Abstract

Importance Antipsychotics are used increasingly in youth for nonpsychotic and off-label indications, but cardiometabolic adverse effects and (especially) type 2 diabetes mellitus (T2DM) risk have raised additional concern.

Objective To assess T2DM risk associated with antipsychotic treatment in youth.

Data Sources Systematic literature search of PubMed and PsycINFO without language restrictions from database inception until May 4, 2015. Data analyses were performed in July 2015, and additional analyses were added in November 2015.

Study Selection Longitudinal studies reporting on T2DM incidence in youth 2 to 24 years old exposed to antipsychotics for at least 3 months.

Data Extraction and Synthesis Two independent investigators extracted study-level data for a random-effects meta-analysis and meta-regression of T2DM risk.

Main Outcomes and Measures The coprimary outcomes were study-defined T2DM, expressed as cumulative T2DM risk or as T2DM incidence rate per patient-years. Secondary outcomes included the comparison of the coprimary outcomes in antipsychotic-treated youth with psychiatric controls not receiving antipsychotics or with healthy controls

Results Thirteen studies were included in the meta-analysis, including 185 105 youth exposed to antipsychotics and 310 438 patient-years. The mean (SD) age of patients was 14.1 (2.1) years, and 59.5% were male. The mean (SD) follow-up was 1.7 (2.3) years. Among them, 7 studies included psychiatric controls (1 342 121 patients and 2 071 135 patient-years), and 8 studies included healthy controls (298 803 patients and 463 084 patient-years). Antipsychotic-exposed youth had a cumulative T2DM risk of 5.72 (95% CI, 3.45-9.48; P < .001) per 1000 patients. The incidence rate was 3.09 (95% CI, 2.35-3.82; P < .001) cases per 1000 patient-years. Compared with healthy controls, cumulative T2DM risk (odds ratio [OR], 2.58; 95% CI, 1.56-4.24; P < .0001) and incidence rate ratio (IRR) (IRR, 3.02; 95% CI, 1.71-5.35; P < .0001) were significantly greater in antipsychotic-exposed youth. Similarly, compared with psychiatric controls, antipsychotic-exposed youth had significantly higher cumulative T2DM risk (OR, 2.09; 95% CI, 1.50-52.90; P < .0001) and IRR (IRR, 1.79; 95% CI, 1.31-2.44; P < .0001). In multivariable meta-regression analyses of 10 studies, greater cumulative T2DM risk was associated with longer follow-up (P < .001), olanzapine prescription (P < .001), and male sex (P = .002) (r2 = 1.00, P < .001). Greater T2DM incidence was associated with second-generation antipsychotic prescription (P ≤ .050) and less autism spectrum disorder diagnosis (P = .048) (r2 = 0.21, P = .044).

Conclusions and Relevance Although T2DM seems rare in antipsychotic-exposed youth, cumulative risk and exposure-adjusted incidences and IRRs were significantly higher than in healthy controls and psychiatric controls. Olanzapine treatment and antipsychotic exposure time were the main modifiable risk factors for T2DM development in antipsychotic-exposed youth. Antipsychotics should be used judiciously and for the shortest necessary duration, and their efficacy and safety should be monitored proactively.

Introduction

Antipsychotics are used increasingly in youth for many psychiatric disorders, particularly second-generation antipsychotics (SGAs).1-3 Although antipsychotic use in youth had long been restricted to schizophrenia spectrum disorders,4,5 significant data for SGA efficacy have accumulated for nonpsychotic disorders, leading to regulatory approval for bipolar mania and irritability associated with autistic disorder and Tourette syndrome.6-9 However, antipsychotic use in youth has broadened substantially to many off-label indications,10,11 including impulsivity, mood dysregulation, aggressive behaviors, depression, and anxiety.12-15

Antipsychotic efficacy should be balanced against adverse effects, which requires adequate information concerning their short-term and (especially) long-term risks. Yet, little is known about long-term risks.16,17 Compared with first-generation antipsychotics (FGAs), SGAs have significantly fewer neuromotor adverse effects but generally have more cardiometabolic consequences, including weight gain, dyslipidemia, and type 2 diabetes mellitus (T2DM).16,18-20 Because cardiometabolic effects, which can start even after short antipsychotic exposure and at low dosages,18,19,21 are associated with increased morbidity and premature mortality, they are a current focus of concern.18,22

