Signal Detection and Placebo Response in Schizophrenia: Parallels with Depression by Craig H

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EVIDENCE-BASED MEDICINE Key Words: Clinical trials, schizophrenia, placebo response, drug-placebo differences

Signal Detection and Placebo Response in Schizophrenia: Parallels with Depression By Craig H. Mallinckrodt, Lu Zhang, William R. Prucka, Brian A. Millen

ABSTRACT ~ Objective: Placebo response and the rate of failed clinical trials are increasing in schizophrenia, resembling previous experience with antidepressant clinical trials. In depression, the percent of patients randomized to placebo was shown to be strongly associated with drug-placebo differences (signal detection). We hypothesized that this factor would also be important in recent schizophrenia clinical trials. To test this hypothesis a database of acute schizophrenia placebo-controlled studies conducted between 1997 and 2008 was constructed. The database contained 27 studies, with 79 active treatment arms. As percentage of patients randomized to placebo increased, mean placebo improvement decreased (p ϭ 0.047) and mean drug-placebo differences tended to increase (p ϭ 0.166). The frequency of significant contrasts from studies with у25% randomized to placebo was 83.3%, compared with 58.3% in studies with Ͻ25% randomized to placebo. Caveats to these findings include limited data andReprint confounding of potentially influential factors. These limitations prevent definitive conclusions. However, results are consistent with previous findings in depression where having a higher percent of patients randomized to placebo increased drug-placebo differences. Psychopharmacology Bulletin. 2010;43(1):53–72.

INTRODUCTION For In diseases of the central nervous system (CNS), approximately 9% of the drugs that enter phase I testing survive to launch, which is lower than all other therapeutic areas except oncology.1 Approximately 50% of the failures occur due to not demonstrating efficacy in Phase II, which is a 15% increase compared with the previous decade.1 Meanwhile, the failure rate of CNS drugs in Phase III is aboutNot 50%.2 Together, these findings point to high rates of false negative and false positive efficacy results as a major obstacle in CNS drug development. Signal detection is the term often used to describe the ability to differentiate

Drs. Mallinckrodt, PhD, Zhang, MS, Prucka, PhD, Millen, PhD, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN. To whom correspondence should be addressed: Craig H. Mallinckrodt, PhD, Lilly Corporate Center, Eli Lilly and CO, Indianapolis, IN 46285. Phone: 317-277-2209; Fax: 317-651-9964; Email: [email protected]

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between an effective drug and placebo; that is, to find a treatment effect when one exists.3 Among the CNS diseases, perhaps the most research on understanding and improving signal detection has been in major depressive disorder (MDD). This work includes examinations of associations between trial design features, trial methods, and signal detection. Examples include study of blinded placebo lead-in periods,3–6 placebo response and its impact on signal detection,7–11 sensitivity of assessment scales and subscales,3,12–18 relationships of design features and analytic methods with outcome,3,19–23 along with general and novel design discussions.7,24–27 Comparatively less research regarding signal detection has been conducted in schizophrenia. However, recent trends in schizophrenia trials are similar to trends previously observed in MDD. For example, a recent report for schizophrenia noted that placebo response was increasing at an alarming rate, and signal detection was becoming more difficult,28 just as had been previously reported for MDD.10 Therefore, it is useful to consider if factors that influence placebo 54 response and signal detection in MDD also influence placebo response Mallinckrodt, Zhang, and signal detection in schizophrenia. If so, then perhaps some of the Prucka, et al. methods thought to improve signal detection in MDD can be applied to schizophrenia. The factor found to have the greatest influence on drug-placebo differences in MDD was the percentage of patients randomized to placebo.9 As the percent Reprintrandomized to placebo increased, drug-placebo differences increased. Therefore, the primary purpose of this investigation was to ascertain if in recent schizophrenia clinical trials the percentage of patients randomized to placebo was associated with the magnitude of drug-placebo differences. Secondary evaluations investigated associations of design features and patientFor characteristics with signal detection.

