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QUEST -
Childhood
AUTHOR Children’s self reported psychotic symptoms and adult schizophreniform disorderChairman’s Rounds, ? Citation: Poulton R, Caspi A, Moffitt TE, et al. Children’s self reported psychotic symptoms and adult schizophreniform disorder: A 15-year longitudinal study. Arch Gen Psychiatry 2000; 57: 1053-1058. Clinical question: Are there childhood risk factors for the development of adult schizophrenia? Study Design Type: Prospective cohort Methods: Patient population: A birth cohort born between April 1, 1972 and March 31, 1973 in Dunedin, New Zealand. 91% (1037) of births participated at age 3. Data used from age 11 and age 26 assessments. 789 births had psychiatric interviews at age 11. 972 had psychiatric interviews at age 26. 761 were psychiatrically assessed at both ages. Those included vs. omitted (assessed at age 26 and not age 11) did not differ significantly in psychiatric diagnosis. Study members assessed via DISC-C for DSM-III at age 11. 5 questions from schizophrenia section scored from 0-2. Children placed into 3 groups (no symptoms, weak symptoms, and strong symptoms). Study members assessed via DIS at age 26. Outcomes: Schizophreniform disorder. Eliminated symptoms with plausible explanations and related to alcohol or drug use or a major depressive episode. For diagnosis, study members must have 1 hallucination symptoms and 2 other symptoms reported as “yes, definitely” from criterion A of DSM. For diagnosis, study members must also have evidence of impairment in at least one area of social or occupational functioning (long term unemployment, poor money management skills, not in a relationship, paranoia, social isolation, poor personal grooming.) These symptoms must occur for at least one month. Several of these symptoms were determined by informants and observers as well as self-report. Analysis: Evaluated relationship with Mantel-Haenszel x2 test and logistic regression equations. Equations contained dummy variables representing both strong and weak symptom groups. Control group was children at age 11 with no symptoms. Results reported with ORs and 95% CIs. Validity Criteria: Patient sample was clearly defined. The 3 age 11 risk groups did not differ by parental SES or on WIS for Children-Revised Full Scale IQ test. Prevalence of mental disorders in Dunedin sample matched prevalence in US National Comorbidity Survey. All patients were accounted for and 95% of patients alive at age 26 were assessed. Outcome criteria were objective and unbiased and explained in a detailed and transparent manner. Sex, social class origins, and age-11 IQ scores were controlled for in the analysis of the cohort. Main Results: Weak symptom group was more likely to meet criteria for adult schizophreniform disorder (OR, 5.1; 95% CI, 1.7-18.3). Strong symptom group was even more likely to meet criteria for diagnosis (OR, 16.4; 95% CI, 3.9-67.8). Odds ratios were unchanged after controlling for sex, social class origins, and age-11 IQ scores. See Table 1. Strong symptom group members were not more likely to have a diagnosis of mania or depressive disorder. Both weak and strong symptom groups were more likely than no symptom children to develop an anxiety disorder, although less likely than for schizophreniform disorder. See Table 2. No children in the cohort had a diagnosis of childhood schizophrenia. One half of strong symptom group had no psychiatric diagnosis at age 11 and those without psychiatric diagnosis were just as likely to report delusions or hallucinations at age 26. Conclusions: This prospective cohort study demonstrates an association between childhood psychotic symptoms and adult schizophreniform disorder. The strengths of the study included prospective cohort design with all patients accounted for and transparent reporting of methods and results. Weaknesses included those inherent to the study design. Other weaknesses are the sample has not yet passed through the entire risk period for psychosis, not all interviews at age 26 were conducted by a psychiatrist, psychotic symptoms were also associated with anxiety disorders, and findings of this study are based on small groups.
AUTHOR SSRIs and routine specialist care with and without cognitive behavioral therapy in adolescents Chairman’s Rounds, August 13, 2007Goodyer I, et al. Selective serotonin reuptake inhibitors (SSRIs and routine specialist care with and without cognitive behavioral therapy in adolescents with major depression: randomized controlled trial. BMJ, 2007;335:142 Is the combination of SSRI and CBT superior to SSRI alone in improving the general functioning of adolescents with moderate to severe major depression? Depression in adolescence is a serious disorder that is both prevalent and carries relatively high risk for suicide and the development of other psychiatric disorders later in life. Results from the treatment of adolescent depression study (TADS) indicated that fluoxetine in conjunction with CBT was superior to fluoxetine alone in treating adolescent depression and possibly preventing suicide. Subsequent studies have failed to reproduce these results raising questions about the study’s validity. Therapy Validity Criteria: Follow up was complete and all patients who entered the trial were accounted for at its completion. Patients were randomized and the randomization was concealed from the evaluators (although not the physicians). The groups were similar and all participants were analyzed within the groups they were initially assigned. The study was not blinded to patients or physicians although assessors were not aware of group allocation. With the exception of CBT participation, groups were treated equally. Randomized Controlled Trial criteria for appropriate design: The trial was funded by NS Health Technology Assessment, University hospitals and a non-profit mental health trust. Although physicians and participants of the trial were aware of the groups they had been assigned to, evaluators remained blinded. Patients were followed up at 12 weeks and 28 weeks. They were chosen from six specialist outpatient psychiatry clinics and referred to 2 major University clinics in England. In all, 510 patients between the ages of 11 and 17 who scored 7 or higher on the Health of the Nation outcome scales were recruited. (Validated scale that indicates moderate to severe depression). Exclusion criteria included schizophrenia, bipolar disorder, pregnancy, need for immediate admission and previous SSRI+CBT with no effect. Suicidal ideation was not an exclusion criterion. All told, 103 patients were randomized to SSRI alone and 105 were randomized to SSRI +CBT. The Health of the Nation outcome scale was the primary outcome measure. Secondary outcomes were the participant rated mood and feelings questionnaire, the observer rated revised children’s depression rating scale, the children’s global assessment scale and the clinical global impression improvement scale. 191/211 participants who entered the study remained for the duration. Main results: Mean values for the two treatments were similar at corresponding assessments. For the primary outcome measure (Health of the Nation) the treatment effect measured across follow up points was 0.001 (-1.52 to 1.52, P=0.99). There was also no evidence of an interaction between baseline severity and treatment for any outcome measure. At 28 weeks, 57/94 (61%) in the SSRI group and 52/98 (53%) of the SSRI+CBT were much or very much improved. 62% of patients in the SSRI+CBT group reported adverse events while only 59% of the SSRI group reported side effects. Conclusions: This study indicates that in adolescents with moderate to severe major depression, treatment with an SSRI combined with CBT does not offer significant benefit over treatment with SSRI alone. This conclusion stands in contrast to the conclusion of TADS, which led to the recommendation that children be started on an SSRI only if they also initiate CBT. While the study attempted to replicate “real world” clinical settings, the degree of follow up SSRI only participants received was more intense than that offered in most clinical settings. The similar response rates between the two groups could underscore the importance of close follow up in the treatment of depression. This study can not be used as evidence to support the efficacy of SSRI efficacy as no placebo was utilized for control.
