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A few additional points are worth making. The truth about childhood psychiatric disorders is that the vast majority of those affected go undiagnosed and untreated. That does not mean that some children do not get a diagnosis that is inaccurate or a treatment that they do not need. Rather, we believe our biggest failing is not identifying and/or treating all those who could benefit. A public health approach to care is the only way to address the burden. Rates of a condition and its treatment are likely to increase over time as we learn more about the condition, develop better treatments, and lessen stigma. This should be expected. We are aware of meta-analyses that state the rates of ADHD are stable over decades for those who undergo a standardized assessment,1 but the CDC’s data are consistent in reporting increasing rates for community ascertainment studies and for those telephone follow-up studies of parent reports of health care provider diagnosis and treatment. Over time, different factors have affected ADHD. During the time in which the CDC has been performing these studies, rates have increased in some racial and ethnic groups, and those rates have become more consistent with overall rates, more female patients are being diagnosed, and rates in adolescents have increased to the point of being similar to those in younger children—all issues that have been targeted by advocacy groups. In addition, our current medicines are much better, and there are more medication options, making it easier for prescribers and families to receive treatment. That said, the tenor of the discussion regarding rising rates in the media seems to suggest that parents and their children are vulnerable to persuasive prescribers eager to prescribe. Our experience with parents is that they are reluctant to medicate, and that generally there is a lag from the time that medication is indicated to when parents agree to treatment. In addition, the fact that medication adherence remains a major challenge for all chronic conditions, including psychiatric conditions, likely means that even with rising rates of diagnosis and treatment, we probably are still not delivering care effectively to children with ADHD. Improving assessment and treatment within the public health approach is what we are advocating. We did not discuss in the editorial an issue for which we do have a concern about the diagnosis of ADHD. The rates identified by the CDC also include children who have been given the ADHD inattentive subtype diagnosis. If there is an area of ADHD assessment that requires substantial

expertise, it is the inattentive subtype. Other highprevalence conditions that can be misdiagnosed as the inattentive subtype are learning disorders and anxiety disorders. Interestingly, our advocacy for identifying anxiety in prepubertal children is probably nowhere nearly as effective as our advocacy for ADHD. So if there is a systematic pattern of misdiagnosis, we should first look at the misdiagnosis of an anxiety disorder as the inattentive subtype. John T. Walkup, MD Rebecca Rendleman, MD, CM Weill Cornell Medical College New York

[email protected]

Disclosure: Please see the disclosure statement in the original article published in January 2014. 0890-8567/$36.00/ª2014 American Academy of Child and Adolescent Psychiatry http://dx.doi.org/10.1016/j.jaac.2014.02.005

REFERENCE 1. Polanczyk GV, Willcutt EG, Salum GA, Kieling C, Rohde LA. ADHD prevalence estimates across three decades: an updated systematic review and meta-regression analysis [Epub ahead of print]. Int J Epidemiol. January 24, 2014.

Ascertainment and Gender in Autism Spectrum Disorders To the Editor: e read with great interest the article from the March issue of the Journal titled “Behavioral and Cognitive Characteristics of Females and Males with Autism in the Simons Simplex Collection” by Frazier et al.1 The investigators analyzed gender differences in standardized measurements in patients with autism spectrum disorder (ASD) from the large Simons Simplex Collection (SSC) dataset, using an approach to take into account potential sampling and measurement biases. They examined all patients with ASD and used regression analyses to examine effects of IQ, age, and other characteristics. The main findings of the article were that female patients with ASD had greater impairments in social communication and adaptive functioning, heightened irritability and externalizing problems, but had lower levels of restricted interests. These differences were small but statistically significant and were largely