METHODS

Search Strategy Three electronic databases were searched in order to identify all placebo Notcontrolled acute schizophrenia clinical trials that began in 1997 or after: http://clinicaltrials.gov/, MEDLINE, and PubMed. In addition, posters from conferences or press releases were included to enlarge the database with recent clinical trials that had not yet been published elsewhere. Search criteria included acute exacerbation of schizophrenia in adult population, double blind placebo-controlled trials, conducted after 1997 (usually with publications/data release during 2000–2009), of 2–6 week

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duration, and had the Positive and Negative Syndrome Scale (PANSS)29 total score as an outcome measure. Completeness of search results was confirmed by examining two recently published meta-analyses.28,30

Data Extraction and Outcomes Relevant data were extracted and entered into the database by one of the authors. Accuracy of data extraction and entry was independently ver- ified by another author. The primary outcome of interest was the difference of drug over placebo in mean change from baseline to endpoint for the PANSS total score in the intent-to-treat study sample (advantage). Typically, all trials reported mean changes based on last-observation- carried-forward (LOCF) analyses, so the LOCF mean change on PANSS total was used in assessing advantage.Trial arm success (yes or no based on p value for drug-placebo contrast р0.05 or Ͼ0.05) and placebo response (in terms of mean improvement from baseline in PANSS total score) were also evaluated. The following factors thought to potentially influence outcome vari- 55 ables were included in the database: year the trial started, percentage of Mallinckrodt, Zhang, patients randomized to placebo (derived from the randomization allo- Prucka, et al. cation of the study design), percent female patients, total number of patients, number of patients in the placebo group,Reprint number of patients in the treatment group, number of sites, average number of placebo patients per site, average number of patients per arm per site, duration of acute treatment, dose regimen (fixed or flexible dosing), average baseline severity, geographic region where the trial was conducted (the United States, outside of the United States, or mixed), and number of countries included in the trial.For Analyses Perhaps the single most useful outcome to assess signal detection would be standardized effect size. However, not all studies reported the standard deviations necessary to compute effect sizes. Therefore, focus was on the mean drug-placebo difference (advantage). The Notdirection, magnitude, and significance of associations between advantage and the various independent factors (design factors and patient characteristics) were assessed using a mixed effect model meta- regression analysis that included study and drug as random effects. The random effect of study accounted for the correlated outcomes resulting from multiple treatment arms being compared to the same placebo arm within each study. The random effect of drug accounted for at least

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some of the possible differences in efficacy between drugs that could have masked or enhanced the differences due to design factors and patient characteristics. However, dose of drug could not be included due to sparseness of data, leading to the possibility that results may have been confounded by dosing differences. Results were weighted by the number of patients in the treatment arm. Numeric variables were assessed as both linear covariates and categorical variables, and non- numeric variables were fit as categorical variables. Ordinal numeric variables were categorized according to their natural categories. Continuous numeric variables were categorized by trichotimizing the variables based on tertile (equal third) splits. To allow assessment of the contribution of each variable independent of the effects of the other variables, a two-step process was used. First, each independent factor was initially included in a univariate analysis. Those variables showing statistical significance where then included in a multivariate analysis along with the percentage of patients randomized to placebo. 56 All analyses included the Kenward-Roger approximation to estimate Mallinckrodt, Zhang, denominator degrees of freedom. SAS software version 9.1 (SAS Institute, Prucka, et al. Cary, North Carolina) was used for analysis. Cook’s D statistic31 was used to assess the influence of individual studies on overall results via the experimental influence procedure in PROC MIXED. Analyses were repeatedReprint after deleting the studies identified by the influence diagnostics as being most influential on the estimate of the regression of advantage on percentage of patients randomized to placebo. Analyses of placebo response (improvement from baseline) included only one result per study. Therefore, the random effect of study was not included. In addition,For drug was not included as a random effect because placebo change is not thought to depend on which active drug(s) is tested. Analyses were weighted by the number of patients in the placebo arm. Other aspects for the analysis of placebo response were the same as described for advantage.

