Let's Be Clear That "Autism Spectrum Disorder Symptoms" Are Not Always Related to Autism Spectrum Disorder

Superior temporal sulcus folding, functional network connectivity, and autistic-like traits in a non-clinical population

BACKGROUND

Autistic-like traits (ALT) are prevalent across the general population and might be linked to some facets of a broader autism spectrum disorder (ASD) phenotype. Recent studies suggest an association of these traits with both genetic and brain structural markers in non-autistic individuals, showing similar spatial location of findings observed in ASD and thus suggesting a potential neurobiological continuum.

METHODS

In this study, we first tested an association of ALTs (assessed with the AQ questionnaire) with cortical complexity, a cortical surface marker of early neurodevelopment, and then the association with disrupted functional connectivity. We analysed structural T1-weighted and resting-state functional MRI scans in 250 psychiatrically healthy individuals without a history of early developmental disorders, in a first step using the CAT12 toolbox for cortical complexity analysis and in a second step we used regional cortical complexity findings to apply the CONN toolbox for seed-based functional connectivity analysis.

RESULTS

Our findings show a significant negative correlation of both AQ total and AQ attention switching subscores with left superior temporal sulcus (STS) cortical folding complexity, with the former being significantly correlated with STS to left lateral occipital cortex connectivity, while the latter showed significant positive correlation of STS to left inferior/middle frontal gyrus connectivity (n = 233; all p < 0.05, FWE cluster-level corrected). Additional analyses also revealed a significant correlation of AQ attention to detail subscores with STS to left lateral occipital cortex connectivity.

LIMITATIONS

Phenotyping might affect association results (e.g. choice of inventories); in addition, our study was limited to subclinical expressions of autistic-like traits.

CONCLUSIONS

Our findings provide further evidence for biological correlates of ALT even in the absence of clinical ASD, while establishing a link between structural variation of early developmental origin and functional connectivity.

Are autistic traits associated with a social-emotional memory bias?

Autistic traits are associated with differential processing of emotional and social cues. By contrast little is known about the relationship of autistic traits to socio-emotional memory, though research suggests an integral relationship between episodic memory processes and psychosocial well-being. Using an experimental paradigm, we tested if autistic traits moderate the effects of negative emotion and social cues on episodic memory (i.e. memory for past events). Young adults (N = 706) with varied levels of self-reported autistic traits (24% in clinical range) encoded images stratified by emotion (negative, neutral) and social cues (social, non-social) alongside a neutral object. After 24 h, item memory for images and associative memory for objects was tested. For item memory, after controlling for anxiety, a small effect emerged whereby a memory-enhancing effect of social cues was reduced as autistic traits increased. For associative memory, memory for pairings between neutral, but not negative, images reduced as autistic traits increased. Results suggest autistic traits are associated with reduced ability to bind neutral items together in memory, potentially impeding nuanced appraisals of past experience. This bias toward more negative, less nuanced memories of past experience may represent a cognitive vulnerability to social and mental health challenges commonly associated with autistic traits and a potential intervention target.

Measuring autism-associated traits in the general population: Factor structure and measurement invariance across sex and diagnosis status of the Social Communication Questionnaire

LAY ABSTRACT

Using questionnaires in research relies on the expectation that they measure the same things across different groups of individuals. If this is not true, then interpretations of results can be misleading when researchers compare responses across different groups of individuals or use in it a group that differs from that in which the questionnaire was developed. For the questionnaire we investigated, the Social Communication Questionnaire (SCQ), we found that parents of boys and girls responded to questionnaire items in largely the same way but that the SCQ measured traits and behaviors slightly differently depending on whether the children had autism. Based on these results, we concluded that researchers using this questionnaire should carefully consider these differences when deciding how to interpret findings. SCQ scores as a reflection of "autism-associated traits" in samples that are mostly or entirely made up of individuals without an autism diagnosis may be misleading and we encourage a more precise interpretation of scores as a broader indication of social-communicative and behavioral traits.

