Abstract
Context
The extant literature on the treatment of pediatric OCD indicates that partial response to serotonin reuptake inhibitors (SRIs) is the norm, and that augmentation with short-term OCD-specific cognitive behavior therapy (CBT) may provide additional benefit.
Objective
To examine the effects of augmenting SRIs with CBT or a brief form of CBT, instructions in CBT (I-CBT) delivered in the context of medication management (MM).
Design
A 12-week, 3 (site: Penn, Duke, Brown) × 3 (treatment conditions: MM, MM+I-CBT, & MM+CBT) × 4 (repeated measures: weeks 0, 4, 8, & 12) randomized controlled trial.
Setting
The outpatient clinics of three academic medical centers between 2004 and 2009.
Participants
Outpatients (N = 124) between the ages of 7–17 with primary OCD and a Children’s Yale-Brown Obsessive Compulsive Scale (CY-BOCS) score ≥ 16 despite an adequate SRI trial.
Interventions
Participants were randomized to receive 12 weeks of: 1) MM (7 sessions), 2) MM+I-CBT (7 sessions) or 3) MM+CBT (7 sessions of MM plus 14 concurrent CBT sessions).
Main Outcome Measures
Responder status as defined as a post-treatment CY-BOCS reduction of 30% or greater compared to baseline; change in continuous CY-BOCS total score over 12 weeks.
Results
MM+CBT was superior to MM and to MM+I-CBT on all outcome measures. In the primary ITT analysis, 68.6% in MM+CBT (95% confidence interval [CI], 53.9%–83.3%) were considered responders, which was significantly better than the 34.0% in MM+I-CBT (95% CI, 18.0% to 50.0%), and 30.0% in MM (95% CI, 14.9% to 45.1%). Planned pairwise comparisons show that MM+CBT was superior to both MM and MM+I-CBT (p < 0.01 for both). MM+I-CBT was not statistically significant from MM (p = 0.72). The number needed to treat (NNT) with MM+CBT versus MM to see one additional RESPONSE at Week 12, on average, was estimated as 3; for MM+CBT versus MM+I-CBT the NNT was also estimated as 3 ;for MM+I-CBT versus MM the NNT was estimated as 25.
Conclusion
Among patients age 7–17 with OCD and partial response to SRI use, the addition of CBT by a psychologist to medication management compared with medication management alone resulted in a significantly greater response rate, whereas, augmentation of medication management with the addition of instructions in CBT by the psychiatrist did not. Dissemination of full CBT augmentation for pediatric OCD partial responders of SRI should be an important public health objective.
Obsessive compulsive disorder (OCD) affects up to 1 in 50 people,1 is evident across development,2 and is associated with substantial dysfunction and psychiatric comorbidity.3,4 Randomized, controlled trial findings supports the efficacy of: 1) pharmacotherapy with serotonin reuptake inhibitors (SRIs); 2) cognitive behavior therapy (CBT) involving exposure plus response prevention (ERP); and 3) combined treatment.5,6,7 However, the paucity of expertise in pediatric OCD prevents most families from accessing ERP or combined treatment. Outcome data for pharmacotherapy alone, which is the most widely available treatment, indicate that partial response is the norm and that clinically significant residual symptoms typically persist even after an adequate trial.8,9 Augmenting SRI treatment with ERP was found efficacious in a randomized controlled trial of adult OCD patients,10 but this approach has yet to be examined in youth with OCD who have achieved partial response on SRIs.
The observations above led us to develop a brief protocol, Instructions in CBT (I-CBT), for delivery in the context of medication management (MM) by child and adolescent psychiatrists. This integrated treatment (MM+I-CBT) was designed for implementation by physicians working in busy clinical practices that impose practical limits on session frequency and duration; our interest in generalizing study findings to such settings informed the sampling frame and treatment protocols for this pragmatic trial. We hypothesized that a full CBT protocol plus medication maintenance (MM+CBT) would be superior to both MM+I-CBT and MM, and that MM+I-CBT would be superior to MM.
METHODS
Design
The rationale, design considerations, assessment instrument psychometrics, and research methods for POTS II have been described elsewhere.11 Briefly, POTS II was a 12-week, 3 (site: Penn, Duke, Brown) × 3 (treatment conditions: MM, MM+I-CBT, & MM+CBT) × 4 (repeated measures at weeks 0, 4, 8, & 12), randomized parallel group controlled trial. Although MM does not control for contact time, it does parallel treatment as typically delivered in community settings. The Institutional Review Board at each site approved the protocol.
Participants
Inclusion criteria were: (1) ages 7–17 years; (2) primary OCD according to DSM-IV-TR criteria; (3) clinically relevant residual OCD symptoms as defined by a ≥16 on the CY-BOCS total score; 4) determined by a study psychiatrist to have experienced a partial response to an adequate SRI trial; and 5) outpatient. Exclusions were: (1) primary mental health diagnosis other than OCD; (2) pervasive developmental disorder(s); (3) failure to meet study requirements for an adequate SRI trial; (4) having failed an adequate CBT trial (>10 sessions); (5) pregnancy; or (6) pediatric autoimmune neuropsychiatric disorders associated with strep infection (PANDAS).
