Abstract
Introduction
Limited information is available regarding treatment practices in applied settings for children and adults with tic disorders (TDs). We describe, for the first time, the treatment of TDs in U.S. children and adults in the outpatient setting.
Methods
Data from the 2003–2010 National Ambulatory Medical Care Survey and the National Hospital Ambulatory Care Survey were used. Descriptive statistics for modality of treatment and class of pharmacological medications were reported by patient and visit characteristics. Separate multivariable logistic regression models were used to examine associations between patient and visit characteristics and classes of medications prescribed.
Results
One third (n = 99) of the sample did not receive any psychiatric or psychological treatment. Nearly two‐thirds received a psychotropic medication. The most common class of medication was alpha‐2 agonists (25%), followed by stimulants (23%), serotonin‐reuptake inhibitors (SRIs) (19%), atypical antipsychotics (18%), anxiolytics (14%), anticonvulsants (11%), and typical antipsychotics (8%). Comorbid disorders and chronicity of problems were significantly associated with the receipt of certain classes of medications. Relatively few patients (18%) received psychotherapy.
Conclusions
If the decision is made to treat tic disorders, the choice of medication is dependent on the primary complaints, severity, chronicity, and the presence of comorbid psychiatric disorders. In general, comorbid externalizing, anxiety and mood disorders appear to influence treatment decisions in addition to TDs.
Keywords: tic disorders, Tourette syndrome, Pharmacotherapy, Psychotherapy, ADHD
Introduction
Tic disorders (TDs) are childhood onset neuropsychiatric disorders1, 2, 3 that are associated with functional impairment,4, 5 reduced quality of life,5 and high comorbidity.1, 6, 7, 8, 9 TDs include Tourette syndrome, transient tics, chronic vocal and motor tics, and TDs not otherwise specified. In children, transient TDs are most common (2.99%), followed by chronic TDs (1.61%), and Tourette syndrome (0.77%).10 Many adolescents with TDs improve in adulthood, with 63% exhibiting sustained tics of varying severity.10, 11, 12 In adults, the prevalence of Tourette syndrome is 0.05%, whereas estimates of all TDs range from 0.08% to 0.42%.10
TD symptoms range in severity and duration, resulting in a range of functional impairment.6, 13, 14 Current research suggests that treatment for TDs should only be administered in cases in which these symptoms cause significant impairment.7, 8, 9, 15, 16, 17, 18 At the time data were collected, treatments included alpha‐2 agonists (e.g., guanfacine, clonidine),7, 8, 17, 19 atypical antipsychotics (e.g., risperidone, ziprasidone, olanzapine, quetiapine),7, 8, 20, 21 typical antipsychotics (e.g., pimozide, haloperidol),20, 21 anticonvulsants (e.g., topiramate, baclofen),21 and behavioral therapy (e.g., habit reversal therapy).7, 8 Several factors must be considered when making treatment decisions: the waxing and waning nature of TDs, severity of impairment, social distress, and comorbid psychiatric conditions.7, 8, 9
Complicating treatment, TDs frequently co‐occur with attention‐deficit/hyperactivity disorder (ADHD),22 obsessive‐compulsive disorder (OCD),22, 23 disruptive behavior disorders (i.e., oppositional defiant disorder [ODD], conduct disorder [CD]),24 and depressive and anxiety disorders.7, 8, 16, 22, 23 Generally, the symptoms perceived as the most problematic play a major role in the type of treatment provided.7, 8 For example, for patients with primary OCD and secondary TD, SRIs are recommended,17, 21 whereas stimulants or alpha‐2 agonists are indicated for patients with primary ADHD and secondary TD.21, 25 In addition, current treatment guidelines for young people call for behavioral interventions for patients with a TD and comorbid psychiatric disorders.18
Only one large U.S. study has described treatment of TDs in children and adolescents. Olfson et al.26 compared children and adolescents enrolled in Medicaid to children covered by private insurance, finding a higher prevalence of comorbid ODD (3.3% vs. 0.6%) and ADHD (7.4% vs. 3.5%) in the Medicaid sample. The authors reported very low rates of psychotherapy claims (<5%), and any psychotropic medication use (11.2% and 7.8% in Medicaid and private insurance, respectively). The most common classes of medications were stimulants, antidepressants, alpha‐2 agonists, antipsychotics, and mood stabilizers.26
Three other large studies have reported the examination of European treatment practices.27, 28, 29 In a retrospective chart review of 400 patients visiting a London specialty clinic, Farag et al.27 examined prescribing trends among patients with Tourette syndrome. A total of 65% of patients were prescribed a medication, and the presence of comorbid ADHD or OCD predicted the prescription of psychotropic medication better than tic severity.27 The most commonly prescribed medications were aripiprazole, risperidone, clonidine, sulpiride, and haloperidol.27 Rickards et al.29 found that physicians tended to prescribe medications based on patient impairment, scientific literature, and their professional experience. The top three medications prescribed were aripiprazole, risperidone, and sulpiride.29 In a review of German health‐insurance claims, Bachmann et al.28 examined trends in prescribing psychotropic medications for TDs among 7058 children (0–19 years). Only 21.2% of children received a psychotropic medication, most commonly methylphenidate, atomoxetine, tiapride, and risperidone.28
The present study presents a review of a large, U.S. dataset of outpatient physicians' practices to examine the patterns of practice regarding children and adults with TDs. This study provides details on the characteristics and proportions of patients receiving pharmacotherapy, psychotherapy, combined pharmacotherapy and psychotherapy, and no treatment. In addition, we characterized the proportions of patients receiving each class of psychotropic mediation and provide adjusted odds ratios to evaluate the effects of patient characteristics on receipt of each class of psychotropic medications.