A Mixed-methods Examination of Culturally Responsive Adaptation to an Evidence-based Parent-mediated Intervention Implemented for Autistic Children

Parent-mediated interventions (PMIs) are considered an evidence-based practice for fostering social communication skills in young autistic children and for promoting parent responsivity and empowerment, yet barriers to caregiver engagement are evident when PMIs are implemented within historically underserved community settings. Issues of caregiver engagement can reflect a lack of fit between PMIs and the needs of diverse families. We used a mixed methods approach to examine barriers to participating in an evidence-based PMI, Project ImPACT (Ingersoll & Dvortcsak, 2019), within an outpatient setting, as well as strategies that clinicians reported using to deliver and adapt Project ImPACT for minoritized families. Participants included 134 caregivers of a child 13 to 48 months with autism or other social communication differences and six clinicians delivering Project ImPACT. Findings suggest that caregivers experience barriers to participating in Project ImPACT and that these barriers are associated with caregivers' ability to complete the program. Although quantitative findings indicate that adaptation to Project ImPACT did not differ by caregiver and child background, qualitative findings highlighted that clinicians attempt to deliver Project ImPACT to respond to the needs of families from minoritized backgrounds by actively considering the family's culture, psychosocial experiences, goals, and specific barriers. Further, both qualitative and quantitative findings suggest that culturally responsive care and adaptations may support caregiver engagement, including rapport, trust, buy-in, and attendance. Approaches to center cultural alongside contextual/psychosocial considerations within family-centered care in the implementation of PMIs are also highlighted.

Differential Diagnosis of Autism and Other Neurodevelopmental Disorders

This article discusses the diagnostic criteria for autism spectrum disorder (ASD), as well as other neurodevelopmental disorders that may be confused with or co-occur with ASD. Practitioners involved in diagnostic assessment of ASD must be well versed in the features that differentiate ASD from other conditions and be familiar with how co-occurring conditions may manifest in the context of ASD. ASD symptoms present differently across development, underscoring the need for training about typical developmental expectations for youth. Periodic reevaluations throughout development are also important because support needs for individuals with autism change over time.

Autism spectrum disorder in ICD-11-a critical reflection of its possible impact on clinical practice and research

This perspective article compares and contrasts the conceptualization of Autism Spectrum Disorder (ASD) in ICD-11 and DSM-5. By guiding the user through the ICD-11 text, it is argued that, in contrast to DSM-5, ICD-11 allows a high variety in symptom combinations, which results in an operationalization of ASD that is in favor of an extreme diverse picture, yet possibly at the expense of precision, including unforeseeable effects on clinical practice, care, and research. The clinical utility is questionable as this conceptualization can hardly be differentiated from other mental disorders and autism-like traits. It moves away from an observable, behavioral, and neurodevelopmental disorder to a disorder of inner experience that can hardly be measured objectively. It contains many vague and subjective concepts that lead to non-falsifiable diagnoses. This bears a large danger of false positive diagnoses, of further increased prevalence rates, limitations of access to ASD-specific services and of increasing the non-specificity of treatments. For research, the hypothesis is that the specificity of ASD will be reduced and this will additional increase the already high heterogeneity with the effect that replication of studies will be hampered. This could limit our understanding of etiology and biological pathways of ASD and bears the risk that precision medicine, i.e., a targeted approach for individual treatment strategies based on precise diagnostic markers, is more far from becoming reality. Thus, a more precise, quantitative description and more objective measurement of symptoms are suggested that define the clinical ASD phenotype. Identification of core ASD subtypes/endophenotypes and a precise description of symptoms is the necessary next step to advance diagnostic classification systems. Therefore, employing a more finely grained, objective, clinical symptom characterization which is more relatable to neurobehavioral concepts is of central significance.

Maternal Autistic Traits and Adverse Birth Outcomes

Importance

Women with a high level of autistic traits in the general population may experience larger health disparities during pregnancy, particularly women diagnosed with autism spectrum disorder (ASD), which in turn may be associated with increased risk of adverse birth outcomes.