NotRESULTS Data Characteristics The data set contained 27 studies with 79 treatment arms to contrast with placebo. A listing of the studies and key outcome variables is provided in the Appendix and summary information is provided in Tables 1 and 2.

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TABLE 1

NUMBER OF TREATMENT ARMS BY DRUG

DRUG (INCLUDES ACTIVE CONTROL ARMS) # OF ARMS LY2140023 5 Aripiprazole 10 Asenapine 8 Bifeprunox 7 Haloperidol 3 Iloperidone 8 Olanzapine 9 Olanzapine long-acting injection 3 Paliperidone 9 Quetiapine 6 Risperidone 7 Sonepiprazole 3 Ziprasidone 1

TABLE 2

NUMBER OF STUDIES BY PERCENTAGE OF PATIENTS RANDOMIZED 57 TO PLACEBO AND NUMBER OF TREATMENT ARMS Mallinckrodt, Zhang, Prucka, et al. EFFECT AND EFFECT LEVELS # OF STUDIES % randomized to placebo 18.2 1 Reprint 20 8 22.2 1 25 11 33.3 2 # of arms 36 412 56For 61

Twenty-three studies and 72 treatment arms had data on both advantage and percentage of patients randomized to placebo.Twenty of these 23 studies randomized 20%–25% of patients to placebo. Of the 25 studies for which the number of treatment arms was reported, 18 were either 4 or 5 arm studies.Not Not all studies contained information on all the variables of interest. For example, number of sites was reported in 17 studies, the geographic region(s) represented in the trial was reported in 16 studies, and number of countries participating in the trial was reported in 15 studies. Therefore, the numbers of observations in an analysis varied depending on which variables were included in that analysis.

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Drug-Placebo Differences Mean change in the placebo group was significantly associated with advantage (mean drug-placebo difference) (p ϭ 0.006). For each one point increase in placebo mean change advantage decreased 0.4 points. Hence, drug-placebo differences did not move in lock step with placebo change, but the relationship was strong. The significance of associations between advantage and design features and patient characteristics are summarized in Table 3. Regarding the percentage of patients randomized to placebo, fitting this effect as a continuous variable yielded a p-value of 0.166, with a regression coefficient of 0.31, indicating advantage increased approximately 3 points for each 10 percent increase in the rate of allocation to placebo. When the percentage of patients randomized to placebo was fit as a categorical effect, differences approached significance (p ϭ 0.051). However, as the least square means in Table 4 illustrate, the differences did not follow a consistent pattern as studies with 20% randomized to placebo yielded mean advantages greater than studies with 22% or 25% randomized to 58 placebo. Nevertheless, the proportion of successful treatment arms (sig- Mallinckrodt, Zhang, Prucka, et al. nificant contrast versus placebo) was 83.3% (30/36) in studies

TABLE 3 Reprint SUMMARY OF ASSOCIATIONS BETWEEN INDEPENDENT VARIABLES AND ADVANTAGE (MEAN DRUG-PLACEBO DIFFERENCE)

VARIABLE LEVELS P-VALUE REGRESSION COEFFICIENT % rand. to placebo Continuous 0.166 0.31 % rand. to placebo For18.2, 20, 22.2, 25, 33.3 0.051 NA1 # of treatment arms Continuous 0.755 –0.33 # of treatment arms 3, 4, 5, 6 0.010 NA1 Year trial started Continuous 0.236 –0.41 % female patients Continuous 0.432 –0.10 Mean baseline severity Continuous 0.923 0.03 # of placebo patients Continuous 0.986 0.0005 # of patients Continuous 0.629 –0.003 Not# of sites Continuous 0.294 –0.08 Avg # of placebo patients per site Continuous 0.027 1.98 Avg # patients per site Continuous 0.126 0.49 # of countries Continuous 0.679 –0.17 Region US, OUS, Mixed 0.579 NA1 Duration (weeks) 2, 4, 6 0.339 NA1 Dosing regiment Fixed, Flex 0.478 NA1 Abbreviations: NA, regression coefficients are not applicable to categorical variables. Least square means for selected categorical variables are presented in Table 4.

