Eur Child Adolesc Psychiatry DOI 10.1007/s00787-014-0541-z
ORIGINAL PAPER
Risk factors for incident major depressive disorder in children and adolescents with attention-deficit/hyperactivity disorder Jeanette M. Jerrell • Roger S. McIntyre Yong-Moon Mark Park
•
Received: 28 August 2013 / Accepted: 21 March 2014 Ó Springer-Verlag Berlin Heidelberg 2014
Abstract The greater burden of illness in youth with cooccurring attention-deficit/hyperactivity disorder (ADHD) and major depressive disorder (MDD) deserves further investigation, specifically regarding the influence of other psychiatric or medical conditions and the pharmacotherapies prescribed. A retrospective cohort design was employed, using South Carolina’s (USA) Medicaid claims’ dataset covering outpatient and inpatient medical services, and medication prescriptions between January, 1996 and December, 2006 for patients B17 years of age. The cohort included 22,452 cases diagnosed with ADHD at a mean age 7.8 years; 1,259 (5.6 %) cases were diagnosed with MDD at a mean age of 12.1 years. The probability of a child with ADHD developing MDD was significantly associated with a comorbid anxiety disorder (aOR = 3.53), CD/ODD (aOR = 3.45), or a substance use disorder (aOR = 2.31); being female (aOR = 1.77); being treated with pemoline (aOR = 1.69), atomoxetine (aOR = 1.31), or mixed amphetamine salts (aOR = 1.28); a comorbid
obesity diagnosis (aOR = 1.29); not being African American (aOR = 1.23), and being older at ADHD diagnosis (aOR = 1.09). Those developing MDD also developed several comorbid disorders later than the ADHD-only cohort, i.e., conduct disorder/oppositional-defiant disorder (CD/ODD), at mean age of 10.8 years, obesity at 11.6 years, generalized anxiety disorder at 12.2 years, and a substance use disorder at 15.7 years of age. Incident MDD was more likely in individuals clustering several demographic, clinical, and treatment factors. The phenotypic progression suggested herein underscores the need for coordinated early detection and intervention to prevent or delay syndromal MDD, or to minimize its severity and associated impairment over time. Keywords Major depressive disorder Attention-deficit/ hyperactivity disorder Conduct disorder Anxiety disorder Obesity
Introduction J. M. Jerrell (&) Department of Neuropsychiatry and Behavioral Science, University of South Carolina School of Medicine, 15 Medical Park, Suite 301, Columbia, SC 29203, USA e-mail: [email protected] R. S. McIntyre Department of Psychiatry, University of Toronto, Toronto, Canada R. S. McIntyre Department of Pharmacology, University of Toronto, Toronto, Canada Y.-M. M. Park Department of Epidemiology and Biostatistics, University of South Carolina Arnold School of Public Health, Columbia, USA
Attention-deficit/hyperactivity disorder (ADHD) is one of the most commonly diagnosed cognitive/behavioral disorders in children and adolescents, with an estimated prevalence of about 3–5 % worldwide [1, 2]. ADHD is characterized by impairments not only in attention and emotional regulation, but also in behavioral control. The etiology of ADHD is likely multifactorial, stemming from a combination of genetic/familial, biological [3–5], and environmental influences [6]. ADHD and externalizing disorders, such as conduct disorder/oppositional-defiant disorder (CD/ODD), have been found to co-occur in 30–50 % of cases in both epidemiologic and clinical samples; internalizing disorders, such as anxiety and
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depression, are also frequently comorbid with ADHD [7– 9]. Major depressive disorder (MDD) occurs in about 2 % of children and 6–8 % of adolescents [1, 10] in the general population. However, the prevalence of MDD in youth with ADHD has been found to be more than five times higher than in those without ADHD [11]. Family and population studies of ADHD and MDD have noted that while personal and familial risk factors between the two disorders are evident, especially in families with diagnosed antisocial disorders, other disorders with externalizing/ aggressive features, anxiety disorders, or substance use disorders are also apparent [8, 12–16]. Age and gender differences have been evident in previous clinical studies wherein females have an earlier age of onset of depressive symptoms or MDD, a more severe course for both illnesses, and a higher risk of developing disruptive, mood, anxiety, and substance use disorders [7, 8, 17, 18]. The onset of MDD is typically several years after the diagnosis of ADHD, suggesting that it may also be the cumulative result of ADHD-related impairments or negative environmental circumstances (e.g., poor psychosocial adjustment in peer or family relationships or child maltreatment) [6, 17], ADHD-related treatments, comorbid conditions that may be pathophysiologically associated with both disorders, e.g., obesity, diabetes mellitus, dyslipidemia, or thyroid disorders [19, 20], or conditions frequently associated with the development of depressive symptoms, e.g., traumatic brain injury [21]. Furthermore, some comorbid disease states, such as epilepsy, cancer, and cardiovascular disease, may initiate depressive symptoms more often in one sex over the other [22]. Previous epidemiologic and clinical studies have demonstrated a generally consistent ‘‘off-trajectory’’ progression of these neurodevelopmental/psychiatric disorders in youth [23], but have not systematically investigated the role of neuroendocrine/metabolic disorders in this progression. Other potential correlates for the development of MDD among youth with ADHD may be the severity of ADHD symptoms. The psychostimulant medications used to treat ADHD may be associated in some patients with dysphoric mood symptoms, and subsequent pre-marketing, controlled studies and post-marketing, clinical reports of psychostimulant- or atomoxetine-associated depression have confirmed this finding in B5 % of treated patients [24–30]. The encompassing aim of this analysis is to further characterize the clinical correlates of the comorbidity of MDD and ADHD, to elucidate their potential significance in earlier identification of those at risk of incident MDD, and to determine the relative influence of ADHD pharmacotherapy on the incidence of MDD in an ADHD cohort. Given the substantially higher rates of long-term impairment, morbidity, and increased risk of mortality
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(from suicide) associated with co-occurring ADHD and MDD compared to having either disorder alone, this area of inquiry deserves further investigation.