Objective

To investigate the association between maternal autistic traits and the risk of adverse birth outcomes in the general population.

Design, Setting, and Participants

This cohort study included mothers of singletons from a nationwide, multicenter prospective birth cohort, the Japan Environmental Children's Study. Expecting mothers were recruited between January 2011 and March 2014. Data were analyzed between June 2021 and November 2023.

Exposures

Autistic traits were self-reported during the second and third trimesters using the short form of the Autism-Spectrum Quotient Japanese version (AQ-J10) (score range, 0-10; clinical range, ≥7).

Main Outcomes and Measures

Data on preterm birth (<37 weeks' gestation) and neonates born small for gestational age (SGA) were transcribed from medical records. Additional analysis of gestational age groups (very preterm birth, <32 weeks' gestation; moderate-to-late preterm birth, 32-36 weeks' gestation) was also performed.

Results

Among 87 687 women (mean [SD] age, 31.2 [5.0] years) included in the study, 2350 (2.7%) had AQ-J10 scores within the clinical range yet only 18 (0.02%) were diagnosed with ASD. A higher AQ-J10 score was associated with an increased risk of all birth outcomes, including preterm births (relative risk [RR] per 1-SD increase, 1.06; 95% CI, 1.03-1.09), moderate-to-late preterm births (RR per 1-SD increase, 1.05; 95% CI, 1.01-1.08), very preterm births (RR per 1-SD increase, 1.16; 95% CI, 1.06-1.26), and child born SGA (RR per 1-SD increase, 1.04; 95% CI, 1.01-1.06) after adjusting for maternal and pregnancy-related factors. The risks of all outcomes increased with higher AQ-J10 scores; compared with women below the clinical range, women within the clinical range had greater risk of preterm births (RR, 1.16; 95% CI, 1.07-1.26), moderate-to-late preterm births (RR, 1.12; 95% CI, 1.03-1.22), very preterm births (RR, 1.49; 95% CI, 1.18-1.89), and a child born SGA (RR, 1.11; 95% CI, 1.04-1.19).

Conclusions and Relevance

In this cohort study, higher level of maternal autistic traits was associated with increased risk of adverse birth outcomes, particularly very preterm birth. Acknowledging the risks and providing tailored and timely antenatal care support to women with a high level of autistic traits in the general population, particularly women with autistic traits within the clinical range, regardless of formal diagnosis, is warranted.

Associations between autism traits and family functioning over time in autistic and non-autistic children

LAY ABSTRACT

Little is known about family functioning over time when raising a child with autism traits, with or without a clinical autism diagnosis. Therefore, we asked caregivers-mostly parents-of a group of 168 children about the family functioning and the child's emotional and behavioral characteristics, as well as autistic traits, twice with about 1 year in between. For numerous reasons, the children were referred to youth mental health care centers, including child and adolescent psychiatric services. Care as usual was offered after the diagnostic assessment if a clinical diagnosis was the assessment outcome. Caregivers reported less problematic family functioning in children with fewer autism traits over time. The child's additional emotional or behavioral characteristics did not seem to influence this relation. Furthermore, we split the whole group into autistic children with a clinical autism diagnosis (58%) and non-autistic children with autism traits but without a clinical diagnosis (42%) to see whether we would find the same results in both groups. Surprisingly, the relation between family functioning and the level of a child's autism traits only held for the subgroup of non-autistic children with autism traits. Thus, raising children with autism traits without a clinical diagnosis may affect family functioning over time. We think that families might have difficulty understanding and adjusting to the autism traits of their children but are lacking the support that is exclusively offered to families of children with a clinical autism diagnosis. We must be cautious because we do not know whether there is a causal relation. Although further research is needed to explore and learn to understand this result, clinicians might consider offering support to families of children with subthreshold autism to prevent problems in family functioning. Because high autism trait levels in non-autistic children may be of a different origin than autism, for example, other neurodevelopmental or mental health problems, family training or support should be tailored to the child's underlying difficulties.