Determination of Eligibility
Eligibility was assessed via a multi-gate procedure designed to minimize patient burden and maximize efficiency: 1) Gate A, a brief telephone screening with the parent/guardian; 2) Gate B, an intake that included obtaining of informed consent from the parent(s) and assent from the participant, assessment of OCD symptoms using the CY-BOCS,12,13 and a review of current medications and their effects.; 3) Gate C, a diagnostic evaluation using the Anxiety Disorders Interview Scale for Children (ADIS-C)14 to survey comorbid conditions; and 4) Gate D, a baseline symptom assessment (week 0) that was followed by a separate meeting in which the outcome of randomization was revealed to the family. Progression from Gate A through Gate D was typically completed within three weeks.
Randomization
Patients were randomly assigned to condition between September 2004 and March 2009, using a computer-generated permuted blocking procedure, stratified by site, gender, age (<12 versus ≥12), and baseline severity as measured with the Clinical Global Impression-Severity scale (CGI<5 versus ≥5).
Treatments
MM
All randomized patients were assigned to a child/adolescent psychiatrist from whom they received maintenance SRI medications for the duration of the study; treatment was provided according to the study’s MM treatment manual. During the trial, downward adjustments of SRI dosing due to medication adverse events were possible, but medication could not be increased without a premature termination. A total of 7 in-person MM visits were conducted over 12 weeks, each lasting approximately 35 minutes. Study pharmacotherapists in MM or in MM+CBT monitored clinical status and medication effects and also offered general encouragement to resist OCD. Systematic or unsystematic ERP, insight-oriented or interpersonal psychotherapies, other CBT interventions, or family therapies were proscribed during the 12-week study period; as with each treatment arm, review of taped sessions in clinical supervision and independent rating of randomly selected tapes was used to promote treatment compliance.
CBT
The CBT protocol was based on a published treatment manual of established efficacy,15 and consisted of 14 hour-long visits conducted over 12 weeks involving: (1) psychoeducation, (2) cognitive training, (3) development of treatment hierarchies to arrange feared situations from least to most anxiety provoking to guide exposure treatment, and (4) ERP. A study psychologist administered CBT augmentation in the MM+CBT condition. Psychoeducation, defining OCD as the identified problem, cognitive training, and development of a treatment hierarchy took place during visits 1– 4; ERP comprised visits 5–12, with the last two sessions incorporating generalization training and relapse prevention. Each session included a statement of goals; review of the previous week; provision of new information; therapist-assisted practice; homework for the coming week; and monitoring procedures. As in clinical practice, study psychiatrists and psychologists were aware that patients assigned to MM+CBT were also seeing another treatment provider.
I-CBT
In the MM+I-CBT condition, the pharmacotherapist assigned to manage medication also provided instruction in CBT procedures. MM+I-CBT was administered according to protocol (7 visits over 12 weeks), with an average time of 45 minutes. The additional psychiatrist time above MM in the MM+I-CBT was used to introduce I-CBT principles and provide time to plan implementation of these skills between sessions. Specifically, I-CBT included psychoeducation, establishing and reevaluating a simple stimulus hierarchy, and identifying ERP targets and homework; two brief telephone check-ins were prescribed during treatment to provide guidance of CBT implementation at home. In contrast to CBT, I-CBT did not include: (1) therapist-assisted exposure; (2) imaginal exposure; and (3) didactic parent sessions. Exclusion of these components was necessitated by our interest in testing a protocol that could be feasibly implemented by psychiatrists in clinical practice settings that do not typically allow for sessions longer than 30 minutes.
Supervision and Oversight
Each site had major supervisory responsibilities: Penn provided clinical supervision of CBT and I-CBT; Duke organized data management and statistical analyses; and Brown provided clinical supervision of all MM. Pharmacotherapists treating cases in the MM+I-CBT condition participated in supervision for both MM and I-CBT. An independent data and safety monitoring board provided regular oversight and met bi-annually during the study and upon its completion.
Measures
DSM–IV-TR diagnoses of OCD and comorbid psychiatric conditions were ascertained using the research diagnostic version of the ADIS-C, an established measure with acceptable psychometric properties.14,16 OCD symptom severity was measured using the CY-BOCS, an interviewer-rated instrument that assess obsessions and compulsions separately on time consumed, distress, interference, degree of resistance, and control; it yields separate severity scores for obsessions and for compulsions (0 – 20), and a composite symptom severity score (0 to 40).12,13 Consistent with signal detection analyses examining the optimal criterion for treatment response,17 a CY-BOCS reduction of 30% or more from baseline to week 12 was used as the criterion for RESPONSE and was the primary dichotomous outcome measure. Secondary, continuous outcome measures of OCD symptom severity, the CY-BOCS and the NIMH-GOCS, were also examined at Week 12.
