Key Points
Question
Does attention-deficit/hyperactivity disorder (ADHD) during childhood increase the risk of subsequent psychotic disorder?
Findings
Pooled estimates from this systematic review and meta-analysis of 12 studies and 1.85 million participants found an increase in the risk of psychotic disorder associated with a diagnosis of ADHD during childhood compared with not having ADHD during childhood.
Meaning
These findings suggest that childhood ADHD is associated with an increased risk of developing a psychotic disorder, and patients need follow-up even after 18 years of age.
This systematic review and meta-analysis provides a quantitative synthesis of studies exploring the association between childhood attention-deficit/hyperactivity disorder and the risk of subsequent psychotic disorder.
Abstract
Importance
Growing evidence supports an association between attention-deficit/hyperactivity disorder (ADHD) in childhood and subsequent psychotic disorders. Both disorders share physiopathological features such as attention deficits, dopaminergic imbalance, and genetic susceptibility. However, the results of epidemiologic studies have been conflicting.
Objective
To provide a quantitative synthesis of studies exploring the association between ADHD and the risk of subsequent psychotic disorder.
Data Sources
A systematic literature search of the MEDLINE, Scopus, PsycInfo, and Web of Science databases was performed from inception until the final analysis on July 7, 2020. No restriction of language was applied.
Study Selection
Cohort and case-control studies examining the relative risk of developing a psychotic disorder in people diagnosed with ADHD at younger than 18 years compared with control individuals without ADHD.
Data Extraction and Synthesis
Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) and Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were followed in reporting results. Two independent reviewers extracted the data and assessed the risk of bias of individual studies using the Newcastle-Ottawa Scale. Preferably adjusted odds ratios (aORs) or hazard ratios from the identified studies were extracted, and ORs were computed when they were not adjusted. A random-effects model was used to calculate the pooled relative effect using the meta package in R.
Main Outcomes and Measures
An association between ADHD (exposure) and psychotic disorder (outcomes); both diagnoses were based on international classification.
Results
A total of 15 studies were included in the review. Twelve studies were pooled in the meta-analysis, representing 1.85 million participants. A diagnosis of ADHD in childhood was associated with a significant increase in the risk of subsequent psychotic disorder, with a pooled relative effect of 4.74 (95% CI, 4.11-5.46; I2 = 43% [95% CI, 0%-70%]). No significant between-group differences were found for subgroup analyses according to psychotic disorder (odds ratio [OR], 5.04; 95% CI, 4.36-5.83) or schizophrenia (OR, 4.59; 95% CI, 3.83-5.50) outcomes, cohort (OR, 4.64; 95% CI, 4.04-5.34) or case-control (OR, 6.81; 95% CI, 4.21-11.03) study design, and adjusted (OR, 4.72; 95% CI, 4.11-5.46) or unadjusted (OR, 3.81; 95% CI, 1.39-10.49) estimates. Meta-regressions were not significant when sex and bias score were used as covariates. No evidence of publication bias was found.
Conclusions and Relevance
These findings suggest that childhood ADHD is associated with an increased risk of a subsequent psychotic disorder. Further studies are required to determine the mechanisms linking these common conditions and whether early intervention for ADHD might reduce the risk of subsequent psychotic disorder.
Introduction
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that typically begins in childhood and is characterized by inattention and/or hyperactivity-impulsivity. Attention-deficit/hyperactivity disorder affects 5% of children and adolescents1 and 2.5% of adults worldwide2 and is frequently associated with other disorders, such as neurodevelopmental disorders, borderline personality, conduct or mood disorders, and psychotic disorders (PDs).
Attention-deficit/hyperactivity disorder and PD share numerous risk factors and neurobiological defects. From a genetic standpoint, shared genetic susceptibility for large, rare chromosomal deletions and duplications3 as well as for common genetic variants have been described,4 and the risk of developing schizophrenia among first-degree relatives of people with ADHD is approximately twice as high as that of in healthy control individuals.5 Similar early environmental risk factors have also been observed in schizophrenia and ADHD, including obstetric complications, preterm birth, and low birth weight.6 From a physiopathological standpoint, ADHD and schizophrenia can be associated with deficits in shared overlapping brain circuits, such as the mesolimbic and mesocortical dopaminergic systems.7,8,9
Overall, epidemiologic evidence examining the association between ADHD and PD remains largely inconsistent. Because PDs cause a high degree of disability, it is important to evaluate potential risk factors. The aim of this study was to synthesize the current evidence regarding the association between ADHD during childhood and the subsequent risk of developing any PD in a systematic review and meta-analysis.
Methods
Protocol and Registration
The recommendations of the Meta-analysis of Observational Studies in Epidemiology (MOOSE) group10 (eTable 1 in the Supplement) and the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline11 were followed. The protocol of this review was registered in PROSPERO in November 2019.58 Changes, clarifications to the preregistered protocol, and post hoc analyses are described below.