Probabilistic Learning of Cue-Outcome Associations is not Influenced by Autistic Traits

According to Bayesian/predictive coding models of autism, autistic individuals may have difficulties learning probabilistic cue-outcome associations, but empirical evidence has been mixed. The target cues used in previous studies were often straightforward and might not reflect real-life learning of such associations which requires learners to infer which cue(s) among many to track. Across two experiments, we compared adult learners with varying levels of autistic traits on their ability to infer the correct cue to learn probabilistic cue-outcome associations when explicitly instructed to do so or when exposed implicitly. We found no evidence for the effect of autistic traits on probabilistic learning accuracy, contrary to the predictions of Bayesian/predictive coding models. Implications for the current Bayesian/predictive coding models are discussed.

What are quantitative traits and how can they be used in autism research?

Quantitative traits are measurable characteristics distributed along a continuous scale thought to relate to underlying biology. There is growing interest in the use of quantitative traits in behavioral and psychiatric research, particularly in research on conditions diagnosed based on reports of behaviors, including autism. This brief commentary describes quantitative traits, including defining what they are, how we can measure them, and key considerations for their use in autism research. Examples of measures include behavioral report scales like the Social Responsiveness Scale and Broader Autism Phenotype Questionnaire, as well as biological measurements, like certain neuroimaging metrics; such measures can capture quantitative traits or constructs like the broader autism phenotype, social communication, and social cognition. Quantitative trait measures align with the Research Domain Criteria (RDoC) approach and can be used in autism research to help gain a better understanding of causal pathways and biological processes. They can also be used to aid identification of genetic and environmental factors involved in such pathways, and thereby lead to an understanding of influences on traits across the entire population. Finally, in some cases, they may be used to gauge treatment response, and assist screening and clinical characterization of phenotype. In addition, practical benefits of quantitative trait measures include improved statistical power relative to categorical classifications and (for some measures) efficiency. Ultimately, research across autism fields may benefit from incorporating quantitative trait measures as a complement to categorical diagnosis to advance understanding of autism and neurodevelopment.

Commentary: Best practices and processes for assessment of autism spectrum disorder - the intended role of standardized diagnostic instruments

Development of standardized diagnostic instruments has facilitated the systematic characterization of individuals with autism spectrum disorders (ASD) in clinical and research settings. However, overemphasis on scores from specific instruments has significantly detracted from the original purpose of these tools. Rather than provide a definitive "answer," or even a confirmation of diagnosis, standardized diagnostic instruments were designed to aid clinicians in the process of gathering information about social communication, play, and repetitive and sensory behaviors relevant to diagnosis and treatment planning. Importantly, many autism diagnostic instruments are not validated for certain patient populations, including those with severe vision, hearing, motor, and/or cognitive impairments, and they cannot be administered via a translator. In addition, certain circumstances, such as the need to wear personal protective equipment (PPE), or behavioral factors (e.g., selective mutism) may interfere with standardized administration or scoring procedures, rendering scores invalid. Thus, understanding the uses and limitations of specific tools within specific clinical or research populations, as well as similarities or differences between these populations and the instrument validation samples, is paramount. Accordingly, payers and other systems must not mandate the use of specific tools in cases when their use would be inappropriate. To ensure equitable access to appropriate assessment and treatment services, it is imperative that diagnosticians be trained in best practice methods for the assessment of autism, including if, how, and when to appropriately employ standardized diagnostic instruments.