Because of the nature of the experimental design, families and clinicians were aware of the condition assignment; consequently, blinding for the primary outcomes was maintained by use of a trained independent evaluator (IE), who was not otherwise involved in any aspects of the study. IEs were trained to a reliable standard via joint interviews, reviews of videotaped interviews, and discussion. Reliability on these measures was maintained via within- and cross-site supervision that included review and re-rating of videotaped interviews on a monthly basis during the study. Approximately 10% of CY-BOCS sessions were randomly selected and then coded by all IEs. Variability among coders was discussed on the call to help stem rater drift. Inter-rater reliability during the trial remained high using the IE-supervisor CY-BOCS rating as the gold standard (ICC = 0.97).
Documentation and Clinical Management of Adverse Events
Because all participants were maintained on active SRI throughout the trial, assessment of adverse events were conducted at each psychiatry treatment visit using the Pediatric Adverse Event Rating Scale (PAERS18).
Sample Size and Power
Assuming RESPONSE rates of 70%, 40%, and 10% for MM+CBT, MM+I-CBT, and MM only, respectively, a 5% Type-I error, two-tailed chi-square test, and a planned total sample size of 150 (50 per group), the study was designed to detect a difference in the three RESPONSE rates, the primary outcome, with 99% probability. Recruitment issues likely related to the FDA’s black box warning about the use of SRIs in youth (October 2004) were encountered early on in the study, however, limiting the final sample size to 124 randomized participants.
Missing Data
As part of the study design, efforts were made to collect all outcomes on all randomized participants even when treatment was prematurely terminated.11 Prior to analysis, we used multiple imputation to replace missing values.19 A sequential regression multivariate imputation algorithm20 was used, as implemented in the IVEware package for SAS.21 The imputation model included all longitudinal outcome measures, time since randomization, treatment indicators, putative moderators and mediators,11 and the four stratification variables described above. Five data sets were generated. Results reported below were calculated using Rubin’s rules19 for combining the results of identical analyses performed on each of the five imputed data sets.
Statistical Analysis
All randomized participants were included in the analyses, in accordance with intention-to-treat principles. A multivariate chi-square test was used to test for between-group differences in RESPONSE rates at Week 12. Group-specific RESPONSE rates and planned pair-wise differences in the RESPONSE rates were also calculated.
Separate longitudinal regression models were used to examine mean differences in the two continuous outcomes (CY-BOCS, NIMH) between the three randomized treatment groups at each assessment visit. Each regression model included indicators of time (assessment visit), group assignment, and all time-by-group interaction terms. Baseline stratification variables employed in the randomization procedure (see above) were also included in each model. Residual error terms were assumed to follow a mean-zero, normal distribution with an unstructured covariance structure used to capture the within person correlation over time. The fitted models were used to report mean scores at each assessment visit and make inferences about between-groups comparisons at the final assessment visit. Tests were two-sided, and a P value of less than 0.05 was considered to indicate statistical significance. The sequential Dunnett test was used to control the overall (familywise) error rate.22 Longitudinal models were fit using PROC MIXED in SAS Statistical Software, Version 9.2 Level 2M2 (SAS Institute, Cary, NC).
To enhance interpretation of the results for RESPONSE, we calculated the number needed to treat (NNT)19 with MM+CBT and MM+I-CBT relative to MM. For the continuous outcomes, we calculated standardized between-group mean differences23 at the week 12 visit.
RESULTS
Recruitment and Retention
The Consort diagram is depicted in detail in Figure 1. Participants were recruited from: (1) site clinics; (2) schools; (3) primary care physicians; (4) mental health providers; and (5) paid and public service advertisements in local media, including newspapers, radio, internet, and television. Of the 124 subjects who underwent randomization, 118 (95.2%) completed at least one post-baseline assessment. The mean number of completed CBT sessions in the MM+CBT condition was 12.50 (CI 95%, 11.38 to 13.62) out of a possible 14 sessions; for I-CBT and MM, the mean number of completed sessions was 6.0 (CI 95%, 5.43 to 6.66) and 6.48 (CI 95%, 6.02 to 6.93) out of a possible 7 sessions, respectively. A total of 101 (81.5%) participants completed acute treatment: 13 dropped out of the study and were lost to follow-up (MM = 5, MM+I-CBT = 5, MM+CBT = 3), and 10 prematurely terminated the assigned treatment due to lack of efficacy, received out-of-protocol treatment, but remained in the study for outcome assessments (MM = 7, MM+I-CBT = 1, MM+CBT = 2). Investigation of post-randomization activity indicated that MM patients were more likely to prematurely terminate and receive out-of-protocol treatment (χ2(2) 6.40, p < .04).
Figure 1.
Consort Diagram
a Gate A exclusions are more than 421 due to some patients having multiple reasons for exclusion.
b Of these, 13 had diagnosis of Pervasive Developmental Disorder or Mental Retardation; 5 had Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections.
Sample Characteristics
Table 1 summarizes the current medication regimens of the randomized sample on the whole, as well as baseline and clinical characteristics presented by treatment condition. No significant between groups differences emerged. All patients were currently taking an SRI, which they had been taking for an average of 74.9 weeks (SD = 73.2; range 9 – 402 weeks) prior to study entry. For 51% of the sample, the current medication was their first SRI trial; 29% had one other past SRI trial, 8.9% had two, 6.5% had three, 2.4% had four, and 1.6% had five. Some concomitant medications for comorbid psychiatric or medical conditions were also permitted, the most common of which were stimulant medications for ADD or ADHD (13.7%).
