation techniques were used for missing data. The average age for children with ASDs in this study was 8.4 (standard deviation = 3.5) years. Almost half of the children (47%) had cognitive impairment (IQ ≤ 70). Total scores for all of the outcome measures were significantly associated with the HUI3 score. The algorithms can be applied to clinical studies containing start measures of children with ASDs to predict QALYs gained from interventions. Autism Res 2014, 7: 649–663.