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TABLE 4

MEAN DRUG-PLACEBO DIFFERENCES FOR SELECTED CATEGORICAL VARIABLES

EFFECT AND EFFECT LEVELS MEAN DRUG-PLACEBO DIFFERENCE* % randomized to placebo 18.2 –2.70 20 8.34 22.2 7.78 25 7.42 33.3 10.74 # of treatment arms 3 7.08 4 7.47 5 9.86 6 –3.77 *a higher value indicates better drug response.

у with 25% randomized to placebo compared with 58.3% (21/36) in 59 Ͻ studies with 25% randomized to placebo. Mallinckrodt, Zhang, The number of treatment arms was not significant when fit as a con- Prucka, et al. tinuous effect, but was significant as a categorical effect. However, the categorical results did not follow a meaningful pattern as the mean advantage for 5-arm studies was greater thanReprint for 4 and 3 arm studies (Table 4). The average number of placebo patients per site was the only other effect significantly associated with advantage (p ϭ 0.027). The regression coefficient of nearly 2 suggested that advantage increased 2 points (that is, the mean drug-placebo difference on PANSS total score increased 2 points) for eachFor increase of one patient in the average number of placebo patients per site. In multivariate analyses of the percentage of patients randomized to placebo and average number of placebo patients per site, neither factor was significantly associated with advantage. However, average number of placebo patients per site remained marginally significant (p ϭ 0.099), whereas percentage of patients randomized to placebo was essentially unrelatedNot to advantage with a regression coefficient near zero and a large p value (p ϭ 0.915).

Placebo Response The significance of associations between mean placebo improvement from baseline and design features and patient characteristics are summarized in Table 5. Regarding the study’s primary focus, the percentage

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TABLE 5

SUMMARY OF ASSOCIATIONS BETWEEN INDEPENDENT VARIABLES AND MEAN PLACEBO RESPONSE

VARIABLE LEVELS P-VALUE REGRESSION COEFFICIENT % rand. to placebo Continuous 0.047 Ϫ0.64 % rand. to placebo 18.2, 20, 22.2, 25, 33.3 0.408 NA1 # of treatment arms Continuous 0.752 0.47 # of treatment arms 3, 4, 5, 6 0.735 NA1 Year trial started Continuous 0.213 0.55 % female patients Continuous 0.049 0.32 Mean baseline severity Continuous 0.330 0.39 # of placebo patients Continuous 0.720 Ϫ0.02 # of patients Continuous 0.658 0.004 # of sites Continuous 0.978 0.003 Avg # of placebo patients per site Continuous 0.234 Ϫ1.58 Avg # patients per site Continuous 0.971 Ϫ0.015 # of countries Continuous 0.021 1.05 60 Region US, OUS, Mixed 0.175 NA1 1 Mallinckrodt, Zhang, Duration (weeks) 2, 4, 6 0.070 NA 1 Prucka, et al. Dosing regiment Fixed, Flex 0.494 NA Abbreviations: NA, regression coefficients are not applicable to categorical variables. Least square means for selected categorical variables are presented in Table 6.Reprint of patients randomized to placebo was significantly associated with mean placebo response (p ϭ 0.047). The regression coefficient was Ϫ0.64, indicating that mean placebo response decreased 6.4 points in PANSS total score for each 10 percent increase in the rate of allocation to placebo. Other factors to significantly influence mean placebo change were per- Forϭ ϭ cent female patients (p 0.049) and number of countries (p 0.021). The regression coefficients for these effects indicated that the mean placebo response (improvement in PANSS total score) increased approximately 3 points for each 10 percent increase in percent female in the study sample, and mean placebo response increased approximately one point for each additional country enrolling patients. NotIn order to more clearly visualize the linear associations, least square means by category are presented Table 6 for selected variables. Mean placebo response consistently decreased across the various categories of percentage of patients randomized to placebo. Results were somewhat less consistent for percent female as the intermediate category for percent female patients and studies with 7 countries had lower mean placebo responses than predicted by a linear trend. Duration of trial had a near significant (p ϭ 0.070) association with mean placebo response,

