Long-Term Metabolic Effects in French-Canadian Children and Adolescents Treated with Second-Generation Antipsychotics in Monotherapy or Polytherapy: A 24-Month Descriptive Retrospective Study

Abstract

French

Objective:

To compare weight and glucose changes of long-term second-generation antipsychotic (SGA) monotherapy versus polytherapy (switching or combining SGAs) in children and adolescents.

Methods:

This is a 24-month retrospective study conducted between November 2005 and June 2013. From 147 antipsychotic-naive patients selected (mean age, 12.8 years; 95% confidence interval [CI], 9.8-15.9), 116 (78.9%) received SGA monotherapy and 31 (21.1%) SGA polytherapy for up to 24 months. Height, weight, and fasting glucose (FG) were measured at baseline and 1, 3, 6, 12, and 24 months. Linear mixed-model analysis was used to compare weight, body mass index z score (BMI z score), and glucose changes between the 2 SGA treatment groups, with the repeated factor being the time relative to baseline at 1, 3, 6, 12, and 24 months.

Results:

Overall, after 24 months of SGA treatment, mean weight increased significantly by 12.8 kg (95% CI, 10.4-15.0), BMI z score by 0.44 (95% CI, 0.21-0.68), and FG levels by 0.29 mmol/L (95% CI, 0.11-0.47). Incidence of overweight/obesity was 22.6%, BMI z score increase over 0.5 was 9.4%, impaired fasting glucose was 9.4%, and type 2 diabetes mellitus was 3.1%. Regarding metabolic effects, no significant difference was found between the subjects taking a single SGA and those exposed to an SGA polytherapy.

Conclusion:

Our study confirms the significant increase of metabolic complications during 24 months of SGA treatment without excluding or confirming a difference between the 2 groups of treatment (mono vs. poly).

Keywords

second-generation antipsychotics children adolescents weight gain obesity glucose abnormalities

During the past decade, increasing use of second-generation antipsychotics (SGAs) for diverse mental health disorders in children and adolescents has been widely reported in international studies.^1

–4 Canadian studies show an increase of 3- to 18-fold in the number of SGA prescriptions, which is disproportionally seen in adolescent boys but also in girls and younger children.^1,5 This increase in prevalence is due to an increased frequency and a longer duration of use.⁶

Multiple studies have demonstrated adverse metabolic effects of SGAs in children and adolescents as well as in adult populations,⁷ with increasing evidence suggesting a greater orexigenic effect of SGAs in youth than in adults.^8
–10

In a clinical setting, switching or combining SGAs is frequent. A Canadian study reported 31% of antipsychotic switches per year of therapy in youth,¹¹ similar to the results of a US adult study (29.5%).¹² In a recent systematic review, the average prevalence of antipsychotic polypharmacy (APP), defined as 2 or more antipsychotics, among antipsychotic-treated youths was 9.6% (5.9% and 12.0% among child and adolescent studies, respectively), with 77.9% of antipsychotics being SGAs.¹³

This observation is a source of considerable concern because of the increased adverse effects of APP reported both in youth¹⁴ and adult¹⁵ populations compared to antipsychotic monotherapy and the lack of established efficacy of APP in the pediatric and adult studies.^13,15,16 Moreover, higher rates of metabolic syndrome and insulin resistance have been reported in adult patients receiving APP compared with those receiving monotherapy.¹⁷

In pediatric populations, the metabolic side effects of SGAs in polytherapy (switching or combining SGAs) have received little attention, and no previous study has directly studied the comparison between the metabolic complications of SGA polytherapy versus monotherapy.

The aim of this study was to compare the metabolic effects of SGA monotherapy with those of SGA polytherapy in antipsychotic-naive children and adolescents in the ‘real-life’ clinical setting, while collecting descriptive data on metabolic changes occurring in children treated with SGAs for such a prolonged period. We hypothesised that the incidence of metabolic complications would be different in the SGA polytherapy group than in the SGA monotherapy group.

Methods

Study Design

The medical charts from patients in the inpatient and outpatient child, adolescent psychiatric ‘Second-Generation Antipsychotic Monitoring Program’ at Hôtel-Dieu de Lévis Hospital (Quebec, Canada) between November 2005 and June 2013 were retrospectively reviewed. This program was started in 2005 to monitor the occurrence of metabolic effects in patients using SGA treatment for the first time. The population in the geographic area served by the Department of Psychiatry of Hôtel Dieu de Lévis hospital is almost exclusively of French-Canadian origin. All study procedures were reviewed and approved by the local ethics and research committee (CER-1213-018). Patients were not required to give informed consent because this was a retrospective study using data recorded in the medical charts.

Subjects

The inclusion criteria for the study subjects were as follows: age under 18 years, no history of antipsychotic treatment, and received treatment with an SGA for at least 1 month during the study. The exclusion criteria included preexisting dyslipidemia, diabetes, or any treatment for metabolic conditions before starting the SGA.

