Individualized approaches to determining likelihood of ASD caseness

确定 ASD 病例可能性的个体化方法

• 批准号: 10656512
• 负责人: Somer L. Bishop
• 金额: $ 79.03万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10656512
• 关键词: Affect; Age; Assessment tool; Attention deficit hyperactivity disorder; Autism Diagnosis; Autism diagnostic; Behavioral; Case Study; Characteristics; Child; Child Behavior Checklist; Classification; Clinical; Data; Data Analyses; Decision Making; Decision Trees; Development; Developmental Delay Disorders; Diagnosis; Diagnostic; Education; Electronics; Evaluation; Explosion; Female; Goals; Guidelines; Health; Heterogeneity; Individual; Infant; Intellectual functioning disability; Interview; Knowledge; Language; Language Disorders; Light; Literature; Machine Learning; Male Adolescents; Measures; Methods; Paper; Parents; Participant; Performance; Persons; Phenotype; Population; Population Characteristics; Predictive Value; Problem behavior; Procedures; Process; Property; Psychometrics; Questionnaires; Recommendation; Reporting; Research; Research Personnel; Research Project Grants; Resources; Risk; Sampling; Screening procedure; Sensitivity and Specificity; Services; Specific qualifier value; Speech; Standardization; Stretching; Subgroup; Symptoms; System; Techniques; Testing; Time; Toddler; Triage; Update; Validation; Weight; Work; Youth; artificial neural network; autism diagnostic observation schedule; autism spectrum disorder; autistic children; behavioral phenotyping; biological sex; clinical diagnosis; clinically significant; cognitive ability; comorbidity; diagnostic accuracy; diagnostic platform; diagnostic tool; ethnic minority; girls; improved; individual variation; instrument; next generation; personalized approach; phrases; prevent; racial minority; recruit; screening; sex; skills; social; social communication; study characteristics; tool; verbal

PROJECT SUMMARY Ongoing development and validation of screening and diagnostic tools has been a major focus of research in autism spectrum disorders (ASD) during the past 30 years. Diagnostic validity of several widely used tools has been established by showing that, in most cases, children with ASD score above established cut-offs, whereas children with non-ASD score below cut-offs. However, a growing body of literature indicates that sensitivity and specificity of ASD symptom measures varies significantly based on the characteristics of the study population. This means that the ability of a given tool to differentiate children with and without ASD is variable, and is affected by an individual's demographic (age, sex), developmental (cognitive ability, language level), and/or behavioral (clinically significant behavior problems) profile. The long-term goal of the proposed research is to transform screening and diagnostic practices through increased individualization of measure selection and interpretation. Phenotypic heterogeneity of youth referred for possible ASD is a well-recognized challenge that prevents one-size-fits-all assessment approaches from being validly employed. Yet, with ever-growing demands for such services, clinical and research entities increasingly rely on specified batteries to make decisions about triage and diagnosis. While use of standardized tools offers many advantages, uniform application or interpretation of specific instruments disregards the vast individual heterogeneity that is a hallmark of ASD. Thus, the field is in need of updated practices, wherein tools are selected, combined, and interpreted in the context of an individual child's presentation, with specific reference to how likely it is that scores on a given test or combination of tests will indicate ASD caseness for that child. Toward this end, the proposed secondary data analysis will identify which tools, and combinations of tools, work best for identifying ASD in sub-groups of youth with shared demographic, developmental, and/or behavioral phenotypes (e.g., in toddler girls with phrase speech vs. verbally fluent adolescent boys with clinically elevated behavior problems). We will analyze data from several widely-used ASD measures, aggregated from more than 17,500 children between the ages of 18 months and 17 years, 11 months. These youth were either clinically referred for ASD diagnostic assessment, assessed due to heightened risk for ASD or other developmental delays, or recruited for ASD-focused research projects. They were assigned a best-estimate diagnosis of ASD or non-ASD (e.g., intellectual disability, ADHD, language disorder) by expert clinicians or clinical-researchers following a comprehensive assessment. By considering the interplay between individual characteristics and instrument scores in the largest sample to date, the proposed study will move the field toward more individualized approaches for establishing ASD caseness. Findings from this study will also directly inform the development of the next generation of tools, procedures, and electronic platforms for diagnostic assessment of ASD.

项目概要 筛查和诊断工具的持续开发和验证一直是以下领域研究的主要焦点 过去 30 年的自闭症谱系障碍 (ASD)。几种广泛使用的工具的诊断有效性 通过证明在大多数情况下，自闭症谱系障碍 (ASD) 分数高于既定界限的儿童，而 非自闭症谱系障碍 (ASD) 分数低于临界值的儿童。然而，越来越多的文献表明，敏感性和 ASD 症状测量的特异性根据研究人群的特征而有很大差异。 这意味着给定工具区分患有自闭症谱系障碍和未患有自闭症谱系障碍的儿童的能力是可变的，并且会受到影响 根据个人的人口统计（年龄、性别）、发育（认知能力、语言水平）和/或行为 （临床上显着的行为问题）概况。 拟议研究的长期目标是通过改变筛查和诊断实践 提高措施选择和解释的个性化。青年人的表型异质性 可能的自闭症谱系障碍（ASD）是一个公认的挑战，它阻碍了一刀切的评估方法 有效就业。然而，随着对此类服务、临床和研究实体的需求不断增长 越来越依赖特定的电池来做出分类和诊断决策。在使用标准化 工具提供了许多优点，特定工具的统一应用或解释忽视了广泛的 个体异质性是 ASD 的标志。因此，该领域需要更新实践，其中工具 根据个别孩子的陈述进行选择、组合和解释，并提供具体参考 给定测试或测试组合的分数表明该孩子患有自闭症谱系障碍的可能性有多大。 为此，拟议的二次数据分析将确定哪些工具以及工具组合有效 最适合在具有共同人口、发育和/或行为特征的青年亚群体中识别自闭症谱系障碍 (ASD) 表型（例如，具有短语言语的幼儿女孩与临床上升高的言语流利的青春期男孩 行为问题）。我们将分析几种广泛使用的 ASD 衡量标准的数据，这些数据来自多个国家 17,500 名 18 个月至 17 岁 11 个月的儿童。这些年轻人要么是临床上 转介进行 ASD 诊断评估，因 ASD 或其他发育风险增加而进行评估 延误，或被招募参加以 ASD 为重点的研究项目。他们被分配了 ASD 的最佳估计诊断 或由临床专家或临床研究人员诊断的非自闭症谱系障碍（例如智力障碍、多动症、语言障碍） 经过综合评估后。通过考虑个体特征和 迄今为止最大样本中的乐器分数，拟议的研究将推动该领域走向更加个性化 建立 ASD 案例的方法。这项研究的结果也将直接为以下领域的发展提供信息： 用于 ASD 诊断评估的下一代工具、程序和电子平台。