Table 1.
Baseline Characteristics and Observed Cases by Timepoint
| VARIABLE | MM Only | MM+I-CBT | MM+CBT | All Subjects |
|---|---|---|---|---|
| STUDY CENTER – N (%) | ||||
| Brown University | 18 (42.9) | 15 (30.2) | 15 (35.7) | 48 (38.7) |
| Duke University Medical Center | 10 (23.8) | 11 (27.5) | 14 (35) | 35 (28.2) |
| University of Pennsylvania | 14 (33.3) | 14 (35) | 13 (32.5) | 41 (33.1) |
| DEMOGRAPHICS | ||||
| Age (SD) | 14.34 (2.51) | 13.76 (2.72) | 12.71 (2.88) | 13.60 (2.77) |
| 7–12 y.o. –N (%) | 14 (33.3) | 16 (40) | 25 (59.5) | 55 (44.4) |
| Female –N (%) | 22 (52.4) | 21 (52.5) | 23 (54.8) | 66 (53.2) |
| Race –N (%) | ||||
| White | 38 (90.5) | 38 (95) | 39 (92.9) | 115 (92.7) |
| Black | 1 (2.4) | 1 (2.5) | 1 (2.4) | 3 (2.4) |
| Asian | 2 (4.8) | 0 | 0 | 2 (1.6) |
| Mixed | 0 | 0 | 1 (2.4) | 1 (0.8) |
| Not Reported | 1 (2.4) | 1 (2.5) | 1 (2.4) | 3 (2.4) |
| Ethnicity | ||||
| Not Hispanic/Latino | 41 (97.6) | 39 (97.5) | 39 (92.9) | 119 (96.0) |
| Hispanic/Latino | 0 | 0 | 2 (4.8) | 2 (1.6) |
| Not Reported | 1 (2.4) | 1 (2.5) | 1 (2.4) | 3 (2.4) |
| OCD BASELINE SEVERITY | ||||
| CY-BOCS (SD) | 26.08 (5.12) | 27.40 (4.75) | 25.45 (5.18) | 26.29 (5.05) |
| NIMH-OCD (SD) | 9.60 (1.77) | 9.95 (1.81) | 9.31 (1.75) | 9.61 (1.78) |
| CGIS (SD) | 4.88 (.15) | 5.10 (.81) | 4.81 (.14) | 4.93 (.90) |
| CGIS<5 –N (%) | 13 (30.9) | 10 (25) | 17 (40.5) | 40 (32.3) |
| CGIS≥5 –N (%) | 29 (69) | 30 (75) | 25 (59.5) | 84 (67.7) |
| BASELINE COMORBIDITIES | ||||
| Any –N (%) | 27 (64.3) | 26 (65) | 21 (50) | 74 (59.7) |
| ADHD –N (%) | 11 (26.2) | 9 (22.5) | 7 (16.7) | 27 (21.8) |
| Anxiety/Mood –N (%) | 20 (47.6) | 18 (45) | 17 (40.5) | 55 (44.4) |
| Tic Disorder –N (%) | 9 (21.4) | 8 (20) | 2 (4.8) | 19 (15.3) |
| Externalizing –N (%) | 1 (2.4) | 1 (2.5) | 0 | 2 (1.6) |
| OBSERVED CASES - N | ||||
| Baseline | 42 | 40 | 42 | 124 |
| Week 4 | 38 | 37 | 39 | 114 |
| Week 8 | 36 | 35 | 38 | 109 |
| Week 12 | 37 | 34 | 39 | 110 |
| CURRENT SRIs | ||||
| Drug |
Number of Participants |
Percent of Sample |
Mean Recommended Dose |
Mean Actual Dose (SD) |
| Sertraline | 40 | 32.3% | 125 | 109.1 (9.2) |
| Fluoxetine | 35 | 28.2% | 40 | 36.4 (2.7) |
| Fluvoxamine | 22 | 17.7% | 175 | 148.3 (17.4) |
| Citalopram** | 13 | 10.5% | 40 | 38.1 (6.3) |
| Paroxetine | 7 | 5.6% | 30 | 34.6 (5.5) |
| Clomipramine | 3 | 2.4% | 150 | 91.7 (8.3) |
| Escitalopram** | 3 | 2.4% | 20 | 18.3 (7.3) |
| Venalfaxine** | 1 | 0.8% | 100 | 100.0 |
Mean dose derived from registration trials, expert recommendation and the applicant's clinical experience
Not included in Expert Consensus Guidelines
Intention-to-treat analysis (ITT)
In the primary ITT analysis1, the percentages of participants at 12 weeks who had at least a 30% reduction in CY-BOCS baseline score were: 68.6% in MM+CBT, (95% CI, 53.9% to 83.3%), 34.0% in MM+I-CBT (95% CI, 18.0% to 50.0%), and 30.0% in MM (95% CI, 14.9% to 45.1%). The multivariate chi-square test2 indicated a significant difference between groups (F(2, 136.57) = 6.44, p = .002). Planned pairwise comparisons show that MM+CBT was superior to both MM (t(100.66) =3.43, p < 0.001) and MM+I-CBT (t(373.62) =3.16, p = 0.002); MM+I-CBT was not statistically significant from MM (t(140.76) =0.35, p = 0.72). Planned pairwise comparisons of the continuous Week 12 outcomes were comparable to the findings for RESPONSE: MM+CBT was superior to both MM (t(189.48) =4.00, p < 0.0001) and MM+I-CBT (t(219.05) =3.26, p = 0.001), and MM+I-CBT and MM were not significantly different from each other (t(390.39) =0.75, p = 0.45) (See Figure 2). For NIMH-GOCS, MM+CBT was superior to both MM (t(208.58) =4.37, p < 0.0001) and MM+I-CBT (t(246.42) =3.29, p = 0.001), and MM+I-CBT and MM were not significantly different from each other (t(437.06) =1.11, p = 0.27). Table 2 provides a detailed description of point estimates, planned comparisons, and the respective effect sizes on each continuous variable.24
Figure 2.