Data Collection

For each patient, we collected the following data: age, sex, psychiatric diagnoses, SGA treatment (total dose/24 hours, duration of use), other medications (total dose/24 hours, duration of use), height, weight, and biochemical assessments (fasting blood glucose). The height, weight, and blood samples were collected at baseline and 1, 3, 6, 12, and 24 months by a clinical nurse who did the follow-up with the patient, the family, and the child psychiatrist.

Diagnoses were made by a child psychiatrist in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM IV-TR) criteria. Clinical data were collected from the chart notes. The main diagnosis was considered the one for which the SGA was prescribed. Other diagnoses were listed as comorbid disorders. In many cases, more than one main diagnosis was recorded because SGAs were used to treat symptoms common to many diagnostics, such as disruptive behavior.

The other medications associated with SGA were grouped in 4 categories: psychostimulants (amphetamine based, methylphenidate based), atomoxetine (to more accurately discriminate the potential metabolic impact of psychostimulants), antidepressants (bupropion, citalopram, fluvoxamine, sertraline, venlafaxine), and mood stabilisers (carbamazepine, lithium, valproic acid). The short- and long-action forms of the same medication were considered together. Any medication taken in a single dose or for less than 1 day was not included.

Treatment

The patients received an SGA (olanzapine, risperidone, quetiapine, or aripiprazole) in monotherapy (the same SGA was prescribed from the beginning to the end of the period of the follow-up) or an SGA in polytherapy (patients switched from one SGA to another or used a combination of 2 SGAs, with the second SGA added between 0.5 and 24 months). The SGA switch was defined as a period of 30 days or less between the first and the second SGAs and the SGA combination as a period of more than 30 days of concomitant SGA treatment.

Measures

The variables studied for metabolic effects were weight; body mass index (BMI), calculated as weight (kg)/height squared (m²); standardised BMI z score, calculated using the children’s BMI percentile-for-age calculator from the Children’s Nutrition Research Center, Baylor College of medicine website (http://www.bcm.edu/cnrc-apps/bodycomp/bmiz2.html); and fasting glucose (FG). The exact day of weight measurement was not always available in the charts; therefore, we calculated the BMI z scores as if the patients were always weighed on the first day of the month to minimise the measurement bias. The BMI z score represents the BMI adjusted for age and sex, thus taking into account the weight gain secondary to the growth process. It allows the comparison between the BMI of children and adolescents of the same age and sex.¹⁸

Overweight was defined as BMI z scores between the 85th and 95th percentiles and obesity as BMI z scores greater than or equal to the 95th percentile.¹⁹ The doses of each SGA were converted in chlorpromazine equivalents.²⁰

Impaired fasting glucose (IFG) or hyperglycemia is defined as FG values of 5.6 to 6.9 mmol/L, and diabetes mellitus (DM) is defined as FG ≥7.0 mmol/L.²¹

Statistical Analysis

The statistical analysis included all the patients with data available at baseline and at least at 1 follow-up assessment time. The data for the characteristics of the sample are presented as means (95% confidence interval [CI]) for the continuous variables and as frequencies and percentages for the categorical variables. All the characteristics of the patients were compared across the 2 SGA treatment groups using the chi-squared test and Fisher’s exact test for the categorical variables and t tests for the continuous variables. We assessed changes in continuous outcomes over time between the 2 SGA treatment groups using the linear mixed model with repeated measures. The repeated factor was the time relative to baseline at 1, 3, 6, 12, and 24 months. For each outcome, we adjusted for age and sex, other medications associated with SGA, and main diagnosis or comorbidities, thus yielding 3 different analyses.

Summary statistics are presented as the adjusted means of change over time (95% CI). Because these data reflect ‘real-life’ clinical situations, the time frame of the measures did not strictly respect the time interval. We averaged data for plus or minus the month interval (e.g., the third month corresponds to data from the second to the fourth months). Incidence was calculated as the proportion of new-onset metabolic complications at each time point divided by the number of patients with available data. All analyses were made using SAS 9.3 (SAS Institute, Cary, NC). The threshold for statistical significance was set at P < 0.05.

Results

A total of 147 patients treated for the first time with an SGA between November 2005 and June 2013 were included in the study. In total 116 (78.9%) received an SGA monotherapy and 31 (21.1%) received an SGA polytherapy. In the polytherapy group, 20 (64.5%) subjects switched SGAs and 11 (35.5%) received a combination of 2 SGAs. The mean duration of the SGA combination was 7.5 months (minimum, 1.5 months; maximum, 24 months). Data were missing at different time points during the follow-up for either weight or FG measures for various clinical reasons as missed appointments or failure to respect the calendar for the blood samples. The number of patients in each treatment group, per each specific molecule and who have data available at each time point, is presented in Figure 1.

Figure 1.

Number of subjects and available data flowchart.

