Letters
0.17% in the study using National Health and Nutrition Examination Survey (NHANES) data by Demmer et al.3 Applying the fraction of confirmed to total undiagnosed diabetes from these studies (2/13 = 0.15) to the Demmer et al3 estimate of 0.17%, the prevalence of true undiagnosed diabetes in NHANES is 0.03%, in line with the 2 other studies. A much larger screening effort is required to determine whether the undiagnosed fraction of type 2 diabetes in youths is similar to that seen in adults.4 Geographic areas included in the SEARCH study were not based on random sampling, and although the sites are geographically diverse and capture some of the regional variability in both type 1 and type 2 diabetes risk in US youths,5 it may not be fully representative of this variation at the national level. Although the concern with geographic representativeness is understandable, we believe the SEARCH study captures the majority of potential geographic differences by reporting racial/ethnic prevalence in a study population that is also quite representative of the racial/ ethnic, sex, education, and income distributions in the United States. Demmer and colleagues note that a national surveillance system is needed for monitoring diabetes among youths to precisely estimate undiagnosed diabetes and regional variation in rates of total diabetes. Such a system does not exist and is needed. Although adequate for adults, the ongoing NHANES infrastructure, with a very small sample of 30 youths with type 1 and 28 with type 2 diabetes from 1999-2010,3 is not able to provide geographic, racial/ethnic, or national estimates of trends with much precision. The SEARCH study investigators have spent the last 15 years establishing an alternate infrastructure. Our prevalence estimates are based on more than 6000 patients with diagnosed diabetes identified from a geographically diverse and racially and ethnically representative denominator of approximately 3 million youths. Our conclusion remains that prevalence of both type 1 and type 2 diabetes has increased substantially between 2001 and 2009 and that ongoing research is needed to identify reasons for these trends. Dana Dabelea, MD, PhD Elizabeth J. Mayer-Davis, PhD Author Affiliations: Department of Epidemiology, Colorado School of Public Health, Aurora (Dabelea); Department of Nutrition, University of North Carolina, Chapel Hill (Mayer-Davis). Corresponding Author: Dana Dabelea, MD, PhD, Department of Epidemiology, Colorado School of Public Health, 13001 E 17th Pl, Aurora, CO 80045 ([email protected]). Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. 1. Dolan LM, Bean J, D’Alessio D, et al. Frequency of abnormal carbohydrate metabolism and diabetes in a population-based screening of adolescents. J Pediatr. 2005;146(6):751-758. 2. Kaufman FR, Hirst K, Linder B, et al; HEALTHY Study Group. Risk factors for type 2 diabetes in a sixth-grade multiracial cohort: the HEALTHY study. Diabetes Care. 2009;32(5):953-955.
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3. Demmer RT, Zuk AM, Rosenbaum M, Desvarieux M. Prevalence of diagnosed and undiagnosed type 2 diabetes mellitus among US adolescents: results from the continuous NHANES, 1999-2010. Am J Epidemiol. 2013;178(7):1106-1113. 4. Cowie CC, Rust KF, Ford ES, et al. Full accounting of diabetes and pre-diabetes in the US population in 1988-1994 and 2005-2006. Diabetes Care. 2009;32(2):287-294. 5. Liese AD, Lawson A, Song HR, et al. Evaluating geographic variation in type 1 and type 2 diabetes mellitus incidence in youth in four US regions. Health Place. 2010;16(3):547-556.