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TABLE 6

MEAN PLACEBO CHANGE FOR SELECTED CATEGORICAL VARIABLES

MEAN PLACEBO CHANGE* % randomized to placebo 18.2 12.9 20 9.4 22.2 7.6 25 7.0 33.3 0.6 % female patients Յ25 5.2 25~33 4.8 Ͼ33 12.5 Duration (weeks) 2 17.5 4 6.3 6 7.5 Region US 4.9 61 OUS 9.4 Mallinckrodt, Zhang, Mixed 10.7 Prucka, et al. Number of Countries 1 4.2 2 4.9 Reprint 3 13.7 4 15.0 7 2.8 8 18.8 9 12.9 10 12.6 Abbreviations: US ϭ The United States, OUS ϭ Outside of the United States. *a higher value indicates a larger placeboFor improvement.

driven by two-week studies having greater mean placebo improvement. Differences by geographic region also approached significance as US trials had smaller mean placebo improvement. In multivariate analyses including the percentage of patients randomized to placebo,Not percent female patients, and number of countries, these factors remained marginally significant with p values between 0.06 and 0.10.

Sensitivity Analyses For the outcome variable advantage, the most influential trials based on Cook’s D statistics were the two trials involving LY2140023. This is not surprising because these trials were at the extremes of percentage of

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patients randomized to placebo (18.2% in study HBBI and 33.3% in study HBBD). These trials were also extreme in their results as both olanzapine and LY2140023 separated robustly in HBBD and did not separate from placebo in HBBI. After removing these two trials from the database, the percentage of patients randomized to placebo did not significantly influence advantage, and in fact showed essentially zero correlation. For placebo response, the most influential trials based on Cook’s D statistics were the HBBD trial of LY2140023 and the quetiapine trial. These two trials had the smallest and second largest placebo group mean changes, respectively. After removing these two trials from the database, the regression of mean placebo change on percentage of patients randomized to placebo was little changed, although the p value increased to 0.153.

Analytic Evaluation of the Importance of Fraction Randomized to Placebo

62 For multi-arm studies where simultaneous pairwise testing of each Mallinckrodt, Zhang, treatment arm versus placebo are the primary outcomes, the impact of Prucka, et al. percent randomized to placebo on the distribution of outcomes was also investigated via an analytic approach involving numeric integra- tion over the assumed normal distribution of trial outcomes.32 For brevity, specific details of the analyticReprint approach are suppressed. Mean estimates of drug-placebo differences were unbiased and not influenced by percent randomized to placebo or the number of arms. Therefore, from a statistical theory perspective, there is no mechanism through which the probability of allocation to placebo or number of arms can create a bias in treatment contrasts. However, for fixedFor total sample size, as the number of treatment arms increased, the variance of each treatment arm contrast was min- imized, and therefore the probability of getting at least one significant drug-placebo contrast was maximized, when the placebo group had greater allocation than the individual treatment arms. Specifically, for studies with 2, 3, and 4 active treatment arms, the maximum probability of at least one significant drug-placebo contrast was achieved Notwith 41.4%, 36.6%, and 33.3% of patients randomized to placebo, respectively.32

DISCUSSION The primary results of this investigation into recent schizophrenia clinical trials suggest that, as in depression, percent randomized to placebo influenced trial outcomes. Specifically, the percentage of