The characteristics of the participants stratified by SGA therapy are presented in Table 1. Subjects were almost exclusively French Canadian. Most subjects were males of similar age in the monotherapy (12.7 years; 95% confidence interval [CI], 9.4-15.9) and polytherapy (13.0 years; 95% CI, 10.0-15.9) groups. Among diagnoses, the only difference was the proportion of psychotic disorders, which was higher in the polytherapy group than in the monotherapy group (45.2% vs. 26.7%; P = 0.047). The category ‘other’ regarding the main psychiatric diagnosis included personality disorder, mental retardation, pervasive developmental disorder, and obsessive-compulsive disorder. At baseline, there was no significant difference between the 2 groups in anthropometric, weight status, and FG levels.

Table 1.

Characteristics of Participants Stratified by SGA Therapy.

	Total (N = 147)	Monotherapy (n = 116)	Polytherapy (n = 31)	P Value^a
Demographics
Age, years, mean (95% CI)	12.8 (9.8 to 15.9)	12.7 (9.4 to 15.9)	13.0 (10.0 to 15.9)	0.7034
Sex, male, n (%)	107 (72.8)	85 (73.3)	22 (71.0)	0.7976
Primary psychiatric diagnosis, n (%)
Psychotic disorder	45 (30.6)	31 (26.7)	14 (45.2)	0.0479
Mood disorder	34 (23.1)	24 (20.7)	10 (32.3)	0.1748
Tic disorder	14 (9.5)	11 (9.5)	3 (9.7)	1.0000
Disruptive behavioral disorder with ADHD	90 (61.2)	70 (60.3)	20 (64.5)	0.6720
Other	17 (11.6)	15 (12.9)	2 (6.5)	0.5271
Comorbid diagnosis, n (%)
Intellectual disability and/or pervasive development disorder	34 (23.1)	29 (25.0)	5 (16.1)	0.2981
Anxiety disorder and/or obsessive-compulsive disorder	22 (15.0)	17 (14.7)	5 (16.1)	0.7833
Substance abuse or dependence	23 (15.6)	18 (15.5)	5 (16.1)	1.0000
Total other medications associated with SGAs, n (%)
Psychostimulant	75 (51.0)	62 (53.4)	13 (41.9)	0.2547
Antidepressant	46 (31.3)	35 (30.2)	11 (35.5)	0.5710
Mood stabiliser	35 (23.8)	21 (18.1)	14 (45.2)	0.0017
Atomoxetine	29 (19.7)	24 (20.7)	5 (16.1)	0.5708
Baseline anthropometric measures,^b mean (95% CI)
Weight (kg)	47.6 (32.4 to 61.2)	48.2 (31.9 to 62.7)	45.2 (32.4 to 56.1)	0.4724
BMI (kg/m²)	20.1 (16.8 to 22.5)	20.2 (16.5 to 22.4)	19.6 (17.2 to 22.7)	0.5664
BMI z score	0.2 (–0.6 to 0.9)	0.2 (–0.7 to 0.9)	0.2 (–0.4 to 0.9)	0.9973
Baseline weight status,^b n (%)				0.3942
Underweight (<5th percentile)	8 (6.1)	8 (7.7)	0 (0)
Normal	96 (73.3)	73 (70.2)	23 (85.2)
Overweight (≥85th to <95th percentile)	16 (12.2)	13 (12.5)	3 (11.1)
Obese (≥95th percentile)	11 (8.4)	10 (9.6)	1 (3.7)
Baseline fasting glucose,^b mmol/L, mean (95% CI)	4.9 (4.6 to 5.2)	4.8 (4.6 to 5.1)	5.0 (4.8 to 5.3)	0.1869
Baseline other medications associated with SGAs, n (%)
Psychostimulant	60 (40.8)	48 (41.4)	12 (39.7)	0.7882
Antidepressant	26 (17.7)	22 (19.0)	4 (12.9)	0.4320
Mood stabiliser	18 (12.2)	13 (11.2)	5 (16.1)	0.5370
Atomoxetine	16 (10.9)	14 (12.1)	2 (6.5)	0.5241
Baseline SGA dose chlorpromazine equivalent, mg/24 h, mean (95% CI)
Olanzapine	134.6 (50.0 to 200.0)	164.3 (100.0 to 200.0)	100.0 (50.0 to 100.0)	0.1989
Risperidone	36.8 (12.5 to 50.0)	35.9 (12.5 to 50.0)	39.3 (25.0 to 50.0)	0.6315
Quetiapine	130.0 (16.7 to 133.3)	143.2 (33.3 to 233.3)	33.3 (16.7 to 66.7)	0.3165
Aripiprazole	20.0 (13.3 to 26.7)	20.0 (13.3 to 26.7)	0 (0.0)
Total SGA dose chlorpromazine equivalent, mg/24 h, mean (95% CI)
Olanzapine	175.3 (100.0 to 300.0)	212.9 (150.0 to 300.0)	133.6 (87.5 to 147.2)	0.1036
Risperidone	52.3 (25.3 to 67.1)	47.5 (25.7 to 56.8)	65.0 (25.0 to 83.3)	0.0197
Quetiapine	171.3 (44.4 to 266.7)	182.9 (44.4 to 286.1)	141.8 (16.7 to 169.4)	0.4800
Aripiprazole	90.6 (42.2 to 116.7)	81.6 (11.7 to 121.1)	94.0 (16.7 to 169.4)	0.8065

ADHD, attention-deficit/hyperactivity disorder; BMI, body mass index; CI, confidence interval; SGA, second-generation antipsychotic.