Cardiometabolic adverse effects of antipsychotics tend to appear faster and to a greater extent in youth than in adults.21,23,24 Antipsychotic treatment results in relevant weight gain in a significant proportion of youth.23,25-27 Whether this overall heightened risk of short-term cardiometabolic adverse effects in youth compared with adults is due to developmental differences or because of less prior antipsychotic exposure and lifetime antipsychotic-related weight gain remains debated.16,17,21

In adults, there is a clear link between antipsychotic treatment and impaired glucose tolerance, insulin resistance, and risk for T2DM that seems to differ across agents,28-30with the most serious concerns revolving around SGAs.31-33 Despite the substantial use of SGAs in youth, far less is known about the T2DM risk in children and adolescents than in adults treated with antipsychotics.34-36

Given these uncertainties, a much smaller available database regarding the difficult-to-study long-term antipsychotic adverse effects in young people, and the importance of T2DM as a potential risk factor for cardiovascular disease,37 we conducted a systematic review and meta-analysis to assess the incidence of T2DM in antipsychotic-exposed youth compared with psychiatric controls and healthy controls. In addition, we sought to identify potential moderators of T2DM risk. Based on the literature in adults, we hypothesized that antipsychotic treatment would be associated with significantly greater T2DM risk than in both control groups.

Methods

This systematic review was conducted in accord with the Meta-analysis of Observational Studies in Epidemiology38 guidelines and the Preferred Reporting Items for Systematic Reviews and Meta-analyses39 standard.

Literature Search

Two independent authors (B.G. and A.R.) searched PubMed/MEDLINE and PsycINFO without language restrictions from database inception until May 4, 2015, using the following search terms: (child* OR adolescent* OR pediatric OR youth) and (antipsych* OR neuroleptic) and (hemoglobin A1C OR HbA1C OR glucose OR hyperglycemia OR diabetes OR prediabetes OR insulin OR hyperinsulinemia). The electronic search was supplemented by a manual review of reference lists from eligible publications and relevant reviews. Authors were contacted for additional information.

Inclusion Criteria

We included longitudinal studies reporting on the incidence of T2DM (defined by American Diabetes Association40 criteria), prescription of antidiabetic medications, or recorded medical diagnosis of T2DM in at least 20 youth 0 to 24 years old exposed to antipsychotics for at least 3 months. When available, T2DM incidence data were included from psychiatric controls unexposed to antipsychotics or from healthy controls. Studies of individuals with T2DM at baseline that reported on the proportion receiving antipsychotics were ineligible for inclusion.

Data Abstraction

Two of us (B.G. and A.R.) abstracted all data, and any inconsistencies were resolved by consensus or by a third author (C.U.C.). When articles reported on overlapping samples, details of the largest study sample for each respective outcome were included.

Data Analysis

Demographic information about the pooled study samples was calculated by weighting the study mean values according to sample size. The unadjusted, cumulative T2DM risk was computed as the number of patients with new onset of study-defined T2DM divided by the number of individuals free of T2DM diagnosis and T2DM treatment at baseline. Incidence rates per patient-year were computed by dividing the number of patients with study-defined T2DM by the number of patient-years of follow-up. Odds ratios (ORs) and 95% CIs were computed by comparing the unadjusted, cumulative T2DM risk in youth exposed to antipsychotics vs the unadjusted, cumulative T2DM risk in psychiatric control youth or healthy control youth and between the 2 control groups. Incidence rate ratios (IRRs) and 95% CIs were used to compare the T2DM incidence rates per patient-year in antipsychotic-exposed youth vs psychiatric control youth or healthy control youth and between the 2 control groups. Data were analyzed with a software program (Comprehensive Meta-Analysis, version 2; http://www.meta-analysis.com). All analyses used a random-effects model41 and were 2-sided, with α = .05. Heterogeneity was assessed with the I2 statistic,42 where I2 of at least 50% indicated significant heterogeneity. The number needed to harm (NNH) was calculated by dividing 1 by the risk difference.

We also conducted exploratory subgroup, sensitivity, and meta-regression analyses to identify potential moderators of the unadjusted, cumulative T2DM risk and incidence rate in antipsychotic-exposed youth. The subgroup analyses examined whether the T2DM risk was replicated when separately analyzing studies restricting their sample to youth 18 years and younger. The sensitivity analyses examined whether the T2DM risk was replicated when separately analyzing (1) studies with different T2DM definitions, (2) studies that potentially included type 1 diabetes mellitus (T1DM), (3) studies that potentially included patients with a prescription of oral antidiabetic medications for reasons other than T2DM, and (4) studies after excluding one study23 with 100% olanzapine-treated youth.

