Heterogeneity within autism spectrum disorder (ASD) is recognized as a challenge to both biological and psychological research, as well as clinical practice. To reduce unexplained heterogeneity, subtyping techniques are often used to establish more homogeneous subtypes based on metrics of similarity and dissimilarity between people. We review the ASD literature to create a systematic overview of the subtyping procedures and subtype validation techniques that are used in this field. We conducted a systematic review of 156 articles (2001-June 2020) that subtyped participants (range N of studies = 17–20,658), of which some or all had an ASD diagnosis. We found a large diversity in (parametric and non-parametric) methods and (biological, psychological, demographic) variables used to establish subtypes. The majority of studies validated their subtype results using variables that were measured concurrently, but were not included in the subtyping procedure. Other investigations into subtypes' validity were rarer. In order to advance clinical research and the theoretical and clinical usefulness of identified subtypes, we propose a structured approach and present the SUbtyping VAlidation Checklist (SUVAC), a checklist for validating subtyping results.

自闭症谱系障碍 (ASD) 的异质性被认为是对生物学和心理学研究以及临床实践的挑战。为了减少无法解释的异质性，子类型技术通常用于基于人与人之间的相似性和不同性的度量来建立更同质的子类型。我们回顾了 ASD 文献，以创建该领域中使用的子类型程序和子类型验证技术的系统概述。我们对 156 篇文章（2001 年至 2020 年 6 月）进行了系统评价，这些文章对参与者进行了亚型（研究范围 N = 17-20,658），其中部分或全部被诊断为 ASD。我们发现用于建立亚型的（参数和非参数）方法和（生物、心理、人口统计）变量存在很大差异。大多数研究使用同时测量但未包括在亚型程序中的变量来验证其亚型结果。对亚型有效性的其他调查较少见。为了推进临床研究以及已识别亚型的理论和临床实用性，我们提出了一种结构化方法并提出了子分型验证清单 (SUVAC)，这是一个用于验证亚型结果的清单。