Methods Data for this study were obtained retrospectively from the South Carolina (SC), USA Medicaid database during an 11-year period from January 1, 1996 through December 31, 2006. Medical claims were used to identify a service encounter, date of service, and the International Classification of Diseases, 9th Clinical Modification diagnosis codes (ICD-9) related to that visit. Selection criteria were age B17 years, continuous enrollment in Medicaid for a minimum of 9 months in each calendar year, and at least one initial service encounter with an ICD-9 diagnosis of 314.00 or 314.01. ICD-9 codes of 314 or 314.1–314.9 indicating hyperkinesis not associated with attention-deficit disorder were omitted from this study. The methods involved in this study were approved by the University of South Carolina Institutional Review Board as exempt from human subject research guidelines (45 Code of Federal Regulations part 46). Within this ADHD cohort, the following categories of diagnosed conditions were evaluated: MDD (ICD-9 codes: 296.2, 296.3), CD/ODD (312.x, 313.81); anxiety (300.0x), obesity (278; 278.00; 278.01), dyslipidemia (272, 288.0, 285.9), type 2 diabetes mellitus (250.00–250.92 with 5th digit = 0.2), type 1 diabetes mellitus (250.00–250.93 with 5th digit = 1.3), thyroid disorders (240.x–246.x), cerebrovascular disorders (436–437; 435; 430–434; 440–448), epilepsy (345.0, 345.00–345.91), seizures (780.3), or migraine headaches (346.x). Comorbid congenital heart defects were coded as 747.0–747.9; organic brain disorders/mental retardation as 310, 310.0–310.9, 318, 318.1, 318.2, 317.xx, 319.xx; traumatic brain injury as 850.xx– 854.xx; and a substance use disorder was coded as 304.x or 305.x. Child abuse or neglect/maltreatment was coded as E967.0–E967.9. Cases with ICD-9 codes for other depressive disorders, bipolar or cyclothymic disorders, or for 250 or 250.1–250.9 without a fifth digit (i.e., ‘‘unspecified diabetes’’) were excluded from this investigation. Under Medicaid, psychiatric diagnoses are generally made by a licensed psychiatrist, whereas medical diagnoses are made by the licensed primary care physician/ pediatrician. Descriptive statistical analyses were performed on the ADHD and MDD cases to determine the prevalence of each condition and any bivariate associations between the predictor variables of interest, i.e., individual risk factors (age at ADHD diagnosis, sex, race); comorbid conditions (i.e., CD/ODD, substance use disorder, obesity, diabetes
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mellitus, dyslipidemia, or thyroid disorders), and pharmacologic interventions received for ADHD (i.e., coded separately as the medication prescribed/not prescribed and as the number of months each medication was filled/refilled from the Medicaid pharmacy file). To address our primary research questions regarding the factors which significantly increase the odds of a child with ADHD being diagnosed with syndromal MDD, two multiple logistic regression equations were constructed to assess the relative odds associated with having any of these independently diagnosed conditions, including individual risk factors (dichotomously coded sex and ethnicity; continuously coded age at ADHD diagnosis), comorbid psychiatric disorders (CD/ODD, anxiety disorder, and substance use disorder), comorbid medical conditions (organic brain conditions or mental retardation, epilepsy, traumatic brain injury, migraine headaches, thyroid disorder, obesity, type 1 diabetes mellitus, type 2 diabetes mellitus, dyslipidemia, congenital heart disease, and cerebrovascular disorder), and the prescribed psychostimulant medication or atomoxetine (coded as yes/no in one regression equation and as the number of months the child was taking/exposed to the medication in the second equation) as predictor variables. Each full regression model was then reduced through a stepwise procedure to reflect only the statistically significant variables associated with being diagnosed with MDD. The measure of association reported for these results is the adjusted odds ratio (aOR) with a corresponding 95 % confidence interval.
Table 1 Descriptive analysis of the cohort of 22,452 youths diagnosed with ADHD Indicator
N (%)
Gender: male
15,508 (69.1)
Race: non-African American
11,501 (51.2)
African American Mean age at ADHD diagnosis (years)
7.8 (±2.9)a
Diagnosed with major depressive disorder
1,259 (5.6)
Mean age at major depressive disorder diagnosis (years)
12.1 (±3.6)
Diagnosed with conduct disorder/oppositional-defiant disorder (CD/ODD)
8,764 (39.0)
Mean age at CD/ODD diagnosis (years)
9.2 (±3.8)
Diagnosed with anxiety
3,194 (14.2) 10.6 (?4.1)
Mean age at anxiety diagnosis (years) Diagnosed with substance use disorder
1,224 (5.5)
Mean age at substance use diagnosis (years)
14.9 (±3.6)
Comorbid medical conditions Diagnosed with obesity
Results The ADHD cohort consisted of 22,624 child and adolescent cases. Descriptive results regarding this cohort (Tables 1, 2) indicate that 69.1 % of the cohort was male and 48.8 % was African American, with a mean age at diagnosis of the ADHD of 7.8 years (SD = 2.9 years). MDD was diagnosed in 5.6 % (N = 1,259) of the cohort at a mean age of 12.1 years (SD = 3.6 years). Thirty-nine percent of the ADHD cohort was diagnosed with CD/ODD at a mean age of 9.2 years, 14.2 % with anxiety disorder, predominantly generalized anxiety disorder, at 10.6 years, and 5.5 % with a substance use disorder at 14.9 years of age. Comorbid medical conditions diagnosed in the ADHD cohort and their prevalence were organic brain conditions or mental retardation (26.2 %), obesity (9.1 %), epilepsy (6.7 %), traumatic brain injury (4.9 %), migraine headaches (4.8 %), thyroid disorder (2.8 %), type 2 diabetes mellitus (1.8 %), congenital heart disease (2.5 %), dyslipidemia (2.2 %), cerebrovascular disorder (2.1 %), and type 1 diabetes mellitus (1.1 %). Abuse was noted as the external cause of injury for 0.25 % (N = 57) of the ADHD cohort (Table 1).
10,951 (48.8)
a
2,047 (9.1)
Mean age at obesity diagnosis (years)
9.5 (±4.8)
Diagnosed with type 1 diabetes mellitus Diagnosed with type 2 diabetes mellitus
246 (1.1) 413 (1.8)
Diagnosed with dyslipidemia
491 (2.8)
Diagnosed with thyroid disorder
635 (2.8)
Diagnosed with congenital heart disease
553 (2.5)
Diagnosed with cerebrovascular disorder
469 (2.1)
Diagnosed with traumatic brain injury
1,090 (4.9)
Diagnosed with migraine headaches
1,076 (4.8)
Diagnosed with epilepsy
1,493 (6.7)
Diagnosed with organic brain disease/mental retardation
5,876 (26.2)
Diagnosed external cause of injury (E-code)
57 (0.25)
±Standard deviation
This clinical cohort was being treated with a range of ADHD medications: 61.9 % were taking methylphenidate, on average, for 17 months; 55.2 % were taking mixed amphetamine salts/dextroamphetamine for an average of 17 months; 1.3 % was taking pemoline, for about 8 months, on average; and 22.1 % were taking atomoxetine for an average of 8 months (Table 2). Diagnosed obesity was higher in those children treated with methylphenidate (16.5 %) and mixed amphetamine salts/dextroamphetamine (12.1 %). As shown in Table 3, in the logistic regression modeling the comorbid conditions along with ADHD
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Eur Child Adolesc Psychiatry Table 2 Prescribed ADHD medications in ADHD cohort ADHD medication
N (%)
Methylphenidate
13,902 (61.9)
Mean months taking methylphenidate
16.8 (±17.9)a
Mixed amphetamine salts/dextroamphetamine
12,396 (55.2)
Mean months taking mixed amphetamine salts/ dextroamphetamine
15.6 (±17.2)
Pemoline
298 (1.3)
Mean months taking pemoline
8.2 (±13.2)
Atomoxetine Mean months taking atomoxetine
4,970 (22.1) 7.7 (±8.8)
a
±Standard deviation
Table 4 Adjusted odds ratios for incident depression related to comorbid conditions, duration of prescribed ADHD medications in months, and individual risk factors (stepwise logistic regression model) Parameter
Adjusted odds ratio
95 % confidence intervals
Sex (female)
1.77**
1.56–2.00
Ethnicity (black)
0.80*
0.71–0.91
Age at ADHD diagnosis
1.09**
1.07–1.11
Conduct disorder/ODD diagnosis
3.47**
3.04–3.97
Anxiety diagnosis
3.53**
3.11–4.01
Substance abuse diagnosis Obesity diagnosis
2.36** 1.28*
1.98–2.81 1.07–1.53
Mixed amphetamine salts/ dextroamphetamine treatment duration
1.01*
1.00–1.01
