Department of Psychiatry and Addictology, University of Montreal, Montreal, Quebec, Canada.
CIUSSS-NIM Research Center, Rivière-des-Prairies, Mental Health Hospital, Montreal, Quebec, Canada.
Autism Res. 2021 Oct;14(10):2213-2220. doi: 10.1002/aur.2494. Epub 2021 Jun 2.
The evolution of autism diagnosis, from its discovery to its current delineation using standardized instruments, has been paralleled by a steady increase in its prevalence and heterogeneity. In clinical settings, the diagnosis of autism is now too vague to specify the type of support required by the concerned individuals. In research, the inclusion of individuals categorically defined by over-inclusive, polythetic criteria in autism cohorts results in a population whose heterogeneity runs contrary to the advancement of scientific progress. Investigating individuals sharing only a trivial resemblance produces a large-scale type-2 error (not finding differences between autistic and dominant population) rather than detecting mechanistic differences to explain their phenotypic divergences. The dimensional approach of autism proposed to cure the disease of its categorical diagnosis is plagued by the arbitrariness of the dimensions under study. Here, we argue that an emphasis on the reliability rather than specificity of diagnostic criteria and the misuse of diagnostic instruments, which ignore the recognition of a prototype, leads to confound autism with the entire range of neurodevelopmental conditions and personality variants. We propose centering research on cohorts in which individuals are selected based on their expert judged prototypicality to advance the theoretical and practical pervasive issues pertaining to autism diagnostic thresholds. Reversing the current research strategy by giving more weight to specificity than reliability should increase our ability to discover the mechanisms of autism. LAY SUMMARY: Scientific research into the causes of autism and its mechanisms is carried out on large cohorts of people who are less and less different from the general population. This historical trend may explain the poor harvest of results obtained. Services and intervention are provided according to a diagnosis that now encompasses extremely different individuals. Last, we accept as a biological reality the constant increase over the years in the proportion of autistic people among the general population. These drifts are made possible by the attribution of a diagnosis of autism to people who meet vague criteria, rather than to people who experienced clinicians recognize as autistic. We propose to change our research strategy by focusing on the study of the latter, fewer in number, but more representative of the "prototype" of autism. To do this, it is necessary to clearly distinguish the population on which the research is carried out from that to which we provide support. People must receive services according to their needs, and not according to the clarity of their diagnosis.
自闭症的诊断演变,从其发现到当前使用标准化工具进行划分,与发病率的稳步上升和异质性的增加是并行的。在临床环境中,自闭症的诊断现在过于模糊,无法指明相关个体所需的支持类型。在研究中,将使用包容性过强、多质标准明确分类的个体纳入自闭症队列,导致群体的异质性与科学进步背道而驰。对仅具有微小相似性的个体进行研究,会导致大规模的第二类错误(即未发现自闭症患者与主流人群之间的差异),而无法发现机制差异以解释其表型差异。为了治疗自闭症的分类诊断,提出了自闭症的维度方法,但该方法受到所研究维度的任意性的困扰。在这里,我们认为,强调诊断标准的可靠性而不是特异性以及诊断工具的误用(忽略对原型的识别),会导致自闭症与整个神经发育状况和人格变体范围相混淆。我们建议将研究重点放在基于专家判断原型性选择个体的队列上,以推进与自闭症诊断阈值相关的理论和实际普遍性问题。通过增加特异性而不是可靠性来改变当前的研究策略,应该会提高我们发现自闭症机制的能力。
通俗译文:自闭症的诊断演变,从其发现到当前使用标准化工具进行划分,与发病率的稳步上升和异质性的增加是并行的。在临床环境中,自闭症的诊断现在过于模糊,无法指明相关个体所需的支持类型。在研究中,将使用包容性过强、多质标准明确分类的个体纳入自闭症队列,导致群体的异质性与科学进步背道而驰。为了治疗自闭症的分类诊断,提出了自闭症的维度方法,但该方法受到所研究维度的任意性的困扰。在这里,我们认为,强调诊断标准的可靠性而不是特异性以及诊断工具的误用(忽略对原型的识别),会导致自闭症与整个神经发育状况和人格变体范围相混淆。我们建议将研究重点放在基于专家判断原型性选择个体的队列上,以推进与自闭症诊断阈值相关的理论和实际普遍性问题。通过增加特异性而不是可靠性来改变当前的研究策略,应该会提高我们发现自闭症机制的能力。