Search Strategy
The electronic databases of MEDLINE, Scopus, PsycInfo, and Web of Science were searched from the date of their creation until November 22, 2019. Keywords describing ADHD and schizophrenia were combined. Filters were used to exclude review articles. No date or language limit was used. The search strategy for MEDLINE is provided in eTable 2 in the Supplement). The reference list of each identified record was reviewed to identify relevant studies. The searches were repeated before the final analysis was performed (July 7, 2020).
Study Selection
The inclusion criteria were as follows: (1) children younger than 18 years with ADHD diagnosed using any official diagnostic criteria (DSM-II to DSM-5 and International Classification of Diseases, Eighth Revision, to International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, because ADHD was not described in earlier versions of these classifications), with comorbid genetic disorders being accepted; (2) the presence of a control group from the general population, a group without any psychiatric diagnosis, or a group with any other psychiatric diagnosis but without ADHD; and (3) original articles published in a peer-reviewed journal, including cohort studies and case-control studies.
The main outcome of interest was the occurrence of any PD diagnosed using any recognized diagnostic criteria, namely, schizophrenia, schizophreniform disorder, schizotypal personality disorder, schizoaffective disorder, delusional disorder, brief psychotic disorder, and psychotic disorder not otherwise specified. Psychotic disorder had to clearly be diagnosed after ADHD, and no specific delay between those 2 diagnoses was needed. Psychotic disorder caused by another medical condition and mood disorders with psychotic features (eg, major depression with psychotic symptoms, bipolar disorder with psychotic symptoms) were not considered among the main outcomes. The exclusion criteria were (1) articles not within the field of interest of this review; (2) attention deficits or impulsive symptoms without any ADHD diagnosis (eg, conduct disorder, oppositional defiant disorder) or adult ADHD diagnosis; (3) any PD diagnosed before or at the same time as ADHD; and (4) case reports, case series, randomized clinical trials, reviews, or meta-analyses.
Data Extraction
Two independent reviewers (A.G. and L.J.) conducted the literature search. Each reviewer checked the relevance of the different studies through their titles and abstracts. Full texts were then read to determine eligibility. Disagreements were resolved through referral to a third author (M.N). Duplicates were managed using the Rayyan web application.12 For each included study, 2 reviewers (A.G. and L.J.) extracted the following variables using a standardized extraction form: study design, sample size, population characteristics, method for diagnosing ADHD and PD, study results with the association’s measure between ADHD and PD (ie, relative risks, odds ratios [ORs], hazard ratios [HRs], and 95% CIs), preferably adjusted whenever possible, and covariates included in subgroup analyses.
Extracted data were verified by a third author (M.N). In case of any missing data or for additional details, the primary authors were contacted by mail or directly by telephone. Ten authors were contacted, and 2 replies were received. When 2 articles had similar data sets, only the most recent article, the one with the largest data set, and/or the one with the lowest risk of bias was retained for the main analysis.
Bias and Quality Assessment
The risk of bias assessment of the included studies was conducted by 2 independent reviewers (A.G. and L.J.) using the Newcastle Ottawa Scale,13 as suggested by the Cochrane collaboration.14 Any discrepancies were resolved by discussion with a third author (M.N.). The Newcastle Ottawa Scale contains 8 items categorized into 3 dimensions: selection, comparability, and, depending on the study type, outcome or exposure. The total maximum score of these 3 dimensions is 9. For the comparability domain, we assessed the comparability of age and sex in the different groups. To assess the adequacy of follow-up duration in cohort studies, we decided to rate studies that followed up the population until 18 years of age as having a low risk of bias, because PD frequently emerges in young adulthood.15
Statistical Analysis
Data were analyzed using R studio software, version 4.0.2, with the “meta” package, version 4.15-1 (R Foundation). Meta-analyses use random-effects models because they allow the true population effect size to differ among studies. Measure of relative effects (ie, relative risk, HR, and OR) used to estimate associations between ADHD and PD were extracted and pooled.16 We extracted adjusted relative effects when available. If multiple adjustments were presented, we chose the model that was most consistent with our direct acyclic graph (eFigure 1 in the Supplement). We chose the model that adjusted for covariates that were classified as potential confounders in the direct acyclic graph because adjustment for mediators and colliders can introduce bias.17 When adjusted relative effects were not available, unadjusted ORs were computed using a 2-by-2 table.
We used the generic inverse variance method to allow studies that did not report raw data to be included in the meta-analyses and to compute unadjusted and adjusted or relative effects.14 When groups were only matched for a criterion, we considered the relative effects to be nonadjusted. We included zero-events studies to be more conservative, because their exclusion could increase the overall association of the exposure.18 When studies had zero events, 0.5 was added to all cell frequencies of these studies. Restricted maximum likelihood estimator for τ2 was used. To compute the summary effect’s CIs, we used both the conventional method for random effects and the Hartung-Knapp modification,19 and we kept the most conservative method (ie, the method that produced the largest CI).20 We used the I2 with its 95% CI to assess the heterogeneity of effect sizes and the Egger test and funnel plots to estimate publication biases.