Recurrence Rates in Autism Spectrum Disorders To the Editor The recent report by Dr Sandin and colleagues1 contributes to a converging body of recent research specifying recurrence rates in autism spectrum disorders (ASD) by analyzing data from a large epidemiological birth cohort in Sweden. The results included a large-scale confirmation that the sex of the proband does not predict familial recurrence risk, indicating that the Carter effect (increased familial recurrence among subsets of cases [eg, females] who have been hypothesized to require higher than usual genetic loading to express the disorder), which was observed for subclinical autistic-like traits in a sample from the United Kingdom and Sweden, 2 may not apply to a majority of clinical autistic syndromes. Another important observation was the lack of a discrepancy in recurrence rates between dizygotic twins and nontwin siblings, tempering concerns raised by previously reported elevations among dizygotic twins that implicated intrauterine environmental factors in autism risk. With regard to heritability, however, both the estimation of total heritability (0.50) and the estimation of nonshared environmental influence (0.50) reported in the study warrant caution because they were based on one of the lower monozygotic twin concordance rates ever reported (tetrachoric correlation of 0.55) and on a relatively small number of clinically affected monozygotic twins (n = 62 total). The correlation was substantially higher when exclusively considering male monozygotic twin pairs (0.70). Sandin et al1 did not separately estimate heritability or nonshared environmental influence for ASD in nontwins or males, the latter particularly relevant given the fact that ASD is 3 times more common in males and there is accumulating evidence that penetrance of many ASD genetic susceptibilities is reduced in females.3 Any extent to which the method of ASD ascertainment led to underrepresentation of the true monozygotic concordance would falsely lower the estimation of heritability and falsely raise the estimation of the influence of nonshared environmental influence. Although Sandin et al1 drew parallels between their results and those of the California Autism Twin Study,4 the respective studies report highly contrasting (essentially incompatible) types of environmental influence; notably, the Swedish study revealed no evidence for the presence of common (shared) environmental influences, which it was well powered to detect. Moreover, regarding its assertion of nonshared environmental influence, the role of de novo mutation (a significant influence on sporadic autism except when involving mono-
JAMA September 17, 2014 Volume 312, Number 11
Copyright 2014 American Medical Association. All rights reserved.
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Letters
zygotic twins) did not appear to be incorporated into the statistical modeling methods used, and should be considered an important contributor to that category of causal influence. John N. Constantino, MD Author Affiliation: Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri. Corresponding Author: John N. Constantino, MD, Departments of Psychiatry and Pediatrics, Washington University School of Medicine, 660 S Euclid Ave, St Louis, MO 63110 ([email protected]). Conflict of Interest Disclosures: The author has completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and reported receiving royalties from Western Psychological Services for the commercial distribution of the Social Responsiveness Scale, a quantitative measure of autistic traits. 1. Sandin S, Lichtenstein P, Kuja-Halkola R, Larsson H, Hultman CM, Reichenberg A. The familial risk of autism. JAMA. 2014;311(17):1770-1777. 2. Robinson EB, Lichtenstein P, Anckarsäter H, Happé F, Ronald A. Examining and interpreting the female protective effect against autistic behavior. Proc Natl Acad Sci U S A. 2013;110(13):5258-5262.
of the potential important results of an analysis such as ours is to facilitate and stimulate a discussion about the specific causes of the disorder. One way to address current concerns about behavioral genetic models of heritability is to complement them with modeling methods using molecular data to estimate heritable and nonheritable factors. We agree with Constantino that de novo mutations would inflate the nonshared environment component term and this may be important. Sven Sandin, PhD Abraham Reichenberg, PhD Author Affiliations: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Sandin); Department of Psychiatry, Ichan School of Medicine at Mount Sinai, New York, New York (Reichenberg). Corresponding Author: Sven Sandin, PhD, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, SE-17177 Stockholm, Sweden ([email protected]).
3. Constantino JN, Charman T. Gender bias, female resilience, and the sex ratio in autism. J Am Acad Child Adolesc Psychiatry. 2012;51(8):756-758.
Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
4. Hallmayer J, Cleveland S, Torres A, et al. Genetic heritability and shared environmental factors among twin pairs with autism. Arch Gen Psychiatry. 2011; 68(11):1095-1102.
1. Grønborg TK, Schendel DE, Parner ET. Recurrence of autism spectrum disorders in full- and half-siblings and trends over time: a population-based cohort study. JAMA Pediatr. 2013;167(10):947-953.
