Screening and diagnostic tools for autism spectrum disorder: Systematic review and meta-analysis
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ABSTRACT:
SUBMITTER: Santos C
PROVIDER: S-EPMC10951453 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:Great efforts focus on early detection of autism spectrum disorder, although some scientists and policy-makers have questioned early universal screening. The aim of this meta-analysis was to evaluate the diagnostic accuracy of the different screening tools. Several electronic databases were used to identify published studies. A Bayesian model was used to estimate the screening accuracy. The pooled sensitivity was 0.72 (95% CI 0.61-0.81), and the specificity was 0.98 (95% CI 0.97-0.99). Subgroup analyses to remove heterogeneity indicated sensitivity was 0.77 (95% CI 0.69-0.84), and specificity was 0.99 (95% CI 0.97-0.99; SD ≤ 0.01). Level 1 screening tools for ASD showed consistent statistically significant results and therefore are adequate to detect autism at 14-36 months.
| S-EPMC6483963 | biostudies-literature
Project description:Language disorder is one of the most prevalent developmental disorders and is associated with long-term sequelae. However, routine screening is still controversial and is not universally part of early childhood health surveillance. Evidence concerning the detection accuracy, benefits, and harms of screening for language disorders remains inadequate, as shown in a previous review. In October 2020, a systematic review was conducted to investigate the accuracy of available screening tools and the potential sources of variability. A literature search was conducted using CINAHL Plus, ComDisCome, PsycInfo, PsycArticles, ERIC, PubMed, Web of Science, and Scopus. Studies describing, developing, or validating screening tools for language disorder under the age of 6 were included. QUADAS-2 was used to evaluate risk of bias in individual studies. Meta-analyses were performed on the reported accuracy of the screening tools examined. The performance of the screening tools was explored by plotting hierarchical summary receiver operating characteristic (HSROC) curves. The effects of the proxy used in defining language disorders, the test administrators, the screening-diagnosis interval and age of screening on screening accuracy were investigated by meta-regression. Of the 2,366 articles located, 47 studies involving 67 screening tools were included. About one-third of the tests (35.4%) achieved at least fair accuracy, while only a small proportion (13.8%) achieved good accuracy. HSROC curves revealed a remarkable variation in sensitivity and specificity for the three major types of screening, which used the child's actual language ability, clinical markers, and both as the proxy, respectively. None of these three types of screening tools achieved good accuracy. Meta-regression showed that tools using the child's actual language as the proxy demonstrated better sensitivity than that of clinical markers. Tools using long screening-diagnosis intervals had a lower sensitivity than those using short screening-diagnosis intervals. Parent report showed a level of accuracy comparable to that of those administered by trained examiners. Screening tools used under and above 4yo appeared to have similar sensitivity and specificity. In conclusion, there are still gaps between the available screening tools for language disorders and the adoption of these tools in population screening. Future tool development can focus on maximizing accuracy and identifying metrics that are sensitive to the dynamic nature of language development.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=210505, PROSPERO: CRD42020210505.