AUTHOR
|
|
Age 17: |
Enrichment
group |
Control
Group |
Effect
Size |
|
Schizotypal
questionnaire |
3.13 |
3.6 |
0.34
(0.02-0.53) |
|
Psychotic
behavior |
0.98 |
1.44 |
0.25
(0.01-0.49) |
|
Conduct
disorder |
5.77 |
8.01 |
0.3
(0.06-0.54) |
|
Age 23: |
Enrichment
group |
Control
Group |
Effect
Size |
RRR |
ARR |
NNT |
|
Schizotypal
questionnaire |
23.68 |
24.01 |
0.02
(-0.28-0.23) |
|
|
|
|
Self-reported
criminal acts |
23.6% |
36.1% |
0.26 |
0.35
(0.05-0.55) |
0.125
(0.0037-0.24) |
8
(4-270) |
|
Court
Record criminal acts |
3.6% |
9.9% |
0.22 |
0.64
(0.15-0.84) |
0.063
(-0.004-0.13) |
16
(8-infinity) |
|
|
Malnourished
from Enrichment Group |
Malnourished
from Control Group |
Effect
size |
|
Cognitive
Disorganization |
~2.6 |
~4.2 |
0.71 |
|
Conduct
Disorder |
~4.4 |
~9.5 |
0.63 |
|
Motor
Excess |
~2.3 |
~4 |
0.61 |
|
Total
Schizotypy |
~18 |
~24 |
0.42 |
|
Interpersonal
Deficits |
~8 |
~12 |
0.56 |
Adverse Effects:
none from treatment
Comments
Strengths and Weaknesses of Study (internal and
external validity): Weaknesses: not intention to treat
(although on schizotypal measures, both groups were missing about the
same percentage of participants, so should even out). On behavioral
studies, the study group (enrichment group) was missing data on a much
larger percentage of patients than the control group, which would bias
it towards a more favorable outcome possibly.
Inability to tell which intervention (exercise, nutrition, or
education) accounted for later beneficial effects, but seems those that
were malnourished at the beginning benefited significantly. Unclear if
raters of questionnaires, etc were blinded to pt’s status in the
study. Only measurement of pt’s schizotypal status was by self-report
questionnaire. Able to extrapolate results from a developing country to
US? Strengths: relatively long follow-up, relatively good numbers
of pts, relatively well matched cohorts. Good they studied nutritional
status.
Study in context of other
available literature and/or current standard-of-care:
widely accepted that nutrition affects brain function and is considered
important, also widely accepted that the most enriched envt
(educational, physical exercise) for children possible yields the best
results
How will this study affect your management of the
putative patient? Might
ask about development status more often
Next
steps for further study of this problem:
study brain imaging, blood tests to see what differences in malnourished
children make them more likely to develop psychopathology. Studying
children at different age ranges to determine the most critical age when
nutrition may be most important in affecting future psychopathology.
Continue to follow for development of schizophrenia. Repeat tests with
longer enrichment period, or with later booster enrichment periods, and
see if changes in effect sizes occur.
Bottom Line: Early environmental enrichment is
associated with small to moderate effect on lowering levels of
antisocial behavior and schizotypal personality in adulthood, and
benefits are greatest for children with poor nutrition.
Chairman's Rounds– 3/6/06
Efficacy of cognitive behavior therapy
as a treatment for anxiety disorders of childhood and adolescence
Clinical
Question: What is the efficacy of cognitive behavior therapy
as a treatment for
anxiety disorders of childhood and adolescence?
Reference: Cartwright-Hatton et al. Systematic Review of the Efficacy of Cognitive Behaviour Therapies for Childhood and Adolescent Anxiety Disorders. British Journal of Clinical Psychology 2004; 43: pp. 421-236.
Background: Anxiety during childhood and adolescence is often unremitting into adulthood, and is associated with other serious conditions, such as depression, and substance misuse. In light of these concerns, recent years have seen an increase in research into the treatment of anxiety disorders in children and adolescents. The published studies, though all reporting positive results for CBT, have varied in reported effects, and their size and complexity.
Objective: To review the efficacy of CBT as a treatment for anxiety disorders of childhood and adolescence, and to examine the methods used in previous studies.
Methods:
Study sources - Electronic databases including Cochrane Controlled Trials Register, Current Controlled Trials, Medline, Embase, Psychinfo, Cinahl, NHS Economic Evaluation Database, National Technical Information Service, ISI Web of Science. Reference lists of recent trials and reviews were examined. Select Journals from 1/1990 to 8/2003 were hand searched (specific journal titles on p423).
