Systematic review of tools to measure outcomes for young children with autism spectrum disorder

BACKGROUND: The needs of children with autism spectrum disorder (ASD) are complex and this is reflected in the number and diversity of outcomes assessed and measurement tools used to collect evidence about children's progress. Relevant outcomes include improvement in core ASD impairments, such as communication, social awareness, sensory sensitivities and repetitiveness; skills such as social functioning and play; participation outcomes such as social inclusion; and parent and family impact.

OBJECTIVES: To examine the measurement properties of tools used to measure progress and outcomes in children with ASD up to the age of 6 years. To identify outcome areas regarded as important by people with ASD and parents.

METHODS: The MeASURe (Measurement in Autism Spectrum disorder Under Review) research collaboration included ASD experts and review methodologists. We undertook systematic review of tools used in ASD early intervention and observational studies from 1992 to 2013; systematic review, using the COSMIN checklist (Consensus-based Standards for the selection of health Measurement Instruments) of papers addressing the measurement properties of identified tools in children with ASD; and synthesis of evidence and gaps. The review design and process was informed throughout by consultation with stakeholders including parents, young people with ASD, clinicians and researchers.

RESULTS: The conceptual framework developed for the review was drawn from the International Classification of Functioning, Disability and Health, including the domains 'Impairments', 'Activity Level Indicators', 'Participation', and 'Family Measures'. In review 1, 10,154 papers were sifted - 3091 by full text - and data extracted from 184; in total, 131 tools were identified, excluding observational coding, study-specific measures and those not in English. In review 2, 2665 papers were sifted and data concerning measurement properties of 57 (43%) tools were extracted from 128 papers. Evidence for the measurement properties of the reviewed tools was combined with information about their accessibility and presentation. Twelve tools were identified as having the strongest supporting evidence, the majority measuring autism characteristics and problem behaviour. The patchy evidence and limited scope of outcomes measured mean these tools do not constitute a 'recommended battery' for use. In particular, there is little evidence that the identified tools would be good at detecting change in intervention studies. The obvious gaps in available outcome measurement include well-being and participation outcomes for children, and family quality-of-life outcomes, domains particularly valued by our informants (young people with ASD and parents).

CONCLUSIONS: This is the first systematic review of the quality and appropriateness of tools designed to monitor progress and outcomes of young children with ASD. Although it was not possible to recommend fully robust tools at this stage, the review consolidates what is known about the field and will act as a benchmark for future developments. With input from parents and other stakeholders, recommendations are made about priority targets for research.

FUTURE WORK: Priorities include development of a tool to measure child quality of life in ASD, and validation of a potential primary outcome tool for trials of early social communication intervention.

STUDY REGISTRATION: This study is registered as PROSPERO CRD42012002223.

FUNDING: The National Institute for Health Research Health Technology Assessment programme.

Biomarker Testing and Pre-emptive Therapy in Preventing Heart Failure

In an attempt to reduce the heart failure epidemic,screening and prevention will become an increasing focus ofmanagement in the wider at-risk population. Refining riskprediction through the use of biomarkers in isolation or incombination is emerging as a critical step in this process.The utility of biomarkers to identify disease manifestationsbefore the onset of symptoms and detrimental myocardialdamage is proving to be valuable. In addition, biomarkers thatpredict the likelihood and rate of disease progression over timewill help streamline and focus clinical efforts and therapeuticstrategies. Importantly, several recent early intervention studiesusing biomarker strategies are promising and indicate thatnot only can new-onset heart failure be reduced but also thedevelopment of other cardiovascular conditions.

Common polygenic variation enhances risk prediction for Alzheimer's disease.

The identification of subjects at high risk for Alzheimer’s disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer’s disease and the accuracy of Alzheimer’s disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer’s Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer’s disease (P = 4.9 × 10−26). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10−19). The best prediction accuracy AUC = 78.2% (95% confidence interval 77–80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer’s disease has a significant polygenic component, which has predictive utility for Alzheimer’s disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes.

Interventions to reduce prejudice and enhance inclusion and respect for ethnic differences in early childhood: A systematic review

A systematic review was conducted of studies evaluating the effects of interventions aimed at reducing ethnic prejudice and discrimination in young children. Articles published between 1980 and 2010 and including children of 8 years and under were identified, harvested, and assessed for quality, both for the exposure/program as well as for the evaluation. In total, 32 studies (14 contact and 18 media or instruction) yielded 62 effects on attitudes and 59 effects on peer relations. An overall count of the positive (40%), non-significant (50%), and negative effects (10%) indicate a mixed picture. Overall, more attitude effects (55%) than peer relations effects (25%) were positive, and media/instruction (47%) was more successful than contact (36%). Most of the effects were observed with children from a majority ethnicity: 67% of the attitude effects were positive, and media/instruction and contact were equally effective at delivering these. Few differences were found as a function of the quality of the exposure and evaluation, but differences were found depending on the context of exposure (naturally occurring or experimental manipulation) and research design (random assignment or self-selection). In conclusion, the findings were more mixed than expected, though sufficiently strong studies exist to provide lessons for future research.


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