^aDifference between groups (chi-squared and Fisher’s exact tests for categorical variables and t tests for continuous variables).

^bCalculated based on the available data (see Figure 1).

No differences between the 2 groups were registered at baseline in the mean SGA doses and the percentage of other medications associated with the SGAs. The mean total SGA dose (in chlorpromazine equivalent) was greater in the polytherapy group than in the monotherapy group (65.0 [95% CI, 25.0-83.3] vs. 47.5 [95% CI, 25.7-56.8]; P = 0.019) for risperidone only. For the other medications associated with the SGAs, more patients were treated with mood stabilisers in the polytherapy group than in the monotherapy group (45.2% vs. 18.1%; P = 0.001).

The type of SGA therapy did not show a significant difference on the metabolic changes between the two groups.

Changes in anthropometric measures and FG in the 2 groups are presented in Table 2. For clarity, all the results are from the analysis adjusting for the age, sex, and other medications associated with the SGAs. The 2 other analyses produced similar results.

Table 2.

Change in Anthropometric and FG Measurements Stratified by SGA Therapy.

	1 Month		3 Months		6 Months		12 Months		24 Months
	Mean (95% CI)	P Value	Mean (95% CI)	P Value	Mean (95% CI)	P Value	Mean (95% CI)	P Value	Mean (95% CI)	P Value
Weight (kg)
Total	1.75 (0.92 to 2.58)	<0.0001	3.83 (2.83 to 4.82)	<0.0001	6.26 (5.03 to 7.49)	<0.0001	9.06 (7.53 to 10.58)	<0.0001	12.76 (10.42 to 15.09)	<0.0001
SGA monotherapy	1.61 (0.71 to 2.52)	0.0006	3.85 (2.76 to 4.94)	<0.0001	6.32 (4.94 to 7.69)	<0.0001	8.68 (6.95 to 10.42)	<0.0001	12.06 (9.37 to 14.75)	<0.0001
SGA polytherapy	2.05 (0.70 to 3.41)	0.0033	3.21 (1.47 to 4.95)	0.0004	5.38 (3.01 to 7.76)	<0.0001	10.27 (7.28 to 13.26)	<0.0001	14.38 (9.71 to 19.04)	<0.0001
BMI (kg/m²)
Total	0.67 (0.33 to 1.01)	0.00001	1.26 (0.86 to 1.66)	<0.0001	1.89 (1.38 to 2.40)	<0.0001	2.45 (1.89 to 3.01)	<0.0001	2.65 (1.73 to 3.58)	<0.0001
SGA monotherapy	0.68 (0.31 to 1.05)	0.00004	1.31 (0.88 to 1.75)	<0.0001	2.01 (1.44 to 2.58)	<0.0001	2.33 (1.70 to 2.97)	<0.0001	2.56 (1.48 to 3.65)	<0.0001
SGA polytherapy	0.59 (0.06 to 1.13)	0.0302	0.95 (0.27 to 1.63)	0.0066	1.33 (0.35 to 2.30)	0.0081	2.82 (1.75 to 3.89)	<0.0001	2.89 (1.04 to 4.74)	0.0025
BMI z score
Total	0.22 (0.09 to 0.35)	0.0010	0.34 (0.20 to 0.49)	<0.0001	0.50 (0.34 to 0.65)	<0.0001	0.56 (0.39 to 0.72)	<0.0001	0.44 (0.21 to 0.68)	0.0002
SGA monotherapy	0.22 (0.08 to 0.36)	0.0022	0.36 (0.20 to 0.52)	<0.0001	0.56 (0.39 to 0.73)	<0.0001	0.54 (0.36 to 0.72)	<0.0001	0.48 (0.21 to 0.75)	0.0005
SGA polytherapy	0.21 (0.003 to 0.41)	0.0470	0.27 (0.02 to 0.52)	0.0320	0.29 (0.01 to 0.56)	0.0405	0.58 (0.29 to 0.87)	0.00001	0.33 (–0.11 to 0.78)	0.1372
FG (mmol/L)
Total	0.02 (–0.14 to 0.17)	0.841	–0.06 (–0.19 to 0.08)	0.4229	0.04 (–0.09 to 0.17)	0.8985	0.08 (–0.06 to 0.22)	0.2722	0.29 (0.11 to 0.47)	0.0021
SGA monotherapy	0.006 (–0.16 to 0.17)	0.9422	–0.09 (–0.23 to 0.06)	0.2501	–0.009 (–0.15 to 0.13)	0.8985	0.07 (–0.10 to 0.24)	0.4186	0.39 (0.19 to 0.60)	0.0002
SGA polytherapy	0.02 (–0.23 to 0.27)	0.8685	0.05 (–0.21 to 0.30)	0.7158	0.28 (0.04 to 0.52)	0.0222	0.09 (–0.16 to 0.34)	0.4897	0.08 (–0.22 to 0.38)	0.6035

BMI, body mass index; CI, confidence interval; FG, fasting glucose; SGA, second-generation antipsychotic.