Types of studies included - RCT
Inclusion criteria - <19y/o, child and adolescent anxiety disorder, no treatment control group, utilization of formal diagnosis as outcome variable, RCT.
Exclusion criteria - Trials exclusively treating OCD, PTSD, simple phobia; trials not specifically treating anxiety disorders unless it was clear that the target d/o of all participants were anxiety-based; trials that treated both diagnosed and undiagnosed (eg subclinical) cases of anxiety; trials relying on self-report measures as outcomes.
Patient population - 6-18 year old children and adolescents with anxiety disorders.
Description of therapy - CBT
Studies screened vs. accepted – Search identified 22 RCT in which CBT had been employed to treat young people with anxiety disorders, and of these, 12 were excluded. 4 were excluded because of there not being a formal diagnosis of an anxiety d/o. 6 were excluded because of there not being an appropriate inactive control group. Of the 10 trials included, 4 were conducted by one research group, and 3 by another research group (“All data ‘appeared’ to be derived from separate samples (final study list on Appendix A).”
Data analysis – For each study, the OR of remission after treatment was estimated. The pooled OR and CI were calculated using the log odds procedure. ITT was used. Where studies included more than one type of CBT (eg. Group and individual), these were pooled to give an overall effect for CBT. A test for heterogeneity was carried out, a random effect estimate of the pooled OR was presented, the relationship between study size and effect size was also examined using weight least square regression.
Outcomes – The main outcome assessment was the number of cases who were diagnosis-free at the post treatment assessment.
Validity:
Focused clinical question? – Yes.
Inclusion criteria appropriate? – No.
Relevant studies omitted? – No. For example, this review didn’t attempt to evaluate the effectiveness of CBT in comparison to other available treatments.
Studies appraised for validity? –Yes. Diagnosis had to be formerly met in all included RCT. The search for relevant studies is detailed. Each study was graded to a standard. Each trial was rated independently (inter-rater reliability r=0.81). When raters had discrepancies, a final score was assigned by consensus.
Assessments of studies reproducible? – Yes, reproducible using same grading system.
Homogeneity among study results? – Test of heterogeneity was carried out , and while p=0.059 shows homogeneity, there was some heterogeneity in the studies.
Results:
1) Table 1:
--5 of 10 randomized cases had non-significant findings (odds ratios crossing 1).
--3 of 5 the remaining randomized cases with significant findings (Flannery’s, Kendall 1994, Spence 2000) had very large confidence intervals, and 1 of these (Flannery’s) nearly crosses 1.
--This leaves 2 RCTs with significant findings and tighter confidence intervals. Hayward et al’s nearly crosses 1 [OR 6.31, 95% CI 1.1-35]. The Barrett et al. study (1996) reports; the odds of recovery (diagnosis-remission) in children with anxiety randomized to receive CBT was 4.19 (95% CI 1.6-11.2) the odds of recovery in children with anxiety randomized to the waiting list control.
--Pooled OR for the 10 RCT was 3.27, 95% CI=1.9-5.6.
--Children randomized to receive CBT had a 225/398 = 56.5% chance of remission of their anxiety. Children who were randomized to control groups had a 73/210 = 34.8% chance of remission.
2) NNT reported as 4 (inflated). Using our ARR (ARR=0.565-0.348=0.217) and taking 1/ARR, 5 children with anxiety must receive CBT to prevent one additional unremitted anxiety. In other words, 5 children with anxiety disorders would need to be treated with CBT in order for one additional case to remit.
3) Figure 1: Test of heterogeneity showed x2(9) = 16.4, p=0.059. There was evidence of reduced effect size for larger studies (Figure illustrates the OR of recovery in relation to study size).
Strengths:
The article re-evaluated the hypotheses and methods used in previous works. Quantitative syntheses allowed for NNT to be estimated.
Weaknesses:
n Most of the trials were efficacy trials and not effectiveness trials.
n There were methodological wknesses in the trials studied regarding randomization methods and whether ITT analysis was used.
n Most included studies were not well-powered studies.
n Although this is a systematic review about anxiety, core patients are missing. They exclude critical anxiety spectrum diagnosis like PTSD, OCD, phobia so that there’s lack of generalizability.
n The paper excluded studies with active controls so non-specific variables could account for why CBT seemed to do better.
n Remission is not clearly defined (“diagnosis-free”) so we don’t have a clear end point in mind, and the paper also doesn’t tell us what diagnostic criteria they used to consider a diagnosis an “Official anxiety d/o.”
n There was non-rigorous vocabulary/lack of systematic use of language in this paper. For instance, we don’t know whether followed up cases were ‘completer analysis’, and we are left to assume randomized cases were conservative estimates LOCF.
n There was lack of rigor in their methodology (could have calculated an RR but used OR, overestimated the NNT).
n Although a number of trials reported f/u outcome data, this was rarely compared to a no treatment control group, so we know little about the long-term effectiveness of CBT.
Clinical Bottom Line: There is little to no evidence for specific benefit for CBT in childhood anxiety. The positive outcome may be due to the general effect of therapy, as there were no active controls. We are uncertain whether CBT is effective in children in the long term/whether it is as effective as other treatments.
Author:
Georgette De Jesus
Chairman's Rounds March 13, 2006
Prevalence Study:
Prevalence of Atypical Antipsychotic Prescription Claims in Youth
with Commercial Insurance
Bottom Line:
This study looks at the 1-year prevalence of atypical antipsychotic use
(based on prescription claims database) by age and sex among children in
US with private insurance. Twenty percent of all prescriptions for
atypicals (when you take all the age groups) were for pts 19 y/o or
younger. Prescription claims for atypicals were more than twice as high
for males. More than 25% of male pts with at least one claim for
atypicals were <9y/o.
