1. Plans for Analysis of Patient Level Data for Pediatric Studies Psychopharmacologic Drugs Advisory Committee and Pediatric Subcommittee of the Anti-Infective Drugs Advisory Committee February 2, 2004 Tarek A. Hammad, MD, PhD, MSc, MS Medical Reviewer Division of Neuropharmacological Drug Products Center for Drug Evaluation and Research, FDA

2. Outline Objective Data –Drugs and Indications –Individual Patients Data –Challenges with Available Data Analysis Plan –Exploratory Analysis Univariate Analysis Crude Analysis –Estimate of Overall Effect –Sensitivity Analysis –Limitations on Interpretation of Data 2 2

3. Objective To evaluate the risk of suicidality associated with the use of antidepressants in pediatric patients using the results of the blinded re- classification of cases –We will address possible sources of imbalance in the data e.g. trial design, duration of exposure, patient population, and other potential confounders –Understand the sources of inconsistency between trials or between drugs, if any

4. Outline Objective Data –Drugs and Indications –Individual Patients Data –Challenges with Available Data Analysis Plan –Exploratory Analysis Univariate Analysis Crude Analysis –Estimate of Overall Effect –Sensitivity Analysis –Limitations on Interpretation of Data 4 4

5. Data Controlled trials conducted in pediatric patients in nine drug development programs Drugs - number of trials : –SSRIs group Fluoxetine (Prozac) - 4 Sertraline (Zoloft) - 3 Paroxetine (Paxil) - 6 Fluvoxamine (Luvox) - 1 Citalopram (Celexa) - 2 –Atypical antidepressants group Bupropion (Wellbutrin) - 2 Venlafaxine (Effexor) - 4 Nefazodone (Serzone) - 2 Mirtazapine (Remeron) - 1 5 5

6. Data, continued... Indications - number of trials –Major Depressive Disorder - 15 –Anxiety Disorders Obsessive Compulsive Disorder - 5 Generalized Anxiety Disorder - 2 Social anxiety Disorder/Social Phobia - 1 –Attention Deficit Hyperactivity Disorder - 2 6 6

7. 7 7 Individual patients data: –Developed a standard format for electronic datasets –Descriptive information about every trial

8. Demographics variables –Age, gender, race, and BMI –Location (North America vs. not) –Setting (inpatient vs. outpatient vs. both) Disease-related variables –Diagnosis –Baseline severity score –Duration of illness prior to treatment Drug-related variables –Drug name –Maximum modal dose –Duration of treatment –Erratic compliance (defined as: not taking drug as prescribed during RCT) 8 8 Requested Variables

9. Outcome-related variables –First suicide-related event (FSE) –Time to FSE –If FSE occurred after discontinuation Psychiatric history variables –Prior history of : oSuicide attempt oSuicide ideation oPsychiatric hospitalization oSubstance abuse oHostility or aggressive behavior oIrritability or agitation Treatment emergent adverse events –Agitation during RCT –Hostility during RCT 9 9 Requested Variables, continued...

10. Challenges with Available Data Quality-related component –Issues related to case ascertainment –Mechanism of data collection among different trials/sponsors (10% rule) Analysis-related component –Trial vs. patient as the unit of analysis –Limitations of pooling data 10

11. Trial vs. Patient as the Unit of Analysis Pooling of data from different trials treating them as one large trial fails to preserve the randomization effect and might introduce bias and confounding Maintaining the randomization guards against the foreseen (e.g. age and gender) and unforeseen (e.g. differences in medical practices or case ascertainment) imbalances between treatment groups The issue of trial similarity is not only pertinent to having the same protocol, but is also pertinent to the implementation of those protocols (implementation of criteria of inclusion and exclusion, patients care in reality…etc) Using trial as unit of analysis (meta-analysis) might result in loss of information 11

12. Limitations of Pooling Data Compatibility of designs and patient populations, duration of treatment, and dose levels Class effect assumption –Implied by pooling drugs –Differences in size of databases 12

13. Outline Objective Data –Drugs and Indications –Individual Patients Data –Challenges with Available Data Analysis Plan –Exploratory Analysis Univariate Analysis Crude Analysis –Estimate of Overall Effect –Sensitivity Analysis –Limitations on Interpretation of Data 13

14. Analysis Plan Statistical computing – SAS, Stata, and JMP Exploratory Analysis –Univariate Analysis Check data compliance & completeness Check for coding error Inspect the spread and shape of continuous variables and frequencies of binary variables –Crude Analysis Risks and rates by drug, indication, and trial Investigate complete separation and quasi- complete separation Investigate presence of interaction Examine potential confounders 14

15. IndicationDrugPlaceboActive ctrl Indication I, overall % Rate trial 1 % Rate trial 2 % Rate Indication II, overall % Rate trial 3 % Rate trial 4 % Rate Analysis Plan, continued... Sample analysis table 15

16. Analysis Plan, continued... Estimate of overall effect – Trial as the Unit of Analysis (optimal): Adjust for confounders on trial level Pool trials data for drug groups within indication groups Exclude trials with no suicidality in both arms Depending on the heterogeneity of the trials’ findings, the variability between trials would be considered in a “fixed” effects or a “random” effects model –Patient as the Unit of Analysis: Poisson regression will be used to model rates of suicidality adjusting for potential confounders Pool patients data for drug groups within indication groups Trials will be adjusted for as a random effect in the model 16

17. Analysis Plan, continued... Sensitivity Analysis –The analysis will be stratified by the level of uncertainty to examine the robustness of the findings

18. Limitations on Interpretation of Data Our goal is to evaluate the risk of suicidality associated with the use of antidepressants in pediatric patients Observed rates of suicidality might not reflect actual rates among patients in the general population Short-term exposure Informative censoring due to patterns of patients discontinuation  no info It remains to be seen if we have enough statistical power to detect differences in the risk of suicidality among various drugs

19. In closing Those are our ideas and some of them were informed by our experience analyzing the data on completed suicides in adults Your feedback on our approach will be appreciated