After excluding a significant effect of study quality using the Newcastle-Ottawa Scale43 (NOS) on the results, a backward elimination mixed random-effects meta-regression analysis was conducted with the initial variables of sex, age, sample size, percentage of patients with specific psychiatric diagnoses, and percentage of patients receiving SGAs (pooled). A second meta-regression analysis replaced pooled SGAs with percentage of patients receiving specific SGAs. Variables were entered into the initial backward elimination model if in univariable analyses they reached P < .20. Publication bias was assessed with the funnel plot, Egger regression test,44 and the “trim and fill” method.45 Finally, descriptive statistical methods were used for the exploratory summary of study-reported correlates of T2DM incidence based on patient-level data not available for study-level meta-regression analyses.

Results

The initial search produced 4647 results, and 4517 studies were excluded on the title or abstract level. Of the remaining 130 references, 117 were excluded after full-text review, yielding 13 meta-analyzable studies23,34,35,46-55 (1 study reported on 2 subsets based on antipsychotic class) (eFigure in the Supplement).

Study Characteristics

Eleven studies34,35,47,48,50-55 (n = 1 825 343) were retrospective database investigations, 2 studies46,49 (n = 565) were prospective naturalistic cohort investigations, and 1 study23 (n = 121) pooled data from 6 prospective olanzapine investigations. The mean (SD) NOS score was 7.4 (1.8), and the median NOS score was 8. Twelve of the 13 studies of antipsychotic-exposed youth provided information on the mean (SD) follow-up duration, which was 1.7 (2.3) years (310 438 patient-years). The study quality was high overall, with scores between 7 and 9 on the NOS in all but 2 studies, which had scores of 3 and 4, respectively (eTable 1 in the Supplement).

Eight studies34,46-48,50,52,55 compared data with a healthy control group, and the mean (SD) follow-up was 1.6 (2.9) years (463 084 patient-years). Seven studies34,35,47,48,51,53,54 had a psychiatric control group, with a mean (SD) follow-up of 1.6 (3.1) years (2 071 135 patient-years). Two studies23,49 did not have a control group (Table 1).

Patient and Treatment Characteristics

The mean (SD) age of the antipsychotic-exposed sample (n = 185 105) was 14.1 (2.1) years (age range, 2-24 years), and a mean (SD) of 59.5% (8.0%) were male. The mean (SD) age of the psychiatric controls (n = 1 342 121) was 13.8 (1.1) years (age range, 5-24 years), and a mean (SD) of 55.7% (9.2%) were male. The mean (SD) age of the healthy controls (n = 298 803) was 13.9 (3.2) years (age range, 4-19 years), and a mean (SD) of 52.6% (9.0%) were male.

In the antipsychotic-exposed sample, most had a disruptive behavior disorder (DBD) or attention-deficit/hyperactivity disorder (ADHD) (in 46.9%) or a mood spectrum disorder, including mood disorder not otherwise specified (in 22.8%,), depression (in 26.9%), bipolar disorder (BPD) (in 16.2%), and BPD or psychosis (in 5.1%). Less commonly observed were anxiety disorders (in 7.9%), psychosis (in 5.7%), pervasive developmental disorder or autism (in 5.3%), substance abuse disorder (in 4.6%), and tic disorders (in 0.0003%). In the psychiatric control group, the psychiatric diagnoses were mainly DBD or ADHD (in 51.8%) and mood spectrum disorder (in 34.1%). Other diagnoses included anxiety disorders (in 8.7%), pervasive developmental disorder or autism (in 5.4%), psychosis (in 0.3%), and substance use disorders (in 0.2%).

All but one study53 provided general information regarding antipsychotic treatment class, consisting predominantly of SGAs (in 94.9% [n = 169 621]), with few youth being treated with FGAs (in 3.7% [n = 6744]) or combinations of 2 or more antipsychotics (in 2.4% [n = 4309]). In 10 studies with specific antipsychotic use data, risperidone was the most commonly used (41.7%), followed by quetiapine fumarate (26.6%), aripiprazole (17.2%), and olanzapine (10.2%).