Background:
-Data supporting the safety and efficacy of atypicals in children and
adolescents are limited.
-These meds are not FDA approved for the pediatric population
-There is evidence suggesting side effects may be greater in the
pediatric population
-These medications are often used off-label to treat behavioral
conditions, rather than actual psychosis.
-There is evidence that atypical antipsychotic use in the pediatric
population is on the rise, and more than doubled from 1996 to 2001.
Reference:
Curtis LH et al. Prevalence of Atypical Antipsychotic Durg Use Among
Commercially Insured Youths in the United States. Arch Pediatr
Adolesc Med. 2005; 159: 362-366.
Methods:
Design- Period Prevalence Study
Setting- US
Patient Population:
-Data on prescription medication claims were collected from the Advance PCS database (largest pharmaceutical benefit manager in the US at the time of the study) for the period of Jan-Dec 2001
-Pt's with at least one prescription drug claim were included.
Exclusions: Adults and pts whose carrier used a single identifier for multiple family members
-Data set (population)- 2 data sets, one including all ages (does not specify how large) and another with 6,213,824 patients 19 years or younger with prescription claim data.
Analysis:
-Claims for clozapine, olanzapine, quetiapine, risperidone and ziprasidone
-Period prevalence for each atypical antipsychotic was calculated individually
-Stratified by sex and age
-x² or Fisher exact tests for differences in proportion/prevalence rates
Follow-up: N/A
Validity: Was the patient sample clearly defined? Yes. Comparison groups delineated? Yes. Were all patients accounted for and analyzed? Yes. Is the population representative of our population? Yes and no- it is representative of the privately insured, but not of the uninsured or Medicaid pts..
Results For pt characteristics, see Table 1. Of all age groups (incl adults), 81,091 pts had at least one claim for an atypical- of these 20.5% were aged 19 or younger. Prevalence of atypical use was more than twice as high for males, and males tended to be younger. Among children 9 y/o and younger, the annual prevalence of atypical use was about 3.5 times higher in boys than girls. More than a fourth of male pts with at least one claim for atypicals were age 9 or younger. Prevalence peaked in males aged 10-14 and in females aged 15-19. Risperidone was the most commonly used in both females and males. Overall 0.3% of youths in the commercially insured population received atypicals (compare this to another study that showed 1.6% of Texas Medicaid enrollees aged 19 and younger received atypicals).
Comments: Strenghts: Large database, impressively large population. Stratified by age and gender. Weaknesses: AdvancePCS data do not include prescriptions filled in inpatient or institutionalized settings. Dataset does not include patients without private insurance. Out of plan drug use was not captured. No guarantee pts were taking meds. Pts with a lower socioeconomic level were not represented. Diagnosis unknown.
Author:
Chris Spongberg
Chairman's Rounds March 26, 2006
Antidepressant Medication in Children
Clinical Question: How has the use of antidepressant medication in children <18 yo during 1997-2002 changed, if at all. And, what may be driving some of these changes.
Reference: National Estimates of Antidepressant Medication Use Among US Children, 1997-2002. Journal of the American Academy of Child and Adolescent Psychiatry. 45:3 March 2006 p 271-279
Background: A threefold increase in the use of antidepressants has been reported among children <18 between 1987 and 1996, but only a number of these antidepressants have FDA approval for pediatric use. Often, these medications are often used “off label” to treat depressive d/o’s and anxiety d/o’s. There is also some evidence that the increased use is consistent with a proportional increase in diagnosis, although there is some variation between gender, race and ethnicity.
Objective: Analyze the data from 1997 to 2002 in the Medical Expenditure Panel Survey (MEPS), which is a yearly survey of a nationally representative sample of civilian, non-institutionalized US households, to evaluate for changes in the use of antidepressants in children less than 18 years old.
Methods:
Design: – Period prevalence study.
Setting: United States
Population: All children under the age of 19 contained in the MEPS database which is a nationally representative household survey of health care use and costs conducted by the Agency for Healthcare Research and Quality in conjunction with the National Center for Health Statistics. See Table 1 for distribution of population characteristics. Antidepressant use was defined by a Rx for TCA’s, SSRI’s, and MAO’s See Table 4 for trends within the class of antidepressants
Analysis: National estimates for use of antidepressants in <19 year olds
- Table 2 shows analysis for each calendar year 1997 thru 2002
- Table 3 shows analysis by subgroups: age, sex, race/ethnicity, family income relative to the poverty line, census region, metropolitan statistical area vs. non-metropolitan statistical areas, health insurance coverage, and impairment as measured by the Columbia Impairment Scale
- Table 4 shows analysis of SSRI vs TCA use by calendar year and age group 0-5, 6-12, and 13-18
- Employed MEPS sampling weights which adjust for complex design and non response, as well as standard Z scores for complex design and correlation across individuals, utilizing STATA 8.2 for these statistical analysis
Follow-up: N/A
Validity
The patient sample was clearly defined. The comparison groups/subgroups were also delineated. In the context of a survey response rate in the 60’s, all patients were accounted for and analyzed The population is representative of our population as it included private, public, and uninsured patients, and captured office, hospital outpt/inpt, and emergency room visits
Results: Estimated prevalence of antidepressant use:
- The percentage of all children receiving an antidep increased from 1.3% in 1997 (95% CI 0.9-1.6) to 1.8% in 2002(95% CI 1.5-2.1), which represents approx. 1.4 mill. users in 2002.
- The increase in use was primarily accounted for by adolescents (13-18 .yo) particularly from 1999 to 2000, while no change occurred in younger children.
- The highest use was also in the 13-18 age group, 3.9% in 2002.
- Initially, males had a higher use but by 2002 the use rate was similar for males and females.