Methods
Our study uses data from the 2003–2010 National Ambulatory Medical Care Survey (NAMCS) and the National Hospital Ambulatory Medical Care Survey (NHAMCS). The surveys have been conducted annually since 1991 by the National Center for Health Statistics (NHCS) and they are nationally representative samples of nonfederal office‐based physicians and ambulatory care departments in general hospitals and short‐stay hospitals.30, 31 Total sample sizes for all years were 230,660 for NAMCS and 268,006 for NHAMCS. The mean, unweighted survey response rate for all 2003–2010 survey years was 62.3% (range: 58.3–66.9%) for the NAMCS and 72.5% (68.3–74.1%) for the NHAMCS. This study was exempt from the University of South Florida's IRB review because it used deidentified, publicly available data.
The diagnoses of interest were TDs, which were determined by examining the three reported diagnosis fields (i.e., one primary and two secondary codes) for ICD‐9‐CM codes: 307.2, 307.20, 307.21, 307.22, or 307.23. Records with primary schizophrenia and related disorders were omitted to reduce confounding with first‐line treatment for TDs. We included cases with comorbid mood disorders, externalizing disorders, ADHD, OCD, ODD, and anxiety disorders. Only records in which the patient was older than 4 years were included to allow for reasonable clinical impression. Each record represents a unique individual.
Because of the high rates of missing data for race and ethnicity in some survey years, staff at the NCHS included a variable that combined these fields and in some cases imputed them (full details can be found in the survey documentation).32 Visits were characterized by new or existing patient, number of visits in the previous 12 months, major reason for visit, and whether the provider was the primary care provider.
Providers and/or survey staff reviewed medical records to determine interventions provided, such as psychotherapy and pharmacotherapy provided during the same visit. Because of limitations of the data, the nature and duration of psychotherapy could not be determined. Pharmacotherapy was determined by examining the eight medication fields, which included the drug name and therapeutic class. A listing of medications in each class is found in Table 1. This study did not assess surgical interventions.
Table 1.
List of prescription medications by cass as determined by Multum Reference List (2011)
| Alpha‐2 Agonists | Anticonvulsants | Anxiolytics | Stimulants | SRIs | Atypical Antipsychotics | Typical Antipsychotics |
|---|---|---|---|---|---|---|
| Clonidine | Carbamazepine | Alprazolam | Atomoxetine | Amoxapine | Aripiprazole | Fluphenazine |
| Guanfacine | Divalproex sodium | Clonazepam | Dexmethylphenidate | Bupropion | Clozapine | Haloperidol |
| Gabapentin | Diphenhydramine | Dextroamphetamine | Citalopram | Olanzapine | Lithium | |
| Lamotrigine | Doxepin | Lisdexamfetamine | Duloxetine | Paliperidone | Pimozide | |
| Oxcarbazepine | Lorazepam | Methylphenidate | Quetiapine | |||
| Topiramate | Modafinil | Escitalopram | Risperidone | |||
| Zonisamide | Fluoxetine | Ziprasidone | ||||
| Fluvoxamine | ||||||
| Imipramine | ||||||
| Mirtazapine | ||||||
| Nortriptyline | ||||||
| Paroxetine | ||||||
| Phenelzine | ||||||
| Sertraline | ||||||
| Trazodone | ||||||
| Venlafaxine |
Statistical Analysis
Unweighted counts, percentages, and standard errors were computed for patients diagnosed with a TD. To account for the complex sampling design (i.e., cluster and strata adjustment), the “svyset” family of commands within Stata 14 (College Station, TX) were used.33 The unweighted counts and percentages were reported because the small number of cases did not allow for valid population weighting (i.e., small cell sizes and relative standard errors >30%). Differences between patient and visit characteristics were compared using a survey‐weighted, Rao‐Scott adjusted χ2 to test differences in proportions at α = 0.05 level.
The association between prescription of a psychotropic medication and patient and visit characteristics were assessed through a logistic regression model for each class of medication. The dependent variable, in each model, was an indicator variable representing the prescription of a given class of medication. We used a build‐down approach to create a parsimonious model, which included covariates that were theoretically important or based on previous research.26, 27, 28, 29 A variable for year of visit was included to control for temporal effects. To ease in interpretation and to add context to our logit results, marginal effects (MEs) were calculated; MEs describe the percent change in baseline probability that is associated with a one‐unit change in the covariate of interest. Only MEs >1% were reported.
Results
Patient and visit characteristics by mutually exclusive modality are provided in Table 2 for all 306 visits. Chi‐square tests of proportions suggest that there was a difference in treatment modality by primary payer (P < 0.01). There were significant differences in proportions of treatment modality by setting (P < 0.001). Most visits were from existing patients with at least one visit in the previous 12 months, but only the number of visits varied by treatment modality (P < 0.001). Primary care physicians provided the minority of visits, but there was no difference in prescribed treatment modality. More than three‐fourths of visits were for a chronic problem, either routine or flare up; treatment modality varied by the reason for the visit (P < 0.001). About half of the visits for TDs did not include a comorbidity.
Table 2.