The following subgroups and meta-regressions were decided a priori: study design, sex, treatment, relevant psychiatric comorbidities, and type of outcome. Regression-based tests were conducted only when 10 or more data points were available.
We conducted sensitivity analyses to determine the association of single studies with the pooled relative effects by omitting studies one at a time and re-estimating the pooled relative effect.21 Contrary to what we wrote in the preregistered protocol, we did not perform a subgroup analysis based on cutoffs for low and high risk of bias. Instead, a meta-regression using Newcastle Ottawa Scale rating as the regressor was conducted post hoc, as recommended in recent guidelines for meta-analyses of epidemiologic studies.16 Subgroup analyses by whether follow-up ended at or after 18 years of age and by country were also performed post hoc. Two-sided P < .05 indicated statistical significance.
Results
Search Results
The literature search generated 5228 articles (Figure 1). Thirteen additional records were identified through manual searches of bibliographies. After the removal of the duplicates, the title and abstract of 3782 records were screened, and 45 of these records were assessed for eligibility by full-text review. Thirty-one articles were excluded because they did not meet the inclusion criteria. The reasons for exclusion are outlined in Figure 1 and eTable 3 in the Supplement. We found no additional articles by searching the references of eligible articles. The additional search performed before the final analysis retrieved 1 article.22 A total of 15 unique studies were included in the systematic review.22,23,24,25,26,27,28,29,30,31,32,33,34,35,36 A total of 12 unique studies were included in the meta-analysis, with a total of 1.85 million unique participants.22,23,24,27,28,29,31,32,33,34,35,36 The arguments for excluding 3 studies are reported in eTable 3 in the Supplement. Characteristics of the included studies are given in Table 1. We used separate estimates for Ottosen et al33 for female and male patients, because they were independent. We pooled them in the meta-analysis.
Figure 1. Flowchart Diagram of Studies Selected for Inclusion in the Systematic Review and Meta-analysis.
Table 1. Study Characteristics.
| Source | Setting | Age at ADHD diagnosis, ya | No. of participants | Age at baseline, mean (SD), y | Age at end of follow-up, ya | Male, % | Outcome | Age at outcome diagnosis, y | No. of cases | Method of diagnosis | International classification | Relative effect (95% CI) | Adjusted covariates |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Cohort studies | |||||||||||||
| Kim-Cohen et al,29 2003 | Birth cohort, New Zealand | Range, 11-15 | ADHD:56 | 3 (0) | NA | NA | Schizophrenia and schizophreniform disorder | 26 | 7 | DISC, DIS-IV | DSM-III, DSM-III-R, DSM-IV | OR, 4.5 (1.8-11) | Sex |
| Controls: 898 | 3 (0) | NA | NA | 26 | 28 | ||||||||
| Biederman et al,24 2006 | Clinically referred participants, US | 11.4 (3.4) | ADHD: 140 | 11.4 (3.4) | 16.4 (3.7) | 0 | Psychotic disorders | NA | 6 | ADHD: K-SADS-E; outcome: SCID | DSM-III-R, DSM-IV | No | No |
| Controls 122 | 12.1 (2.9) | 17.1 (3.0) | 0 | NR | 0 | ||||||||
| Biederman et al,23 2006 | Clinically referred participants, US | Range, 6-17 | ADHD: 112 | 10.6 (3) | 21.6 (3.3) | 100 | Psychotic disorders | NA | 3 | ADHD: K-SADS-E; outcome: SCID | DSM-III-R, DSM-IV | HR, 4.4 (NA) | Baseline age and socioeconomic status |
| Controls: 105 | 11.5 (3.7) | 22.8 (4.0) | 100 | NA | 0 | ||||||||
| Miller et al,31 2008 | Clinically referred participants, US | 9.21 (1.19) | ADHD: 96 | 9.21 (1.19) | 18.31 (1.60) | 88.5 | Schizotypal personality disorder | NA | 2 | ADHD: IOWA Conners Rating Scale, DISC; outcome: SCID-II | DSM-IV | No | No |
| Controls: 85 | NA | 18.52 (1.65) | 87.1 | NA | 0 | ||||||||
