Dosing of risperidone and divalproex sodium
The mean dose for risperidone at endpoint was 1.44
mg/day (SD=0.72). The mean dose for divalproex sodium at endpoint was 838.24
mg/day (SD=260.58). Serum level at endpoint was 96.1
μg/mL. Medication dose for the clinical predictor groups is included in .
Demographic Characteristics, Clinical Characteristics, and Descriptive Statistics for All Study Measures for the Total Sample and by Clinical Predictor Subgroup
We report the demographic and clinical characteristics, as well as descriptive statistics for all study measures at baseline and end treatment, for the total sample and stratified by the aggression and DBD co-morbidity subgroups in . Chi square and t-test analyses were conducted to examine group differences in the demographic and clinical characteristics between the medication groups as well as the clinical predictor groups, as indicated in and reported next.
The risperidone (n
=32) and divalproex groups (n
=33) were compared and were not significantly different in gender, racial background, co-morbidity with a DBD, age, or aggression. The two groups were significantly different from each other in terms of treatment completion (χ2
<0.05), with fewer youth completing treatment in the divalproex group (n
=17, 51.5%) as compared with the risperidone group (n
=27, 84.4%). Reasons for premature discontinuation (Pavuluri et al. 2010
) such as increased irritability, hospitalization, being lost to follow-up, ineffectiveness, depression, suicidal behavior, rash, and tics did not differ significantly among the predictor groups as discussed next.
As just noted, we report the age, gender, ethnicity, medication assignment and endpoint dose values, co-morbidities, aggression levels, and descriptive statistics for all outcome measures for youth with and without DBD co-morbidity (n=29 and n=36, respectively) in . Analyses revealed that the DBD co-morbidity groups were not significantly different with regard to age, gender, racial background, and attrition. Further, groups did not significantly differ in terms of their baseline level of aggression or medication condition. Differences in the outcome measures among groups are discussed in the longitudinal analyses presented next.
Additionally, presents sample characteristics and descriptive statistics for the aggression subgroups. Youth with high levels of baseline aggression (n=21) versus low baseline aggression (n=39) were compared and were not significantly different with regard to age, racial background, and attrition. Further, the groups did not differ in terms of their co-morbidity with a DBD or medication condition. However, the two groups were significantly different from each other in terms of gender (χ2=6.4, p<0.05). Given this difference, post hoc analyses were examined while controlling for gender. Of note, 5 youth did not provide baseline aggression data and, thus, were excluded from all analyses examining aggression as a predictor. Chi-square and t-test analyses confirmed that youth with and without aggression data did not significantly differ in terms of gender, racial background, attrition, medication condition, or co-morbidity with DBD. Differences in outcome measures for high and low-aggression youth across treatment are discussed next.
Finally, preliminary analyses examined the relationship between the clinical predictors, aggression, and DBD co-morbidity in this sample. Findings demonstrated that aggression was equally distributed across co-morbid and non-co-morbid youth and, similarly, rates of DBD co-morbidity were equally distributed across high- and low-aggression groups. In our sample, aggression and DBD co-morbidity were not significantly correlated, rPB=0.15, p=ns. Thus, findings indicate that aggression and DBD co-morbidity are distinct, nonoverlapping constructs within the current sample.
DBD co-morbidity and treatment response
We hypothesized that the presence of co-morbid DBD would be associated with poorer treatment response as compared with PBD youth without co-morbid DBD diagnoses. In addition, exploratory hypotheses examined interactions between co-morbidity and medication type (risperidone vs. divalproex). To test these hypotheses, MRMs as just specified were conducted separately for manic symptoms, depressive symptoms, and global functioning. Results of the three models, including parameter estimates, SEs, t-values, and p-values, are presented in ; baseline and endpoint values for manic symptoms, depressive symptoms, and global functioning are reported in .
Table 2. Co-morbid Disruptive Behavior Disorder Mixed-Effects Regression Models on Manic Symptoms (Young Mania Rating Scale [YMRS]), Depression Symptoms (Child Depression Rating Scale-Revised [CDRS=R]), and Global Functioning (Child and Adolescent Functioning (more ...)
The first model examined co-morbid DBD as a predictor of manic symptom response. As shown in , results for the Time effect indicated that all youth experienced an improvement in symptoms across treatment. In addition, in support of our hypothesis, findings revealed a significant Comorbid DBD×Time interaction, indicating that manic symptom response over time differed for youth with co-morbid DBD versus non-DBD youth. However, in contrast to the direction of our hypotheses, examination of manic symptom trajectories suggests that youth with co-morbid DBD experienced a slightly steeper (i.e., stronger) treatment response initially (e.g., from baseline to week 2, mean YMRS scores improved by 15.31 points for youth with DBD versus a 12-point reduction in YMRS scores for youth with non-DBD co-morbidities), although the magnitude of group differences diminished by mid-treatment (e.g., week 3 mean YMRS scores for youth with DBD were 11.19 (SD=7.13) and 10.39 (SD=8.84) for youth with non-DBD co-morbidities). However, this interaction was qualified by the significant three-way Co-morbidity×Medication Type×Time interaction, indicating that treatment response over time for co-morbid versus non-co-morbid youth was moderated by medication type. To best illustrate this interaction, displays mean YMRS scores across treatment as a function of co-morbidity status and medication type. As the figure reveals, youth with PBD with co-morbid DBD experienced greater improvement in manic symptoms in response to risperidone versus divalproex, whereas youth with non-co-morbid DBD experienced similar trajectories of symptom improvement in both medication groups. Moreover, youth with PBD with co-morbid DBD in the risperidone group evidenced the strongest symptom response overall, although all groups showed similar responses by end treatment.