In Reply We share Dr Constantino’s interest in determining if there are differences in the etiology of ASD between males and females. We did not compare the heritability of ASD between males and females in the study for 2 reasons. First, even a large population-based study such as ours has limited power to detect statistically significant sex differences in heritability. Second, we addressed the question of sex effects in our recurrence risk analysis. We did not observe important or statistically significant differences in recurrence risk in siblings and cousins for the different sibling and cousin sex combinations. The relative risk for males or females was not dependent on the sex of the proband. Furthermore, an epidemiological study from Denmark also did not find support for sex-related differences in recurrence risk.1 We look forward to seeing this topic addressed further in future populationbased studies. Several factors may affect concordance rates. Some earlier twin studies used interviews, rating scales, or both to score different autistic traits and applied preselected cutoffs to define autism.2,3 The pairwise concordance using such an approach may differ from pairwise concordance based on clinical diagnosis as reflected in our study. The source population, methods of ascertainment, handling of time trends, and participation rates may also affect observed concordance rates. The models we fitted are complex and, like any statistical model, do come with some underlying assumptions. Furthermore, the models can only give crude estimates of the sources and nature of the disease, and therefore we were cautious not to overinterpret our estimates or speculate what the exact sources underlying our estimates might be. Yet one
2. Lundström S, Chang Z, Råstam M, et al. Autism spectrum disorders and autistic like traits: similar etiology in the extreme end and the normal variation. Arch Gen Psychiatry. 2012;69(1):46-52. 3. Lichtenstein P, Carlström E, Råstam M, Gillberg C, Anckarsäter H. The genetics of autism spectrum disorders and related neuropsychiatric disorders in childhood. Am J Psychiatry. 2010;167(11):1357-1363.
Certification of Mobile Apps for Health Care To the Editor A Viewpoint by Dr Powell and colleagues1 highlighted just how difficult it is for patients and clinicians to identify safe, effective mobile apps for health care, with the thousands of apps in the marketplace having received little review or clinical evaluation. The authors called for more “rigorous certification criteria and unbiased accrediting bodies,” claiming the need for certification of apps. Although certification of apps sounds reasonable, we do not believe it is a scalable strategy that will address more than a small fraction of the market. Happtique, a commercial app certification company, recently suspended their app certification program, underscoring the concept of health app certification as a flawed proposition.2 The number of features, diversity of information, and rapid pace of development are key market factors that make certification difficult to achieve. Powell et al1 cited examples of organizations, such as the nonprofit Health On the Net Foundation and the for-profit Underwriters Laboratories, that purport to be successful at disseminating credible consumer information. However, the Health On the Net Foundation’s HONcode takes 12 to 18 months to review a website.3 The challenge in both certification and clinical evidence is that traditional methods have not adapted to the fastpaced nature of technology. Traditional randomized clinical trials are expensive, lengthy endeavors, which mHealth researchers have often lamented.4 Researchers aiming to
jama.com
JAMA September 17, 2014 Volume 312, Number 11
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Universite Laval User on 05/11/2015
1155
0.17% in the study using National Health and Nutrition Examination Survey (NHANES) data by Demmer et al.3 Applying the fraction of confirmed to total undiagnosed diabetes from these studies (2/13 = 0.15) to the Demmer et al3 estimate of 0.17%, the prevalence of true undiagnosed diabetes in NHANES is 0.03%, in line with the 2 other studies. A much larger screening effort is required to determine whether the undiagnosed fraction of type 2 diabetes in youths is similar to that seen in adults.4 Geographic areas included in the SEARCH study were not based on random sampling, and although the sites are geographically diverse and capture some of the regional variability in both type 1 and type 2 diabetes risk in US youths,5 it may not be fully representative of this variation at the national level. Although the concern with geographic representativeness is understandable, we believe the SEARCH study captures the majority of potential geographic differences by reporting racial/ethnic prevalence in a study population that is also quite representative of the racial/ ethnic, sex, education, and income distributions in the United States. Demmer and colleagues note that a national surveillance system is needed for monitoring diabetes among youths to precisely estimate undiagnosed diabetes and regional variation in rates of total diabetes. Such a system does not exist and is needed. Although adequate for adults, the ongoing NHANES infrastructure, with a very small sample of 30 youths with type 1 and 28 with type 2 diabetes from 1999-2010,3 is not able to provide geographic, racial/ethnic, or national estimates of trends with much precision. The SEARCH study investigators have spent the last 15 years establishing an alternate infrastructure. Our prevalence estimates are based on more than 6000 patients with diagnosed diabetes identified from a geographically diverse and racially and ethnically representative denominator of approximately 3 million youths. Our conclusion remains that prevalence of both type 1 and type 2 diabetes has increased substantially between 2001 and 2009 and that ongoing research is needed to identify reasons for these trends. Dana Dabelea, MD, PhD Elizabeth J. Mayer-Davis, PhD Author Affiliations: Department of Epidemiology, Colorado School of Public Health, Aurora (Dabelea); Department of Nutrition, University of North Carolina, Chapel Hill (Mayer-Davis). Corresponding Author: Dana Dabelea, MD, PhD, Department of Epidemiology, Colorado School of Public Health, 13001 E 17th Pl, Aurora, CO 80045 ([email protected]). Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. 1. Dolan LM, Bean J, D’Alessio D, et al. Frequency of abnormal carbohydrate metabolism and diabetes in a population-based screening of adolescents. J Pediatr. 2005;146(6):751-758. 2. Kaufman FR, Hirst K, Linder B, et al; HEALTHY Study Group. Risk factors for type 2 diabetes in a sixth-grade multiracial cohort: the HEALTHY study. Diabetes Care. 2009;32(5):953-955.