| S-EPMC8904415 | biostudies-literature
Project description:ImportanceContemporary studies raise concerns regarding the implications of excessive screen time on the development of autism spectrum disorder (ASD). However, the existing literature consists of mixed and unquantified findings.ObjectiveTo conduct a systematic review and meta-analyis of the association between screen time and ASD.Data sourcesA search was conducted in the PubMed, PsycNET, and ProQuest Dissertation & Theses Global databases for studies published up to May 1, 2023.Study selectionThe search was conducted independently by 2 authors. Included studies comprised empirical, peer-reviewed articles or dissertations published in English with statistics from which relevant effect sizes could be calculated. Discrepancies were resolved by consensus.Data extraction and synthesisThis study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline. Two authors independently coded all titles and abstracts, reviewed full-text articles against the inclusion and exclusion criteria, and resolved all discrepancies by consensus. Effect sizes were transformed into log odds ratios (ORs) and analyzed using a random-effects meta-analysis and mixed-effects meta-regression. Study quality was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. Publication bias was tested via the Egger z test for funnel plot asymmetry. Data analysis was performed in June 2023.Main outcomes and measuresThe 2 main variables of interest in this study were screen time and ASD. Screen time was defined as hours of screen use per day or per week, and ASD was defined as an ASD clinical diagnosis (yes or no) or ASD symptoms. The meta-regression considered screen type (ie, general use of screens, television, video games, computers, smartphones, and social media), age group (children vs adults or heterogenous age groups), and type of ASD measure (clinical diagnosis vs ASD symptoms).ResultsOf the 4682 records identified, 46 studies with a total of 562 131 participants met the inclusion criteria. The studies were observational (5 were longitudinal and 41 were cross-sectional) and included 66 relevant effect sizes. The meta-analysis resulted in a positive summary effect size (log OR, 0.54 [95% CI, 0.34 to 0.74]). A trim-and-fill correction for a significant publication bias (Egger z = 2.15; P = .03) resulted in a substantially decreased and nonsignificant effect size (log OR, 0.22 [95% CI, -0.004 to 0.44]). The meta-regression results suggested that the positive summary effect size was only significant in studies targeting general screen use (β [SE] = 0.73 [0.34]; t58 = 2.10; P = .03). This effect size was most dominant in studies of children (log OR, 0.98 [95% CI, 0.66 to 1.29]). Interestingly, a negative summary effect size was observed in studies investigating associations between social media and ASD (log OR, -1.24 [95% CI, -1.51 to -0.96]).Conclusions and relevanceThe findings of this systematic review and meta-analysis suggest that the proclaimed association between screen use and ASD is not sufficiently supported in the existing literature. Although excessive screen use may pose developmental risks, the mixed findings, the small effect sizes (especially when considering the observed publication bias), and the correlational nature of the available research require further scientific investigation. These findings also do not rule out the complementary hypothesis that children with ASD may prioritize screen activities to avoid social challenges.
| S-EPMC10709772 | biostudies-literature
Project description:Autism Spectrum Disorder (ASD) has traditionally been evaluated and diagnosed via behavioral assessments. However, increasing research suggests that neuroimaging as early as infancy can reliably identify structural and functional differences between autistic and non-autistic brains. The current review provides a systematic overview of imaging approaches used to identify differences between infants at familial risk and without risk and predictive biomarkers. Two primary themes emerged after reviewing the literature: (1) neuroimaging methods can be used to describe structural and functional differences between infants at risk and infants not at risk for ASD (descriptive), and (2) neuroimaging approaches can be used to predict ASD diagnosis among high-risk infants and developmental outcomes beyond infancy (predicting later diagnosis). Combined, the articles highlighted that several neuroimaging studies have identified a variety of neuroanatomical and neurological differences between infants at high and low risk for ASD, and among those who later receive an ASD diagnosis. Incorporating neuroimaging into ASD evaluations alongside traditional behavioral assessments can provide individuals with earlier diagnosis and earlier access to supportive resources.