- Use increased for both white and black children (1.7% to 2.4% and 0.3% to 0.9%) respectively, but not in Hispanic children.
- While use increased more markedly among children from lower income families, by 2002 there was no statistically significant differences in antidepressant use among privately, publicly or uninsured children.
- Use of SSRI’s increased from 0.8% (95% CI 0.6%-1.1%) in 1997 to 1.6% (95% CI 1.3%-1.9% p <0.001) in 2002, while there is no statistically significant change in TCA, there is a decrease in the 6-12 age group.
Comments:
Strengths – Large sample size, evaluated as group and subgroups, cross referenced parental self report of prescriptions with pharmacy database although unclear on how discrepancies were managed
Weaknesses –The database used does not address the issue of whether the antidep are appropriately prescribed, relied in part on the parents self recall and willingness to provide info.
CLINICAL BOTOM LINE:
The analysis indicated that the use of SSRI’s in adolescents doubled nationwide during 1997 to 2000, but remained stable from 2000 thru 2002. The authors suggest this may be attributable to the publication of clinical trials in the late 90’s showing the efficacy of SSRI’s in the treatment of childhood depression. Additionally, no increase was detected among children younger than 13 during this period. Future study could involve analysis of antidep use from 2002-2005.
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Clinical Question: How has the use of antidepressant medication in children <18 yo during 1997-2002 changed, if at all. And, what may be driving some of these changes.
Reference: National Estimates of Antidepressant Medication Use Among US Children, 1997-2002. Journal of the American Academy of Child and Adolescent Psychiatry. 45:3 March 2006 p 271-279
Background: A threefold increase in the use of antidepressants has been reported among children <18 between 1987 and 1996, but only a number of these antidepressants have FDA approval for pediatric use. Often, these medications are often used “off label” to treat depressive d/o’s and anxiety d/o’s. There is also some evidence that the increased use is consistent with a proportional increase in diagnosis, although there is some variation between gender, race and ethnicity.
Objective: Analyze the data from 1997 to 2002 in the Medical Expenditure Panel Survey (MEPS), which is a yearly survey of a nationally representative sample of civilian, non-institutionalized US households, to evaluate for changes in the use of antidepressants in children less than 18 years old.
Methods:
Design: – Period prevalence study.
Setting: United States
Population: All children under the age of 19 contained in the MEPS database which is a nationally representative household survey of health care use and costs conducted by the Agency for Healthcare Research and Quality in conjunction with the National Center for Health Statistics. See Table 1 for distribution of population characteristics. Antidepressant use was defined by a Rx for TCA’s, SSRI’s, and MAO’s See Table 4 for trends within the class of antidepressants
Analysis: National estimates for use of antidepressants in <19 year olds
- Table 2 shows analysis for each calendar year 1997 thru 2002
- Table 3 shows analysis by subgroups: age, sex, race/ethnicity, family income relative to the poverty line, census region, metropolitan statistical area vs. non-metropolitan statistical areas, health insurance coverage, and impairment as measured by the Columbia Impairment Scale
- Table 4 shows analysis of SSRI vs TCA use by calendar year and age group 0-5, 6-12, and 13-18
- Employed MEPS sampling weights which adjust for complex design and non response, as well as standard Z scores for complex design and correlation across individuals, utilizing STATA 8.2 for these statistical analysis
Follow-up: N/A
Validity
The patient sample was clearly defined. The comparison groups/subgroups were also delineated. In the context of a survey response rate in the 60’s, all patients were accounted for and analyzed The population is representative of our population as it included private, public, and uninsured patients, and captured office, hospital outpt/inpt, and emergency room visits
Results: Estimated prevalence of antidepressant use:
- The percentage of all children receiving an antidep increased from 1.3% in 1997 (95% CI 0.9-1.6) to 1.8% in 2002(95% CI 1.5-2.1), which represents approx. 1.4 mill. users in 2002.
- The increase in use was primarily accounted for by adolescents (13-18 .yo) particularly from 1999 to 2000, while no change occurred in younger children.
- The highest use was also in the 13-18 age group, 3.9% in 2002.
- Initially, males had a higher use but by 2002 the use rate was similar for males and females.
- Use increased for both white and black children (1.7% to 2.4% and 0.3% to 0.9%) respectively, but not in Hispanic children.
- While use increased more markedly among children from lower income families, by 2002 there was no statistically significant differences in antidepressant use among privately, publicly or uninsured children.
- Use of SSRI’s increased from 0.8% (95% CI 0.6%-1.1%) in 1997 to 1.6% (95% CI 1.3%-1.9% p <0.001) in 2002, while there is no statistically significant change in TCA, there is a decrease in the 6-12 age group.
Comments:
Strengths – Large sample size, evaluated as group and subgroups, cross referenced parental self report of prescriptions with pharmacy database although unclear on how discrepancies were managed
Weaknesses –The database used does not address the issue of whether the antidep are appropriately prescribed, relied in part on the parents self recall and willingness to provide info.
CLINICAL BOTOM LINE:
The analysis indicated that the use of SSRI’s in adolescents doubled nationwide during 1997 to 2000, but remained stable from 2000 thru 2002. The authors suggest this may be attributable to the publication of clinical trials in the late 90’s showing the efficacy of SSRI’s in the treatment of childhood depression. Additionally, no increase was detected among children younger than 13 during this period. Future study could involve analysis of antidep use from 2002-2005.
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Author:
Stephen T. Vas
Risperidone in Childen with Autism Spectrum Disorders
Chairman's Rounds March 27, 2006
Clinical Question: Is long-term use of risperidone for behavioral control in children with autism spectrum disorders superior to short term use in terms of efficacy and safety?