CYBOCS Scores During 12 Weeks of Acute Treatment
Points are group-specific estimated mean CY-BOCS scores at each time point. Point-estimates were derived from the fitted linear mixed models, averaged over site, gender, age (<12 versus ≥12), and baseline severity (CGI-S<5 versus ≥5). Error bars are point-wise 95% CIs.
Table 2.
Group-specific response rates, mean scores, and between-group effect sizes at Week 12.
| Week 12 Variable | Responder Statusa | CY-BOCSb | NIMH-GOCSc |
|---|---|---|---|
| Estimated Meansd | |||
| MM+CBT | 0.69 (0.54, 0.83) | 14.23 (11.85, 16.62) | 5.59 (4.82, 6.36) |
| MM+I-CBT | 0.34 (0.18, 0.50) | 20.05 (17.45, 22.65) | 7.47 (6.65, 8.30) |
| MM-Only | 0.30 (0.15, 0.45) | 21.35 (18.89, 23.80) | 8.08 (7.29, 8.89) |
| Effect Sizese | |||
| MM+CBT v. MM-Only | 0.39 (0.16, 0.61) | 0.85 (0.43, 1.27) | 0.93 (0.51, 1.35) |
| MM+CBT v. MM+I-CBT | 0.35 (0.13, 0.56) | 0.70 (0.28, 1.12) | 0.70 (0.28, 1.12) |
| MM+I-CBT v. MM-Only | 0.04 (−0.18, 0.26) | 0.16 (−0.25, 0.56) | 0.23 (−0.18, 0.63) |
Abbreviations: CY-BOCS, Children’s Yale-Brown Obsessive Compulsive Scale; NIMH: National Institute of Mental Health Global Obsessive Compulsive Scale; MM = Medication Management; I-CBT: Instruction in Cognitive Behavioral Therapy Procedures by Psychiatrist; CBT: Cognitive Behavioral Therapy by Psychologist.
Responder Status scores range from 0.0 to 1.00 reflecting the percentage of responders.
CY-BOCS scores range from 0 to 40 with larger scores reflecting more OCD symptoms.
NIMH-GOCS scores range from 1 to 15 with larger scores reflecting more OCD symptoms.
For Responder Status: estimated rate of response (30% reduction of CY-BOCS from baseline) at Week 12 (95% CI). For CY-BOCS, NIMH, and CGI-S estimated mean score at Week 12 (95% CI) from the fitted linear mixed models, averaged over site, gender, age (<12 versus ≥12), and baseline severity (CGI-S<5 versus ≥5).
For Responder Status: between-groups difference in estimated response rate at Week 12 (95% CI). For CY-BOCS, NIMH, and CGI-S: between-groups difference in estimated mean score at Week 12 divided by the pooled standard deviation of the outcome at Week 12, otherwise known as Cohen’s d (95% CI). Cohen’s d between 0.50–0.79 is considered a medium effect; Cohen’s d ≥ 0.80 is considered a large effect.1 All effect size estimates are reported such that positive scores indicate that the first treatment group was superior to the comparison group in functioning.
A multivariate chi-square test found no statistically significant site × treatment interactions for RESPONSE at the 12 week visit (p = 0.28). Similarly, no sites × treatment interactions were found at week 12 visit for the continuous outcomes: CY-BOCS (p = 0.15) or NIMH (p = 0.72).
Effect Estimates of Clinical Significance
Treatment effect sizes for Week 12 CY-BOCS were 0.85 (95% CI, 0.43 to 1.27) for MM+CBT versus MM, and 0.16 for MM+I-CBT versus MM; these correspond to large and small treatment effect sizes, respectively. The number needed to treat (NNT) with MM+CBT versus MM to see one additional RESPONSE at Week 12, on average, was estimated as 3; for MM+CBT versus MM+I-CBT the NNT was also estimated as 3; for MM+I-CBT versus MM the NNT was estimated as 25.