Count, percent, and χ2 for characteristics of patients receiving no treatment, psychotherapy, and/or pharmacotherapy
| Visit Characteristics | Pharmacotherapy, n (%) | Psychotherapy, n (%) | Combined Therapy, n (%) | No Therapy, n (%) | Full Sample, n (%) |
|---|---|---|---|---|---|
| Overall | 152 (49.7) | 13 (4.2) | 42 (13.7) | 99 (32.4) | 306 (100) |
| Age, y (mean ± SD) | (18.3 ± 1.2) | (16.9 ± 3.1) | (19.8 ± 2.7) | (16.4 ± 1.5) | (17.8 ± 0.9) |
| Age range, y | 6 to 71 | 5 to 41 | 6 to 58 | 4 to 79 | 4 to 79 |
| Sex | |||||
| Female | 30 (47.6) | 1 (1.6) | 6 (9.5) | 26 (42.3) | 63 (20.6) |
| Male | 122 (50.2) | 12 (4.9) | 36 (14.8) | 73 (30.4) | 243 (79.4) |
| Race/ethnicity | |||||
| White, non‐Hispanic | 119 (51.3) | 10 (4.3) | 38 (16.4) | 65 (28.0) | 232 (75.8) |
| Black, non‐Hispanic | 12 (44.4) | 0 (0) | 3 (11.1) | 12 (44.4) | 27 (8.8) |
| Hispanic | 15 (45.5) | 2 (6.1) | 0 (0) | 16 (48.5) | 33 (10.8) |
| Other, non‐Hispanic | 6 (42.9) | 1 (7.1) | 1 (7.1) | 6 (42.9) | 14 (4.6) |
| Region | |||||
| Northeast | 45 (48.9) | 5 (5.4) | 13 (14.1) | 29 (31.5) | 92 (30.1) |
| Midwest | 51 (54.8) | 5 (5.4) | 15 (16.1) | 22 (23.7) | 93 (30.4) |
| South | 35 (54.7) | 2 (3.1) | 9 (14.1) | 18 (28.1) | 64 (20.9) |
| West | 21 (36.8) | 1 (1.8) | 5 (8.8) | 30 (52.6) | 57 (18.6) |
| Primary payer** | |||||
| Private | 81 (48.5) | 3 (1.8) | 26 (15.6) | 57 (34.1) | 167 (54.6) |
| Medicare | 8 (72.7) | 0 (0) | 0 (0) | 3 (27.3) | 11 (3.6) |
| Medicaid | 42 (50.6) | 8 (9.6) | 10 (12.1) | 23 (27.7) | 83 (3.6) |
| Self‐pay | 5 (31.3) | 2 (12.5) | 6 (37.5) | 3 (18.8) | 16 (5.2) |
| Other | 16 (55.2) | 0 (0) | 0 (0) | 13 (44.8) | 29 (9.5) |
| Care setting*** | |||||
| Office‐based | 75 (55.2) | 1 (.7) | 19 (14.0) | 41 (30.2) | 136 (44.4) |
| Outpatient | 77 (45.3) | 12 (7.1) | 23 (13.5) | 58 (34.1) | 170 (55.6) |
| Visit status | |||||
| Existing patient | 137 (54.2) | 11 (4.3) | 38 (15.0) | 67 (26.5) | 253 (82.7) |
| New patient | 15 (28.3) | 2 (3.8) | 4 (7.5) | 32 (60.4) | 53 (17.3) |
| Visits in past 12 mo*** | |||||
| 0 | 22 (32.8) | 3 (4.5) | 5 (7.5) | 37 (55.2) | 67 (21.9) |
| 1–2 | 62 (59.1) | 4 (3.8) | 5 (4.8) | 34 (32.4) | 105 (34.3) |
| 3–5 | 29 (53.7) | 2 (3.7) | 9 (16.7) | 14 (25.9) | 54 (17.6) |
| 6+ | 39 (48.8) | 4 (5.0 | 23 (28.8) | 14 (17.5) | 80 (26.1) |
| Reason for visit*** | |||||
| New/acute | 11 (23.9) | 1 (2.2) | 4 (8.7) | 30 (65.2) | 46 (15.0) |
| Chronic, routine | 114 (56.7) | 10 (5.0) | 33 (16.4) | 44 (21.9) | 201 (65.7) |
| Chronic, flare up | 17 (48.6) | 1 (2.9) | 5 (14.3) | 12 (34.3) | 35 (11.4) |
| Other | 10 (41.7) | 1 (4.2) | 0 (0) | 13 (54.2) | 24 (7.8) |
| Primary care provider | |||||
| Yes | 22 (47.8) | 0 (0) | 2 (4.3) | 22 (47.8) | 46 (15.0) |
| No | 130 (50.0) | 13 (5.0) | 40 (15.4) | 77 (29.6) | 260 (85.0) |
| Diagnosis(es)*** | |||||
| Tic disorders only | 73 (46.5) | 5 (3.2) | 9 (5.7) | 70 (44.6) | 149 (48.7) |
| Tic + OCD | 2 (33.3) | 1 (16.7) | 2 (33.3) | 1 (16.7) | 6 (2.0) |
| Tic + ADHD | 36 (55.4) | 1 (1.5) | 2 (12.5) | 5 (31.3) | 65 (21.2) |
| Tic + ODD | 1 (33.3) | 1 (33.3) | 1 (9.1) | 2 (18.2) | 3 (0.1) |
| Tic + anxiety | 7 (63.6) | 1 (1.5) | 1 (33.3) | 0 | 11 (3.6) |
| Tic + mood | 7 (43.8) | 2 (12.5) | 10 (15.4) | 18 (27.7) | 16 (5.2) |
| ≥3 disorders | 26 (54.2) | 2 (4.2) | 17 (35.4) | 3 (6.3) | 48 (15.7) |
For all Rao‐Scott adjusted chi‐square analyses: **P < 0.01; ***P < 0.001.
