Autism spectrum disorder: Consensus guidelines on assessment, treatment and research from the British Association for Psychopharmacology

Howes, Oliver; Rogdaki, Maria; Findon, James; Wichers, Robert; Charman, Tony; King, Bryan H.; Loth, Eva; McAlonan, Gráinne; McCracken, James T.; Parr, Jeremy; Povey, Carol; Santosh, Paramala; Wallace, Simon; Simonoff, Emily; Murphy, Declan

doi:10.1177/0269881117741766

Cited by 233 publications

(202 citation statements)

References 278 publications

(347 reference statements)

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“…While most treatment approaches are early intensive behavioral intervention (EIBI) and naturalistic developmental behavioral intervention (NDRI), the existing literature suggests that they have variable levels of effectiveness and in some cases may not significantly affect core autism features such as social-communication difficulties [59][60][61][62][63] . Currently there are also no medical treatments that significantly affect the core characteristics of autism 64,65 . Rather than advocating a 'one-size-fits-all' approach to treatment, most recent best practice recommendations specifically highlight the critical need for future research to identify factors that explain heterogeneity in response to treatment, in order to better individualize treatment approaches and to better target changes in core symptomatology 59,63 .Heterogeneity also limits basic scientific progress towards understanding autism.…”

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confidence: 99%

Big data approaches to decomposing heterogeneity across the autism spectrum

Lombardo

Lai

Baron‐Cohen

2018

Preprint

120

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Autism is a diagnostic label based on behavior. While the diagnostic criteria attempts to maximize clinical consensus, it also masks a wide degree of heterogeneity between and within individuals at multiple levels of analysis. Understanding this multi-level heterogeneity is of high clinical and translational importance. Here we present organizing principles to frame the work examining multi-level heterogeneity in autism. Theoretical concepts such as 'spectrum' or 'autisms' reflect non-mutually exclusive explanations regarding continuous/dimensional or categorical/qualitative variation between and within individuals. However, common practices of small sample size studies and case-control models are suboptimal for tackling heterogeneity. Big data is an important ingredient for furthering our understanding heterogeneity in autism. In addition to being 'feature-rich', big data should be both 'broad' (i.e. large sample size) and 'deep' (i.e. multiple levels of data collected on the same individuals). These characteristics help ensure the results from a population are more generalizable and facilitate evaluation of the utility of different models of heterogeneity. A model's utility can be shown by its ability to explain clinically or mechanistically important phenomena, but also by explaining how variability manifests across different levels of analysis. The directionality for explaining variability across levels can be bottom-up or top-down, and should include the importance of development for characterizing change within individuals. While progress can be made with 'supervised' models built upon a priori or theoretically predicted distinctions or dimensions of importance, it will become increasingly important to complement such work with unsupervised data-driven discoveries that leverage unknown and multivariate distinctions within big data. Without a better understanding of how to model heterogeneity between autistic people, progress towards the goal of precision medicine may be limited.. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/278788 doi: bioRxiv preprint first posted online Mar. 9, 2018; 3 Autism occurs in approximately 1-2% of the population 1 and autistic individuals'wellbeing is a major public health issue. In economic terms, the lifetime individual cost of autism is estimated at $2.4 (£1.5) million in the USA and UK and annual population costs are around $268 billion in the USA 2,3 . While interest in and science on autism has been growing rapidly, progress towards translating scientific knowledge into high-impact clinical practice has been less rapid. We are still far from delivering more effective intervention and support, more precise and earlier diagnosis, better understanding and prediction of prognosis and development, and personalization of support and intervention. All of these points are within the scope of stratified psychiatry 4 and precision me...

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confidence: 99%

Big data approaches to decomposing heterogeneity across the autism spectrum

Lombardo

Lai

Baron‐Cohen

2018

Preprint

120

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“…The authors seem to agree that exogenous melatonin improves sleep delay as well as extends overall sleep duration in the group of patients with ASD and ADHD. British Society of Psychopharmacology in 2018 [121] based on Rossignol and Frye data from 2011 (evidence level Ia) [107] and Cortesi et al from 2012 (evidence level Ib) [90] recommends the use of melatonin in children with ASD. Data on the effects of melatonin on behavior are less numerous.…”

Section: Discussionmentioning

confidence: 99%

Efficacy and Safety of Melatonin Treatment in Children with Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder—A Review of the Literature