Reference: Long-Term Effects of Risperidone in Children With Autism Spectrum Disorders: A Placebo Discontinuation Study. Troost PW et al. Journal of American Academic Child and Adolescent Psychiatry. 44:11; 1137-1144, November 2005.
Background: Atypical antipsychotic medications have been shown to be effective short-term agents for behavioral management of hyperactivity, self-injurious behavior, aggression, stereotypies, and extreme change intolerance in children with autism spectrum disorders. There have been little data regarding longer-term effects of these pharmaceutical agents.
Objective: To compare relapse rates in behavioral symptoms (irritability, aggression, agitation, sterotypy, social withdrawal) in two groups of children with autistic spectrum disorders who have either been discontinued from risperidone treatment or maintained on it.
Methods:
Design/Setting - Blinded, randomized, multisite, site-stratified, controlled trial—discontinuation/placebo vs. risperidone maintenance 8 weeks after 24-weeek open-label risperidone treatment. Participants recruited from university child and adolescent psychiatry centers in the Netherlands.
Inclusion criteria - Age 5-17yo, meeting DSM-IV-TR criteria for a pervasive developmental disorder (autistic disorder, Asperger disorder, or pervasive developmental disorder NOS); diagnoses made by Autism Diagnostic Interview-Revised (ADI-R) combined with clinical judgement; patients must demonstrate clinically significant behavioral problems (tantrums, aggression, self-injurious behavior, or combination thereof) defined as rating of moderate or higher on Clinical Global Impressions of Severity Scale (CGI-S) as determined by clinician and concomitant score of 18 or higher on Irritability Scale of the Aberrant Behavior Checklist (ABC) (rated by parent and confirmed by child psychiatrist); must respond to short-term risperidone tx; wt ≥ 15kg; “mental age” ≥ 18months; use of stimulants allowed for comorbid ADHD as long as no adjustments of dosage during study; anticonvulsants allowed for treatment of seizure d/o if dose stable ≥ 4weeks and seizure free for ≥6months. Washout of ineffective alternate pharmacologic treatment over 7-28 days prior to study. Consent of parent and of patient if patient over 12 years old.
Exclusion criteria – Not meeting inclusion criteria. Use of effective alternate pharmacologic treatment.
Population- 77 pts screened®41 did not meet inclusion criteria or unwilling to give final consent®36 pts all treated with risperidone®10 did not respond by 8-weeks®26 patients identified as short-term responders and entered into complete study®2 subjects discontinued over next four months due to unacceptable weight®pts randomized into 2 groups of 12 (d/c vs. maintenance). See Table 1.
Treatment protocol – Pt’s screened at baseline used Vineland Adaptive Behavioral Scales (semistructured interview) to assess skills in communication, daily living, socialization, and motor domains. Parents/caregivers educated about behavioral measures to prevent wt gain associated with atypical antipsychotic meds. Pt’s initially dosed by weight. Dose adjustments permitted according to clinical assessment of improvement vs. adverse events to maximum dose of 4mg for children < 45kg and 6mg for children weighing > 45kg. Pts treated for 8 weeks and assessed for short-term response (as defined as ≥ 25% ABC irritability score reduction and rating of “much improved” or “very much improved” on CGI-S); non-responders excluded from study. Patients randomized to continuation vs. discontinuation group. Subjects seen every 4 weeks for assessments of efficacy, safety, and possible dose adjustments plus weekly during “discontinuation phase). Open-label phase for 24-weeks. Discontinuation phase: either maintained for 8 weeks on risperidone or dose reduced by 25% each week for three weeks followed by placebo for 5 weeks.
Outcomes - PRIMARY-differences in relapse rates between treatment groups (relapse defined as occurrence of CGI-SC scores of “much worse” or “very much worse” for ≥ 2 consecutive weeks when compared to baseline of discontinuation phase and minimum increase of 25% increase in Irritability score on most recent ABC (time –to relapse compared using Kaplan-Meier procedure). SECONDARY OUTCOMES between group baseline to endpoint changes in all ABC scores) using Mann-Whentey U test, 2-sided. Prestudy baseline to 24 open-label endpoint changes) all subscales of ABC, vital signs, laboratory test results, and weight) examined w/ 2-sided Wilcoxon signed rank test (Z-scores using Dutch population normative growth/weight changes). Safety monitored by routine lab tests, EKG, PE before treatment and at wks 8, 24, and study end. Wt and vitals q4weeks in open-label phase and weekly at d/c phase. Each visit investigators inquired about intercurrent illnesses, health problems, concomitant meds, and administered 32-item questionnaire about energy level, muscle stiffness, motor restlessness, bowel/bladder habits, sleep, and appetite. Simpson-Angus Scale and AIMS for neuroleptic-related SE. AE rated by severity, duration, management and outcome.
Validity: Patients randomized? à YES randomization sequence generated by outside vendor and stratified by investigation site// Randomization blinded? à pts, caregivers and evaluators all unaware of assignment of placebo vs. tx// Patients analyzed in groups to which they were randomized? à YES Pt’s evaluated within group originally assigned regardless of tx YES ITT analysis for all pts enrolled using LOCF// Groups similar w/ respect to known prognostic factors? à YES See Table 1. // Groups treated equally except for intervention? à YES // Follow-up complete? à YES // All patients accounted for at end of study? à YES. 10 short-term nonresponders described as similar to remainder in terms of baseline characteristics including age, sex, race, mental development, educational placement, DSM-IV dx, ABC subscores, CGI, previous meds and concomitant meds (raw data not shown).