1154
3. Demmer RT, Zuk AM, Rosenbaum M, Desvarieux M. Prevalence of diagnosed and undiagnosed type 2 diabetes mellitus among US adolescents: results from the continuous NHANES, 1999-2010. Am J Epidemiol. 2013;178(7):1106-1113. 4. Cowie CC, Rust KF, Ford ES, et al. Full accounting of diabetes and pre-diabetes in the US population in 1988-1994 and 2005-2006. Diabetes Care. 2009;32(2):287-294. 5. Liese AD, Lawson A, Song HR, et al. Evaluating geographic variation in type 1 and type 2 diabetes mellitus incidence in youth in four US regions. Health Place. 2010;16(3):547-556.
Recurrence Rates in Autism Spectrum Disorders To the Editor The recent report by Dr Sandin and colleagues1 contributes to a converging body of recent research specifying recurrence rates in autism spectrum disorders (ASD) by analyzing data from a large epidemiological birth cohort in Sweden. The results included a large-scale confirmation that the sex of the proband does not predict familial recurrence risk, indicating that the Carter effect (increased familial recurrence among subsets of cases [eg, females] who have been hypothesized to require higher than usual genetic loading to express the disorder), which was observed for subclinical autistic-like traits in a sample from the United Kingdom and Sweden, 2 may not apply to a majority of clinical autistic syndromes. Another important observation was the lack of a discrepancy in recurrence rates between dizygotic twins and nontwin siblings, tempering concerns raised by previously reported elevations among dizygotic twins that implicated intrauterine environmental factors in autism risk. With regard to heritability, however, both the estimation of total heritability (0.50) and the estimation of nonshared environmental influence (0.50) reported in the study warrant caution because they were based on one of the lower monozygotic twin concordance rates ever reported (tetrachoric correlation of 0.55) and on a relatively small number of clinically affected monozygotic twins (n = 62 total). The correlation was substantially higher when exclusively considering male monozygotic twin pairs (0.70). Sandin et al1 did not separately estimate heritability or nonshared environmental influence for ASD in nontwins or males, the latter particularly relevant given the fact that ASD is 3 times more common in males and there is accumulating evidence that penetrance of many ASD genetic susceptibilities is reduced in females.3 Any extent to which the method of ASD ascertainment led to underrepresentation of the true monozygotic concordance would falsely lower the estimation of heritability and falsely raise the estimation of the influence of nonshared environmental influence. Although Sandin et al1 drew parallels between their results and those of the California Autism Twin Study,4 the respective studies report highly contrasting (essentially incompatible) types of environmental influence; notably, the Swedish study revealed no evidence for the presence of common (shared) environmental influences, which it was well powered to detect. Moreover, regarding its assertion of nonshared environmental influence, the role of de novo mutation (a significant influence on sporadic autism except when involving mono-
JAMA September 17, 2014 Volume 312, Number 11
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Universite Laval User on 05/11/2015
jama.com
Letters
zygotic twins) did not appear to be incorporated into the statistical modeling methods used, and should be considered an important contributor to that category of causal influence. John N. Constantino, MD Author Affiliation: Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri. Corresponding Author: John N. Constantino, MD, Departments of Psychiatry and Pediatrics, Washington University School of Medicine, 660 S Euclid Ave, St Louis, MO 63110 ([email protected]). Conflict of Interest Disclosures: The author has completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and reported receiving royalties from Western Psychological Services for the commercial distribution of the Social Responsiveness Scale, a quantitative measure of autistic traits. 1. Sandin S, Lichtenstein P, Kuja-Halkola R, Larsson H, Hultman CM, Reichenberg A. The familial risk of autism. JAMA. 2014;311(17):1770-1777. 2. Robinson EB, Lichtenstein P, Anckarsäter H, Happé F, Ronald A. Examining and interpreting the female protective effect against autistic behavior. Proc Natl Acad Sci U S A. 2013;110(13):5258-5262.