Post-hoc Analysis
Since MM participants were more likely to prematurely terminate and receive additional treatment outside of their assigned treatment arm, we conducted a post-hoc analysis to investigate whether the conclusions of the main ITT findings would change if we accounted for individuals who received out-of-protocol treatment after premature termination. These analyses (see Web Appendix) mirrored the ITT findings: for all outcomes, MM+CBT was superior to MM+I-CBT and MM, with no difference between MM+I-CBT and MM.
Adverse Event Analyses
A summary of adverse event rates is reported in Table 3. No between-groups differences emerged on these variables. Two participants had serious adverse events (SAEs) during the study. One child in MM made a suicide attempt during the trial, which led to a psychiatric hospitalization, premature termination, and changes to medication/therapy to better treat the child’s comorbid depression. A child in MM+I-CBT reported suicidal thoughts during the last treatment visit due to teasing by classmates. Given the context in which these thoughts arose (e.g., social difficulties at school), this SAE was determined to be unrelated to treatment.
Table 3.
Adverse Events by Treatment Group
| Variable | MM Only (N=42) |
MM+ICBT (N-40) |
MM+CBT (N=42) |
All Subjects (N=124) |
P Value |
|---|---|---|---|---|---|
| Having at Least One AE | 37 | 33 | 39 | 109 | 0.36 |
| Having at Least One Drug-Related AE | 20 | 14 | 21 | 55 | 0.34 |
| AE Leading to Withdrawal | 5 | 3 | 2 | 10 | 0.48 |
| Severe AE | 1 | 1 | 0 | 2 | 0.59 |
Note: AE = Adverse Event; The reported P value was calculated with the use of Pearson’s chi-square statistic.
COMMENT
Augmentation of maintenance SRI medication with CBT was efficacious, indicating that the combination of CBT and medication is superior to medication monotherapy whether delivered as acute treatment as in POTS I7 or as augmentation. The magnitude of symptom reduction observed on the CY-BOCS was somewhat smaller than seen in the POTS I study of combined acute treatment; whether this reflects a sampling differences or a sequencing effect is unknown. Nevertheless, it is encouraging that CBT remained efficacious even in children and adolescents who had experienced partial response to medication treatment.
With respect to the potential utility of a brief form of CBT integrated into medication management, point estimates for MM+I-CBT showed improvement relative to MM, but there was insufficient evidence that these conditions differed on average on any of our primary or secondary outcome measures. Further, while more MM patients dropped out or were prematurely terminated, secondary analyses suggested that the impact of MM+I-CBT (NNT = 25 relative to the NNT for MM+CBT of 3) remained small relative to MM alone. Reasons for the lack of a discernible effect may include lower intensity (brevity), less provider contact time in MM+I-CBT versus in MM+CBT, omission of key CBT components particularly in-session exposure exercises, or some combination of these factors. Moreover, while POTS II used a dual doctor versus single doctor framework, the study provides no guidance about whether CBT for pediatric OCD should be provided by psychologists versus psychiatrists. Full CBT by a psychiatrist providing medication management is a more than reasonable option for the family fortunate enough to find a CBT-trained child psychiatrist.
Sample heterogeneity with respect to treatment history and current medication trial resulted from an intentional design decision, and reflected our primary interest in addressing the practical problem of partial response that affects many if not most pediatric OCD patients treated in community settings. We believe that this sampling frame improves generalizability to such settings, though we acknowledge that it also reduced experimental control over the potential effects of such variability. However, despite following recruitment strategies recommended by experts,25 POTS II paralleled the broader OCD treatment literature in its failure to attract more than a few minority participants, which leaves unknown the applicability of our findings to these groups.
Findings from POTS I and II are consistent with a growing evidence base that supports the use of ERP as an initial or augmentative treatment for patients of all ages with OCD. Effectiveness studies conducted with samples across the age spectrum have indicated that good outcomes are not limited to highly selected RCT samples26,27,28,29 and can be achieved in community agencies by supervised therapists who are themselves not OCD experts.30,31 Accordingly, these collective findings highlight the importance of disseminating CBT for pediatric OCD into community settings so that affected children have options beyond medication management alone. Further, POTS II findings indicate that these dissemination efforts should focus on making the full CBT protocol more widely available in such settings rather than on attempting to create and disseminate truncated versions of this efficacious form of treatment. Towards these ends, research must focus on developing, evaluating, and comparing various models for disseminating CBT beyond the academic medical context.
Supplementary Material
Acknowledgments
Funding/Support: The Pediatric OCD Treatment Study II was supported by NIMH grants 2R01MH055126-08A2 (Penn), 2R01MH055121-06A2 (Duke) and 1R01MH064188-01A2 (Brown).
Role of the Sponsors: The study sponsors had no role in the design and conduct of the study; in the collection, management, analysis, and interpretation of the data; or in the preparation, review, or approval of the manuscript.
Footnotes
Throughout the analyses, adjusted degrees of freedom are presented as suggested by Barnard and Rubin (1999) and implemented using the EDF option in SAS.
We conducted this test using the SAS macro, COMBCHI [ref], for imputed data sets. In this macro, Chi-square results are combined and reported as an F-statistic.