Newly developed metabolic complications after up to 24 months of SGA treatment are presented in Table 3. Overall, at 24 months, 22.6% of subjects became overweight or obese, 42.9% had a BMI z score increase over 0.5, 9.4% developed IFG, and 1 subject (3.1%) developed DM, with similar incidence in the 2 groups, except for DM.

Table 3.

Incidence of Metabolic Complications Stratified by SGA Therapy.

	1 Month, n (%)	3 Months, n (%)	6 Months, n (%)	12 Months, n (%)	24 Months, n (%)
Overweight or obese (≥85th percentile)
Total	4/77 (5.2)	15/93 (16.1)	15/73 (20.5)	11/53 (20.8)	12/53 (22.6)
SGA monotherapy	2/64 (3.1)	11/73 (15.1)	10/58 (17.2)	6/40 (15.0)	9/40 (22.5)
SGA polytherapy	2/13 (15.4)	4/20 (20.0)	5/15 (33.3)	5/13 (38.5)	3/13 (23.1)
BMI z augmentation >0.5
Total	14/77 (18.2)	30/93 (32.3)	31/73 (42.5)	28/53 (52.8)	21/49 (42.9)
SGA monotherapy	10/64 (13.0)	24/73 (32.9)	24/58 (41.4)	20/40 (50.0)	15/37 (40.5)
SGA polytherapy	4/13 (30.8)	6/20 (30.0)	7/15 (46.7)	8/13 (61.5)	6/12 (50.0)
Hyperglycemia (FG ≥5.6 to <6.9 mmol/L)
Total	6/35 (17.1)	5/59 (8.5)	6/49 (12.2)	2/28 (7.1)	3/32 (9.4)
SGA monotherapy	5/26 (19.2)	4/47 (8.5)	4/39 (10.3)	1/19 (5.3)	2/22 (9.1)
SGA polytherapy	1/9 (11.1)	1/12 (8.3)	2/10 (20.0)	1/9 (11.1)	1/10 (10.0)
Type 2 diabetes mellitus (FG ≥7.0 mmol/L)
Total	0/35	0/59	0/49	0/28	1/32 (3.1)
SGA monotherapy	0/26	0/47	0/39	0/19	1/22 (4.5)
SGA polytherapy	0/9	0/12	0/10	0/9	0/10

BMI, body mass index; FG, fasting glucose; SGA, second-generation antipsychotic.

Discussion

This is a descriptive study conducted in a clinical naturalistic setting with antipsychotic-naive children and adolescents reporting on long-term metabolic changes secondary to SGA therapy. We compared long-term metabolic changes between SGA monotherapy and polytherapy (switching or combining SGAs). Although the results showed continuing metabolic changes over time, no significant conclusion could be drawn from the mono- versus polytherapy comparison on weight gain, BMI z scores, and FG changes.

The results of our study are concordant with the recent systematic review and exploratory meta-analysis of randomised controlled studies comparing APP versus antipsychotic monotherapy in adult patients with schizophrenia, which revealed no additional adverse effect burden with APP.²² Similarly, in adolescents and young adults treated with antipsychotics for the first episode psychosis, a retrospective naturalistic cross-sectional study examining the metabolic abnormalities showed that APP (prescribed to 25% of the cohort study) was not a significant predictor of obesity/weight gain.²³

However, 2 previous retrospective cohort studies^14,24 (both with the same cohort), evaluating factors associated with metabolic adverse events of antipsychotic use in antipsychotic-naive youth, reported a significantly higher risk for incident obesity/weight gain and DM in subjects treated with antipsychotic polytherapy. The study by McIntyre and Jerrell²² has several differences regarding antipsychotic treatment and population characteristics. Our study counted only SGA treatment, whereas in their study, patients received second- or first-generation antipsychotics. Illness characteristics are also different, as indicated by fewer subjects in our study (53.7% vs. 91%) suffering from psychotic disorder and affective disorder/mood disorder, as increased risk of obesity was associated with untreated psychosis (2.8- to 3.5-fold) or bipolar disorder (1.2- to 1.5-fold).^25,26 In addition, compared to our study, McIntyre and Jerrell’s²⁴ cohort had a higher percentage of subjects treated with antidepressants (79.5% vs. 31.3%) and mood stabilisers (45.8% vs. 23.8%). As antidepressants and mood stabilisers were also associated with an increased risk of obesity when associated with antipsychotics in the aforementioned study, although not in ours, one cannot rule out the possibility that this particular comedication is a confounding factor in the estimated obesity risk.