Rzepka-Migut¹,

Paprocka

2020

Brain Sciences

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Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental disorders with disturbed melatonin secretion profile and sleep problems. The growing incidence of ASD and ADHD inspires scientists to research the underlying causes of these conditions. The authors focused on two fundamental aspects, the first one being the presentation of the role of melatonin in ASD and ADHD and the second of the influence of melatonin treatment on sleep disorders. The authors present the use of melatonin both in the context of causal and symptomatic treatment and discuss melatonin supplementation: Dosage patterns, effectiveness, and safety. Sleep disorders may have a different clinical picture, so the assessment of exogenous melatonin efficacy should also refer to a specific group of symptoms. The review draws attention to the wide range of doses of melatonin used in supplementation and the need to introduce unified standards especially in the group of pediatric patients.Brain Sci. 2020, 10, 219 2 of 21 requiring flexibility and behavioral problems [9]. In the presented disorders, the clinical picture is heterogeneous [10] and the etiology is still unclear [11].Autism spectrum disorder (ASD) can be defined based on the diagnostic criteria which include communication and social interaction disorders and limited repetitive patterns of behavior and interests. In addition to the fundamental symptoms, many patients also present with anxiety attacks, (self)-aggression, mood disorders, and sleep difficulties [12,13]. The first symptoms of autism are observed already in early childhood and usually persist throughout life. An increase in the incidence of ASD has been reported over recent years. According to the CDC's Autism and Developmental Disabilities Monitoring (ADDM) report in 2000 the incidence of ASD was estimated at 1 in 150 children, in 2014 this incidence was 1 diagnosis in 59 children at the age of 8 [14]. The causes of this tendency may be different, e.g., a higher standard of medical and diagnostic care [15], higher social awareness, and the older age of parents at childbearing [16,17]. The etiology of ASD is most likely multifactorial [11], being the result of genetic and environmental factors [6]. Hallmayer et al. indicated the predominance of environmental factors, estimating the shared environmental component to be 58% and heritability to 38%. This distribution was similar among women and men [18]. So far multiple potential risk factors for ASD have been reported in the literature, including the use of illicit drugs during pregnancy, medications, organophosphate pesticides [19], fatty acid deficiency [20], gestational diabetes, and low birth weight [11]. Despite numerous scientific studies, no genetic abnormality that would account for more than 1% of ASD has been identified yet [11]. One of the hypothesis defines ASD as a collection of many forms of a rare monogenic disorder with a different etiology [21]. Ten percent of ASD can be explained as a component of a specific genetic sy...

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“…For example, mood dysregulation with its clinical manifestations of irritability can be a target for pharmacotherapy 51. Clinical trials to test risperidone and aripiprazole for irritability in the context of neurodevelopmental disorders such as autism have already led to the acceptance of this construct, which is not per se a diagnostic category, by drug regulatory authorities 52. Likewise, psychopharmacology aimed at evaluating treatments for mood dysregulated youths seems to be an innovative approach to address an important clinical need.…”

Section: Unmet Needsmentioning

confidence: 99%

Twenty years of progress in paediatric psychopharmacology: accomplishments and unmet needs

Vitiello

Davico

2018

Evid Based Mental Health

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The systematic assessment of the efficacy and safety of psychiatric medications in children and adolescents started about 20 years ago. Since then, a considerable number of randomised clinical trials have been conducted, including also a series of publicly funded comparative effectiveness studies to evaluate the therapeutic benefit of medications relative to psychosocial interventions, alone or combined with medications. On the whole, these studies have been informative of the paediatric pharmacokinetics, efficacy and safety of the most commonly used psychotropics. As a consequence, a number of meta-analyses have been conducted that have documented both the benefits and harms of the most common medication groups, such as stimulants, antidepressants and antipsychotics. Evidence-based practice guidelines have been produced, and clinicians can now better estimate the therapeutic value and the risk of treatment, at least at the group mean level. However, most clinical trials have been conducted in research settings, and this limits the generalisability of the results. There is a need for evaluating treatment effects under usual practice conditions, through practical trials. The ongoing debate about the proper role of pharmacotherapy in child mental health can be advanced by comparative effectiveness research to assess the benefit/risk ratio of pharmacotherapy vis-à-vis alternative treatment modalities. In addition, analyses of large population databases can better inform on the impact of early treatment on important distal outcomes, such as interpersonal functioning, social and occupational status, quality of life and risk for disability or mortality. Thus far, paediatric psychopharmacology has been mostly the application to children of medications that were serendipitously discovered and developed for adults. By focusing on the neurobiological mechanisms of child psychopathology, it may be possible to identify more precise pharmacological targets and arrive at a truly developmental psychopharmacology.

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Autism spectrum disorder: Consensus guidelines on assessment, treatment and research from the British Association for Psychopharmacology

Cited by 233 publications

References 278 publications

Big data approaches to decomposing heterogeneity across the autism spectrum

Big data approaches to decomposing heterogeneity across the autism spectrum

Efficacy and Safety of Melatonin Treatment in Children with Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder—A Review of the Literature

Twenty years of progress in paediatric psychopharmacology: accomplishments and unmet needs

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