POTS Team:
PIs: Martin Franklin (Penn), Jennifer Freeman, Leonard (Brown), John March (Duke)
Co-Is: Penn: Muniya Khanna, Edna Foa; Brown: Abbe Garcia; Duke: Jeffrey Sapyta, Phoebe Moore, Allan Chrisman, David Fitzgerald
Principal Statisticians: Scott Compton (Duke), Daniel Almirall (Michigan)
Author Contributions: Dr. Franklin had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analyses.
Study concept and design, obtained funding: Compton, Foa, Franklin, Freeman, Garcia, March, Moore
Acquisition of data: Choate-Summers, Compton, Edson, Foa, Franklin, Freeman, Garcia, Khanna, March, Moore, Sapyta
Analysis and interpretation of data: Almirall, Compton, Franklin, Freeman, Garcia, March, Sapyta
Drafting of the manuscript: Almirall, Compton, Edson, Franklin, Freeman, Garica, March, Sapyta
Critical revision of the manuscript for important intellectual content: Almirall, Compton, Edson, Foa, Franklin, Freeman, Garcia, March, Sapyta
Statistical analysis: Almirall, Compton, March, Sapyta
Administrative, technical, or material support: Almirall, Compton, Edson, Sapyta
Study supervision: Choate-Summers, Franklin, Freeman, March, Moore
Financial Disclosures:
Dr. March has received speaker fees from Pfizer, consulting fees from Pfizer and Wyeth, and research support from Pfizer and Lilly, and has served as a scientific advisor for Pfizer and on the data and safety monitoring board for Organon, Astra-Zeneca, and Pfizer. Ms. Edson and Drs. Franklin, Sapyta, Freeman, Khanna, Compton, Almirall, Moore, Choate-Summers, Garcia and Foa do not have any financial conflicts of interest to report.
Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, NJ: L. Erlbaum Associates; 1988.
REFERENCES
- 1.Ruscio AM, Stein DJ, Chiu WT, Kessler RC. The epidemiology of obsessive compulsive disorder in the National Comorbidity Survey Replication. Molecular Psychiatry. 2010;15:53–63. doi: 10.1038/mp.2008.94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Piacentini J, Bergman RL. Obsessive-compulsive disorder in children. Psychiatr Clin North Am. 2000;23(3) doi: 10.1016/s0193-953x(05)70178-7. 519–533.4. [DOI] [PubMed] [Google Scholar]
- 3.Piacentini J, Bergman LR, Keller M, McCracken J. Functional impairment in children and adolescents with obsessive-compulsive disorder. J Child Adol Psychop. 2003;13(2) Suppl:S61–S69. doi: 10.1089/104454603322126359. [DOI] [PubMed] [Google Scholar]
- 4.Swedo SE, Rapoport JL, Leonard HL, Lenane M. Obsessive-compulsive disorder in children and adolescents: Clinical phenomenology of 70 consecutive cases. Arch Gen Psychiat. 1989;46(4):335–341. doi: 10.1001/archpsyc.1989.01810040041007. [DOI] [PubMed] [Google Scholar]
- 5.Watson HJ, Rees CS. Meta-analysis of randomized, controlled treatment trials for pediatric obsessive-compulsive disorder. Jnl Clin Psychol Psychiat. 2008;49:489–498. doi: 10.1111/j.1469-7610.2007.01875.x. [DOI] [PubMed] [Google Scholar]
- 6.Abramowitz JS, Whiteside SP, Deacon BJ. The effectiveness of treatment for pediatric obsessive-compulsive disorder: A meta-analysis. Behav Ther. 2005;36(1):55–63. [Google Scholar]
- 7.Pediatric OCD Treatment Study Team. Cognitive-behavioral therapy, sertraline, and their combination for children and adolescents with obsessive-compulsive disorder: The Pediatric OCD Treatment Study (POTS) randomized controlled trial. JAMA. 2004;292:1969–1976. doi: 10.1001/jama.292.16.1969. [DOI] [PubMed] [Google Scholar]
- 8.March JS, Biederman J, Wolkow R, et al. Sertraline in children and adolescents with obsessive–compulsive disorder: A multicenter randomized controlled trial. JAMA. 1998;280(20):1752–1756. doi: 10.1001/jama.280.20.1752. [DOI] [PubMed] [Google Scholar]
- 9.Riddle MA, Reeve EA, Yaryura-Tobias JA, et al. Fluvoxamine for children and adolescents with obsessive-compulsive disorder: A randomized, controlled, multicenter trial. J Am Acad Child Psy. 2001;40(2):222–229. doi: 10.1097/00004583-200102000-00017. [DOI] [PubMed] [Google Scholar]
- 10.Simpson HB, Foa EB, Liebowitz MR, et al. A randomized, controlled trial of cognitivebehavioral therapy for augmenting pharmacotherapy in obsessive-compulsive disorder. A. m J Psychiat. 2008;165(5):621–630. doi: 10.1176/appi.ajp.2007.07091440. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Freeman JB, Choate-Summers ML, Garcia AM, et al. The Pediatric Obsessive-Compulsive Disorder Treatment Study II: Rationale, design and methods. Child and Adolescent Psychiatry and Mental Health. 2009;3:1–15. doi: 10.1186/1753-2000-3-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Goodman W, Price L, Rasmussen S. The Yale-Brown Obsessive Compulsive Scale, I: Development, use, reliability. Arch Gen Psychiat. 1989;46:1006–1011. doi: 10.1001/archpsyc.1989.01810110048007. [DOI] [PubMed] [Google Scholar]