Moreover, 25.8% of the patients in our SGA polytherapy group were treated with aripiprazole (only 1.7% in monotherapy), while in McIntyre and Jerrell’s²⁴ cohort, SGAs with a lower metabolic impact, such as aripiprazole or ziprasidone, were only marginally used (less than 5% of the subjects).^25,27,28

Our results overall show that, after 24 months of SGA therapy, there is a significant increase in mean weight, BMI z score, and FG level; in addition, a notable number of subjects developed obesity or a clinically significant increase in their BMI z score. When compared with the results of a recent prospective study in youth treated for 12 months with risperidone or quetiapine,²⁹ our results show similar weight gain but less of an increase in FG, as well as fewer newly developed metabolic complications, suggesting a more favourable 24-month evolution of the metabolic complications than at 12 months. It is possible that the combination of antipsychotics that have low and high impacts on metabolic effects, other than weight gain, in our study has decreased the general effects compared to the study with only risperidone and quetiapine.

Regarding the glucose homeostasis, after 24 months of SGA treatment, the FG levels increased significantly, and we registered a notable incidence of hyperglycemia (9.4%). Consistently, a recent review analysing 506 SGA-treated subjects reported an incidence rate of 7.5% of IFG.³⁰ The incidence of DM in our study was 3.1%, which is consistent with a greater cumulative antipsychotic dose and treatment duration²⁹ and with the incidence rate of DM found in other studies.^31,32 In addition, Jerrell and McIntyre¹⁴ found a DM incidence rate of 3.1%. Even if it is relatively rare, the occurrence of DM remains of great clinical importance, as studies^33,34 showed increased morbidity and mortality associated with an earlier onset.³⁵

The results of this study should be interpreted in consideration of its limitations. Due to the naturalistic design and the retrospective data collection, the metabolic monitoring at 12 and 24 months was relatively low, which limited the data available for the analyses and influenced the statistical power of our results. Because of the small sample size, we cannot exclude or confirm a difference between the 2 SGA therapy groups.

In addition, in the polytherapy group, the SGA combination was present for a variable and sometimes short period, thus possibly limiting the metabolic impact of the second SGA. Furthermore, for half the patients who switched antipsychotics, the switch occurred during the first month of SGA treatment. In this case, the first SGA taken for a short period might have less influence on the weight gain and glucose abnormalities.

The reasons for switching or combining SGAs were not clearly described in the medical charts. Clinically, this could reflect a more severe pathology, supported as well by a significantly higher percentage of patients treated for psychotic disorder and receiving a mood stabiliser in the polytherapy group. Also the homogeneity of the population sample analysed in our study can limit the generalisability of the results. Finally, given the variability of SGA doses in the clinical sample, we were unable to adjust in the statistical analyses for the SGA chlorpromazine-equivalent dose. Despite the mean dose of risperidone being significantly higher in the SGA polytherapy than in the monotherapy group, more subjects received risperidone in the monotherapy group than in the polytherapy group (65.5% vs. 51.6%).

Strengths

One strength of our study is the genetic homogeneity of our sample. The clinical population was almost exclusively French Canadian, limiting the differences attributable to ethnic genetic diversity. Also, unlike many studies of metabolic effects of SGAs, our recruitment was restricted to an antipsychotic-naive population, leading to more accurate conclusions about the first exposure to SGAs. Finally, this is one of the few long-term studies of metabolic complications in child and adolescent populations that can be informative regarding metabolic complications of single, sequential, or combined SGA use in drug-naive populations.

Conclusion

Our study confirms a significant increase in weight, BMI z score, and FG associated with long-term SGA treatment in antipsychotic-naive children and adolescents without excluding or confirming a difference existing between the 2 groups. Long-term prospective studies with larger sample sizes and inclusion of a control group are needed to investigate the metabolic effects of SGAs in single, sequential, or combined use.

Clinical Significance

Our 24-month descriptive retrospective naturalistic study was not sufficiently powered to determine if there is a significant difference between the metabolic complications of SGA treatment in monotherapy or polytherapy in youth. However, despite its naturalistic limitations, it reflects the clinical reality, with ‘real’ unbiased selected patients having complex diagnoses and treatments, and provides clinical information on long-term evolution of the weight gain and FG changes secondary to SGA monotherapy or polytherapy. This is important given that in clinical situations, when an SGA is recommended, the average number of SGAs trials for a given patient is between 2 and 3.³⁶

