ReviewSeminars in pediatric neurology2020
Towards a Multivariate Biomarker-Based Diagnosis of Autism Spectrum Disorder: Review and Discussion of Recent Advancements.
Review in Seminars in pediatric neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 36 citations in OpenAlex.
- Translational Study of Using FOCM/TS Metabolites for Supporting Autism Spectrum Disorder Diagnosis.Annals of biomedical engineering · 2026Article
- Machine learning model to identify gut microbiome-derived metabolites as potential biomarkers of autism spectrum disorder: a pilot study.BMC psychiatry · 2026Article
- Home-based eye tracking for early autism screening: a scoping review of approaches, evidence, and implementation challenges.BMC psychiatry · 2026Article
- Network-Based Prioritization of Network-Peripheral Gene Modules in Autism Spectrum Disorder Using Integrative Transcriptomic and Proteomic Data.Journal of molecular neuroscience : MN · 2026Article
- Integrating Gut-Brain Axis: Exploring the Neurogastrointestinal Interactions and Therapeutic Potentials in Autism Spectrum Disorder.Endocrine, metabolic & immune disorders drug targets · 2026Review
- Urinary Porphyrin Profiles and Trace Element Imbalances in Children with Autism Spectrum Disorders: Insights into Environmental and Metabolic Biomarkers.International journal of molecular sciences · 2025Article
- Pre-autism: Advancing early identification and intervention in autism.World journal of clinical cases · 2024Article
- Quantifying attention in children with intellectual and developmental disabilities through multicenter electrooculogram signal analysis.Scientific reports · 2024Article
- Deep learning based joint fusion approach to exploit anatomical and functional brain information in autism spectrum disorders.Brain informatics · 2024Article
- Predicting Problematic Behavior in Autism Spectrum Disorder Using Medical History and Environmental Data.Journal of personalized medicine · 2023Article
- Early Diagnosis of Autism Spectrum Disorder: A Review and Analysis of the Risks and Benefits.Cureus · 2023Review
- Prosodic signatures of ASD severity and developmental delay in preschoolers.NPJ digital medicine · 2023Article
- Towards the Development of a Diagnostic Test for Autism Spectrum Disorder: Big Data Meets Metabolomics.The Canadian journal of chemical engineering · 2023Article
- Multivariate Analysis of Metabolomic and Nutritional Profiles among Children with Autism Spectrum Disorder.Journal of personalized medicine · 2022Article
- Discriminant analysis and binary logistic regression enable more accurate prediction of autism spectrum disorder than principal component analysis.Scientific reports · 2022Article
- Editorial: The role of epigenetics in neuropsychiatric disorders.Frontiers in molecular neuroscience · 2022Article
- Multi-site harmonization of MRI data uncovers machine-learning discrimination capability in barely separable populations: An example from the ABIDE dataset.NeuroImage. Clinical · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
An ever-evolving understanding of autism spectrum disorder (ASD) pathophysiology necessitates that diagnostic standards also evolve from being observation-based to include quantifiable clinical measurements. The multisystem nature of ASD motivates the use of multivariate methods of statistical analysis over common univariate approaches for discovering clinical biomarkers relevant to this goal. In addition to characterization of important behavioral patterns for improving current diagnostic instruments, multivariate analyses to date have allowed for thorough investigation of neuroimaging-based, genetic, and metabolic abnormalities in individuals with ASD. This review highlights current research using multivariate statistical analyses to quantify the value of these behavioral and physiological markers for ASD diagnosis. A detailed discussion of a blood-based diagnostic test for ASD using specific metabolite concentrations is also provided. The advancement of ASD biomarker research promises to provide earlier and more accurate diagnoses of the disorder.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.