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patients randomized to placebo was significantly associated with mean placebo change and approached significance for its association with mean drug-placebo differences. As in depression, more favorable outcomes tended to be seen in studies that had higher percentages of patients randomized to placebo. However, these results must be inter- preted in light of several limitations. Although all available placebo-controlled trials in schizophrenia since 1997 were included, only 23 studies provided data on both the percentage of patients randomized to placebo and mean placebo change and advantage. Therefore, power was lacking to find relevant associations between patient characteristics, design factors, and outcomes. Moreover, the range of percent randomized to placebo was limited as 20 of the 23 studies randomized 20% to 25% of patients to placebo. Only two studies randomized 33.3% of patients to placebo. Further, the ability to assess the impact of design features on outcomes was limited as trials tended to have similar design features. As a result, confounding of factors was present. In some cases, information about design features or patient characteristics were not available, fur- 63 ther limiting the sample size. Mallinckrodt, Zhang, While an association between percentage of patients randomized to Prucka, et al. placebo and placebo response was seen, analytical results showed no direct mechanism for this relationship. Therefore, any influence of percentage of patients randomized to placebo onReprint placebo change or mean placebo-drug differences must be indirect through other mechanism(s) such as patient and clinician expectation, or other subjective factors. The role expectation plays in trial outcome has received increasing attention in the literature.33–42 These results support the hypothesis that trial design influences participant expectations of improvement and trial outcomes. For The analytic results also indicated that the probability of getting at least one significant drug-placebo contrast within a multi-arm study was maximized by randomizing more patients to placebo than to the individual active treatment arms. The basis for this can be appreciated by considering a trial with equal allocation. If one patient is added to the placebo group the power for all drug-placebo contrasts is increased, whereasNot if one patient is added to an active treatment arm that is the only contrast where power will be increased. Other exploratory results suggested the potential for fewer countries in the trial to be associated with decreased placebo response. This association was driven by trials with 1 or 2 countries enrolling patients having appreciably smaller placebo mean response than trials conducted in 3 or more countries. However, number of countries was not significantly associated with drug-placebo differences. Results by geographic

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region suggested that trials in the United States (US) may have lower mean placebo response but this did not translate into greater drug- placebo differences. Studies with greater than 33% of female patients tended to have greater mean placebo response than studies with fewer females. It is important to note that percent of female patients is not a design feature, but rather an outcome of the trials. Therefore, this effect may reflect other design or trial conduct features that influenced outcome. The significant association between the average numbers of placebo patients per site with mean drug-placebo difference is interesting. The average number of placebo patients per site is a function of both the proportion of patients randomized to placebo and the number of sites. We had a priori hypothesized that these two attributes constituted a meaningful measure of data structure, with studies having a high average number of placebo patients per site having greater potential for dis- criminating an active drug from placebo. This and the other significant exploratory outcomes are subject to one 64 additional limitation not applicable to the primary objective assessing Mallinckrodt, Zhang, associations with the percentage of patients randomized to placebo. No Prucka, et al. adjustments for multiplicity have been implemented. Any reasonable adjustment across the array of exploratory outcomes would result in no significant differences. Therefore, results from exploratory outcomes are perhaps useful in generating hypothesesReprint for further investigation in more extensive databases. Limitations to the present investigation prevent definitive conclusions regarding the association of the percentage of patients randomized to placebo with mean placebo change and drug-placebo differences in recent schizophrenia trials. However, interpretations are strengthened by correspondence with previouslyFor reported results in depression. In both depression and the present schizophrenia results trials with greater percentages of patients randomized to placebo had lower placebo response and greater drug-placebo differences. Therefore, signal detection may be improved if an adequate proportion of patients are randomized to placebo. ✤ NotFUNDING This work was supported by Eli Lilly and Company.

ACKNOWLEDGEMENT Authors would like to thank Virginia Stauffer, Mark Enerson, Mark Leusch, Bruce Kinon, Diane Bakaysa, and Robert Baker for assistance in developing the database and helpful comments in review of this work.