Results: PRIMARY OUTCOME: Figure 2. 8 of 12 (67%) in placebo grp relapsed vs. 3/12 (25%) of risperidone grp (p=0.049, one-sided). Mean time to relapse in placebo 6±1 wks vs. 7±1 wks in risp grp. ARR was 0.42. NNH was 3—“For every 3 children with autistic spectrum disorders discontinued from risperidone treatment there was an incident of 1 child who demonstrated a relapse in behavioral problems.” There were no significant difference btwn groups in any of the ABC sub-scores except for irritability. All subscales improved significantly from baseline to end of open-label phase and all subscales except for irritability remained significantly improved from baseline to end of discontinuation phase. Effect sizes on irritability between two groups can be estimated at cohen’s d=0.8 (“large effect size”). Baseline-to-discontinuation effect sizes are as follows: for irritability cohen’s d=1.33 (“very large effect size”); for social withdrawal cohen’s d=1.13 (very large effect size); for stereotypy cohen’s d=0.42 (“medium effect size”); for hyperactivity cohen’s d=1.02 (“large effect”); for inappropriate speech cohen’s d=0.67 (“medium effect size”). Side Effects See Table 3. Significant increased appetite and weight gain (5.7±2.8kg in 24 wks; range 1.2-11.7kg; Z=4.46, p<0.0001, two-sided). All side effects “mild-to-moderate” range. No significant changes in AIMS and Simpson-Angus. Neuro se included tremor (once), muscle rigidity (twice), restlessness (twice). Authors do not compare two groups at end of discontinuation phase. No clinically meaningful changes in individual or mean lab tests/vitals/EKGs.
Strengths: Adequately powered blinded RCT. Not clearly sponsored by Janssen Cilag BV.
Limitations: a) Heterogeneous diagnoses within “autism spectrum disorder” (pdd NOS?) limits precision, especially given small sample sizes. b) Large average or above-average IQ may limit generalizability c) ethnically homogenous d) no information about concomitant psychotherapy, medical comorbitities, home-life structure, social-economic status e) no full placebo control f) no comparison of groups for side-effects g) Table 2 unclear regarding age of subjects.
Comments: a) Without placebo group, how do we know what is specific effect of atypical antipsychotic versus non-specific structured visits. b) For study purporting to study long-term effects of risperidone treatment this study 6 months is hardly long-term: what are brain developmental sequelae, hormonal/sexual development sequelae, neurologic and metabolic sequelae? Initial responses attenuated somewhat by 24 weeks. What is long-term benefit? How much will they attenuate further out? c) Side-effect comparison btwn groups is shockingly absent! Why? d) Significant weight gain in just 6-months. Risk of atypicals may be more justified in psychosis where agents presumably treating aspect of underlying pathology vs. behavioral mgmt in autism spectrum disorders, for children with communication deficits who thus have difficulty expressing any subjective benefit or harm. No significant difference btwn 2 groups except for irritability. Is this a justification for continued use even if atypicals started? Is this a type-II error or just earlier relapsing ssx compared to others? Does benefit otherwise persist? Again difficult to tell with just 8-week f/u. f) What of other measures such as school performance? Atypicals may cloud cognitive functioning (less of an issue with risperidone) So may anxiety, a significant side-effect. g) Anxiety may also aggravate behavioral problems. h) How do we generalize with from this small heterogeneous group? Authors say short-term non-responders same at baseline in terms of sex, age, race, mental development, educational placement, DSM-IV dx, ABC subscores, CGI, previous meds, concomitant meds. Don’t show data, but must assume that this is true. But with such a small heterogeneous sample of diagnoses, what does it mean that 28% did not respond in 8-wks?
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Clinical Bottom Line: Study shows short-term benefit persisting approximately 2 months after 4-month treatment of risperidone with exception of irritability. Does not show non-specific benefit or side-by-side comparison of SE between grps. 6-month study only. Would be extremely reluctant to start a child w/ autistic spectrum d/o on risperidone for behavioral treatment. If this behavior was severely disruptive, would consider short-term use only and look for alternate means to manage irritability. |
Author:
Seamus Bhatt-Mackin
Suicidality In Pediatric Patients
Chairman’s Rounds April 10th 2006
Clinical Question: Do SRI antidepressant drugs increase suicidality in pediatric patients?
Suicidality in Pediatric Patients Treated With Antidepressant Drugs Arch Gen Psychiatry 2006; 63:332-9
Background: Suicide is the third leading cause of death in the United States at ages 10 through 24 years. There are suggestions that SRI antidepressants increase suicidal risk; in addition, antidepressant drugs have not been demonstrated to reduce short-term suicidal risk.
Methods:
Types of studies – randomized placebo-controlled trials
Study sources -- 23 trials
conducted in 9 drug development programs (unpublished) and 1 trial in a
NIMH-sponsored multicenter trial (published)
Inclusion criteria – placebo-controlled trials submitted to the FDA and TADS (March, JAMA
2004)
Studies screened vs. accepted
- 4 trials had no suicide related events (SRE) in the drug or placebo
group (bupropion in ADHD, 2 trials of nefazodone in MDD, venlafaxine xr
in GAD). 17 of 24 included depression rating scales with an item
related to suicide (no description of which studies were excluded)
Description of therapy –
treatment with an antidepressant medication (citalopram, fluoxetine,
paroxetine, sertraline, venlafaxine, mirtazepine) for 4 to 16 weeks
compared to placebo.
Patient population – pediatric patients diagnosed with MDD, OCD, GAD, ADHD
Exposure window – adverse
events were included if they occurred within the double-blind acute
treatment period or within 1 day of the end of this period. (what about
drop-out from the original studies?)
Data collection/extraction –
Two types of data were evaluated and analyzed. For adverse event data,
the manufacturers of the 9 drugs searched their own internal databases
for suicide-related events (SRE) using text strings (suic, overdos,
attempt, cut, gas, hang, hung, jump, mutilate-, overdos-, self damage-,
self harm, self inflict, self-injur-, shoot, slash, suic-), performed by
personnel blinded to the treatment assignment. Narrative summaries were
then provided for each of the events. For suicide item score data,
rating scales on a subset of the studies (Children’s Depression Rating
Scale-Revised, Hamilton Depression Rating Scale, Montgomerty Asberg
Depression Rating Scale).