Outcome Definitions

The analyzed studies used the following definitions of T2DM: (1) the prescription of an antidiabetic medication or a clinical diagnosis of T2DM (6 studies35,47,50,53-55 [42.9%]), (2) T2DM diagnosis based on a fasting blood glucose level of at least 126 mg/dL (2 studies23,46 [14.3%]) (to convert glucose level to millimoles per liter, multiply by 0.0555), (3) a recorded T2DM diagnosis and antidiabetic medication prescription (2 studies52 [14.3%]), (4) an antidiabetic medication prescription only (1 study51 with 2 separate samples [7.2%]), (5) a clinical diagnosis of T2DM only (1 study48 [7.2%]), (6) a questionnaire-based T2DM diagnosis (1 study49 [7.2%]), or (7) a T2DM diagnosis, antidiabetic medication, glycated hemoglobin level of at least 7%, or random plasma glucose level of at least 200 mg/dL (1 study34 [7.2%]). Regarding T2DM definition, 7 studies23,34,46,47,49,50,53 potentially included cases of T1DM, while 5 studies34,47,50,53,54 would have potentially included patients treated with oral antidiabetic medications for reasons other than T2DM (Table 1). Procedures to reduce confounding, including matching and multivariable analysis, are summarized in eTable 2 in the Supplement.

T2DM in Antipsychotic-Exposed Youth, Psychiatric Controls, and Healthy Controls

The meta-analytically calculated T2DM risk was highest in the antipsychotic-exposed cohort, with an unadjusted, cumulative risk of 5.72 (95% CI, 3.45-9.48) per 1000 patients and an incidence rate of 3.09 (95% CI, 2.35-3.82) per 1000 patient-years (P < .001 for both). The risk was intermediate in psychiatric controls, with an unadjusted, cumulative risk of 2.61 (95% CI, 0.80-8.52) per 1000 patient-years and an incidence rate of 1.74 (95% CI, 1.10-2.38) per 1000 patient-years (P < .001 for both). The risk was lowest in healthy controls, with an unadjusted, cumulative risk of 2.15 (95% CI, 0.84-5.47) per 1000 patient-years and an incidence rate of 1.28 (95% CI, 0.78-1.79) per 1000 patient-years (P < .001 for both) (Table 2).

Subtracting the risk in psychiatric controls and healthy controls from that in antipsychotic-exposed youth, these numbers translate into an excess of 3.11 and 3.57 new T2DM cases per 1000 psychiatric controls and healthy controls, or an NNH of 322 and 280, respectively. With regard to the incidence, the numbers correspond to an excess of 1.35 and 2.41 T2DM cases per 1000 patient-years of antipsychotic exposure or follow-up compared with psychiatric controls and healthy controls, or an NNH of 740 or 398 per patient-year, respectively.

T2DM in Antipsychotic-Exposed Youth vs Psychiatric Controls and Healthy Controls

Compared with psychiatric controls, T2DM risk was significantly greater in antipsychotic-exposed youth compared with psychiatric controls, with an OR of 2.09 (95% CI, 1.50-2.90; P < .001) and an IRR of 1.79 (95% CI, 1.31-2.44; P < .001). In addition, T2DM risk was significantly greater in antipsychotic-exposed youth compared with healthy controls, with an OR of 2.58 (95% CI, 1.56-4.24; P < .001) and an IRR of 3.02 (95% CI, 1.71-5.35; P < .001) (Table 2). These findings were based on 8 studies (298 803 patients and 463 084 patient-years) (Figure 1 and Figure 2). Furthermore, psychiatric controls had higher T2DM risk than healthy controls, with an OR of 1.57 (95% CI, 1.29-1.90; P < .001) and an IRR of 2.02 (95% CI, 1.42-2.87; P < .001) (Table 2).

No publication bias was identified for any of the comparisons (P = .39 to P = .72 for cumulative, unadjusted risk and P = .26 to P = .91 for incidence) (Egger regression test). In the antipsychotic-exposed youth vs psychiatric controls, the trim and fill method identified one missing study in the comparison of cumulative, unadjusted risk (adjusted OR, 1.96; 95% CI, 1.44-2.66; P < .001) and 2 missing studies in the comparison of the incidence (adjusted IRR, 1.51; 95% CI, 1.13-2.01; P < .001).

Sensitivity Analyses: Moderation of the Results by Precision of T2DM Definition and Study Quality

The results of the unadjusted, cumulative T2DM risk and incidence, as well as those of the group comparisons, were replicated independent of T2DM definition, the possibility of T1DM inclusion, or the potential inclusion of patients treated with oral antidiabetic medications for reasons other than T2DM. These results are summarized in Figure 3 and in eTable 3 and eTable 4 in the Supplement.