- 13.Scahill L, Riddle MA, McSwiggin-Hardin M, Ort SI. Children's Yale-Brown Obsessive Compulsive Scale: Reliability and validity. J Am Acad Child Psy. 1997;36:844–852. doi: 10.1097/00004583-199706000-00023. [DOI] [PubMed] [Google Scholar]
- 14.Silverman W, Albano A. The Anxiety Disorders InterviewSchedule for DSM-IV, Child and Parent Versions. San Antonio, TX: The Psychological Corp; 1996. [Google Scholar]
- 15.March J, Mulle K. OCD in Children and Adolescents: A Cognitive-Behavioral Treatment Manual. New York, NY: Guilford Press; 1998. [Google Scholar]
- 16.Silverman WK, Saavedra LM, Pina AA. Test-retest reliability of anxiety symptoms and diagnoses with anxiety disorders interview schedule forDSM-IV: Child and parent versions. J Am Acad Child Psy. 2001;40(8):937–944. doi: 10.1097/00004583-200108000-00016. [DOI] [PubMed] [Google Scholar]
- 17.Tolin DF, Abramowitz JS, Diefenbach GJ. Defining response in clinical trials for obsessivecompulsive disorder: A signal detection analysis of the yale-brown obsessive compulsive scale. J Clin Psychiatry. 2005;66:1549–1557. doi: 10.4088/jcp.v66n1209. [DOI] [PubMed] [Google Scholar]
- 18.March J, Karayal O, Chrisman A. CAPTN: The Pediatric Adverse Event Rating Scale. The Scientific Proceedings of the 2007 Annual Meeting of the American Academy of Child and Adolescent Psychiatry; 23–28 October 2007; Boston. 2007. p. 241. [Google Scholar]
- 19.R: A Language and Environment for Statistical Computing. [cited 2009];R: A language and environment for statistical computing. 2007 Available from: http://www.R-project.org.
- 20.Rubin DB. Multiple imputation for nonresponse in surveys. New York, NY: Wiley; 1987. p. 258. [Google Scholar]
- 21.Raghunathan TE, et al. A Multivariate Technique for Multiply Imputing Missing Values Using a Sequence of Regression Models. Survey Methodology. 2001;27:85–95. [Google Scholar]
- 22.Miller RG. Simultaneous statistical inference. New York: McGraw-Hill; 1966. [Google Scholar]
- 23.Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, NJ: L. Erlbaum Associates; 1988. [Google Scholar]
- 24.Allison PD. [Accessed June 14th, 2011];SAS Macros. http://www.pauldallison.com/Download3.html. Updated June 14th, 2011.
- 25.Williams M, Powers M, Yun Y, Foa EB. Minority participation in randomized controlled trials for obsessive-compulsive disorder. J Anxiety Disord. 2010;24(2):171–177. doi: 10.1016/j.janxdis.2009.11.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Franklin ME, Abramowitz JS, Kozak MJ, Levitt JT, Foa EB. Effectiveness of exposure and ritual prevention for obsessive-compulsive disorder: randomized compared with nonrandomized samples. J Consult Clin Psychol. 2000;68:594–602. [PubMed] [Google Scholar]
- 27.Tenneij NJ, van Megen HJGM, Denys DAJP, Westenberg HGM. Behavior therapy augments response of patients with obsessive-compulsive disorder responding to drug treatment. J Clin Psychiat. 2005;66(9):1169–1175. doi: 10.4088/jcp.v66n0913. [DOI] [PubMed] [Google Scholar]
- 28.Rothbaum BO, Shahar F. Behavioral treatment of obsessive-compulsive disorder in a naturalistic setting. Cog Beh Prac. 2000;7:262–270. [Google Scholar]
- 29.Warren R, Thomas JC. Cognitive–behavior therapy of obsessive–compulsive disorder in private practice: An effectiveness study. J Anxiety Disord. 2001;15(4):277–285. doi: 10.1016/s0887-6185(01)00063-9. [DOI] [PubMed] [Google Scholar]
- 30.Nakatani E, Mataix-Cols D, Micali N, Turner C, Heyman I. Outcomes of cognitive behaviour therapy for obsessive compulsive disorder in a clinical setting: A 10-year experience from a specialist OCD service for children and adolescents. Child and Adolescent Mental Health. 2009;14(3):133–139. [Google Scholar]
- 31.Valderhaug R, Larsson B, Gottestam KG, Piacentini J. An open clinical trial of cognitivebehaviour therapy in children and adolescents with obsessive-compulsive disorder administered in regular outpatient clinics. Behav Res Ther. 2007;45(3):577–589. doi: 10.1016/j.brat.2006.04.011. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.