Table 3 Adjusted odds ratios for incident depression related to comorbid conditions, prescribed medications, and individual risk factors (stepwise logistic regression model)
Atomoxetine treatment duration
1.01*
1.00–1.02
Methylphenidate treatment duration
1.01*
1.00–1.01
Parameter
* Significant at p = 0.01 or less
Adjusted odds ratio
95 % confidence intervals
Sex (female)
1.77**
1.56–2.00
Ethnicity (black)
0.81*
0.71–0.92
Age at ADHD diagnosis
1.09**
1.07–1.12
Conduct disorder/odd diagnosis
3.45**
3.02–3.94
Anxiety diagnosis
3.53**
3.11–4.01
Substance abuse diagnosis
2.31**
1.94–2.76
Obesity
1.29*
1.08–1.54
Mixed amphetamine salts/ dextroamphetamine treatment
1.28*
1.12–1.45
Pemoline treatment
1.69*
1.18–2.44
Atomoxetine treatment
1.31*
1.14–1.50
* Significant at p = 0.01 or less ** Significant at p \ 0.0001
pharmacotherapies as prescribed/not prescribed, ten predictor variables were significantly associated with increased odds of a child being diagnosed with MDD: being diagnosed with an anxiety disorder (aOR = 3.53), CD/ODD (aOR = 3.45), or a substance use disorder (aOR = 2.31); being female (aOR = 1.77); being treated with pemoline (aOR = 1.69); being diagnosed with obesity (aOR = 1.29); being treated with atomoxetine (aOR = 1.31) or mixed amphetamine salts/dextroamphetamine (aOR = 1.28); not being African American (aOR = 1.23); and being older at ADHD diagnosis (aOR = 1.09). The odds of developing MDD increased approximately 9 % per year older the patient was when ADHD was diagnosed, after adjusting for other confounding factors. More specifically, children with ADHD who developed MDD were older at ADHD diagnosis and also developed several comorbid disorders later than the
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** Significant at p \ 0.0001
ADHD-only cohort, i.e., CD/ODD at mean age of 10.8 years, obesity at 11.6 years, anxiety disorder at 12.2 years, and a substance use disorder at 15.7 years of age. None of the other covariates demonstrated a statistically significant association with incident MDD. In the second logistic regression equation (Table 4) capturing length/duration of exposure to the ADHD medications, ten variables were also identified as significantly associated with higher odds of a child being diagnosed with MDD: being diagnosed with an anxiety disorder (aOR = 3.53), CD/ODD (aOR = 3.47), or a substance use disorder (aOR = 2.36); being female (aOR = 1.77); being diagnosed with obesity (aOR = 1.28); being treated with methylphenidate (aOR = 1.01), mixed amphetamine salts/ dextroamphetamine (aOR = 1.01), or atomoxetine (aOR = 1.01); not being African American (aOR = 1.25); and being older at ADHD diagnosis (aOR = 1.09). The size of the ORs was about the same for all of the demographics and comorbid medical conditions in the two equations, but the longer a child was exposed to one of three ADHD pharmacotherapies, the greater his/her chances of being diagnosed with MDD, i.e., about 1 % more per month of pharmacotherapy. None of the other covariates demonstrated a statistically significant association with incident MDD.
Discussion ADHD is a major health concern in youth, and its role in a ‘‘prodromal period’’ preceding the diagnosis of several
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comorbid and chronic psychiatric disorders, especially more severe mood disorders such as MDD, deserves further exploration. Whereas ADHD was generally diagnosed at 7.8 years of age, MDD was diagnosed in 6.3 % of this cohort at a mean age of 12.1 years, confirming that the onset of MDD is typically several years after the diagnosis of ADHD [17]. The MDD prevalence in this ADHD cohort comports with general population study rates of 2 % of children and 6–8 % of adolescents [1, 10], but is not as high as Angold et al.’s [11] estimate, perhaps due to methodological differences, i.e., Angold et al.’s cohort was drawn from the general population and included a sizeable percentage of untreated cases, whereas our cohort was composed only of physician-diagnosed and treated cases. Our results also substantiate previous findings that females and older children/adolescents are more likely to develop incident MDD, as well as externalizing and internalizing psychiatric disorders (CD/ODD, anxiety, and substance use disorders) [1, 11, 17, 18]. That African Americans were less likely to develop depression is a new finding in this literature, but may be the result of clinical bias among practitioners during the epoch examined, wherein African Americans were less likely, in general, to be diagnosed with affective disorders [32]. Comorbid medical conditions diagnosed in this ADHD cohort and their prevalence were primarily organic brain conditions or mental retardation, obesity, epilepsy, traumatic brain injury, migraine headaches, thyroid disorder, type 2 diabetes mellitus, congenital heart disease, dyslipidemia, cerebrovascular disorder, and type 1 diabetes mellitus, which again comports with the results from disparate previous studies [6, 18–20, 22]. However, in this community-based service system analysis, only obesity was significantly and consistently associated with incident MDD, controlling for all the other comorbid psychiatric and medical conditions investigated and demographic differences. The diagnosis of obesity may be related to endogenous factors [33] or to the ADHD medications that the children were taking for several years prior to being diagnosed with MDD and treated with antidepressants, but more precise clinical research studies are necessary to determine the nature of this relationship. Incident MDD also appears to be associated with ADHD-related treatments and their duration [6, 7, 24, 25]. The children in our ADHD cohort were being treated with a range of pharmacotherapies, but only those treated with pemoline, atomoxetine, or dextroamphetamine/mixed amphetamine salts were statistically more likely to develop syndromal MDD. Since pemoline was withdrawn from the USA commercial market due to liver toxicity early in the study period covered and atomoxetine was introduced to the USA commercial market in the last few years of the
study period, low numbers of patients in these medication groups may have skewed the statistical results. When duration of exposure to the other ADHD pharmacotherapies was investigated, there were no changes in the relative contribution of the demographic and comorbid conditions as predictors of incident MDD. The duration of ADHD treatment may also be related to the presence of a more severe, complicated form of ADHD, but we have no means of assessing ADHD severity in this data set. To our knowledge, these are the first large-scale clinical results to quantify this association and support some previous clinical observations, while contradicting the results of other systematic studies in smaller clinical samples [24–30]. These contradictory findings may indicate that, in susceptible individuals, exposure to certain ADHD medications may be associated with amplification of affective symptomatology, but that ADHD pharmacotherapies in general do not attenuate or approximate the influence of comorbid psychiatric disorders or demographic/individual risk factors (i.e., genetic/biological factors) on incident MDD. Indeed, whereas the presence of comorbid CD/ODD and anxiety disorder were associated with a[250 % increase in the likelihood of developing MDD, the ADHD pharmacotherapies were associated with only a 28–69 % overall increase or a 1 % increase for every month of exposure. Therefore, their potential clinical impact may be fairly minimal and observable only in the susceptible individuals. Nevertheless, the overall risk/benefit ratio of taking these medications in pediatric patients with diagnosed ADHD is relatively low and our results need to be replicated in future clinical research studies. Most importantly, comorbid psychiatric disorders were also prevalent in the ADHD cohort: 39.2 % with CD/ODD, 14.4 % were diagnosed with anxiety disorder, and 5.5 % with a substance use disorder, evidence that comports with findings by previous investigators [1]. Moreover, comorbid anxiety and CD/ODD conditions were the most significant factors predicting an increased probability of children with ADHD developing incident MDD and thus, may represent heterotypic continuity, i.e., different manifestations of the same underlying pathologic process, across different developmental stages into adulthood that is potentially useful in distinguishing a pathway to MDD, its complex trajectory, and guiding treatment decision making for the comorbid disorders [1]. The comorbidities of ADHD, MDD, CD/ODD, or anxiety disorder may represent a discernible and more complicated/severe endophenotype requiring multiple interventions over time extending into adulthood [8, 26, 34]. Taken together with recent results from genetic studies demonstrating a moderate correlation between ADHD and MDD [35], and neuroimaging findings which implicate some overlapping regions and neural circuits in the