Studies that potentially included T1DM cases yielded significantly higher “T2DM” incidence rates per patient-year than those that did not (P = .03). Conversely, the unadjusted, cumulative risk and all group comparisons were unaffected by this T2DM definition. Study quality, measured with the NOS, was not associated with the unadjusted, cumulative T2DM risk (P = .19) or exposure-adjusted T2DM incidence rate (P = .67) (eTable 1 in the Supplement).

Moderation by Age: Samples With Patients 18 Years or Younger Only

The results for the unadjusted, cumulative risk, for the incidence, and for the group differences were replicated when excluding studies with patients older than 18 years. The mean age of the study samples did not significantly moderate the unadjusted, cumulative T2DM risk (P = .31) or T2DM incidence (P = .43).

Mediation by Follow-up Time

Increased T2DM risk with antipsychotic treatment was mediated by longer follow-up duration (P < .001). Conversely, study follow-up duration did not mediate T2DM incidence (P = .47), which was already adjusted for patient-years.

Multivariable Model

In the multivariable meta-regression model pooling all SGAs together, only longer follow-up duration emerged as a significant mediating variable of cumulative T2DM risk in antipsychotic-exposed youth (r2 = 0.70, P < .001) (eTable 5 in the Supplement). When entering individual SGAs separately, greater T2DM risk was associated with longer follow-up duration (P < .001), olanzapine prescription (P < .001), and male sex (P = .002) (10 studies, r2 = 1.00, P < .001) (eTable 6 in the Supplement).

Pooling SGAs together, greater T2DM incidence was associated with SGA prescription (P ≤ .05), whereas autism spectrum disorder diagnosis (P = .048) was associated with lower T2DM incidence (13 studies, r2 = 0.21, P = .04) (eTable 7 in the Supplement). When entering individual SGAs separately to the model, no significant moderators emerged for T2DM incidence.

Correlates of T2DM Incidence Identified in Published Studies

Demographics

The findings regarding the influence of sex and age on T2DM risk during antipsychotic treatment have been inconsistent.35,48,50-52 These results are summarized in eTable 8 in the Supplement.

Diagnosis

One study35 showed a significantly elevated risk for patients with BPD and either conduct disorder or ADHD. Other diagnoses associated with T2DM were autism, DBD, and mood disorders,34 while one study51 did not find any significant effects of psychiatric diagnoses on the risk of or time until developing T2DM using multivariable analyses (eTable 8 in the Supplement).

Antipsychotic Medication, Dosage, and Exposure Time

One study47 found an elevated T2DM risk when comparing SGAs vs FGAs (hazard ratio, 3.39, 95% CI, 0.83-13.90), while another study35 found an elevated risk when restricting the cohort to SGA users. Conversely, 2 single cohorts (each receiving either FGAs or SGAs) had similar T2DM risk.52

In 2 studies,35,54 ziprasidone hydrochloride or aripiprazole was associated with higher T2DM risk compared with other SGAs (eTable 5 in the Supplement). Lower T2DM risk was reported for aripiprazole in another study.48 Furthermore, clozapine51 and antipsychotic polypharmacy48 were associated with significantly increased T2DM risk.

The T2DM risk did not vary significantly by baseline antipsychotic dosage but increased with cumulative dose of all antipsychotics, especially with risperidone and in children 6 to 17 years old.35 No significant dosage-associated risk was found in another study51 using defined daily dose instead of the actual mean daily dose. Whereas one study35 reported an increased T2DM risk within the first year of antipsychotic exposure (which was sustained for ≥1 year even after antipsychotic treatment discontinuation), another study54 did not find a significant effect of antipsychotic exposure time on T2DM risk.

Coprescribed Medication

Effects of coprescribed medications on T2DM risk were reported in only 2 studies.35,54 One study54 indicated an increased T2DM risk with adjunctive antidepressant use, whereas the results were inconsistent regarding adjunctive stimulant treatment in both studies.

Glucose Level Screening

One study35 demonstrated an increased T2DM risk related to glucose level screening. This result was found both for antipsychotic users who did or did not have a glucose level screening at baseline or during the follow-up period.

Discussion

This meta-analysis of T2DM risk in antipsychotic-exposed youth indicates that the unadjusted, cumulative T2DM risk and incidence of T2DM, respectively, were 2.6-fold and 3.0-fold higher compared with healthy controls and 2.1-fold and 1.8-fold higher compared with psychiatric controls. The attenuated difference compared with psychiatrically ill youth reflects that unhealthy lifestyle behaviors and other pharmacological treatments associated with psychiatric disorders likely also contribute to the risk of weight gain or obesity, metabolic abnormalities, and T2DM. For example, BPD and depression, as well as mood stabilizers and antidepressants, have been associated with metabolic syndrome and T2DM.33,56-59 Accordingly, T2DM risk was also 1.5-fold and 2.0-fold higher in psychiatrically ill youth not exposed to antipsychotics compared with healthy controls.