| Gau et al,27 2010 | Participants mainly from National Taiwan University Hospital | 6.7 (2.7) | ADHD: 296 | 6.7 (2.7) | 12.9 (1.6) | 85.5 | Psychotic disorders | NA | 2 | K-SADS-E | DSM-IV | No | No |
| Controls: 185 | 6.8 (NA) | 12.91 (1.46) | 72.4 | NA | 0 | ||||||||
| Dalsgaard et al,26 2014 | Clinical sample from Aarhus University Hospital, Denmark | 8.0 (2.2) | ADHD: 208 | 8.0 (2.2) | NA | 88 | Schizophrenia and schizophreniform disorder | Mean (SD), 31 (6.6) | 8 | Case records and clinical reassessment | DSM-IV, ICD-8, ICD-10 | RR, 4.3 (1.9-8.57) | Sex, age, calendar time |
| Controls: NA | NA | NA | NA | NA | NA | ||||||||
| Maibing et al,30 2015 | General population, Denmark | NA | ADHD: total population (603 348) NA | 10 (0) | NA | NA | Psychotic disorders | <22 | 230 | National case records | ICD-10 | >5 y after ADHD onset, IRR, 2.43 (1.93-3.01) | Sex, age, calendar period, first-degree relatives with psychiatric disorder, birth weight, gestational age, 5-min APGAR score, parental age at birth |
| Controls: NA | 10 (0) | NA | NA | <22 | 2855 | ||||||||
| Shyu et al,35 2015 | General population, Taiwan | 9.4 (3.3) | ADHD: 73 049 | 9.4 (3.3) | 79.8 | NA | Psychotic disorders | 14.7 (4) | 1270 | National case records | ICD-9 | HR, 5.20 (4.30-6.30) | Sex, age, psychiatric comorbidities |
| Controls: 73 049 | 9.6 (3.8) | 72.5 | NA | 16.5 (3.3) | 128 | ||||||||
| Chen et al,25 2015 | General population, Taiwan | 9.68 (6.68) | ADHD: 5694 | 9.68 (6.68) | 76.6 | NA | Schizophrenia | 20.31 (8.93) | 39 | National case records | ICD-9 | OR, 13.73 (7.65-24.64) | Sex, age, level of urbanization |
| Controls: 27 540 | NA | NA | NA | 28.20 (10.97) | 17 | ||||||||
| Hennig et al,28 2017 | Birth cohort, UK | NA | ADHD: 107 | 7.58 (NA) | Total 49.4 | 18 (NA) | Psychotic disorders | 18 | 3 | ADHD: DAWBA; outcome: PLIKS | DSM-IV | OR, 3.06 (0.54-17.46) | Sex, IQ, ethnic minority status, family history of schizophrenia, urban upbringing, maternal educational level, diabetes during pregnancy, income support, other personal psychiatric diagnostics |
| Controls: 5421 | 7.58 (NA) | 18 (NA) | 18 | 54 | |||||||||
| Vitiello et al,36 2017 | Follow-up of an RCT of treatment strategies for ADHD, US | NA | ADHD: 579 | 8.5 (0.8) | 80 | 25.12 (1.07) | Psychotic disorders | NA | 6 | ADHD: DISC; Outcome: Psychosis screener and follow-up diagnostic impression | DSM-IV | OR, 1.00 (0.34-2.95) | Age matching |
| Controls: 289 | NA | 79 | 24.58 (1.15) | NA | 2 | ||||||||
| Niarchou et al,32 2019 | Clinical sample from different sites, Europe and US | NA | ADHD: 106 | Total: 11.2 (3.1) | Total: 49 | Total: 14.3 (3.6) | Psychotic disorders | NA | 10 | Depending on site location, CAPA C-DISC, K-SADS,SCID, DICA | DSM-IV-TR, DSM-5 | OR, 5.92 (1.52-28.56) | Sex, age, IQ, site of assessment |
| Controls: 144 | NA | 6 | |||||||||||
| Ottosen et al,33 2019 | General population. Denmark | NA | ADHD: 31 302 | NA | 71.8 | NA | Schizophrenia | NA | 688 | National case records | ICD-8, ICD-10 | Female HR, 4.90 (4.27-5.63); male HR, 4.06 (3.67-4.49) | Age, calendar time, gestational age, birthweight, 5-min APGAR score, maternal educational level, paternal income, maternal and paternal ages at time of child's birth, history of psychiatric disorders in first-degree relatives |
| Controls: 1 572 641 | NA | 50.9 | NA | NA | 9506 | ||||||||
| Björkenstam et al,22 2020 | General population, Sweden | NA | ADHD: 18 139 | NA | 39.8 | NA | Psychotic disorders (schizophrenia and other nonaffective psychotic disorders) | Range 15-29 | 492 | National case records | ICD-10 | OR, 5.14 (4.35-6.07) | Sex, birth year, place of birth, parental country of birth, parental education al level, parental history of psychiatric disorder, ASD, time of follow-up. |
| Controls: 72 437 | NA | 39.8 | NA | Range 15-29 | 290 | ||||||||