| S-EPMC9139416 | biostudies-literature
Project description:BackgroundThe aim of this study was to assess the efficiency and safety of acupuncture in core symptomatic improvement of children with autism spectrum disorder (ASD).MethodsWe searched the following databases: Cochrane Library, PubMed, Embase, Medline, China National Knowledge Infrastructure (CNKI), Wanfang, Chinese Science and Technology Periodical (VIP) and Chinese Biological Medicine (CBM), from 1 January 2012 to 25 September 2022. The Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS), and Autism Treatment Evaluation Checklist (ATEC) were adopted as outcome indicators. Three reviewers independently assessed the risk of bias (ROB) and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE)assessment. Utilizing Review Manager (RevMan) 5.3 and Stata 12.0, data were analyzed.ResultsA total of 38 trials were included, and 2862 participants participated in qualitative synthesis and meta-analysis. Only 1 trial was assessed as having a low ROB, and 37 trials were assessed as having an overall high ROB. The quality of evidence for most indicators were considered very low by the GRADE criteria. The results showed that acupuncture groups might have a higher clinical effective rate than nonacupuncture groups (relative risk [RR] = 1.33,95% confidence interval [CI] = 1.25-1.41; heterogeneity: x2=18.15, P = .64, I2 = 0%). Regarding changes in ABC scores, the acupuncture groups might exhibit greater decrease than nonacupuncture groups (MMD = -6.06, 95%CI = -7.25 to -4.87, P < .00001; heterogeneity: x2 =73.37, P = .03, I2 = 77%). In terms of changes in CARS score, acupuncture group may benefit more than nonacupuncture group (MMD = -3.93, 95%CI = 4.90 to -2.95, P < .00001; heterogeneity: x2=234.47, P < .00001, I2 = 90%). Additionally, in terms of ATEC score, acupuncture groups showed more benefit than nonacupuncture groups (MMD = -10.24, 95%CI = -13.09 to -7.38, P < .00001; heterogeneity: x2=45.74, P = .04, I2 = 85%). Both subgroup analysis and sensitivity analysis are existing heterogeneity. Only 1 RCT study involved adverse events with mild symptoms that did not interfere with treatment and evaluation.ConclusionChildren with ASD may benefit from acupuncture because of its effectiveness and safety. Nevertheless, given the low quality of the evidence for the assessed outcomes and the high ROB of analyzed trials, the results should be regarded with caution.
| S-EPMC11309618 | biostudies-literature
Project description:Autism spectrum disorder (ASD) is a neurodevelopmental disorder with complex clinical manifestations that arise between 18 and 36 months of age. Social interaction deficiencies, a restricted range of interests, and repetitive stereotyped behaviors are characteristics which are sometimes difficult to detect early. Several studies show that microRNAs (miRs/miRNAs) are strongly implicated in the development of the disorder and affect the expression of genes related to different neurological pathways involved in ASD. The present systematic review and meta-analysis addresses the current status of miRNA studies in different body fluids and the most frequently dysregulated miRNAs in patients with ASD. We used a combined approach to summarize miRNA fold changes in different studies using the mean values. In addition, we summarized p values for differential miRNA expression using the Fisher method. Our literature search yielded a total of 133 relevant articles, 27 of which were selected for qualitative analysis based on the inclusion and exclusion criteria, and 16 studies evaluating miRNAs whose data were completely reported were ultimately included in the meta-analysis. The most frequently dysregulated miRNAs across the analyzed studies were miR-451a, miR-144-3p, miR-23b, miR-106b, miR150-5p, miR320a, miR92a-2-5p, and miR486-3p. Among the most dysregulated miRNAs in individuals with ASD, miR-451a is the most relevant to clinical practice and is associated with impaired social interaction. Other miRNAs, including miR19a-3p, miR-494, miR-142-3p, miR-3687, and miR-27a-3p, are differentially expressed in various tissues and body fluids of patients with ASD. Therefore, all these miRNAs can be considered candidates for ASD biomarkers. Saliva may be the optimal biological fluid for miRNA measurements, because it is easy to collect from children compared to other biological fluids.
| S-EPMC11424746 | biostudies-literature
Project description:ObjectiveGlutamate plays an important role in brain development, neuronal migration, differentiation, survival and synaptogenesis. Recent studies have explored the relationship between blood glutamate levels and autism spectrum disorder (ASD). However, the findings are inconsistent. We undertook the first systematic review with a meta-analysis of studies examining blood glutamate levels in ASD compared with controls.MethodsA literature search was conducted using PubMed, Embase, and the Cochrane Library for studies published before March 2016. A random-effects model was used to calculate the pooled standardized mean difference (SMD) of the outcomes. Subgroup analyses were used to explore the potential sources of heterogeneity, and the publication bias was estimated using Egger's tests.ResultsTwelve studies involving 880 participants and 446 incident cases were included in this meta-analysis. The meta-analysis provided evidence for higher blood glutamate levels in ASD [SMD = 0.99, 95% confidence interval (95% CI) = 0.58-1.40; P < 0.001] with high heterogeneity (I2 = 86%, P < 0.001) across studies. The subgroup analyses revealed higher glutamate levels in ASD compared with controls in plasma [SMD = 1.04, 95% CI = 0.58-1.50; P < 0.001] but not true in serum [SMD = 0.79, 95% CI = -0.41-1.99; P = 0.20]. Studies employing high performance liquid chromatography (HPLC) or liquid chromatography-tandem mass spectrometry (LC-MS) assays also revealed higher blood glutamate levels in ASD. A sensitivity analysis found that the results were stable, and there was no evidence of publication bias.ConclusionsBlood glutamate levels might be a potential biomarker of ASD.