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essential features of these conditions [36–38], it seems likely that the comorbidity of ADHD, MDD, and CD/ODD is due to a shared neurobiologic diathesis, arising from overlapping pathophysiologies. There is also mounting evidence from biological marker studies of multiple, dysregulated, contributing factors being associated with MDD, e.g., growth factors, cytokines, hormones, and endocrine/ metabolic markers; however, it remains unclear how the predictive algorithms derived from comprehensive biomarker panels will be affected by psychiatric comorbidities [39]. Additional neuroimaging, genetic, and biomarker studies are needed to further explicate this potential nexus of pathophysiologies. Our results suggest that these studies might productively be focused on children with ADHD who develop comorbid CD/ODD and anxiety disorder during the 6–12 years of age range, to identify a set of predictors with greater sensitivity and specificity which could not only inform and improve treatment decision making, but may also lead to earlier detection of the complex/severe cases and suggest prevention/pre-emption strategies. While a substance use disorder was statistically significant in this MDD cohort, which comports with previous studies [7, 12–18], it consistently developed after the MDD and in a small subset of the adolescents. Substance use disorder may represent a condition that is secondary to the comorbid ADHD/MDD/CD/ODD/anxiety disorders, perhaps developing due to inadequate control of the multiple symptom constellations present in these complex cases. The perspective provided by this longitudinal database has several strengths. The cohort represents a large, heterogeneous group of children and adolescents being treated for diagnosed ADHD and varying periods of exposure to the ADHD medications examined. Generally, there is sufficient power in the treated cohort to detect somewhat low-incidence comorbid psychiatric or medical conditions. Previous studies have found that although observational (Medicaid) databases provide much less detailed information on individuals than would a structured research interview, the medical and psychiatric diagnoses coded and the utilization data are more reliable than patient or family self-reports [40] and administrative claims data have been used to accurately identify positive predictive values for outcomes such as suicidal behavior or antidepressant adherence in children [41, 42]. The cohort is also representative of pediatric patients in routine care settings in the southeastern USA states and other small states with predominantly small-city and rural populations in terms of age, sex, racial demographics, and Medicaid eligibility, but these results may not be generalizable to other patient groups [43–45]. Furthermore, these results need to be interpreted with several limitations in mind. Secondary administrative data sets and observational techniques were used, and no
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structured research or clinical interviews were employed to confirm any of the diagnoses assigned by the pediatrician or psychiatrist. Identification of psychiatric and non-psychiatric medical conditions was based on spontaneous selfreporting to or observation by a primary care physician or psychiatrist, and their designation of each diagnosis in the Medicaid billing system; consequently, the prevalence/ incidence of these conditions may be an underestimate which we cannot quantify. The low proportion of MDD and other important medical and psychiatric conditions in the current study may not be due to sample differences, but to problems in the accuracy of physician coding of multiple diagnoses. There may also be some inherent bias in the coding of medical diagnoses or interventions to maximize revenue, which we cannot quantify, that may result in underestimates of the medical conditions considered. Moreover, the methods employed in this study focus exclusively on diagnosed cases seeking treatment, not to the prevalence of MDD in an epidemiologic/community sample of cases that may include those not seeking or receiving treatment. Data regarding key risk factors such as family history of obesity, related metabolic disorders, and related psychiatric disorders were not available to the investigators and are not modeled in these analyses. Children and adolescents who dropped out of treatment, who were periodically ineligible for Medicaid, or who died before they were registered in Medicaid coverage are not represented in this data set. These results report associations and, as a result, directions of causality cannot be inferred. Finally, although many significant covariates have been controlled for, other unmeasured differences in patients or their treatment, including non-pharmacological treatments, may explain the findings. In conclusion, the picture provided by these treated population-based findings provides an opportunity for the primary care physician/pediatrician and psychiatrist rendering early care to identify a diagnostic subgroup which is rapidly developing several more chronic and severe psychiatric disorders. Our results suggest that several neurodevelopmental disorders are intricately associated with MDD developing in children with ADHD, and that its etiology appears to be multifactorial, stemming from a combination of individual (sex, ethnicity, age), biological/ genetic (CD/ODD, anxiety disorders, and obesity), and environmental influences (exposure to pharmacotherapies). Studies in adults with mood disorders and ADHD have elucidated many of these same comorbidities and demographic factors, indicating that this subphenotype is a severe, complex, and chronic condition, requiring multiple treatment interventions over time. Increasing the clinical knowledge base regarding factors predicting the long-term development of a more severe and complicated subphenotype should serve as an impetus for the use of clinical
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intervention strategies which could optimize long-term outcomes in this high-risk group. Pediatric and psychiatric providers are behooved to be more vigilant in detecting the anticipated emergence of comorbid symptoms and disorders, especially anxiety, CD/ODD, and MDD; to stratify individuals as being at higher/highest risk for developing a severe, complex, and chronic condition; and to provide early interventions to delay incident syndromal MDD or minimize its severity and associated impairment over time. Acknowledgments Data acquisition was supported by a State Mental Health Data Infrastructure Grant (SAMHSA SM54192). Funding for the statistical analyses was provided through a Clinical Incentive Research Grant from the University of South Carolina, Office of the Provost. The views expressed do not necessarily represent those of the funding agency or official findings of the South Carolina Department of Health and Human Services (Medicaid). Conflict of interest Dr. Jerrell has received research grants from and served on national advisory boards for NIH, Eli Lilly, and Bristol Myers Squibb; Dr. McIntyre has received honoraria for speaking and served as a consultant to Schering-Plough, received research grants from Eli Lilly, Stanley Medical Research Institute, and National Alliance for Research on Schizophrenia and Depression, and served on advisory boards for AstraZeneca, Bristol Myers Squibb, France Foundation, GlaxoSmithKline, Janssen-Ortho, Solvay/Wyeth, Eli Lilly, Lundbeck, Organon, Biovail, Pfizer, and Shire. Dr. Park reports no competing interests. None of these entities had any involvement in this investigation.