FIG. 1. Mean manic symptoms (YMRS) scores over time as a function of disruptive behavior disorders (DBD) co-morbidity and medication type. DBD=presence of a co-morbid disruptive behavior disorder; No DBD=absence of a co-morbid disruptive behavior disorder; D=divalproex; (more ...)
Results for depressive symptoms indicated a significant main effect for time, such that all youth experienced an improvement in symptoms across treatment. Results also indicated a significant main effect for co-morbidity, with youth with co-morbid-DBD experiencing lower levels of depressive symptoms overall (M=30.58, SD=13.01) as compared with youth with non-DBD co-morbidities (M=33.35, SD=14.55). However, in contrast to hypotheses, youth with and without co-morbid DBD experienced similar trajectories of depressive symptom improvement over time (i.e., nonsignificant effect for Co-morbidity×Time; see for endpoint CDRS values by DBD group). Thus, co-morbidity was not associated with a poorer treatment response for depressive symptoms. Further, co-morbidity did not significantly moderate the trajectories of symptom response among the two medication groups.
Regarding global functioning, results of the third model revealed that again, all youth improved in terms of their global functioning (as measured by the CAFAS) across treatment. In addition, findings revealed a trend for the Co-morbid DBD×Time interaction, which indicated that improvement in global functioning across treatment differed for the co-morbid-DBD versus non-co-morbid youth. Findings held across medication type, as indicated by the nonsignificant Co-morbidity×Time×Medication. To illustrate this trend, displays mean CAFAS scores over time as a function of co-morbidity. Consistent with our hypotheses, results indicate that the non-DBD group experienced a differential pattern of change in global functioning over time as compared with youth with co-morbid-DBD. Further, as the figure reveals, group differences became more exaggerated across treatment: the co-morbid group's initial steep reduction in functional problems appeared to plateau by mid-treatment, whereas the non-DBD group experienced consistent declines in problematic functioning across treatment. By end treatment, mean global functioning for co-morbid youth (M=21.67, SD=36.31) continued to exceed clinical significance, signaling the need for continued outpatient care, whereas mean scores for non-co-morbid youth approached nonimpaired functioning (M=12.35, SD=35.27).
Mean global functioning (CAFAS) scores over time as a function of DBD co-morbidity. CAFAS=Child and Adolescent Functioning Assessment Scale, DBD=disruptive behavior disorders.
Aggressive features and treatment response
We also hypothesized that aggressive features may complicate treatment for youth with PBD, as indicated by a poorer treatment response for youth with high levels of baseline aggression versus youth with low levels of aggression. To examine the influences of aggression on each outcome measure, we conducted three MRMs identical to the models just described. Results of these models are presented in , and lists the baseline and endpoint values for manic symptoms, depressive symptoms, and global functioning for high- and low-aggression youth.
Table 3. Aggressive Features Mixed-Effects Regression Models on Manic Symptoms (Young Mania Rating Scale [YMRS]), Depression Symptoms (Child Depression Rating Scale-Revised [CDRS=R]), and Global Functioning (Child and Adolescent Functioning Assessment Scale [CAFAS]) (more ...)
Results for manic symptom response revealed a significant main effect for time, such that all youth improved in their manic symptoms across treatment. However, in contrast with expectations, youth with high baseline aggression demonstrated similar manic symptom responses as low-aggression youth (i.e., nonsignificant effects for Aggression×Time; see for endpoint YMRS values). Further, the three-way interaction of Aggression×Time×Medication was not significant, indicating that high- and low-aggression youth experienced similar improvement across medication type. Similarly, findings for depressive symptoms revealed that all youth improved in response to pharmacologic intervention. Response trajectories for depressive symptoms were similar for high- versus low-aggression youth, across medication groups. As indicates, all youth experienced similar levels of depressive symptoms by end-point treatment. Thus, aggression did not predict manic or depressive symptom response to pharmacotherapy.
Regarding global functioning, findings revealed a significant main effect for aggression as well as a significant Aggression×Time interaction. That is, global functioning trajectories differed for high- versus low-aggression youth with PBD in response to treatment. displays mean global functioning (CAFAS) scores across treatment for the low- and high-aggression groups. As the figure reveals, all youth improve in terms of global functioning across treatment. However, in line with expectations, high-aggression youth experienced worse global functioning by end treatment versus low-aggression youth. Specifically, low-aggression youth experienced functioning within the normal range (M=11.00, SD=27.70), whereas high-aggression youth continued to experience clinically significant levels of impairment (M=25.33, SD=43.73). Again, findings held across medication type, as evidenced by the nonsignificant Aggression×Time×Medication. Thus, despite similar symptom response trajectories, high-aggression youth experienced attenuated improvement in global functioning as compared with their low aggression counterparts.
Mean global functioning (CAFAS) scores over time as a function of baseline aggression level (high, low). *Differences at each time point p<0.05. CAFAS=Child and Adolescent Functioning Assessment Scale.
Post hoc analyses
Given the gender differences in aggression, post hoc analyses included gender as a control in all MRMs for aggression as well as DBD co-morbidity. Results revealed similar effects to those obtained in the original models, such that the inclusion of gender did not alter the significance, direction, or magnitude of findings in any model.