Outcomes– For the adverse event data (SRE)
narratives were categorized by an expert group at Columbia U. into 5
groups (i. suicide attempt, ii. preparatory actions toward immediate
suicidal behavior, iii. suicidal ideation, iv. self-injury with intent
unknown, v. injury events with not enough information)
Primary Outcome
“suicidal behavior or ideation” = i. + ii + iii
Secondary Outcome “possible suicidal behavior or ideation” =
i. + ii. + iii. + iv. + v
For the suicide item data from depression scales in 17 of 24 trials, an increase of 1 pt or more on item 3 of HAM-D, 2 pts on CDRS-R or MADRS; “worsening of suicidality” if patient had baseline score, “emergence of suicidality” if no baseline score
Classification of SREs – No completed suicides. 427 potential suicide-related adverse events. 260 events classified as other psychiatric or medical events not related to suicidality (167 remain); 11 classified as self-injury with nonsuicidal intent (156 remain); 47 occurred in 21 patients who had more than 1 event (130 unique patients); 21 events occurred outside exposure window (109 remain). Add 11 events from TADS (see below) for a total of 120 SREs.
Possible explanatory variables – age, sex, history of suicide attempt or ideation were examined by a stratified analysis. Attributes of primary trials were examined, including inclusion and exclusion criteria; no attribute consistently explained the observed differences in the risk estimates between trials within or between drug development programs.
Data analysis – risk ratio = relative risk; risk difference = absolute risk reduction (1/NNT)
Data were pooled to generate an overall estimate using both fixed-effects and random-effects approaches. The test for heterogeneity was not significant.
Validity:
Focused clinical question? – yes
Inclusion criteria appropriate? – yes
Relevant studies omitted? – unclear Studies appraised
for validity? – hopefully (=no)
Assessments of studies reproducible? – unclear
Homogeneity among study results? – unclear
Results:
Suicide-related events:
RR for primary outcome in MDD treated with SSRI 1.66 (95% CI, 1.02-2.68)
RR for primary outcome in all conditions (MDD, GAD, OCD) 1.95 (95% CI, 1.28-2.98)
Primary Outcome (n = 89 / 3841 patients; risk difference 0.01 (95% CI, 0.01-0.02)
Secondary Outcome (n = 120 / 3841 patients; risk difference 0.02 (95% CI 0.01-0.03)
TADS SRE data (drug, n = 9 / 109 patients; placebo, n = 2 / 112); risk difference 0.064 (95% CI, *smbm*)
Suicide Item
Scores:
Risk ratio for “worsening of suicidality” 0.92
(95% CI, 0.76-1.11)Risk ratio for “emergence of
suicidality” 0.93 (95% CI, 0.75-1.15)
Sensitivity analysis: comparison between a fixed-effects model and a random-effects model; comparison between the primary and secondary outcome; but not? Comparison between suicide-related events and suicide item scores?
Strengths – increased power with combination of data sets
Weaknesses- small sample size, short-term observation period, variability of diagnosis, broad range of “pediatric” age group, flexible dosing, studies not intended to address this question, different evaluators from each drug company construct a narrative and unmasking of their blinding during the construction of the narrative, the increase seen in adverse event data not also found in the suicide item score data, primary outcome measure for the meta-analysis was not a primary outcome measure for the studies, unpublished data with little opportunity to judge the quality of the original studies
Comments: parents and the rights of minors; morbidity of untreated psychiatric illness; published data and the emergence of trial registries; unwieldy politics surrounding this issue
“suicidal ideation, as ascertained incidentally in trials, is a convenient but probably unreliable, nonequivalent, and potentially misleading surrogate for suicidal behavior (attempts or suicides)”
“Typically, antidepressant trials involve rates of suicides and attempts that are not lower than in other clinical samples of depressed patients, despite initial screening and close clinical monitoring.”
– Baldessarini, commentary on this meta-analysis in accompanying commentary
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CLINICAL BOTTOM LINE Antidepressant drugs may increase “suicide-related events”, but they have not been shown to increase suicide attempts or suicide completions. (BLACK BOX WARNING: methods differ significantly between the drug-company data and TADS data, but they are simply combined at the end; “only the TADS showed a statistically significant excess of suicidality in the drug treated group) |
1. What is the direction of effect?
2. What is the size of effect (and the uncertainty surrounding that effect)?
3. Is the effect consistent across studies?
4. What is the strength of evidence for the effect?
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[In meta-analysis:] A model that calculates a pooled effect estimate using the assumption that all observed variation between studies is caused by the play of chance. Studies are assumed to be measuring the same overall effect. An alternative model is the random-effects model. |
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[In meta-analysis:] A statistical model in which both within-study sampling error (variance) and between-studies variation are included in the assessment of the uncertainty (confidence interval) of the results of a meta-analysis. See also fixed-effect model. When there is heterogeneity among the results of the included studies beyond chance, random-effects models will give wider confidence intervals than fixed-effect models. |
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An analysis used to determine how sensitive the results of a study or systematic review are to changes in how it was done. Sensitivity analyses are used to assess how robust the results are to uncertain decisions or assumptions about the data and the methods that were used. |
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1. Used in a general sense to describe the variation in, or diversity of, participants, interventions, and measurement of outcomes across a set of studies, or the variation in internal validity of those studies. 2. Used specifically, as statistical heterogeneity, to describe the degree of variation in the effect estimates from a set of studies. Also used to indicate the presence of variability among studies beyond the amount expected due solely to the play of chance. See also homogeneous, I2. |