| Case-control study | |||||||||||||
| Rubino et al,34 2009 | Voluntarily hospitalized patients at a university hospital, Italy | 18 (maximum) | Cases: 197 with schizophrenia (84 with ADHD) | 35.8 (11.11) | NA | 69.2 | NA | NA | NA | Cases: SCID; ADHD: retrospective K-SADS | DSM-IV | OR, 6.81 (4.18-11.07) | Matching sex, age |
| Controls: 300 (29 with ADHD)b | 35.7 (11.1) | NA | 50.0 | ||||||||||
Abbreviations: ASD, autism spectrum disorders; CAPA, Child and Adolescent Psychiatric Assessment; C-DISC, Computerized Diagnostic Interview Schedule for Children; DAWBA, Development and Well-Being Assessment questionnaire; DICA, Diagnostic Interview for Children and Adolescents; DISC, Diagnostic Interview Schedule for Children; DIS-IV, Diagnostic Interview Schedule for the DSM-IV; HR, hazard ratio; ICD-8, International Classification of Diseases, Eighth Revision); ICD-9, International Classification of Diseases, Ninth Revision; ICD-10, International Statistical Classification of Diseases and Related Health Problems, Tenth Revision; IRR, incidence risk ratio (RR); K-SADS, Kiddie Schedule for Affective Disorders and Schizophrenia; K-SADS-E, K-SADS–Epidemiological; NA, not applicable; OR, odds ratio; PLIKS, Psychosis-Like Symptoms Interview; SCID, Structured Clinical Interview for DSM-IV Axis I Disorders; SCID-II, Structured Clinical Interview for DSM-IV Personality Disorders.
Presented as mean (SD) unless otherwise indicated.
Unpaid volunteers in several different settings.
Characteristics of Studies Included in the Systematic Review
The characteristics of the included studies are reported in Table 2. The research retrieved 1 case-control study34 and 14 cohort studies.22,23,24,25,26,27,28,29,30,31,32,33,35,36 Participants were from a local birth cohort (2 studies28,29), a clinical sample (8 studies23,24,26,27,31,32,34,36), or the general population (5 studies22,25,30,33,35).
Table 2. Newcastle-Ottawa Scale for Assessing the Quality of Nonrandomized Studiesa.
| Study type by source | Representativeness of the exposed cohort | Selection of the nonexposed cohort | Ascertainment of exposure | Demonstration that outcome of interest was not present at start of study | Comparability of cohorts | Assessment of outcome | Was follow-up long enough for outcomes to occur? | Adequacy of follow-up of cohorts | Total |
|---|---|---|---|---|---|---|---|---|---|
| Cohort | |||||||||
| Kim-Cohen et al,29 2003 | 1 | 1 | 1 | 0 | 2 | 1 | 1 | 1 | 8 |
| Biederman et al,24 2006 | 1 | 1 | 1 | 1 | 2 | 1 | 0 | 1 | 8 |
| Biederman et al,23 2006 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 1 | 9 |
| Miller et al,31 2008 | 1 | 0 | 1 | 0 | 2 | 1 | 0 | 1 | 6 |
| Gau et al,27 2010 | 1 | 1 | 1 | 1 | 2 | 1 | 0 | 1 | 8 |
| Dalsgaard et al,26 2014 | 1 | 0 | 1 | 0 | 2 | 1 | 1 | 1 | 7 |
| Maibing et al,30 2015 | 1 | 1 | 1 | 1 | 2 | 1 | 0 | 1 | 8 |
| Shyu et al,35 2015 | 1 | 1 | 1 | 1 | 2 | 1 | 0 | 1 | 8 |
| Chen et al,25 2015 | 1 | 1 | 1 | 0 | 2 | 1 | 0 | 1 | 7 |
| Hennig et al,28 2017 | 1 | 1 | 1 | 0 | 2 | 1 | 1 | 0 | 7 |
| Vitiello et al,36 2017 | 1 | 1 | 1 | 1 | 2 | 0 | 1 | 0 | 7 |
| Niarchou et al,32 2019 | 0 | 1 | 1 | 1 | 2 | 1 | 0 | 1 | 7 |
| Ottosen et al,33 2019 | 1 | 1 | 1 | 1 | 2 | 1 | 0 | 1 | 8 |
| Björkenstam et al,22 2020 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 1 | 9 |
| Case-control | Is the case definition adequate? | Representativeness of the cases | Selection of controls | Definition of controls | Comparability of cases and controls | Ascertainment of exposure | Same method of ascertainment for cases and controls | Nonresponse rate | Total |
| Rubino et al,34 2009 | 1 | 0 | 1 | 0 | 2 | 1 | 1 | 0 | 6 |
A study can be awarded a maximum of 1 point per cell for every criterion except comparability, which can receive 2 points. The presence 1 point means a low risk of bias for the variable considered.