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ORIGINAL PAPER
Risk factors for incident major depressive disorder in children and adolescents with attention-deficit/hyperactivity disorder Jeanette M. Jerrell • Roger S. McIntyre Yong-Moon Mark Park
•
Received: 28 August 2013 / Accepted: 21 March 2014 Ó Springer-Verlag Berlin Heidelberg 2014
Abstract The greater burden of illness in youth with cooccurring attention-deficit/hyperactivity disorder (ADHD) and major depressive disorder (MDD) deserves further investigation, specifically regarding the influence of other psychiatric or medical conditions and the pharmacotherapies prescribed. A retrospective cohort design was employed, using South Carolina’s (USA) Medicaid claims’ dataset covering outpatient and inpatient medical services, and medication prescriptions between January, 1996 and December, 2006 for patients B17 years of age. The cohort included 22,452 cases diagnosed with ADHD at a mean age 7.8 years; 1,259 (5.6 %) cases were diagnosed with MDD at a mean age of 12.1 years. The probability of a child with ADHD developing MDD was significantly associated with a comorbid anxiety disorder (aOR = 3.53), CD/ODD (aOR = 3.45), or a substance use disorder (aOR = 2.31); being female (aOR = 1.77); being treated with pemoline (aOR = 1.69), atomoxetine (aOR = 1.31), or mixed amphetamine salts (aOR = 1.28); a comorbid
obesity diagnosis (aOR = 1.29); not being African American (aOR = 1.23), and being older at ADHD diagnosis (aOR = 1.09). Those developing MDD also developed several comorbid disorders later than the ADHD-only cohort, i.e., conduct disorder/oppositional-defiant disorder (CD/ODD), at mean age of 10.8 years, obesity at 11.6 years, generalized anxiety disorder at 12.2 years, and a substance use disorder at 15.7 years of age. Incident MDD was more likely in individuals clustering several demographic, clinical, and treatment factors. The phenotypic progression suggested herein underscores the need for coordinated early detection and intervention to prevent or delay syndromal MDD, or to minimize its severity and associated impairment over time. Keywords Major depressive disorder Attention-deficit/ hyperactivity disorder Conduct disorder Anxiety disorder Obesity
Introduction J. M. Jerrell (&) Department of Neuropsychiatry and Behavioral Science, University of South Carolina School of Medicine, 15 Medical Park, Suite 301, Columbia, SC 29203, USA e-mail: [email protected] R. S. McIntyre Department of Psychiatry, University of Toronto, Toronto, Canada R. S. McIntyre Department of Pharmacology, University of Toronto, Toronto, Canada Y.-M. M. Park Department of Epidemiology and Biostatistics, University of South Carolina Arnold School of Public Health, Columbia, USA
Attention-deficit/hyperactivity disorder (ADHD) is one of the most commonly diagnosed cognitive/behavioral disorders in children and adolescents, with an estimated prevalence of about 3–5 % worldwide [1, 2]. ADHD is characterized by impairments not only in attention and emotional regulation, but also in behavioral control. The etiology of ADHD is likely multifactorial, stemming from a combination of genetic/familial, biological [3–5], and environmental influences [6]. ADHD and externalizing disorders, such as conduct disorder/oppositional-defiant disorder (CD/ODD), have been found to co-occur in 30–50 % of cases in both epidemiologic and clinical samples; internalizing disorders, such as anxiety and
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depression, are also frequently comorbid with ADHD [7– 9]. Major depressive disorder (MDD) occurs in about 2 % of children and 6–8 % of adolescents [1, 10] in the general population. However, the prevalence of MDD in youth with ADHD has been found to be more than five times higher than in those without ADHD [11]. Family and population studies of ADHD and MDD have noted that while personal and familial risk factors between the two disorders are evident, especially in families with diagnosed antisocial disorders, other disorders with externalizing/ aggressive features, anxiety disorders, or substance use disorders are also apparent [8, 12–16]. Age and gender differences have been evident in previous clinical studies wherein females have an earlier age of onset of depressive symptoms or MDD, a more severe course for both illnesses, and a higher risk of developing disruptive, mood, anxiety, and substance use disorders [7, 8, 17, 18]. The onset of MDD is typically several years after the diagnosis of ADHD, suggesting that it may also be the cumulative result of ADHD-related impairments or negative environmental circumstances (e.g., poor psychosocial adjustment in peer or family relationships or child maltreatment) [6, 17], ADHD-related treatments, comorbid conditions that may be pathophysiologically associated with both disorders, e.g., obesity, diabetes mellitus, dyslipidemia, or thyroid disorders [19, 20], or conditions frequently associated with the development of depressive symptoms, e.g., traumatic brain injury [21]. Furthermore, some comorbid disease states, such as epilepsy, cancer, and cardiovascular disease, may initiate depressive symptoms more often in one sex over the other [22]. Previous epidemiologic and clinical studies have demonstrated a generally consistent ‘‘off-trajectory’’ progression of these neurodevelopmental/psychiatric disorders in youth [23], but have not systematically investigated the role of neuroendocrine/metabolic disorders in this progression. Other potential correlates for the development of MDD among youth with ADHD may be the severity of ADHD symptoms. The psychostimulant medications used to treat ADHD may be associated in some patients with dysphoric mood symptoms, and subsequent pre-marketing, controlled studies and post-marketing, clinical reports of psychostimulant- or atomoxetine-associated depression have confirmed this finding in B5 % of treated patients [24–30]. The encompassing aim of this analysis is to further characterize the clinical correlates of the comorbidity of MDD and ADHD, to elucidate their potential significance in earlier identification of those at risk of incident MDD, and to determine the relative influence of ADHD pharmacotherapy on the incidence of MDD in an ADHD cohort. Given the substantially higher rates of long-term impairment, morbidity, and increased risk of mortality
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(from suicide) associated with co-occurring ADHD and MDD compared to having either disorder alone, this area of inquiry deserves further investigation.