No difference in mean age by treatment modality.
Rows may not add to 100% because of rounding.
Table 3 presents the percentage and characteristics of visits and patients receiving each class of psychotropic medications prescribed. Table 4 presents the results of the logit model for the use of each class by selected patient and visit characteristics.
Table 3.
Percent of patients receiving each class of psychotropic medication by characteristic
| Visit Characteristics | Alpha‐2 Agonist, n (%) | Atypical Antipsychotic, n (%) | Typical Antipsychotic, n (%) | Stimulant, n (%) | SRI, n (%) | Anxiolytic, n (%) | Anticonvulsant, n (%) |
|---|---|---|---|---|---|---|---|
| Overall | 77 (25.2) | 54 (17.6) | 23 (7.5) | 69 (22.6) | 57 (18.6) | 44 (14.4) | 32 (10.5) |
| Age, y (mean ± SD) | (13.4 ± 0.9) | (17.5 ± 2.0) | (23.7 ± 3.3) | (13.4 ± 1.1) | (21.6 ± 2.2) | (29.1 ± 2.9) | (18.9 ± 2.7) |
| Age range, y | 6 to 44 | 6 to 68 | 9 to 65 | 6 to 62 | 7 to 62 | 8 to 71 | 6 to 58 |
| Sex | |||||||
| Female | 9 (14.3) | 7 (11.1) | 4 (6.3) | 8 (12.7) | 16 (25.4) | 13 (20.6) | 5 (7.9) |
| Male | 68 (28.0) | 47 (19.3) | 19 (7.8) | 61 (25.1) | 41 (16.9) | 31 (12.8) | 27 (11.1) |
| Race/ethnicity | |||||||
| White, non‐Hispanic | 67 (28.9) | 46 (19.8) | 20 (8.6) | 53 (22.8) | 51 (22.0) | 36 (15.5) | 26 (11.2) |
| Black, non‐Hispanic | 6 (22.2) | 5 (18.5) | 1 (3.7) | 5 (18.5) | 3 (11.1) | 4 (14.8) | 4 (14.8) |
| Hispanic | 3 (9.1) | 3 (9.1) | 1 (3.0) | 9 (27.3) | 1 (3.0) | 1 (3.0) | 1 (3.0) |
| Other, non‐Hispanic | 1 (7.1) | 0 | 1 (7.1) | 2 (14.3) | 2 (14.3) | 3 (21.4) | 1 (7.1) |
| Region | |||||||
| Northeast | 22 (23.9) | 23 (25.0) | 5 (5.4) | 15 (16.3) | 18 (19.6) | 11 (12.0) | 10 (10.9) |
| Midwest | 29 (28.0) | 15 (16.1) | 10 (10.8) | 28 (30.1) | 12 (12.9) | 18 (19.4) | 7 (7.5) |
| South | 18 (28.1) | 10 (15.6) | 6 (9.4) | 16 (25.0) | 14 (21.9) | 7 (10.9) | 8 (12.5) |
| West | 11 (19.3) | 54 (17.7) | 2 (3.5) | 10 (17.5) | 13 (22.8) | 8 (14.0) | 7 (12.3) |
| Primary payer | |||||||
| Private | 40 (24.0) | 33 (19.8) | 14 (8.4) | 39 (23.4) | 40 (24.0) | 25 (15.0) | 15 (9.0) |
| Medicare | 2 (18.2) | 1 (9.1) | 3 (27.3) | 1 (9.1) | 0 | 4 (36.4) | 0 |
| Medicaid | 25 (30.1) | 15 (18.1) | 5 (6.0) | 18 (21.7) | 9 (10.8) | 11 (13.3) | 14 (16.9) |
| Self‐Pay | 6 (37.5) | 3 (18.8) | 1 (6.3) | 4 (25.0) | 5 (31.3) | 2 (12.5) | 0 |
| Other | 4 (13.8) | 2 (6.9) | 0 | 7 (24.1) | 3 (10.3) | 2 (6.9) | 3 (10.3) |
| Care setting | |||||||
| Office‐based | 31 (22.8) | 25 (18.4) | 12 (7.1) | 40 (29.4) | 30 (22.1) | 24 (17.7) | 18 (13.2) |
| Outpatient | 46 (27.1) | 29 (17.1) | 11 (8.1) | 29 (17.1) | 27 (15.9) | 20 (11.8) | 14 (8.2) |
| Visit status | |||||||
| Existing patient | 69 (27.3) | 54 (21.3) | 21 (8.3) | 62 (24.5) | 52 (20.6) | 42 (16.6) | 31 (12.3) |
| New patient | 8 (15.1) | 0 | 2 (3.8) | 7 (13.2) | 5 (9.4) | 2 (3.8) | 1 (1.9) |
| Visits in past 12 mo | |||||||
| 0 | 11 (16.4) | 4 (6.0) | 2 (3.0) | 10 (14.9) | 8 (11.9) | 3 (4.5) | 5 (7.5) |
| 1–2 | 28 (26.7) | 16 (15.2) | 10 (9.5) | 16 (15.2) | 12 (11.4) | 13 (12.4) | 11 (10.5) |
| 3–5 | 17 (31.5) | 7 (13.0) | 6 (11.1) | 17 (31.5) | 14 (25.9) | 12 (22.2) | 4 (7.4) |
| 6+ | 21 (26.3) | 27 (33.8) | 5 (6.3) | 26 (32.5) | 23 (28.8) | 16 (20.0) | 12 (15.0) |
| Reason for visit | |||||||
| New/acute | 7 (15.2) | 2 (4.3) | 2 (4.3) | 1 (2.2) | 6 (13.0) | 2 (4.3) | 0 |