Although the T2DM risk was significantly higher in antipsychotic-exposed youth than in psychiatric controls and healthy controls, the number of actual excess cases was low, at least during the mean (SD) follow-up of 1.7 (2.3) years (range, 0.38-8.81 years). Nevertheless, the clinical importance of these findings is underscored by studies60,61 showing increased morbidity and mortality associated with an earlier T2DM onset. The relevance of our findings is further underscored by the fact that T2DM is only the most severe outcome of an interplay between antipsychotic exposure and genetic and lifestyle factors that lead to obesity and insulin resistance, which in and of themselves have serious health risks, especially when starting early in life.16,18-22,60,61 Our meta-analysis identified 3.1 and 3.6 excess T2DM cases per 1000 psychiatric controls and healthy controls, respectively, as well as an excess of 1.4 and 2.4 T2DM cases per 1000 patient-years of antipsychotic exposure or follow-up compared with psychiatric controls and healthy controls, respectively. This increased risk must be balanced carefully against the potential benefits of antipsychotics4-6,9,15,17,26 and underscores the need for prescribers to exhaust lower-risk treatment alternatives before initiating antipsychotic treatment and to routinely monitor youth for weight gain and metabolic abnormalities.

Caution should be especially high in patients with nonpsychotic disorders, in whom clinicians should aim for the shortest necessary treatment duration. This caveat is underscored by the fact that follow-up and thereby treatment duration increased T2DM risk.

In multivariable analyses, T2DM risk was significantly greater in male individuals than in female individuals, in youth treated with olanzapine, and in those with longer follow-up duration. The T2DM incidence was significantly greater in youth treated with SGAs but was lower in youth with autism spectrum disorder. The greater risk for T2DM in male individuals is consistent with data in adults.16,60 Our results confirm that T2DM risk with SGAs is not homogeneous and that olanzapine treatment is a major modifiable risk factor. Whether the lower risk in youth with autism spectrum disorder is driven by other diagnostic groups that are associated with a higher T2DM risk (eg, mood or psychosis spectrum disorders) or by comedications used for these patients31,33,34,56,59,62 requires further clarification. Study quality assessed with the NOS did not significantly affect the findings. Although not all aspects of study quality are covered by the criteria in the NOS, many of those relevant to the study of T2DM were captured by the additional subgroup and sensitivity analyses, which confirmed the overall results.

In patient-level analyses of T2DM risk factors conducted in the original studies, youth in mid to late adolescence seemed to have a greater T2DM risk, likely due to longer antipsychotic exposure or puberty-related insulin resistance.63 The results regarding sex-related risk remained inconclusive. Youth with mood disorder diagnoses seemed to have a higher risk of antipsychotic-related T2DM than youth with other diagnoses (eg, autism spectrum disorder), which is consistent with the findings of our meta-regression analysis. Other risk factors included antidepressant cotreatment, consistent with elevated T2DM risk compared with healthy controls in antidepressant-treated youth,34 as well as cumulative antipsychotic duration and dose and antipsychotic cotreatment, likely related to greater medication exposure and illness severity. Finally, in one study,54 aripiprazole was associated with a significantly higher T2DM risk than risperidone, with an additional, trend-level higher risk for ziprasidone. Because both aripiprazole and ziprasidone have the lowest risk of weight gain and metabolic abnormalities in youth in prospective investigations,16 these database study findings are likely owing to the increased likelihood that higher-risk patients or those with concerning cardiometabolic adverse effects due to other antipsychotics are being started on or switched to these 2 lower-risk antipsychotics. This hypothesis is supported by a large Danish registry study51 of 7139 antipsychotic-naive patients followed up for 6.6 years in which aripiprazole was associated with a reduced T2DM risk, while olanzapine (as in our meta-regression analysis and in most prospective studies16,18,19,21) and low-potency FGAs and clozapine were associated with an elevated T2DM risk.31 Because all but one study23 (which focused on olanzapine treatment only) reported on naturalistic settings with a range of antipsyhotics, a detailed comparison of different antipsychotics was not possible in this meta-analysis.