Also, in our study, the most frequent diagnosis for the SGA prescription was the disruptive behavioral disorder with attention-deficit hyperactivity disorder, which surpassed those of psychotic and mood disorders in both groups. This contrasts with the American Academy of Child and Adolescent Psychiatry guidelines, which do not recommend SGA use in children and adolescents for the disruptive behavior disorders.³⁷ Clinicians should consider psychosocial or other alternative pharmacological interventions to the SGAs, particularly when treating disruptive behaviors.³⁷

Moreover, the increase in weight, BMI z score, and FG seen regardless of the type of SGA treatment used (mono- or polytherapy) remains of great concern given that childhood obesity can adversely affect nearly every organ system. Serious consequences include hypertension, dyslipidemia, diabetes, fatty liver disease,^38,39 an increased risk of cardiovascular disease from early childhood onwards,⁴⁰ and psychosocial problems such as low self-esteem, development of eating disorders and depression,^41
–43 and increased morbidity and mortality associated with an earlier onset of DM.³⁵

These findings emphasise that clinical benefits must outweigh the risks when prescribing SGAs and that the length of the SGA treatment should be carefully planned. It also highlights the need for practitioners to follow monitoring guidelines from the beginning to the end of the SGA prescription to treat the metabolic complications as early as they are identified. Clinically, the combination of 2 or more antipsychotics should be avoided as its efficacy and safety are not clearly established.

Footnotes

Acknowledgements

We thank Radhia Ben Amor and Marie-Eve Brodeur, research assistants, for assistance with the data collection and organisation of the database.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was founded by the Daoussis Bourse of the Department of Psychiatry, University of Montreal.

References

Alessi-Severini

Biscontri

Collins

. Ten years of antipsychotic prescribing to children: a Canadian population-based study. Can J Psychiatry. 2012;57(1):52–58.

Karanges

Stephenson

McGregor

. Longitudinal trends in the dispensing of psychotropic medications in Australia from 2009-2012: focus on children, adolescents and prescriber specialty. Aust N Z J Psychiatry. 2014;48(10):917–931.

Olfson

King

Schoenbaum

. Treatment of young people with antipsychotic medications in the United States. JAMA Psychiatry. 2015;72(9):867–874.

Zito

Safer

de Jong-van den Berg

. A three-country comparison of psychotropic medication prevalence in youth. Child Adolesc Psychiatry Ment Health. 2008;2(1):26.

Ronsley

Scott

Warburton

. A population-based study of antipsychotic prescription trends in children and adolescents in British Columbia, from 1996 to 2011. Can J Psychiatry. 2013;58(6):361–369.

Patten

Waheed

Bresee

. A review of pharmacoepidemiologic studies of antipsychotic use in children and adolescents. Can J Psychiatry. 2012;57(12):717–721.

Roy

Bedard

Desmarais

. Age-dependent metabolic effects of second-generation antipsychotics in second-generation antipsychotic-naive French Canadian patients. J Child Adolesc Psychopharmacol. 2010;20(6):479–487.

De Hert

Detraux

van Winkel

. Metabolic and cardiovascular adverse effects associated with antipsychotic drugs. Nat Rev Endocrinol. 2012;8(2):114–126.

Martinez-Ortega

Funes-Godoy

Diaz-Atienza

. Weight gain and increase of body mass index among children and adolescents treated with antipsychotics: a critical review. Eur Child Adolesc Psychiatry. 2013;22(8):457–479.

10.

Sengupta

Klink

Stip

. Weight gain and lipid metabolic abnormalities induced by olanzapine in first-episode, drug-naive patients with psychotic disorders. Schizophr Res. 2005;80(1):131–133.

11.

Linton

Barr

Honer

. Antipsychotic and psychostimulant drug combination therapy in attention deficit/hyperactivity and disruptive behavior disorders: a systematic review of efficacy and tolerability. Curr Psychiatry Rep. 2013;15(5):355.

12.

Nyhuis

Faries

Ascher-Svanum

. Predictors of switching antipsychotic medications in the treatment of schizophrenia. BMC Psychiatry. 2010;10:75.

13.

Toteja

Gallego

Saito

. Prevalence and correlates of antipsychotic polypharmacy in children and adolescents receiving antipsychotic treatment. Int J Neuropsychopharmacol. 2014;17(7):1095–1105.

14.

Jerrell

McIntyre

. Adverse events in children and adolescents treated with antipsychotic medications. Hum Psychopharmacol. 2008;23(4):283–290.

15.

Gallego

Nielsen

De Hert

. Safety and tolerability of antipsychotic polypharmacy. Expert Opin Drug Saf. 2012;11(4):527–542.

16.

Jureidini

Tonkin

Jureidini

. Combination pharmacotherapy for psychiatric disorders in children and adolescents: prevalence, efficacy, risks and research needs. Paediatr Drugs. 2013;15(5):377–391.

17.

Correll

Frederickson

Kane

. Does antipsychotic polypharmacy increase the risk for metabolic syndrome? Schizophr Res. 2007;89(1-3):91–100.

18.