| S-EPMC4938426 | biostudies-literature
Project description:IntroductionChildren and adolescents with autism spectrum disorder (ASD) appear to be at greater risk of excess weight gain. The aim of this systematic review and meta-analysis was to examine whether children with ASD have a greater prevalence of obesity and whether the prevalence of ASD is higher in children with obesity.MethodsWe conducted a systematic search on PubMed, Scopus, and PsychINFO until May 21, 2021. We used the meta package in the R in order to calculate the pooled prevalence and relative risk of obesity in children with ASD.ResultsWe found 20 eligible studies investigating the prevalence of obesity in children with ASD, with the prevalence ranging from 7.9 to 31.8% and from 1.4 to 23.6% among controls. All but three studies originated from the USA. The proportion of children with obesity in ASD populations was 17% (95% confidence interval [CI]: 13-22). The relative risk of obesity in children with ASD compared with control children was 1.58 (95% CI: 1.34-1.86). There were no controlled studies reporting on the prevalence of ASD in children with obesity.ConclusionChildren and adolescents with ASD have a higher prevalence of obesity than healthy controls. There is a need for further prevalence studies of obesity in children with ASD, especially outside the USA, since the few European studies carried out have failed to show a significant difference between obesity prevalence in children with and without ASD. There is no knowledge at all regarding the prevalence of ASD among children with obesity.
| S-EPMC9210004 | biostudies-literature
Project description:Youngest students in their class, with birthdates just before the school entry cut-off date, are overrepresented among children receiving an Attention-Deficit/Hyperactivity Disorder (ADHD) diagnosis or medication for this. This is known as the relative age effect. This systematic review and meta-analysis summarises the evidence on the influence of relative age on ADHD symptoms, diagnosis and medication prescribing. As no review to date has investigated the association with autism spectrum disorder (ASD) diagnosis, this is also examined. Following prospective registration with PROSPERO, we conducted a systematic review according to the PRISMA guidelines. We searched seven databases: Medline, Embase, PsycInfo, Web of Science Core Collection, ERIC, Psychology and Behavioural Sciences Collection, and Cochrane Library. Additional references were identified from manual search of retrieved reviews. We performed a meta-analysis of quantitative data. Thirty-two studies were included, thirty-one investigated ADHD and two ASD. Younger relative age was associated with ADHD diagnosis and medication, with relative risks of 1.38 (1.36-1.52 95% CI) and 1.28 (1.21-1.36 95% CI) respectively. However, risk estimates exhibited high heterogeneity. A relative age effect was observed for teacher ratings of ADHD symptoms but not for parent ratings. With regard to ASD, the youngest children in their school year were more likely to be diagnosed with ASD. This review confirms a relative age effect for ADHD diagnosis and prescribed ADHD medication and suggests that differences in teacher and parent ratings might contribute to this. Further research is needed on the possible association with ASD.
| S-EPMC11868292 | biostudies-literature
Project description:The suggested overlap between autism spectrum disorder (ASD) and gender dysphoria/incongruence (GD/GI) has been much disputed. This review showed a relationship between ASD traits and GD feelings in the general population and a high prevalence of GD/GI in ASD. Our meta-analyses revealed that the pooled estimate of the prevalence of ASD diagnoses in GD/GI people was 11% (p < .001) and the overall effect size of the difference in ASD traits between GD/GI and control people was significant (g = 0.67, p < .001). Heterogeneity was high in both meta-analyses. We demonstrated that the chances that there is not a link between ASD and GD/GI are negligible, yet the size of it needs further investigation.
| S-EPMC10313553 | biostudies-literature