A systematic review of predictors of suicidal thoughts and behaviors among autistic adults: Making the case for the role of social connection as a protective factor

Autistic adults are a high-risk population for suicidal thoughts and behaviors (STBs). Accordingly, this systematic review aims to review the prevalence of STBs among autistic adults, review the risk and protective factors for STBs in autistic adults, and formulate a disorder-specific conceptualization of risk in this population. We systematically searched PsycINFO and Google Scholar for all studies published prior to March 28th, 2022. We included empirical articles focused on autistic adults, ages 18 years and older, reporting on suicide-related outcomes. In total, 45 peer-reviewed empirical articles were included in the current systematic review. The most frequently studied factors in relation to suicide risk among autistic adults were interpersonal constructs (42.4% of total studies looking at risk/protective factors) and depressive symptoms (36.4% of total studies looking at risk/protective factors). We conclude by summarize two key content areas: exploring social and interpersonal constructs and better understanding the role of depressive symptoms in autism. As researchers continue to explore STBs among autistic adults, it will be necessary to addressing the overreliance on autistic symptoms instead of autism diagnoses, measurement issues of STBs, and a need for treatment adaptations.

Contributions of face processing, social anhedonia and mentalizing to the expression of social autistic-like traits

Introduction

Quantitative autistic-like traits (QATs) are a constellation of traits that mirror those of clinical autism and are thought to share the same mechanisms as the condition. There is great interest in identifying the genetic and neurobiological basis of QATs, but progress is hindered by the composite nature of these clinically based constructs. Social QATs are defined according to the diagnostic criteria for autism, comprising multiple potential neural mechanisms that may contribute to varying degrees. The objective of this study was to decompose social QATs into more specific constructs, in line with the Research Domain Criteria (RDoC). We chose constructs with trait-like properties and known or suggested significance for autistic social function: (1) social anhedonia, (2) prosopagnosia (face blindness), and (3) mentalizing (attributing mental states to images of eyes). We hypothesized that these constructs may all contribute to observed variance in social QATs.

Methods

We recruited 148 adults with a broad range of QATs (mean age 37.9 years, range 18-69; 50% female; 5.4% autistic) to an experimental behavioral study conducted online. We estimated social QATs using the social factor of the Comprehensive Autistic Traits Inventory. We used the Oxford Face Matching Task and the Reading the Mind in the Eyes Test to measure face matching ability and mentalizing, respectively. Social anhedonia traits were measured with the Anticipatory and Consummatory Interpersonal Pleasure Scale, and prosopagnosic traits with the 20-item Prosopagnosia Index. A combination of frequentist and Bayesian statistics was used to test the social constructs as predictors of social QATs.

Results

We found that social anhedonic traits, prosopagnosic traits, and face matching performance were likely predictors of social QATs, whereas mentalizing showed limited contribution.

Conclusion

The findings support prosopagnosic and anhedonic traits, but not mentalizing deficits, as dimensional predictors of individual differences in social function across the autistic spectrum. Further, the study strongly suggests that social reward systems and face processing networks play significant and independent roles in autistic-like social function.

Autistic traits heighten sensitivity to rejection-induced social pain

Autistic traits-subclinical forms of characteristics associated with autism spectrum disorders-are associated with poor social interactions and high risks for mental health disorders. We hypothesized that altered sensitivity to social rejection is an important contributor to psychological distress observed among individuals with high autistic traits. Experiment 1 adopted a social-judgment task and compared behavioral and neural activity in response to social rejection between participants exhibiting either high or low autistic traits (HAT and LAT, respectively). Rejection-induced hurt feelings, P3 amplitudes, and θ-oscillation magnitudes were greater in the HAT group than in the LAT group. Mediation analysis indicated that autistic traits heighten rejection-induced social pain through increasing frontal-midline θ-oscillations. Responses to nonsocial feedback in the age-judgment task were comparable, confirming that the between-group differences were specific to social negative feedback. Experiment 2 assessed the association between autistic traits, rejection sensitivity, and psychological distress among randomly recruited participants. Results showed that autistic traits affected depressive/anxious symptomatology partially through heightened rejection sensitivity. Therefore, autistic traits heighten sensitivity to rejection-induced social pain that leads to psychological distress. This finding will help facilitate the development of strategies for coping with social pain and improving mental health for individuals with high autistic traits.