The results of this meta-analysis need to be interpreted within several limitations. First, although we were able to meta-analyze 13 studies with 185 105 antipsychotic-exposed youth, the main limitations are few studies with data on T2DM risk and the short and heterogeneous mean follow-up duration of 1.7 years (range, 0.38-8.81 years). Second, identified studies were heterogeneous regarding design, patient ascertainment, sample characteristics, assessments, outcomes, and matching procedures compared with the control groups, likely contributing to heterogeneity of the results. For example, retrospective database studies and prospective, observational, or open-label studies were combined. While this choice increased heterogeneity, both study types have their strengths and weaknesses, which are complementary, with higher generalizability of the samples in the database studies but greater granularity of the assessments and precision T2DM definitions in the prospective studies. However, although the findings were heterogeneous, subgroup and sensitivity analyses replicated the overall results, indicating that the effect size estimates varied within the significantly greater T2DM risk range and not between significant and nonsignificant results. Moreover, the results were unaffected by study quality, which generally was high. Third, there are several restrictions because of the naturalistic setting in all but one study23 (which focused on olanzapine treatment only), as well as the fact that data of all but 3 studies23,46,49 were collected retrospectively. Consequently, the results might have been affected by the following factors: (1) part of the follow-up period could have occurred after stopping antipsychotic treatments, resulting in a conservative T2DM risk estimate associated with antipsychotic use in youth; (2) metabolically higher-risk youth might be channeled to lower-risk medication (channeling bias); (3) generally, low glucose level testing rates in youth receiving antipsychotics64,65 may have resulted in undetected T2DM cases (surveillance bias),66 adding to the conservative bias of the results and requiring additional studies with adequate glucose level monitoring; and (4) cases reported as T2DM might have been incorrectly classified (eg, by the counting of T1DM or other illnesses for which antidiabetic medication was prescribed [misclassification bias]), leading to potentially inflated outcomes. However, these biases appear to have been small because they did not significantly affect the overall results when conducting subgroup and sensitivity analyses. Moreover, the different T2DM definitions that can lead to an inflated rate or to a deflated rate affected the comparison groups equally. Fourth, although schizophrenia spectrum disorders have been associated with T2DM development,62,67,68 too few antipsychotic-exposed youth had such disorders to enable meaningful subgroup or meta-regression analyses. Fifth, because long-term follow-up studies of antipsychotic-exposed youth for T2DM (which is a distal and low-rate adverse effect) are difficult to conduct,69 all but 2 studies were observational, database studies, restricting the available data. For example, much potentially relevant data on T2DM-related variables were missing in the databases (eg, family history of T2DM, body mass index, smoking status, diet and exercise behaviors, and illness severity) and were therefore not available for confounding adjustment. Because T2DM is a long-term adverse effect that is related to treatment, illness, behavioral, genetic, and environmental factors, more prospective, long-term observational studies of youth treated with antipsychotics are needed that assess relevant risk factors for T2DM beyond antipsychotic treatment.

Conclusions

The results of this meta-analysis indicate an association between antipsychotic treatment and increased risk for the development of T2DM in youth. These risks should be considered in the clinical risk-benefit evaluation when initiating or continuing antipsychotic treatment in this age group. Although the absolute incidence rates are small (at least during a mean follow-up period of 1.7 years), antipsychotics should only be used when lower-risk interventions have failed, and differential tolerability profiles should influence the antipsychotic choice, including avoidance of olanzapine.18,19,21,70 Antipsychotics should be used judiciously and for the shortest necessary duration. Furthermore, routine and proactive monitoring of cardiovascular risk factors should be enforced when prescribing antipsychotics to youth. Patients and their caregivers also need to be informed about possible adverse effects and supported in alleviating cardiometabolic risk via healthy nutrition and physical activities.18,27,71-74

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Correction: This article was corrected on March 2, 2016, to fix an error in author affiliations.

Submitted for Publication: October 5, 2015; final revision received November 11, 2015; accepted November 12, 2015.

Corresponding Author: Christoph U. Correll, MD, Psychiatry Research, Zucker Hillside Hospital, North Shore–Long Island Jewish Health System, 75-59 263rd St, Glen Oaks, NY 11004 (ccorrell@nshs.edu).

Published Online: January 20, 2016. doi:10.1001/jamapsychiatry.2015.2923.

Author Contributions: Drs Galling and Correll had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Galling, Correll.

Acquisition, analysis, or interpretation of data: Galling, Roldán, R. E. Nielsen, J. Nielsen, Gerhard, Carbon, Stubbs, Vancampfort, De Hert, Olfson, Kahl, Martin, Guo, Lane, Sung, Liao, Arango, Correll.