| Chronic, routine | 60 (30.0) | 46 (22.9) | 18 (9.0) | 56 (27.9) | 42 (20.9) | 33 (16.4) | 26 (12.9) |
| Chronic, flare up | 8 (22.9) | 3 (8.6) | 3 (8.6) | 9 (25.7) | 7 (20.0) | 6 (17.1) | 5 (14.3) |
| Other | 2 (8.3) | 3 (12.5) | 0 | 3 (12.5) | 2 (8.3) | 3 (12.5) | 1 (4.2) |
| Primary care provider | |||||||
| Yes | 10 (21.7) | 5 (10.9) | 1 (2.2) | 11 (23.9) | 7 (15.2) | 7 (15.2) | 5 (10.9) |
| No | 67 (25.8) | 49 (18.9) | 22 (8.5) | 58 (22.3) | 50 (19.2) | 37 (14.2) | 27 (10.4) |
| Diagnosis(es) | |||||||
| Tic disorders only | 30 (19.1) | 21 (13.4) | 18 (11.5) | 10 (6.4) | 18 (11.5) | 18 (11.5) | 18 (11.5) |
| Tic + OCD | 1 (16.7) | 2 (33.3) | 0 | 1 (16.7) | 3 (50.0) | 0 | 0 |
| Tic + ADHD | 21 (32.3) | 12 (18.5) | 3 (4.6) | 2 (12.5) | 8 (12.3) | 7 (10.8) | 3 (4.6) |
| Tic + ODD | 2 (66.7) | 0 | 1 (33.3) | 0 | 0 | 0 | 0 |
| Tic + anxiety | 2 (18.2) | 1 (9.1) | 0 | 2 (18.2) | 3 (27.3) | 4 (36.4) | 0 |
| Tic + mood | 2 (12.5) | 4 (25.0) | 0 | 2 (12.5) | 4 (25.0) | 6 (37.5) | 3 (18.8) |
| ≥3 disorders | 19 (39.6) | 14 (29.2) | 1 (2.1) | 24 (50.0) | 21 (43.8) | 9 (18.8) | 8 (16.7) |
Counts and percentages represent the proportion of patients with a given characteristic receiving each medication.
Receipt of each medication is not mutually exclusive; therefore, neither the columns nor rows will sum to 100%.
SRI, serotonin reuptake inhibitor; OCD, obsessive compulsive disorder; ADHD, attention‐deficit hyperactivity disorder; ODD, oppositional‐defiant disorder.
Table 4.
Odds ratios and 95% confidence intervals for patients receiving specific pharmacotherapies
| Alpha‐2 Agonist, OR (95% CI) | Atypical Antipsychotic, OR (95% CI) | Typical Antipsychotic, OR (95% CI) | Stimulant, OR (95% CI) | SRI, OR (95% CI) | Anxiolytic, OR (95% CI) | Anticonvulsant, OR (95% CI) | |
|---|---|---|---|---|---|---|---|
| Age | 0.96 (0.93, 0.98) | 1.00 (0.97, 1.03) | 1.02 (0.99, 1.05) | 0.98 (0.94, 1.02) | 1.02 (1.00, 1.05) | 1.04 (1.02, 1.07) | 0.99 (0.96, 1.02) |
| Sex | |||||||
| Female | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
| Male | 1.75 (0.67, 4.56) | 1.70 (0.57, 5.08) | 1.43 (0.45, 4.49) | 1.95 (0.60, 6.34) | 0.62 (0.23, 1.66) | 0.67 (0.27, 1.71) | 1.26 (0.39, 4.01) |
| Race/ethnicity | |||||||
| White, non‐Hispanic | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
| Black, non‐Hispanic | 1.09 (0.38, 3.17) | 2.03 (0.54, 7.61) | 0.42 (0.04, 4.33) | 1.59 (0.55, 4.54) | 1.02 (0.23, 4.41) | 0.71 (0.22, 2.32) | 2.56 (0.60, 10.91) |
| Hispanic | 0.22 (0.05, 0.90) | 0.48 (0.07, 3.44) | 0.40 (0.06, 2.65) | 2.72 (0.86, 8.60) | 0.08 (0.00, 2.12) | 0.19 (0.03, 1.28) | 0.20 (0.01, 3.23) |
| Other, non‐Hispanic | 0.33 (0.03, 3.49) | Empty | 1.02 (0.14, 7.33) | 1.18 (0.28, 4.94) | 0.43 (0.06, 3.10) | 1.83 (0.44, 7.65) | 0.43 (0.03, 5.91) |
| Region | |||||||
| Northeast | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
| Midwest | 1.11 (0.38, 3.17) | 0.49 (0.23, 1.03) | 2.51 (0.77, 8.19) | 4.97 (1.65, 15.03) | 0.57 (0.21, 1.59) | 1.93 (0.80, 4.67) | 0.52 (0.21, 1.30) |
| South | 1.65 (0.61, 4.46) | 0.43 (0.18, 1.05) | 1.60 (0.38, 6.66) | 4.38 (1.31, 14.67) | 1.62 (0.67, 3.92) | 0.91 (0.30, 2.77) | 1.06 (0.37, 3.05) |
| West | 1.06 (0.38, 2.93) | 0.36 (0.11, 1.22) | 1.31 (0.25, 6.94) | 1.45 (0.43, 4.85) | 1.38 (0.03, 1.19) | 1.91 (0.58, 6.22) | 1.66 (0.45, 6.09) |
| Reason for visit | |||||||
| New/acute | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