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mediated by lower cognitive ability seen in female patients, with the exception of restricted interests and irritability. We also conducted an analysis of gender differences in standardized measurements in patients from the Autism Consortium (AC), Autism Genetics Resource Exchange (AGRE), and Autism Speaks Autism Treatment Network (ATN) datasets, in addition to the SSC. We selected patients older than 5 years with an Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule (ADOS) diagnosis of autism or ASD. We found differences in results pertaining to gender-specific presentations in autism depending on ascertainment protocols. Our conclusions, therefore, are that gender differences in autism presentation are highly dependent on ascertainment or the context in which patients present. The SSC is designed for simplex pedigrees specifically2 and therefore may not be generalizable to the ASD population as a whole. Our approach differed from that of Frazier et al. in that we further separated patients into groups based on verbal ability and the ADOS module administered. This created subgroups of comparable age and IQ across datasets. Overall, we found it difficult to draw generalizable conclusions because results were often inconsistent between datasets and differed based on subgroup. Results in the SSC in particular were often different from those in the other datasets. For example, the SSC had a higher maleto-female ratio than the other datasets. This was most striking in those who were fluently verbal, among whom the male-to-female ratio in SSC was 7.6 versus 4.4, 5.9, and 6.2 seen in the AGRE, AC, and ATN, respectively. Furthermore, results differed depending on which subgroup was analyzed. In nonverbal patients (administered module 1 of the ADOS), we found no statistically significant gender differences in any dataset. In those with phrase speech (ADOS module 2), our results in the SSC and the ATN datasets were consistent with those of Frazier et al., with female patients having lower IQ and lower Vineland Adaptive Behavioral Scale scores. We also found more impairing externalizing symptoms in female patients on the Child Behavior Checklist in this subgroup, but only in SSC participants. The overall profile for those who had fluent speech (ADOS module 3 or 4) was slightly different in the SSC than in the other datasets. Consistent with Frazier et al., in the SSC we noted slightly lower IQ scores and Vineland Adaptive

Behavioral Scale daily living scores in female patients but no differences between genders in Social Responsiveness Scale, Child Behavior Checklist, or ADOS severity scores. However, in the AC, AGRE, and ATN datasets, there were no significant differences between genders or slightly better scores on Vineland Adaptive Behavioral Scale standard scores, Social Responsiveness Scale raw total scores, and ADOS severity scores, in contrast to the SSC. This is similar to other studies and suggests that female patients with ASD who have higher IQs might in fact have similar or better social communication abilities than male patients with ASD.3,4 In summary, we applaud Frazier et al. for their careful study and agree that this is a step forward in understanding the nature of gender differences in ASD. In addition, we believe the results of the study raise important questions for the field. In analyzing multiple datasets, we found it difficult to make broad generalizations about the female phenotype in ASD, possibly owing to different ascertainment approaches used in creating the datasets. The SSC dataset was designed for simplex pedigrees specifically, the AGRE dataset emphasized recruitment of multiplex families, the AC dataset is geographically limited to Boston-area families, and the ATN dataset recruited individuals from multiple clinical sites across the country. Future work with large existing datasets should take into account ascertainment protocols when conclusions are drawn and before generalizing results to the full population and spectrum of people with ASD. Yamini J. Howe,

MD

Hasbro Children’s/Rhode Island Hospital Brown University Providence, RI

Yvette Yatchmink,

MD, PhD

Hasbro Children’s/Rhode Island Hospital Brown University Providence, RI

Emma W. Viscidi,

PhD

School of Public Health Brown University Providence, RI

Eric M. Morrow,

MD, PhD

Emma Pendleton Bradley Hospital and Brown University Medical School Brown University Providence, RI