Representativeness of autistic samples in studies recruiting through social media

Survey-based research with recruitment through online channels is a convenient way to obtain large samples and has recently been increasingly used in autism research. However, sampling from online channels may be associated with a high risk of sampling bias causing findings not to be generalizable to the autism population. Here we examined autism studies that have sampled on social media for markers of sampling bias. Most samples showed one or more indicators of sampling bias, in the form of reversed sex ratio, higher employment rates, higher education level, lower fraction of individuals with intellectual disability, and later age of diagnosis than would be expected when comparing with for example population study results from published research. Findings from many of the included studies are therefore difficult to generalize to the broader autism population. Suggestions for how research strategies may be adapted to address some of the problems are discussed. LAY SUMMARY: Online surveys offer a convenient way to recruit large numbers of participants for autism research. However, the resulting samples may not fully reflect the autism population. Here we investigated the samples of 36 autism studies that recruited participants online and found that the demographic composition tended to deviate from what has been reported about the autism population in previous research. The results may thus not be generalizable to autism in general.

Bias in measurement of autism symptoms by spoken language level and non-verbal mental age in minimally verbal children with neurodevelopmental disorders

Increasing numbers of children with known genetic conditions and/or intellectual disability are referred for evaluation of autism spectrum disorder (ASD), highlighting the need to refine autism symptom measures to facilitate differential diagnoses in children with cognitive and language impairments. Previous studies have reported decreased specificity of ASD screening and diagnostic measures in children with intellectual disability. However, little is known about how cognitive and language abilities impact the measurement of specific ASD symptoms in this group. We aggregated a large sample of young children (N = 1196; aged 31-119 months) to examine measurement invariance of ASD symptoms among minimally verbal children within the context of the Autism Diagnostic Observation Schedule (ADOS) Module 1. Using confirmatory factor analysis (CFA) and moderated non-linear factor analysis (MNLFA), we examined how discrete behaviors were differentially associated with the latent symptom domains of social communication impairments (SCI) and restricted and repetitive behaviors (RRB) across spoken language levels and non-verbal mental age groupings. While the two-factor structure of SCI and RRB held consistently across language and cognitive levels, only partial invariance was observed for both ASD symptom domains of SCI and RRB. Specifically, four out of the 15 SCI items and one out of the three RRB items examined showed differential item functioning between children with "Few to No Words" and those with "Some Words"; and one SCI item and one RRB item showed differential item functioning across non-verbal mental age groups. Moreover, even after adjusting for the differential item functioning to reduce measurement bias across groups, there were still differences in ASD symptom domain scores across spoken language levels. These findings further underscore the influence of spoken language level on measurement of ASD symptoms and the importance of measuring ASD symptoms within refined spoken language levels, even among those with minimal verbal abilities.

The role of alexithymia and autistic traits in predicting quality of life in an online sample

BACKGROUND

Autistic people tend to report poorer Quality of Life (QOL) than comparison groups, though some studies do report more optimistic findings. Higher autistic traits are also related to poorer QOL. However, the role of alexithymia in this relationship has not been explored.

METHOD

A total of 163 participants (N = 53 autistic and N = 111 comparison) consented to take part; however, 30 participants were excluded due to missing data (who did not differ from those who were retained on age, gender, education, employment, or living status), leaving a final sample of 133 (N = 42 Autistic and 91 Comparison participants). Demographic information (including age, gender) was collected, alongside self-report measures of autistic traits, mental health, alexithymia, and QOL. We estimated regression models based on pre-registered analysis, and we conducted exploratory network analyses.

RESULTS

Alexithymic traits did not predict QOL when controlling for covariates. Depression significantly predicted Physical, Psychological, and Social QOL. When examining the impact of just alexithymic traits and autistic traits, both were significantly associated with Physical and Psychological QOL. For participants with a low depression score, the correlation between alexithymia and QOL was strong; suggesting that depression occludes the association between alexithymia and QOL. Network analyses suggested that depression and anxiety exert direct effects on Physical and Psychological QOL, whereas alexithymia scores may influence Physical QOL via autistic traits.