| Chronic, routine | 2.48 (1.05, 5.87) | 5.93 (1.29, 27.23) | 2.01 (0.35, 11.54) | 12.65 (1.80, 88.83) | 1.19 (0.39, 3.61) | 4.64 (0.98, 21.98) | 6.38 (0.22, 183.62) |
| Chronic, flare up | 1.32 (0.41, 4.24) | 1.39 (0.20, 9.65) | 2.00 (0.24, 16.59) | 12.03 (1.41, 102.76) | 0.74 (0.17, 3.14) | 4.11 (0.65, 25.82) | 7.39 (0.28, 192.25) |
| Other | 0.58 (0.08, 4.27) | 3.94 (0.33, 47.22) | Empty | 9.29 (0.71, 122.46) | 0.20 (0.03, 1.19) | 1.99 (0.24, 16.41) | Empty |
| Primary care provider | |||||||
| Yes | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
| No | 0.85 (0.35, 2.07) | 1.44 (0.41, 5.02) | 3.56 (0.40, 31.79) | 0.79 (0.24, 2.57) | 0.72 (0.28, 1.82) | 0.66 (0.20, 2.17) | 0.70 (0.21, 2.30) |
| Comorbidities | |||||||
| OCD | 0.61 (0.14, 2.77) | 1.71 (0.48, 6.11) | Empty | 0.68 (0.16, 2.80) | 12.55 (3.82, 41.26) | 0.41 (0.08, 2.12) | Empty |
| ADHD | 1.18 (0.64, 2.19) | 1.31 (0.69, 2.49) | 0.43 (0.10, 1.89) | 11.05 (5.18, 23.59) | 1.34 (0.64, 2.82) | 1.20 (0.45, 3.20) | 0.64 (0.26, 1.58) |
| ODD | 5.73 (0.97, 33.84) | 1.25 (0.36, 4.37) | 0.56 (0.08, 3.93) | 1.39 (0.53, 3.66) | 0.43 (0.07, 2.72) | 2.44 (0.41, 14.51) | 1.82 (0.26, 12.77) |
| Anxiety disorders | 3.21 (1.29, 8.02) | 0.77 (0.20, 3.05) | 0.48 (0.06, 3.73) | 3.75 (1.15, 12.24) | 5.96 (1.93, 18.42) | 2.53 (0.89, 7.22) | 0.21 (0.02, 2.12) |
| Mood disorders | 1.03 (0.39, 2.71) | 1.79 (0.67, 4.81) | Empty | 2.57 (0.71, 9.31) | 3.12 (1.02, 9.56) | 1.78 (0.68, 4.66) | 3.26 (1.26, 8.39) |
Each column represents a distinct logistic regression model with receipt of medication as the outcome and no receipt as the reference.
Bold denotes a statistically significant (α = 0.05) odds ratio. Reference for dependent variables was not receiving the medication.
SRI, serotonin reuptake inhibitor; OCD, obsessive compulsive disorder; ADHD, attention‐deficit hyperactivity disorder; ODD, oppositional‐defiant disorder; Ref., reference group.
“Empty” cells represent no observations.
Year of visit was included in the model to control for temporal effects but was omitted from the table for brevity and lack of significant effects.
Increasing age was associated with decreased odds of being prescribed alpha‐2 agonists (OR = 0.96, P = 0.002). This equates to a 0.6% decrease in the probability of being prescribed an alpha‐2 agonist for each additional year of age. Conversely, increasing age was associated with a 1.04 increase in the odds (0.4% increase in the probability) of being prescribed an anxiolytic medication for each additional year in age. No other age differences achieved significance.
Race and ethnicity were generally not associated with the receipt of any class of psychotropic medications, with one exception: Hispanic patients were less likely to be prescribed an alpha‐2 agonist (OR = 0.22, P = 0.035) compared to white, non‐Hispanic patients. This represents an 18% decrease in the probability of Hispanic patients receiving the alpha‐2 agonists compared to white patients.
Regional differences emerged only for stimulants. The odds of being prescribed a stimulant was 4.97 greater for Midwestern (P = 0.005), and 4.38 greater odds for Southern versus Northeastern physicians (P = 0.017). These odds represent an increase of 17.3% and 15.7% in the probability of receiving a prescription from Midwestern and Southern physicians, respectively, relative to Northern physicians.