Methods Data for this study were obtained retrospectively from the South Carolina (SC), USA Medicaid database during an 11-year period from January 1, 1996 through December 31, 2006. Medical claims were used to identify a service encounter, date of service, and the International Classification of Diseases, 9th Clinical Modification diagnosis codes (ICD-9) related to that visit. Selection criteria were age B17 years, continuous enrollment in Medicaid for a minimum of 9 months in each calendar year, and at least one initial service encounter with an ICD-9 diagnosis of 314.00 or 314.01. ICD-9 codes of 314 or 314.1–314.9 indicating hyperkinesis not associated with attention-deficit disorder were omitted from this study. The methods involved in this study were approved by the University of South Carolina Institutional Review Board as exempt from human subject research guidelines (45 Code of Federal Regulations part 46). Within this ADHD cohort, the following categories of diagnosed conditions were evaluated: MDD (ICD-9 codes: 296.2, 296.3), CD/ODD (312.x, 313.81); anxiety (300.0x), obesity (278; 278.00; 278.01), dyslipidemia (272, 288.0, 285.9), type 2 diabetes mellitus (250.00–250.92 with 5th digit = 0.2), type 1 diabetes mellitus (250.00–250.93 with 5th digit = 1.3), thyroid disorders (240.x–246.x), cerebrovascular disorders (436–437; 435; 430–434; 440–448), epilepsy (345.0, 345.00–345.91), seizures (780.3), or migraine headaches (346.x). Comorbid congenital heart defects were coded as 747.0–747.9; organic brain disorders/mental retardation as 310, 310.0–310.9, 318, 318.1, 318.2, 317.xx, 319.xx; traumatic brain injury as 850.xx– 854.xx; and a substance use disorder was coded as 304.x or 305.x. Child abuse or neglect/maltreatment was coded as E967.0–E967.9. Cases with ICD-9 codes for other depressive disorders, bipolar or cyclothymic disorders, or for 250 or 250.1–250.9 without a fifth digit (i.e., ‘‘unspecified diabetes’’) were excluded from this investigation. Under Medicaid, psychiatric diagnoses are generally made by a licensed psychiatrist, whereas medical diagnoses are made by the licensed primary care physician/ pediatrician. Descriptive statistical analyses were performed on the ADHD and MDD cases to determine the prevalence of each condition and any bivariate associations between the predictor variables of interest, i.e., individual risk factors (age at ADHD diagnosis, sex, race); comorbid conditions (i.e., CD/ODD, substance use disorder, obesity, diabetes
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mellitus, dyslipidemia, or thyroid disorders), and pharmacologic interventions received for ADHD (i.e., coded separately as the medication prescribed/not prescribed and as the number of months each medication was filled/refilled from the Medicaid pharmacy file). To address our primary research questions regarding the factors which significantly increase the odds of a child with ADHD being diagnosed with syndromal MDD, two multiple logistic regression equations were constructed to assess the relative odds associated with having any of these independently diagnosed conditions, including individual risk factors (dichotomously coded sex and ethnicity; continuously coded age at ADHD diagnosis), comorbid psychiatric disorders (CD/ODD, anxiety disorder, and substance use disorder), comorbid medical conditions (organic brain conditions or mental retardation, epilepsy, traumatic brain injury, migraine headaches, thyroid disorder, obesity, type 1 diabetes mellitus, type 2 diabetes mellitus, dyslipidemia, congenital heart disease, and cerebrovascular disorder), and the prescribed psychostimulant medication or atomoxetine (coded as yes/no in one regression equation and as the number of months the child was taking/exposed to the medication in the second equation) as predictor variables. Each full regression model was then reduced through a stepwise procedure to reflect only the statistically significant variables associated with being diagnosed with MDD. The measure of association reported for these results is the adjusted odds ratio (aOR) with a corresponding 95 % confidence interval.
Table 1 Descriptive analysis of the cohort of 22,452 youths diagnosed with ADHD Indicator
N (%)
Gender: male
15,508 (69.1)
Race: non-African American
11,501 (51.2)
African American Mean age at ADHD diagnosis (years)
7.8 (±2.9)a
Diagnosed with major depressive disorder
1,259 (5.6)
Mean age at major depressive disorder diagnosis (years)
12.1 (±3.6)
Diagnosed with conduct disorder/oppositional-defiant disorder (CD/ODD)
8,764 (39.0)
Mean age at CD/ODD diagnosis (years)
9.2 (±3.8)
Diagnosed with anxiety
3,194 (14.2) 10.6 (?4.1)
Mean age at anxiety diagnosis (years) Diagnosed with substance use disorder
1,224 (5.5)
Mean age at substance use diagnosis (years)
14.9 (±3.6)
Comorbid medical conditions Diagnosed with obesity
Results The ADHD cohort consisted of 22,624 child and adolescent cases. Descriptive results regarding this cohort (Tables 1, 2) indicate that 69.1 % of the cohort was male and 48.8 % was African American, with a mean age at diagnosis of the ADHD of 7.8 years (SD = 2.9 years). MDD was diagnosed in 5.6 % (N = 1,259) of the cohort at a mean age of 12.1 years (SD = 3.6 years). Thirty-nine percent of the ADHD cohort was diagnosed with CD/ODD at a mean age of 9.2 years, 14.2 % with anxiety disorder, predominantly generalized anxiety disorder, at 10.6 years, and 5.5 % with a substance use disorder at 14.9 years of age. Comorbid medical conditions diagnosed in the ADHD cohort and their prevalence were organic brain conditions or mental retardation (26.2 %), obesity (9.1 %), epilepsy (6.7 %), traumatic brain injury (4.9 %), migraine headaches (4.8 %), thyroid disorder (2.8 %), type 2 diabetes mellitus (1.8 %), congenital heart disease (2.5 %), dyslipidemia (2.2 %), cerebrovascular disorder (2.1 %), and type 1 diabetes mellitus (1.1 %). Abuse was noted as the external cause of injury for 0.25 % (N = 57) of the ADHD cohort (Table 1).
10,951 (48.8)
a
2,047 (9.1)
Mean age at obesity diagnosis (years)
9.5 (±4.8)
Diagnosed with type 1 diabetes mellitus Diagnosed with type 2 diabetes mellitus
246 (1.1) 413 (1.8)
Diagnosed with dyslipidemia
491 (2.8)
Diagnosed with thyroid disorder
635 (2.8)
Diagnosed with congenital heart disease
553 (2.5)
Diagnosed with cerebrovascular disorder
469 (2.1)
Diagnosed with traumatic brain injury
1,090 (4.9)
Diagnosed with migraine headaches
1,076 (4.8)
Diagnosed with epilepsy
1,493 (6.7)
Diagnosed with organic brain disease/mental retardation
5,876 (26.2)
Diagnosed external cause of injury (E-code)
57 (0.25)
±Standard deviation
This clinical cohort was being treated with a range of ADHD medications: 61.9 % were taking methylphenidate, on average, for 17 months; 55.2 % were taking mixed amphetamine salts/dextroamphetamine for an average of 17 months; 1.3 % was taking pemoline, for about 8 months, on average; and 22.1 % were taking atomoxetine for an average of 8 months (Table 2). Diagnosed obesity was higher in those children treated with methylphenidate (16.5 %) and mixed amphetamine salts/dextroamphetamine (12.1 %). As shown in Table 3, in the logistic regression modeling the comorbid conditions along with ADHD
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Eur Child Adolesc Psychiatry Table 2 Prescribed ADHD medications in ADHD cohort ADHD medication
N (%)
Methylphenidate
13,902 (61.9)
Mean months taking methylphenidate
16.8 (±17.9)a
Mixed amphetamine salts/dextroamphetamine
12,396 (55.2)
Mean months taking mixed amphetamine salts/ dextroamphetamine
15.6 (±17.2)
Pemoline
298 (1.3)
Mean months taking pemoline
8.2 (±13.2)
Atomoxetine Mean months taking atomoxetine
4,970 (22.1) 7.7 (±8.8)
a
±Standard deviation
Table 4 Adjusted odds ratios for incident depression related to comorbid conditions, duration of prescribed ADHD medications in months, and individual risk factors (stepwise logistic regression model) Parameter
Adjusted odds ratio
95 % confidence intervals
Sex (female)
1.77**
1.56–2.00
Ethnicity (black)
0.80*
0.71–0.91
Age at ADHD diagnosis
1.09**
1.07–1.11
Conduct disorder/ODD diagnosis
3.47**
3.04–3.97
Anxiety diagnosis
3.53**
3.11–4.01
Substance abuse diagnosis Obesity diagnosis
2.36** 1.28*
1.98–2.81 1.07–1.53
Mixed amphetamine salts/ dextroamphetamine treatment duration
1.01*
1.00–1.01