Risk of Bias
The overall quality of each study is reported in Table 2. Of the studies included in the meta-analysis, 3 studies28,29,31 presented a high risk of bias in the domain outcome of interest absent at the start of the study because the study did not report relevant information. Six studies were rated as having a high risk of bias concerning the adequacy of follow-up duration because the follow-up ended before 18 years of age for all of the included population27 or part of it.24,30,31,32,33,35 In 1 study,32 the selected population with ADHD was not representative of general ADHD cases, because it involved participants with ADHD and a 22q11 deletion syndrome. For the selection of controls, we were concerned about 2 studies, one that compared a local clinical sample to a national sample of controls26 and one that provided no sufficient information about the selection process for controls.31 The case-control study34 was rated as having a high risk of bias regarding the representativeness of the cases because it involved patients with PD who were admitted on a voluntary basis and excluded those who presented with memory loss or verbal dysfunction. These criteria could have led to the selection of patients with less severe cases of PD. No information on diagnosis status for the control group was provided, leading to a risk of bias in the control definition domain.
Results of the Meta-analysis
Risk of PD After ADHD
For the primary analysis, 12 studies22,23,24,27,28,29,31,32,33,34,35,36 were identified in which a diagnosis of ADHD was present and PD was the outcome of interest; they had a total of 124 095 participants with ADHD and 1 725 760 controls. The prevalence of PD in cohort studies for the whole population ranged from 0.4% to 6.4% (median, 1.1%; interquartile range [IQR], 0.8%-1.8%); the prevalence among the control population ranged from 0 to 4.2% (median, 0.5%; IQR, 0%-1.2%); and the prevalence among the ADHD population ranged from 0.7% to 12.5% (median, 2.7%; IQR, 2.0%-3.2%). The results suggest that a childhood diagnosis of ADHD increases the risk of subsequent PD with a relative effect of 4.74 (95% CI, 4.11-5.46; I2 = 43% [95% CI, 0%-70%]) (Figure 2).
Figure 2. Forest Plot for Studies of the Association of Attention-Deficit Hyperactivity Disorder With Schizophrenia.
HR indicates hazard ratio; OR, odds ratio.
aIncludes female patients only.
bIncludes male patients only.
Subgroup Analysis and Meta-regressions
The results were consistent when only studies that provided an adjusted measure were included. Six studies were included to estimate the pooled adjusted effect size, with an overall effect of 4.72 (95% CI, 4.24-5.27) and I2 = 42% (95% CI, 0%-76%). When considering only unadjusted OR, the pooled effect size was 3.81 (95% CI, 1.39-10.49; I2 = 53% [95% CI, 0%-81%]), without subgroup difference (P = .59). The results of subgroup analyses of diagnostic outcome (PD vs schizophrenia), study design, country, and follow-up after or before 18 years of age are presented in Figure 3. No significant between-group differences were found for subgroup analyses according to psychotic disorder (odds ratio [OR], 5.04; 95% CI, 4.36-5.83) or schizophrenia (OR, 4.59; 95% CI, 3.83-5.50) outcomes, cohort (OR, 4.64; 95% CI, 4.04-5.34) or case-control (OR, 6.81; 95% CI, 4.21-11.03) study design, and adjusted (OR, 4.72; 95% CI, 4.11-5.46) or unadjusted (OR, 3.81; 95% CI, 1.39-10.49) estimates.
Figure 3. Forest Plot of Subgroup Meta-analysis for Association of Attention-Deficit Hyperactivity Disorder With Psychotic Disorder.
Graph shows results of random-effects model. OR indicates odds ratio.
Meta-regression analysis showed that sex (estimate, −0.0019; standard error, 0.0016; OR for each percent of male increase, 0.998 [95% CI, 0.994-1.001]; P = .27) and Newcastle Ottawa Scale score (estimate, −0.0076; standard error, 0.1032; OR for each point increase, 0.99 [95% CI, 0.79-1.25]; P = .94) were not significantly associated with the pooled relative effects (eFigure 2 and 3 in the Supplement). Because of insufficient data, we could not include pharmacological treatment and comorbid psychiatric disorders as covariates.
We performed a post hoc sensitivity analysis in which we removed the study by Niarchou et al32 because the population was highly specific (22q11 deletion syndrome) and the study by Rubino et al34 because it was the only case-control study. After removing these studies, the overall effect size was 4.63 (95% CI, 3.99-5.37; I2 = 45%).
Bias and Heterogeneity
Visual inspection of the funnel plot for the primary analysis did not indicate publication bias (eFigure 4 in the Supplement). The Egger test was not indicative of publication bias.
Overall interstudy heterogeneity was moderate (I2 = 43%; 95% CI, 0%-70%). Excluding 1 study36 reduced the heterogeneity to low (I2 = 18%), with a pooled effect size of 4.83 (95% CI, 4.40-5.30). All sensitivity analyses excluding outliers and influential studies can be found in eFigures 5 to 7 and eTable 4 in the Supplement.