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Dr. Howe has received support for training from the Maternal Child Health Bureau (MCHB) under training grant T77MC09797. Dr. Morrow has received support from the National Institutes of Health (NIH) / National Institute of General Medical Sciences (NIGMS) P20GM103645-01A1 and a Career Award in Medical Science from the Burroughs Wellcome Fund. The authors gratefully acknowledge resources provided by the Autism Genetic Resource Exchange (AGRE) Consortium and participating AGRE families. The AGRE is a program of Autism Speaks and is supported in part by grant 1U24MH081810 from the National Institute of Mental Health (NIMH) to Clara M. Lajonchere (principal investigator). The authors also acknowledge the use of data for the analyses obtained from the Autism Speaks Autism Treatment Network (ATN) database and thank the ATN participants and ATN Research Group for their valuable contribution to this research. The authors thank the families who agreed to participate in the Autism Consortium (AC). The AC is a collaborative effort of Boston Medical Center, Children’s Hospital Boston, Cambridge Health Alliance, the Massachusetts General Hospital Lurie Center, and Tufts Medical Center. The authors are grateful to all the families at the participating Simons Simplex Collection (SSC) sites and the principal investigators (A. Beaudet, R. Bernier, J. Constantino, E. Cook, E. Fombonne, D. Geschwind, D. Grice, A. Klin, D. Ledbetter, C. Lord, C. Martin, D. Martin, R. Maxim, J. Miles, O. Ousley, B. Peterson, J. Piggot, C. Saulnier, M. State, W. Stone, J. Sutcliffe, C. Walsh, and E. Wijsman). Disclosure: Dr. Howe has received support from Autism Consortium. Dr. Yatchmink has received grants and funding from the MCHB. Dr. Viscidi has received support from a T32 predoctoral training grant to conduct research on autism spectrum disorders. Dr. Morrow has received awards and/or funding from NIH/NIGMS under the Neuroscience COBRE Project, NIH/NIMH, NIH/National Center for Research Resources (NCRR) under Perinatal Medicine COBRE, Rhode Island Hospital, Brown University, the Simons Foundation Autism Research Initiative, and the Society of Biological Psychiatry. He holds a patent for Methods for Treatment of Microcephaly-Associated Autism Disorders (U.S. Patent Application No.: 61/739,351; International Application No.: PCT/US2013/076609). 0890-8567/$36.00/ª2014 American Academy of Child and Adolescent Psychiatry http://dx.doi.org/10.1016/j.jaac.2014.04.003

REFERENCES 1. Frazier TW, Georgiades S, Bishop SL, Hardan AY. Behavioral and cognitive characteristics of females and males with autism in the Simons Simplex Collection. J Am Acad Child Adolesc Psychiatry. 2014;53:329-340. 2. Fischbach GD, Lord C. The Simons Simplex Collection: a resource for identification of autism genetic risk factors. Neuron. 2010;68: 192-195. 3. Lai MC, Lombardo MV, Pasco G, et al. A behavioral comparison of male and female adults with high functioning autism spectrum conditions. PLoS One. 2011;6:e20835. 4. Mandy W, Chilvers R, Chowdhury U, Salter G, Seigal A, Skuse D. Sex differences in autism spectrum disorder: evidence from a large sample of children and adolescents. J Autism Dev Disord. 2012;42: 1304-1313.

Dr. Frazier et al. reply: he letter to the editor by Morrow et al.1 asserts that variability in ascertainment influences the pattern of sex differences in the autism phenotype. They briefly present results of analyses examining sex differences across 4 separate samples (Autism Consortium, Autism Genetic Resource Exchange, Autism Treatment

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Network, and Simons Simplex Collection), with inconsistent findings across samples after stratifying by age and IQ. The inconsistency of results is intriguing and might imply that sex differences in the autism phenotype tend to be small in magnitude, making them difficult to detect across samples and especially difficult to detect across subsamples of age and IQ. We would encourage them to look at effect sizes in addition to significance to see whether there is less variability in the magnitude of differences and to consider statistical power in each of the subsamples they examine. Even with these caveats in mind, we agree with the central tenet of the commentary, that sampling variability can influence sex differences, and would like to point out several additional potential confounds to which future studies should carefully attend. These include balanced sampling of the demographic and clinical characteristics of male and female subjects (selection bias), measurement equivalence, inclusion of broad and focused measurements, and attention to sources (such as caregiver report, clinician observation, or objective testing). Balanced ascertainment of male and female demographic and clinical characteristics is essential to comparability of naturally occurring groups beyond the sampling variability described in the commentary. In addition to age and IQ, it is important to consider common comorbidities, race/ethnicity, family characteristics (birth order, marital status, etc.), socioeconomic status, history of regression of skills, and expressive speech (verbal versus nonverbal). Others might exist, but future studies would be wise to consider each of these as potential modifiers of sex differences. Single- versus multiple-incidence families also can be a useful variable to examine, although we suspect that sex discrepancies are not greatly influenced by this variable. Our own work has shown symptom differences by family incidence type, but these differences tend to be modest in magnitude.2 An unknown but probably nontrivial proportion of single-incidence families would become multiple-incidence families with additional births (stoppage effect), further diluting differences. In our study of sex differences, we checked for balanced ascertainment across 15 variables and found it to be quite good. However, this will not be the case in all samples, and propensity methods should be used, even in situations where the balance is only slightly askew.3 We also checked for measurement equivalence of

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Ascertainment and gender in autism spectrum disorders.

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