Table 3 Adjusted odds ratios for incident depression related to comorbid conditions, prescribed medications, and individual risk factors (stepwise logistic regression model)
Atomoxetine treatment duration
1.01*
1.00–1.02
Methylphenidate treatment duration
1.01*
1.00–1.01
Parameter
* Significant at p = 0.01 or less
Adjusted odds ratio
95 % confidence intervals
Sex (female)
1.77**
1.56–2.00
Ethnicity (black)
0.81*
0.71–0.92
Age at ADHD diagnosis
1.09**
1.07–1.12
Conduct disorder/odd diagnosis
3.45**
3.02–3.94
Anxiety diagnosis
3.53**
3.11–4.01
Substance abuse diagnosis
2.31**
1.94–2.76
Obesity
1.29*
1.08–1.54
Mixed amphetamine salts/ dextroamphetamine treatment
1.28*
1.12–1.45
Pemoline treatment
1.69*
1.18–2.44
Atomoxetine treatment
1.31*
1.14–1.50
* Significant at p = 0.01 or less ** Significant at p \ 0.0001
pharmacotherapies as prescribed/not prescribed, ten predictor variables were significantly associated with increased odds of a child being diagnosed with MDD: being diagnosed with an anxiety disorder (aOR = 3.53), CD/ODD (aOR = 3.45), or a substance use disorder (aOR = 2.31); being female (aOR = 1.77); being treated with pemoline (aOR = 1.69); being diagnosed with obesity (aOR = 1.29); being treated with atomoxetine (aOR = 1.31) or mixed amphetamine salts/dextroamphetamine (aOR = 1.28); not being African American (aOR = 1.23); and being older at ADHD diagnosis (aOR = 1.09). The odds of developing MDD increased approximately 9 % per year older the patient was when ADHD was diagnosed, after adjusting for other confounding factors. More specifically, children with ADHD who developed MDD were older at ADHD diagnosis and also developed several comorbid disorders later than the
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** Significant at p \ 0.0001
ADHD-only cohort, i.e., CD/ODD at mean age of 10.8 years, obesity at 11.6 years, anxiety disorder at 12.2 years, and a substance use disorder at 15.7 years of age. None of the other covariates demonstrated a statistically significant association with incident MDD. In the second logistic regression equation (Table 4) capturing length/duration of exposure to the ADHD medications, ten variables were also identified as significantly associated with higher odds of a child being diagnosed with MDD: being diagnosed with an anxiety disorder (aOR = 3.53), CD/ODD (aOR = 3.47), or a substance use disorder (aOR = 2.36); being female (aOR = 1.77); being diagnosed with obesity (aOR = 1.28); being treated with methylphenidate (aOR = 1.01), mixed amphetamine salts/ dextroamphetamine (aOR = 1.01), or atomoxetine (aOR = 1.01); not being African American (aOR = 1.25); and being older at ADHD diagnosis (aOR = 1.09). The size of the ORs was about the same for all of the demographics and comorbid medical conditions in the two equations, but the longer a child was exposed to one of three ADHD pharmacotherapies, the greater his/her chances of being diagnosed with MDD, i.e., about 1 % more per month of pharmacotherapy. None of the other covariates demonstrated a statistically significant association with incident MDD.
Discussion ADHD is a major health concern in youth, and its role in a ‘‘prodromal period’’ preceding the diagnosis of several
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comorbid and chronic psychiatric disorders, especially more severe mood disorders such as MDD, deserves further exploration. Whereas ADHD was generally diagnosed at 7.8 years of age, MDD was diagnosed in 6.3 % of this cohort at a mean age of 12.1 years, confirming that the onset of MDD is typically several years after the diagnosis of ADHD [17]. The MDD prevalence in this ADHD cohort comports with general population study rates of 2 % of children and 6–8 % of adolescents [1, 10], but is not as high as Angold et al.’s [11] estimate, perhaps due to methodological differences, i.e., Angold et al.’s cohort was drawn from the general population and included a sizeable percentage of untreated cases, whereas our cohort was composed only of physician-diagnosed and treated cases. Our results also substantiate previous findings that females and older children/adolescents are more likely to develop incident MDD, as well as externalizing and internalizing psychiatric disorders (CD/ODD, anxiety, and substance use disorders) [1, 11, 17, 18]. That African Americans were less likely to develop depression is a new finding in this literature, but may be the result of clinical bias among practitioners during the epoch examined, wherein African Americans were less likely, in general, to be diagnosed with affective disorders [32]. Comorbid medical conditions diagnosed in this ADHD cohort and their prevalence were primarily organic brain conditions or mental retardation, obesity, epilepsy, traumatic brain injury, migraine headaches, thyroid disorder, type 2 diabetes mellitus, congenital heart disease, dyslipidemia, cerebrovascular disorder, and type 1 diabetes mellitus, which again comports with the results from disparate previous studies [6, 18–20, 22]. However, in this community-based service system analysis, only obesity was significantly and consistently associated with incident MDD, controlling for all the other comorbid psychiatric and medical conditions investigated and demographic differences. The diagnosis of obesity may be related to endogenous factors [33] or to the ADHD medications that the children were taking for several years prior to being diagnosed with MDD and treated with antidepressants, but more precise clinical research studies are necessary to determine the nature of this relationship. Incident MDD also appears to be associated with ADHD-related treatments and their duration [6, 7, 24, 25]. The children in our ADHD cohort were being treated with a range of pharmacotherapies, but only those treated with pemoline, atomoxetine, or dextroamphetamine/mixed amphetamine salts were statistically more likely to develop syndromal MDD. Since pemoline was withdrawn from the USA commercial market due to liver toxicity early in the study period covered and atomoxetine was introduced to the USA commercial market in the last few years of the
study period, low numbers of patients in these medication groups may have skewed the statistical results. When duration of exposure to the other ADHD pharmacotherapies was investigated, there were no changes in the relative contribution of the demographic and comorbid conditions as predictors of incident MDD. The duration of ADHD treatment may also be related to the presence of a more severe, complicated form of ADHD, but we have no means of assessing ADHD severity in this data set. To our knowledge, these are the first large-scale clinical results to quantify this association and support some previous clinical observations, while contradicting the results of other systematic studies in smaller clinical samples [24–30]. These contradictory findings may indicate that, in susceptible individuals, exposure to certain ADHD medications may be associated with amplification of affective symptomatology, but that ADHD pharmacotherapies in general do not attenuate or approximate the influence of comorbid psychiatric disorders or demographic/individual risk factors (i.e., genetic/biological factors) on incident MDD. Indeed, whereas the presence of comorbid CD/ODD and anxiety disorder were associated with a[250 % increase in the likelihood of developing MDD, the ADHD pharmacotherapies were associated with only a 28–69 % overall increase or a 1 % increase for every month of exposure. Therefore, their potential clinical impact may be fairly minimal and observable only in the susceptible individuals. Nevertheless, the overall risk/benefit ratio of taking these medications in pediatric patients with diagnosed ADHD is relatively low and our results need to be replicated in future clinical research studies. Most importantly, comorbid psychiatric disorders were also prevalent in the ADHD cohort: 39.2 % with CD/ODD, 14.4 % were diagnosed with anxiety disorder, and 5.5 % with a substance use disorder, evidence that comports with findings by previous investigators [1]. Moreover, comorbid anxiety and CD/ODD conditions were the most significant factors predicting an increased probability of children with ADHD developing incident MDD and thus, may represent heterotypic continuity, i.e., different manifestations of the same underlying pathologic process, across different developmental stages into adulthood that is potentially useful in distinguishing a pathway to MDD, its complex trajectory, and guiding treatment decision making for the comorbid disorders [1]. The comorbidities of ADHD, MDD, CD/ODD, or anxiety disorder may represent a discernible and more complicated/severe endophenotype requiring multiple interventions over time extending into adulthood [8, 26, 34]. Taken together with recent results from genetic studies demonstrating a moderate correlation between ADHD and MDD [35], and neuroimaging findings which implicate some overlapping regions and neural circuits in the