CONCLUSION

In sum, depression is a pervasive negative predictor of multiple QOL domains. The role of alexithymia in predicting QOL dimensionally and categorically was not ruled out, given our exploratory analyses, we suggest that interventions which target alexithymia may positively impact QOL for those who score low on depressive symptoms.

Childhood diagnoses in individuals identified as autistics in adulthood

Background

Autism is a developmental condition, where symptoms are expected to occur in childhood, but a significant number of individuals are diagnosed with autism for the first time in adulthood. Here, we examine diagnoses given in childhood among individuals that are diagnosed with autism in adulthood, to investigate whether the late autism diagnosis might be explained by misdiagnosis in childhood or diagnostic overshadowing.

Methods

Through the Danish National Patient Registry, we identified individuals diagnosed with autism in adulthood (N = 2199), as well as a control sample with no records of an autism diagnosis (N = 460,798) and calculated how many had received different psychiatric or neurological diagnoses in childhood.

Results

We found that most childhood diagnoses were overrepresented in those with an adult autism diagnosis, and attention-deficit hyperactivity disorder, affective disorders, anxiety, and stress disorders were the most prevalent childhood conditions in this group. However, 69% of males and 61% of females with adult autism diagnoses were not found to have received any of the investigated diagnoses before 18 years of age, and most childhood diagnoses were given after the age of 12.

Limitations

Milder to moderate cases of psychiatric conditions that have been solely treated by family physicians or school psychologists may not be fully included in our dataset. The study is based on data from the Danish health care system, and further research is needed to assess whether the findings can be generalized to other countries.

Conclusion

A majority of those with an adult autism diagnosis had no records of having received any of the investigated diagnoses in childhood. In these cases, the late autism diagnosis is therefore unlikely to be explained by either misdiagnosis or overshadowing. This result is at odds with the prevailing notion that autistic symptoms tend to diminish with age. Therefore, further research is warranted to examine how and if early signs of autism may have manifested among these individuals, and how similar they are to autistic people diagnosed earlier in their development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-021-00478-y.

Time-to-event estimation of birth prevalence trends: A method to enable investigating the etiology of childhood disorders including autism

An unbiased, widely accepted estimate of the rate of occurrence of new cases of autism over time would facilitate progress in understanding the causes of autism. The same may also apply to other disorders. While incidence is a widely used measure of occurrence, birth prevalence-the proportion of each birth year cohort with the disorder-is the appropriate measure for disorders and diseases of early childhood. Studies of autism epidemiology commonly speculate that estimates showing strong increases in rate of autism cases result from an increase in diagnosis rates rather than a true increase in cases. Unfortunately, current methods are not sufficient to provide a definitive resolution to this controversy. Prominent experts have written that it is virtually impossible to solve. This paper presents a novel method, time-to-event birth prevalence estimation (TTEPE), to provide accurate estimates of birth prevalence properly adjusted for changing diagnostic factors. It addresses the shortcomings of prior methods. TTEPE is based on well-known time-to-event (survival) analysis techniques. A discrete survival process models the rates of incident diagnoses by birth year and age. Diagnostic factors drive the probability of diagnosis as a function of the year of diagnosis. TTEPE models changes in diagnostic criteria, which can modify the effective birth prevalence when new criteria take effect. TTEPE incorporates the development of diagnosable symptoms with age. General-purpose optimization software estimates all parameters, forming a non-linear regression. The paper specifies all assumptions underlying the analysis and explores potential deviations from assumptions and optional additional analyses. A simulation study shows that TTEPE produces accurate parameter estimates, including trends in both birth prevalence and the probability of diagnosis in the presence of sampling effects from finite populations. TTEPE provides high power to resolve small differences in parameter values by utilizing all available data points.