of the potential important results of an analysis such as ours is to facilitate and stimulate a discussion about the specific causes of the disorder. One way to address current concerns about behavioral genetic models of heritability is to complement them with modeling methods using molecular data to estimate heritable and nonheritable factors. We agree with Constantino that de novo mutations would inflate the nonshared environment component term and this may be important. Sven Sandin, PhD Abraham Reichenberg, PhD Author Affiliations: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Sandin); Department of Psychiatry, Ichan School of Medicine at Mount Sinai, New York, New York (Reichenberg). Corresponding Author: Sven Sandin, PhD, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, PO Box 281, SE-17177 Stockholm, Sweden ([email protected]).
3. Constantino JN, Charman T. Gender bias, female resilience, and the sex ratio in autism. J Am Acad Child Adolesc Psychiatry. 2012;51(8):756-758.
Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
4. Hallmayer J, Cleveland S, Torres A, et al. Genetic heritability and shared environmental factors among twin pairs with autism. Arch Gen Psychiatry. 2011; 68(11):1095-1102.
1. Grønborg TK, Schendel DE, Parner ET. Recurrence of autism spectrum disorders in full- and half-siblings and trends over time: a population-based cohort study. JAMA Pediatr. 2013;167(10):947-953.
In Reply We share Dr Constantino’s interest in determining if there are differences in the etiology of ASD between males and females. We did not compare the heritability of ASD between males and females in the study for 2 reasons. First, even a large population-based study such as ours has limited power to detect statistically significant sex differences in heritability. Second, we addressed the question of sex effects in our recurrence risk analysis. We did not observe important or statistically significant differences in recurrence risk in siblings and cousins for the different sibling and cousin sex combinations. The relative risk for males or females was not dependent on the sex of the proband. Furthermore, an epidemiological study from Denmark also did not find support for sex-related differences in recurrence risk.1 We look forward to seeing this topic addressed further in future populationbased studies. Several factors may affect concordance rates. Some earlier twin studies used interviews, rating scales, or both to score different autistic traits and applied preselected cutoffs to define autism.2,3 The pairwise concordance using such an approach may differ from pairwise concordance based on clinical diagnosis as reflected in our study. The source population, methods of ascertainment, handling of time trends, and participation rates may also affect observed concordance rates. The models we fitted are complex and, like any statistical model, do come with some underlying assumptions. Furthermore, the models can only give crude estimates of the sources and nature of the disease, and therefore we were cautious not to overinterpret our estimates or speculate what the exact sources underlying our estimates might be. Yet one
2. Lundström S, Chang Z, Råstam M, et al. Autism spectrum disorders and autistic like traits: similar etiology in the extreme end and the normal variation. Arch Gen Psychiatry. 2012;69(1):46-52. 3. Lichtenstein P, Carlström E, Råstam M, Gillberg C, Anckarsäter H. The genetics of autism spectrum disorders and related neuropsychiatric disorders in childhood. Am J Psychiatry. 2010;167(11):1357-1363.
Certification of Mobile Apps for Health Care To the Editor A Viewpoint by Dr Powell and colleagues1 highlighted just how difficult it is for patients and clinicians to identify safe, effective mobile apps for health care, with the thousands of apps in the marketplace having received little review or clinical evaluation. The authors called for more “rigorous certification criteria and unbiased accrediting bodies,” claiming the need for certification of apps. Although certification of apps sounds reasonable, we do not believe it is a scalable strategy that will address more than a small fraction of the market. Happtique, a commercial app certification company, recently suspended their app certification program, underscoring the concept of health app certification as a flawed proposition.2 The number of features, diversity of information, and rapid pace of development are key market factors that make certification difficult to achieve. Powell et al1 cited examples of organizations, such as the nonprofit Health On the Net Foundation and the for-profit Underwriters Laboratories, that purport to be successful at disseminating credible consumer information. However, the Health On the Net Foundation’s HONcode takes 12 to 18 months to review a website.3 The challenge in both certification and clinical evidence is that traditional methods have not adapted to the fastpaced nature of technology. Traditional randomized clinical trials are expensive, lengthy endeavors, which mHealth researchers have often lamented.4 Researchers aiming to
jama.com
JAMA September 17, 2014 Volume 312, Number 11
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Universite Laval User on 05/11/2015
1155