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essential features of these conditions [36–38], it seems likely that the comorbidity of ADHD, MDD, and CD/ODD is due to a shared neurobiologic diathesis, arising from overlapping pathophysiologies. There is also mounting evidence from biological marker studies of multiple, dysregulated, contributing factors being associated with MDD, e.g., growth factors, cytokines, hormones, and endocrine/ metabolic markers; however, it remains unclear how the predictive algorithms derived from comprehensive biomarker panels will be affected by psychiatric comorbidities [39]. Additional neuroimaging, genetic, and biomarker studies are needed to further explicate this potential nexus of pathophysiologies. Our results suggest that these studies might productively be focused on children with ADHD who develop comorbid CD/ODD and anxiety disorder during the 6–12 years of age range, to identify a set of predictors with greater sensitivity and specificity which could not only inform and improve treatment decision making, but may also lead to earlier detection of the complex/severe cases and suggest prevention/pre-emption strategies. While a substance use disorder was statistically significant in this MDD cohort, which comports with previous studies [7, 12–18], it consistently developed after the MDD and in a small subset of the adolescents. Substance use disorder may represent a condition that is secondary to the comorbid ADHD/MDD/CD/ODD/anxiety disorders, perhaps developing due to inadequate control of the multiple symptom constellations present in these complex cases. The perspective provided by this longitudinal database has several strengths. The cohort represents a large, heterogeneous group of children and adolescents being treated for diagnosed ADHD and varying periods of exposure to the ADHD medications examined. Generally, there is sufficient power in the treated cohort to detect somewhat low-incidence comorbid psychiatric or medical conditions. Previous studies have found that although observational (Medicaid) databases provide much less detailed information on individuals than would a structured research interview, the medical and psychiatric diagnoses coded and the utilization data are more reliable than patient or family self-reports [40] and administrative claims data have been used to accurately identify positive predictive values for outcomes such as suicidal behavior or antidepressant adherence in children [41, 42]. The cohort is also representative of pediatric patients in routine care settings in the southeastern USA states and other small states with predominantly small-city and rural populations in terms of age, sex, racial demographics, and Medicaid eligibility, but these results may not be generalizable to other patient groups [43–45]. Furthermore, these results need to be interpreted with several limitations in mind. Secondary administrative data sets and observational techniques were used, and no
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structured research or clinical interviews were employed to confirm any of the diagnoses assigned by the pediatrician or psychiatrist. Identification of psychiatric and non-psychiatric medical conditions was based on spontaneous selfreporting to or observation by a primary care physician or psychiatrist, and their designation of each diagnosis in the Medicaid billing system; consequently, the prevalence/ incidence of these conditions may be an underestimate which we cannot quantify. The low proportion of MDD and other important medical and psychiatric conditions in the current study may not be due to sample differences, but to problems in the accuracy of physician coding of multiple diagnoses. There may also be some inherent bias in the coding of medical diagnoses or interventions to maximize revenue, which we cannot quantify, that may result in underestimates of the medical conditions considered. Moreover, the methods employed in this study focus exclusively on diagnosed cases seeking treatment, not to the prevalence of MDD in an epidemiologic/community sample of cases that may include those not seeking or receiving treatment. Data regarding key risk factors such as family history of obesity, related metabolic disorders, and related psychiatric disorders were not available to the investigators and are not modeled in these analyses. Children and adolescents who dropped out of treatment, who were periodically ineligible for Medicaid, or who died before they were registered in Medicaid coverage are not represented in this data set. These results report associations and, as a result, directions of causality cannot be inferred. Finally, although many significant covariates have been controlled for, other unmeasured differences in patients or their treatment, including non-pharmacological treatments, may explain the findings. In conclusion, the picture provided by these treated population-based findings provides an opportunity for the primary care physician/pediatrician and psychiatrist rendering early care to identify a diagnostic subgroup which is rapidly developing several more chronic and severe psychiatric disorders. Our results suggest that several neurodevelopmental disorders are intricately associated with MDD developing in children with ADHD, and that its etiology appears to be multifactorial, stemming from a combination of individual (sex, ethnicity, age), biological/ genetic (CD/ODD, anxiety disorders, and obesity), and environmental influences (exposure to pharmacotherapies). Studies in adults with mood disorders and ADHD have elucidated many of these same comorbidities and demographic factors, indicating that this subphenotype is a severe, complex, and chronic condition, requiring multiple treatment interventions over time. Increasing the clinical knowledge base regarding factors predicting the long-term development of a more severe and complicated subphenotype should serve as an impetus for the use of clinical
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intervention strategies which could optimize long-term outcomes in this high-risk group. Pediatric and psychiatric providers are behooved to be more vigilant in detecting the anticipated emergence of comorbid symptoms and disorders, especially anxiety, CD/ODD, and MDD; to stratify individuals as being at higher/highest risk for developing a severe, complex, and chronic condition; and to provide early interventions to delay incident syndromal MDD or minimize its severity and associated impairment over time. Acknowledgments Data acquisition was supported by a State Mental Health Data Infrastructure Grant (SAMHSA SM54192). Funding for the statistical analyses was provided through a Clinical Incentive Research Grant from the University of South Carolina, Office of the Provost. The views expressed do not necessarily represent those of the funding agency or official findings of the South Carolina Department of Health and Human Services (Medicaid). Conflict of interest Dr. Jerrell has received research grants from and served on national advisory boards for NIH, Eli Lilly, and Bristol Myers Squibb; Dr. McIntyre has received honoraria for speaking and served as a consultant to Schering-Plough, received research grants from Eli Lilly, Stanley Medical Research Institute, and National Alliance for Research on Schizophrenia and Depression, and served on advisory boards for AstraZeneca, Bristol Myers Squibb, France Foundation, GlaxoSmithKline, Janssen-Ortho, Solvay/Wyeth, Eli Lilly, Lundbeck, Organon, Biovail, Pfizer, and Shire. Dr. Park reports no competing interests. None of these entities had any involvement in this investigation.
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