Patients with routine visits for chronic problems had greater odds of receiving alpha‐2 agonists (OR = 2.48, P = 0.039), atypical antipsychotics (OR = 5.93, P = 0.023), and stimulants (OR = 12.65, P = 0.011) compared to patients with new or acute problems. This represents a 13.1% increase in the probability of receiving a prescription for alpha‐2 agonists for a routine visit for a chronic problem relative to a visit for new problems. Similarly, patients with a routine visit for a chronic problem experienced a 20.2% increase in the probability of receiving a stimulant, and a 17.5% increase in the probability of receiving an atypical antipsychotic relative to patients with a visit for a new problem. Finally, the odds of receiving a stimulant for a flare‐up of a chronic problem were 12.03 greater than for new problem (P = 0.023), equating to a 19.6% increase in the probability of receiving a stimulant for a flare up of a chronic condition relative to a new problem. There was no significant difference in prescription practice among physicians who were the patients' primary care providers and those who were not the primary care providers.
Comorbid conditions were significantly associated with the receipt of alpha‐2 agonists, SRIs, and anticonvulsants. Patients with comorbid anxiety disorders had 3.21 greater odds (P = 0.013), or 19.6% increase in probability, of receiving an alpha‐2 agonist compared to those without anxiety disorders. In addition, for patients with a comorbid anxiety disorder, the odds of being prescribed a stimulant were 3.75 greater (P = 0.028) than for patients without an anxiety disorder. This represented a 16.2% increase in the probability of being prescribed a stimulant. Patients with ADHD had 11.05 greater odds (P < 0.001), or a 33.1% increase in the probability, of receiving a stimulant medication compared to patients without ADHD. In terms of receiving an SRI, the odds were higher for patients with OCD (OR = 12.55, P < 0.001), anxiety disorders (OR = 5.96, P = 0.002), and mood disorders (OR = 3.12, P = 0.047) relative to patients without each of these disorders. The increased probability of receiving a stimulant was 39.1% for OCD, 25.5% for anxiety disorders, and 14.9% for mood disorders, relative to patients without each of these disorders. Patients with comorbid mood disorders had 3.26 greater odds (P = 0.015), or a 14.8% increase in probability, of receiving an anticonvulsant medication.
Discussion
We report on outpatient treatments provided to patients with TDs. In our sample of 306 children and adults, we found that one‐third (n = 99) did not receive treatment, whereas nearly two‐thirds received pharmacotherapy, and few patients received psychotherapy. Of the patients who were prescribed medications, alpha‐2 agonists were most frequent, followed closely by stimulants, SRIs, and atypical antipsychotics. This pattern is reasonable, given the profile of comorbid conditions and chronicity in our population, and it follows the results reported by others.26, 28, 29
Consistent with others, this sample contained a high proportion of males, children and adolescents, and white, non‐Hispanic patients.10, 34, 35 Our sample included fewer patients with comorbid psychiatric disorder than would be expected (~50% vs. ~80%).16, 22, 24 This discrepancy might be a result of methodology (e.g., differences in participating physicians, or the population seeking care), or it could be because of a lack of adequate reporting in the dataset. Because the dataset only provided three diagnosis codes per patient, it is possible that secondary or tertiary TDs are being underreported in patients with multiple disorders. Nonetheless, the comorbid disorders that did appear were primarily externalizing disorders (i.e., ADHD, ODD) or multiple disorders, but relatively few OCD diagnoses. The low number of comorbid OCD diagnoses may suggest that TDs are not being recorded in patients with OCD, which would be true if OCD symptoms were mild or unrecognized. It may also suggest variable rates of OCD within the population of patients with TDs. Alternatively, the lower‐than‐expected number of OCD diagnoses might be a result of the difficulties of overlapping symptoms between TD and OCD,1, 7, 18 resulting in undiagnosed OCD.
We observed treatment patterns that were significantly associated with patient characteristics. For example, increasing age was associated with decreasing odds of being prescribed alpha‐2 agonists. This might be a result of the evidence supporting the use of clonidine and guanfacine as first‐line treatments in youth with comorbid ADHD.8, 36, 37, 38, 39, 40 We also found that Hispanic patients were less likely to be prescribed a medication. This might be explained by cultural beliefs that psychotropic medications are stigmatized, unacceptable, or suggest serious illness41 resulting in lower use.42 The lower rates of prescriptions for Hispanic patients might also be explained by differences in the populations served by the surveyed physicians' offices, or may be because of actual differences in the epidemiology of TDs by race and ethnicity.
The most important treatment decision regarding TDs is the decision of whether to treat at all.18, 20 The proportion of untreated patients in our sample was consistent with others.27 This decision must be weighed against the severity, impairment, and likelihood of remission of the TDs with the side effect profile of psychotropic medications. In our sample, one‐third did not receive any treatment, suggesting that these individuals had neither problematic TDs, nor comorbid disorders necessitating treatment. It may also reflect a patient preference to forego treatment.
We also found that only 18% of patients received psychotherapy either alone, or in combination with pharmacotherapy. This is not surprising given the setting, yet behavioral interventions have shown medium to large effect sizes in patients with moderate to severe TDs43, 44, 45, 46, 47 as well as the established efficacy of cognitive‐behavioral interventions for OCD,48 anxiety,49 depressive,50 and behavioral disorders.51 Further, despite the efficacy of pharmacotherapy for TDs, side effects are a concern. Taken together, this suggests a need for greater dissemination of behavioral interventions among those treating patients with TDs.