Correll

Carlson

. Endocrine and metabolic adverse effects of psychotropic medications in children and adolescents. J Am Acad Child Adolesc Psychiatry. 2006;45(7):771–791.

19.

Ogden

Kuczmarski

Flegal

. Centers for Disease Control and Prevention 2000 growth charts for the United States: improvements to the 1977 National Center for Health Statistics version. Pediatrics. 2002;109(1):45–60.

20.

Woods

. Chlorpromazine equivalent doses for the newer atypical antipsychotics. J Clin Psychiatry. 2003;64(6):663–667.

21.

American Association of Diabetes (ADA). Diagnosis and classification of diabetes mellitus. Diabetes Care. 2007;30(suppl 1): S42–S47.

22.

Galling

Roldan

Rietschel

. Safety and tolerability of antipsychotic co-treatment in patients with schizophrenia: results from a systematic review and meta-analysis of randomized controlled trials. Expert Opin Drug Saf. 2016;15(5):591–612.

23.

Curtis

Henry

Watkins

. Metabolic abnormalities in an early psychosis service: a retrospective, naturalistic cross-sectional study. Early Interv Psychiatry. 2011;5(2):108–114.

24.

McIntyre

Jerrell

. Metabolic and cardiovascular adverse events associated with antipsychotic treatment in children and adolescents. Arch Pediatr Adolesc Med. 2008;162(10):929–935.

25.

De Hert

Correll

Bobes

. Physical illness in patients with severe mental disorders: I. Prevalence, impact of medications and disparities in health care. World Psychiatry. 2011;10(1):52–77.

26.

Maina

Salvi

Vitalucci

. Prevalence and correlates of overweight in drug-naive patients with bipolar disorder. J Affect Disord. 2008;110(1-2):149–155.

27.

Pringsheim

Lam

Ching

. Metabolic and neurological complications of second-generation antipsychotic use in children: a systematic review and meta-analysis of randomized controlled trials. Drug Saf. 2011;34(8):651–668.

28.

Raffin

Gianitelli

Consoli

. Management of adverse effects of second-generation antipsychotics in youth. Curr Treat Options Psychiatry. 2014;1(1):84–105.

29.

Ronsley

Nguyen

Davidson

. Increased risk of obesity and metabolic dysregulation following 12 months of second-generation antipsychotic treatment in children: a prospective cohort study. Can J Psychiatry. 2015;60(10):441–450.

30.

Galling

Correll

. Do antipsychotics increase diabetes risk in children and adolescents? Expert Opin Drug Saf. 2015;14(2):219–241.

31.

Andrade

Roblin

. Antipsychotic medication use among children and risk of diabetes mellitus. Pediatrics. 2011;128(6):1135–1141.

32.

Nielsen

Laursen

Vernal

. Risk of diabetes in children and adolescents exposed to antipsychotics: a nationwide 12-year case-control study. J Am Acad Child Adolesc Psychiatry. 2014;53(9):971–979.e6.

33.

D’Adamo

Caprio

. Type 2 diabetes in youth: epidemiology and pathophysiology. Diabetes Care. 2011;34(suppl 2): S161–S165.

34.

Pinhas-Hamiel

Zeitler

. Acute and chronic complications of type 2 diabetes mellitus in children and adolescents. Lancet. 2007;369(9575):1823–1831.

35.

Galling

Roldan

Nielsen

. Type 2 diabetes mellitus in youth exposed to antipsychotics: a systematic review and meta-analysis. JAMA Psychiatry. 2016;73(3):247–259.

36.

Pringsheim

Panagiotopoulos

Davidson

. The Canadian Alliance for Monitoring Effectiveness and Safety of Antipsychotics in Children (CAMESA) guideline group: evidence-based recommendations for monitoring safety of second-generation antipsychotics in children and youth. Paediatr Child Health. 2011;16(9):581–589.

37.

AACAP. Practice parameter for the use of atypical antipsychotic medications in children and adolescents. 2011. Available from www.aacap.org Recommendation 2:10. [cited 2017 April 7].

38.

Daniels

. Complications of obesity in children and adolescents. Int J Obes (Lond). 2009;33(suppl 1):S60–S65.

39.

Han

Lawlor

Kimm

. Childhood obesity. Lancet. 2010;375(9727):1737–1748.

40.

Owen

Whincup

Orfei

. Is body mass index before middle age related to coronary heart disease risk in later life? Evidence from observational studies. Int J Obes (2005). 2009;33(8):866–877.

41.

Erickson

Robinson

Haydel

. Are overweight children unhappy? Body mass index, depressive symptoms, and overweight concerns in elementary school children. Arch Pediatr Adolesc Med. 2000;154(9):931–935.

42.

Field

Camargo

Jr Taylor

. Overweight, weight concerns, and bulimic behaviors among girls and boys. J Am Acad Child Adolesc Psychiatry. 1999;38(6):754–760.

43.

Strauss

. Childhood obesity and self-esteem. Pediatrics. 2000;105(1):e15.