Discussion
To our knowledge, this is the first meta-analysis of observational studies assessing the association between an ADHD diagnosis and a subsequent diagnosis of PD. Our main analysis found an increased risk of PD, with a pooled relative effect of 4.74 (95% CI, 4.11-5.46) for participants with childhood ADHD with moderate heterogeneity and no evidence of publication bias. Most of the included studies had a low risk of bias. The association remained high for the more restrictive diagnosis of schizophrenia. The use of sex as a covariate in the meta-regression did not modify the estimated association.
Many potential mechanisms could underlie the association between ADHD and subsequent psychosis. This association could be explained by a common developmental path with shared genetic susceptibility or social environmental factors.4,5 Prenatal factors, such as diabetes during pregnancy or neonatal complications, are also frequently reported as risk factors for both disorders.6,37 Some of the studies included in our meta-analysis considered these factors a priori for adjustment.22,28,33 The factors for adjustment were chosen based on available literature for 2 studies28,33; 1 study provided no justification22; and none of the studies used a direct acyclic graph to analyze possible confounding factors.
It is also possible that the association between ADHD and PD is mediated by other factors. Attention-deficit/hyperactivity disorder has been described as a risk factor for substance use disorder (SUD),38 possibly because of increased impulsivity39 and a deficit in the dopaminergic reward system,40 and SUD, especially the use of cannabis, has been described as a risk factor for PD.41,42 Attention-deficit/hyperactivity disorder could increase the risk of developing a PD through the development of a comorbid SUD.43 In Björkenstam et al,22 an association between childhood ADHD and PD was reported with an OR of 5.14 (95% CI, 4.35-6.07), but after adjusting for SUD, this association decreased to an OR of 3.65 (95% CI, 3.02-4.40). Reduction of the OR after adjustment could be owing to a purely confounding or mediation effect of SUD or both. However, the missing information on SUD diagnosis could be missing not at random and thus leading to a systematic bias.44 Furthermore, one of the largest included studies did not measure or adjust for SUD.35
Causality interpretation of the cannabis-schizophrenia association, whether it is entirely causal, entirely noncausal, or partly causal and partly confounded by social/genetic effects and/or reverse causation, is still undergoing debate.45 Future longitudinal studies assessing the risk of subsequent PD in children with ADHD should retrieve specific information on SUD (eg, start of the substance use, amount and type of substance use, and time of diagnosis) to bring insight on the causal path from ADHD to PD.
Another important issue regarding the association between ADHD and PD is the potential effect of psychostimulant prescriptions in children with ADHD. In our review, we found that few studies included this variable in the analysis. To date, research on the possible association between chronic psychostimulant treatment and the later risk of PD has yielded inconsistent results. Some studies found no increased risk of PD after psychostimulant treatment.26,46 A within-individual population-based cohort study found no increased incidence of psychotic events comparing 12 weeks immediately before and after initiation of methylphenidate use among patients with ADHD.46 However, a review of 49 randomized clinical trials by the US Food and Drug Administration47 found significantly more psychotic- or manic-type effects during the follow-up of children taking psychostimulants compared with those taking a placebo. In 92% of these cases,48 stopping stimulant therapy was associated with a remission of the psychotic symptoms without use of an antipsychotic. In our review, 1 study35 found that the use of methylphenidate hydrochloride among patients with ADHD significantly increased the risk of developing any PD (HR, 1.20; 95% CI, 1.04-1.40) but did not significantly increase the risk of developing schizophrenia (HR, 1.16; 95% CI, 0.94-1.42) compared with that of patients with ADHD who were never exposed to methylphenidate. One of the main remaining issues is that data on the long-term adverse effects of psychostimulants remain scarce.49
Finally, ADHD symptoms in childhood could be misdiagnosed as ADHD entities instead of as prodromes of PD. Patients with PD often show neuropsychological deficits and the deterioration of academic functioning before the onset of full-blown psychosis, such as attention disorders, heightened levels of impulsivity, and deficits in executive function.50,51 Misclassification bias could occur if SUD and psychostimulant use increase psychotic symptoms and substance-induced psychosis,52 which could be misdiagnosed as schizophrenia. However, substance-induced psychosis was associated with an increased risk of conversion to schizophrenia (HR, 77.3; 95% CI, 65.2-91.7), which could mitigate this misclassification bias.53
Strengths and Limitations
This study has several strengths. It was based on a protocol that was defined a priori and published on PROSPERO before the beginning of the literature search. It considered the age- and development-dependent occurrence of comorbidity in ADHD by selecting studies that evaluated the development of a PD after the onset of ADHD. Another strength is the large sample size, with participants across Europe, the US, Taiwan, and New Zealand. Regarding the main outcome, no publication bias and low-moderate heterogeneity were found.