Drafting of the manuscript: Galling, Correll.

Critical revision of the manuscript for important intellectual content: Galling, Roldán, R. E. Nielsen, J. Nielsen, Gerhard, Carbon, Stubbs, Vancampfort, De Hert, Olfson, Kahl, Martin, Guo, Lane, Liao, Arango, Correll.

Statistical analysis: Galling, Correll.

Administrative, technical, or material support: Roldán, R. E. Nielsen, Guo, Lane, Sung, Liao, Arango.

Study supervision: Correll.

Conflict of Interest Disclosures: Dr R. E. Nielsen reported receiving research grants from Lundbeck for clinical trials; reported receiving speaker fees from Bristol-Myers Squibb, AstraZeneca, Janssen-Cilag, Lundbeck, Servier, Otsuka Pharmaceuticals, and Eli Lilly; and reported serving as a paid advisor to AstraZeneca, Eli Lilly, Lundbeck, Otsuka Pharmaceuticals, Takeda, and Medivir. Dr J. Nielsen reported receiving speaker honoraria from HemoCue, Lundbeck, and Bristol-Myers Squibb and reported receiving research grants from Lundbeck and Pfizer. Dr Gerhard reported receiving honoraria for lectures or consulting from Boehringer Ingelheim and Merck and reported receiving compensation as an expert witness on behalf of Roche. Dr Carbon reported having the same disclosures as Dr Correll because of a family relationship. Dr Vancampfort reported receiving grant and research support from Research Foundation–Flanders. Dr De Hert reported being a paid consultant for, receiving grant or research support and honoraria from, and serving on the speakers’ bureaus or advisory boards of Janssen-Cilag, Lundbeck, and Takeda. Dr Olfson reported being principal investigator on a grant to Columbia University from Sunovion Pharmaceuticals. Dr Kahl reported receiving speaker honoraria and a research grant from Servier and reported receiving speaker honoraria from Lundbeck, GSK, AstraZeneca, Eli Lilly, and Otsuka Pharmaceuticals. Dr Martin reported receiving an editorial stipend from American Academy of Child and Adolescent Psychiatry and reported receiving book royalties from Wolters Kluwer. Dr Guo reported receiving speaker honoraria from AstraZeneca, Eli Lilly, and Novartis and reported receiving research grants from Eli Lilly, Bristol-Myers Squibb, Janssen-Cilag, Novartis, and Roche-Genentech. Dr Arango reported being a paid consultant to or receiving honoraria or grants from Abbot, Amgen Inc, Bristol-Myers Squibb, Fundación Alicia Koplowitz, Instituto de Salud Carlos III, Janssen-Cilag, Lundbeck, Merck, Ministerio de Ciencia e Innovación, Ministerio de Sanidad, Ministerio de Economía y Competitividad, Mutua Madrileña, Otsuka Pharmaceuticals, Pfizer, Roche, Servier, Shire, Schering-Plough, and Takeda. Dr Correll reported being a paid consultant or advisor to or receiving honoraria from AbbVie, Actavis, Actelion, Alexza, Alkermes, Bristol-Myers Squibb, Cephalon, Eli Lilly, Genentech, Gerson Lehrman Group, Intra-Cellular Therapies, Janssen/Johnson & Johnson, Lundbeck, MedAvante, Medscape, Merck, Otsuka Pharmaceuticals, Pfizer, ProPhase Labs, Reviva, Roche, Sunovion Pharmaceuticals, Supernus Pharmaceuticals, Takeda, Teva, and Vanda and reported receiving grant support from American Academy of Child and Adolescent Psychiatry, Bendheim Foundation, Bristol-Myers Squibb, National Institute of Mental Health, Novo Nordisk A/S, Otsuka Pharmaceuticals, Takeda, and Thrasher Foundation. No other disclosures were reported.

Funding/Support: This work was supported in part by the Zucker Hillside Hospital, by grant P30MH090590 from the National Institute of Mental Health Advanced Center for Intervention and Services Research for the Study of Schizophrenia, and by grant U19 HS021112 from the Agency of Healthcare Research and Quality.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: Jeanette M. Jerrell, PhD (University of South Carolina School of Medicine), Daniela C Moga, MD, PhD, (University of Kentucky), David M. Rubin, MD, MSCE (University of Pennsylvania), and Elaine H. Morrato, DrPH, MPH, CPH (Colorado School of Public Health Health Systems, Management & Policy), provided unpublished data relevant to the analyses. Neither received compensation outside of her or his usual salary.