There were few patterns of treatment that emerged as significant from our models. It appears that comorbid conditions are related to the medication prescribed. For example, stimulant prescriptions were higher in patients with ADHD, whereas alpha‐2 agonists were more likely to occur among patients with anxiety disorders than those without. This follows trends observed in a German study of children,28 and supports the notion that TDs are treated as secondary to the comorbid disorder unless they are causing significant distress.20 Similarly, SRIs were more likely prescribed to patients with OCD, anxiety, or mood disorders, following European prescribing patterns.29 This may suggest that the TD was secondary to OCD, anxiety, and mood disorders, for which SRIs are first‐line pharmacological treatments. Interestingly, stimulants were more likely to be prescribed to patients with anxiety disorders than those without, even controlling for ADHD diagnoses. There appears to be at least some support that stimulant use might have positive effects on anxiety disorders.52 We also found evidence of greater anticonvulsant use among patients with comorbid mood disorders, which makes sense given the mood‐stabilizing effects.53, 54
In the intervening time after the study period (i.e., 2003–2010), a growing body of evidence has shown support for behavioral therapy in the treatment of TDs. More specifically, Comprehensive Behavioral Intervention for Tics (CBIT) has trialed in children and adults, demonstrating significant improvement in symptoms.43, 44, 45, 46, 47 This intervention provides an effective alternative to psychotropic medications, with fewer side effects. This intervention may be combined with psychotropic mediations for patients with greater severity and/or comorbid disorders. Because of limitations in the dataset, we were not able to assess specific types of psychotherapeutic interventions (e.g., behavior therapy, CBIT, CBT, psychodynamic).
This study has several limitations. First, because of the relatively heterogeneous sample, some groups had small sizes. This created issues with model convergence and wide confidence intervals, which required paring down the models. We reported MEs (the average change in probabilities) to aid in the interpretation of the odds ratios. Second, we were unable to assess the severity of the disorder. This is a common limitation of administrative‐type data, but we included comorbid conditions and the chronicity of the problem to mitigate against this omission. Third, another limitation of using secondary data was the determination of the primary reason for the visit. It is possible that the order of importance was manipulated to maximize reimbursement or recorded in an arbitrary manner. In either case, we cannot be certain which medication or service is intended to treat which condition when multiple diagnoses are present. Fourth, it is possible that another provider delivered psychotherapy and other pharmacotherapy, thus this information would not be available in the study dataset, artificially lowering the prevalence of treatments. Finally, because this is a cross‐sectional study, we do not have information about medication adherence. It is possible that medication was prescribed, but never filled, used, or was filled but prematurely discontinued. Future research should address this concern, given the frequency and severity of side effects of these medications.
Conclusions
Nearly two‐thirds of children and adults with TDs, received pharmacotherapy, whereas one‐third did not receive any treatment. Few patients received psychotherapy, highlighting the need for improved dissemination of evidence‐based treatments in clinical practice. This sample was similar in terms of demographics, but differed in the prevalence of comorbid conditions compared to other samples. The class of medications used in pharmacotherapy appears to be driven largely by comorbid conditions and chronicity of TDs. This study was the first to examine treatment practices in a large community sample in the United States.
Author Roles
1. Research project: A. Conception, B. Organization, C. Execution; 2. Statistical Analysis: A. Design, B. Execution, C. Review and Critique; 3. Manuscript: A. Writing of the first draft, B. Review and Critique.
J.L.S.: 1A, 1B, 1C, 2A, 2B, 2C, 3A, 3B
S.G.: 1A, 1B, 2A, 2B, 2C, 3B
N.M.: 1A, 1B, 1C, 3A, 3B
T.K.M.: 2C, 3B
E.A.S.: 1A, 1B, 1C, 2A, 2C, 3A, 3B
Disclosures
Ethical Compliance Statement: We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this work is consistent with those guidelines. We confirm that the approval of an institutional review board was not required for this work.
Funding Sources and Conflicts of Interest: No specific funding was received for this work. The authors declare that there are no conflicts of interest relevant to this work.
Financial Disclosures for the previous 12 months: J.L.S., S.G., and N.M. report no sources of funding. All authors report no conflicts of interest. E.A.S. received research support from the following: NIH: 1R01HD080096‐01A1; the (Australian) National Health and Medical Research Council; the International OCD Foundation; and the All Children's Hospital Research Foundation. E.A.S. also receives publication royalties from Wiley, Elsevier, Springer, and the American Psychological Association. E.A.S. is a consultant for Ruijin Hospital, China. T.K.M. received research support from the following: NIH/NIMH: 1RO1MH093381‐01A1, 1R21MH087849‐01A1, 1R01HD080096‐01A1, R34; Centers for Disease Control and Prevention: 5U01DD000509‐02; International OCD Foundation; PANDAS Network; Massachusetts General Hospital; AstraZeneca Pharmaceuticals; Sunovion Pharmaceuticals, Inc.; F. Hoffmann‐LaRoche Ltd; Neurocrine Biosciences, Inc.; Teva Pharmaceuticals; Allergan plc; Shire Pharmaceuticals; Pfizer, Inc.; Psyadon Pharmaceuticals, Inc.; Otsuka Pharmaceuticals. T.K.M. received travel support from the Tourette Syndrome Association and honoraria from grand rounds lectures.
Acknowledgments
We thank Alessandro S. De Nadai, MA, for insightful input on data analysis and presentation.
Relevant disclosures and conflicts of interest are listed at the end of this article.
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