The results of our systematic review and meta-analysis should be considered in light of the study’s limitations. Our search strategy could have omitted abstracts that did not state that PD was an included outcome. However, the funnel plot in our study did not favor publication bias.
Three studies22,33,35 using a large population database contributed most to the pooled relative effect. Limitation of population databases includes undiagnosed conditions, lack of detailed clinical information, reliance on diagnosis code for outcome and exposure, missing data, medications taken outside of recorded prescriptions, and prescriptions filled but not taken.
There was substantial clinical heterogeneity among studies with respect to the population studied, the classification criterion used for diagnosis, and the nature of the outcome. All the studies used international classifications to support the diagnosis, but they differed in the versions they used. Specifically, cohort studies with a long follow-up duration switched classifications over time, which may have altered the rate of diagnosis made by clinicians. Deflated rates of diagnosis have been reported between DSM versions, with a decrease in PD and schizotypical personality disorder diagnoses between the DSM-III and the DSM-III-R and a decrease in schizophreniform disorder diagnoses between the DSM-III-R and the DSM-IV. No changes are reported from the DSM-IV to the DSM-5.54 However, the reported changes in diagnostic rates are nondifferential (ie, occurring for both the exposed and control groups).
In addition, even when the studies fulfilled the inclusion and exclusion criteria, establishing with certainty the chronology of ADHD and psychotic events in studies that were not designed for this purpose remained difficult.28,31 The mean time between ADHD and PD diagnoses and the mean follow-up time were not systematically reported. As follow-up lengthens and events accrue, the OR increases and the relative risk decreases, which could be responsible for methodological heterogeneity and effect estimation bias.55 Moreover, patients with ADHD could have an earlier diagnosis of a PD. Because the length of follow-up and the mean age at PD diagnosis were not clearly reported, the onset of a PD among participants in the control group could occur after the end of follow-up. The consequence would be an overestimation of the association between ADHD and PD. Finally, residual and unmeasured confounding is of particular concern in observational studies, and therefore, important confounding factors may not always be considered or available, as discussed above.
Conclusions
The main finding of this study is that children and adolescents with ADHD appear to be at an increased risk of developing a PD. Given that PDs have a major functional effect,56 early detection and appropriate management are essential to improve the prognosis of children diagnosed with ADHD.57 To improve our knowledge, further cohort studies should be conducted. Ideally, these studies would ensure a sufficiently long follow-up to account for the mean age at which PDs develop. Such studies should consider the use of psychostimulants and the role of SUD in the causal path between ADHD and PD.
eTable 1. MOOSE (Meta-analyses of Observational Studies in Epidemiology) Checklist
eTable 2. Research Strategy for PubMed (MEDLINE)
eTable 3. Studies Excluded
eTable 4. Table of the Influence on Estimate and Heterogeneity of Omitted Studies Detected in the Influence Analysis
eFigure 1. Direct Acyclic Graph for the Association Between ADHD and Psychotic Disorder
eFigure 2. Bubble Plot for the Meta-regression With Sex as Percentage of Male
eFigure 3. Bubble Plot for the Meta-regression With Bias Score on the Newcastle Ottawa Scale (NOS)
eFigure 4. Funnel Plot of Relative Effect for the Association Between Attention-Deficit/Hyperactivity Disorder and Psychotic Disorder
eFigure 5. Baujat Plot of Adjusted and Crude Estimate for the Association of Attention-Deficit/Hyperactivity Disorder and Psychotic Disorder
eFigure 6. Forest Plot of the Leave-One-Out-Analyses
eFigure 7. Influence Analysis Plot of Crude and Adjusted Estimate for the Association Between ADHD and Psychotic Disorder
eReferences.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eTable 1. MOOSE (Meta-analyses of Observational Studies in Epidemiology) Checklist
eTable 2. Research Strategy for PubMed (MEDLINE)
eTable 3. Studies Excluded
eTable 4. Table of the Influence on Estimate and Heterogeneity of Omitted Studies Detected in the Influence Analysis
eFigure 1. Direct Acyclic Graph for the Association Between ADHD and Psychotic Disorder
eFigure 2. Bubble Plot for the Meta-regression With Sex as Percentage of Male
eFigure 3. Bubble Plot for the Meta-regression With Bias Score on the Newcastle Ottawa Scale (NOS)
eFigure 4. Funnel Plot of Relative Effect for the Association Between Attention-Deficit/Hyperactivity Disorder and Psychotic Disorder
eFigure 5. Baujat Plot of Adjusted and Crude Estimate for the Association of Attention-Deficit/Hyperactivity Disorder and Psychotic Disorder
eFigure 6. Forest Plot of the Leave-One-Out-Analyses
eFigure 7. Influence Analysis Plot of Crude and Adjusted Estimate for the Association Between ADHD and Psychotic Disorder
eReferences.