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SIGNAL DETECTION IN SCHIZOPHRENIA ) ALUE P V ( continued AN- AGE* T ADV - T MENT TREA CHANGE* PLACEBO CHANGE* DOSE

65 Mallinckrodt, Zhang, Prucka, et al. DRUG OL LAIOL LAI 300 mg/2w 405 mg/4w 8.83 8.83 22.68 20.03 13.85 11.2 <0.001 <0.001 olanzapine 15 mg QD 12.9 16.66 3.76 0.25 olanzapine 15 mg QD –3.7 19 22.7 <0.001 risperidone 6 mg QD 5 15.7 10.7 <0.001 haloperidol 10 mg QD 2.9 13.8 10.9 <0.001 aripiprazole 30 mg QD 2.9aripiprazole 30 mg QD 11.4 5 8.5 13.9 0.009 8.9 0.003 LY2140023LY2140023 20 mg BIDLY2140023 40 mg BID 12.9 80 mg BID 12.9 12.9Reprint 11.92 12.45 11.4 –0.98 –0.44 0.717 –1.49 0.87 0.579 ET S ATA BASELINE D % FEMALE

ONTROLLED For C TION DURA- (WEEKS) LACEBO P # OF ARM . % TO RAND. NotEXP PLACEBO CHIZOPHRENIA S ART YEAR ST 2005 33.32007 3 18.2 4 62004 26.2 4 25 94.8 43.51997 4 LY2140023 25 98.62 40 mg BID 4 LY21400231997 –3.7 4 5 mg BID 25 29.5 12 12.9 4 101 4 10.72 30.4 15.7 OL LAI 4 <0.001 –2.18 99.3 210 mg/2w 0.415 30 aripiprazole 8.83 15 mg QD 94.4 20.63 2.9 aripiprazole 11.8 20 mg QD 15.5 <0.001 5 12.6 <0.001 14.5 9.5 0.001 1 2 3 4 5 APPENDIX ISTING OF THE L STUDY Patil 2007 Lauriello 2009 Kane 2002 Potkin 2003 Kinon 2009

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66 Mallinckrodt, Zhang, Prucka, et al. DRUG aripiprazolearipiprazole 15 mg QD 20 mg QD 2.33aripiprazole 2.33aripiprazole 5 mg QD 11.73 10 mg QD 14.44 5.3 9.4 5.3 12.11 <0.01 <0.001 10.6 11.3 5.3 6 0.058 0.03 paliperidonepaliperidone 9 mg QD 12 mg QD 4.1 4.1paliperidonepaliperidone 9 mg QD 17.2 15 mg QD 23.3 2.8 13.1 2.8paliperidone 19.2 <0.001 12 mg QD <0.001 16.3 19.9 8 12.9 17.2 <0.001 <0.001 17.5 8.5 <0.001 Reprintolanzapine 10 mg QD 4.1olanzapine 10 mg QD 19.9olanzapine 2.8 15.8 10 mg QD NA 18.1 8 15.3 18.4 NA 10.4 NA BASELINE

% FEMALE For TION DURA- (WEEKS) # OF ARM . %

NotEXP RAND. TO PLACEBO ) ART YEAR ST 2000 252003 4 25 62004 4 20 22.4 6 92.7 52004 NA 20 aripiprazole 6 10 mg QD 91 52004 48 2.33 aripiprazole 25 6 15.04 93.9 2 mg QD 4 12.71 32 paliperidone 5.3 <0.001 6 mg QD 6 93 8.2 4.1 26 paliperidone 2.9 17.9 3 mg QD 93.7 0.289 13.8 2.8 paliperidone <0.001 6 mg QD 15 8 11.6 <0.001 15.7 7 0.006

CONTINUED 6 7 8 9 10 STUDY McEvoy 2007 CTR 2005 Kane 2006 Davidson 2007 Marder 2007 APPENDIX (

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SIGNAL DETECTION IN SCHIZOPHRENIA ) ( continued QD 15 23.4 8.4 <0.001 BID 15 17.1 2.1BID 0.333 9.9 9.4 –0.5 NA

67 Mallinckrodt, Zhang, Prucka, et al. asenapine 10 mg BID 11.1asenapine 10 mg BID 13.4 14.6 2.3 19.4 NA 4.8 0.038 quetiapine 300–400 mg olanzapine NA 9.9 NA NA NA olanzapine NA 11.1 NA NA NA risperidone 3 mg BID 5.3 10.9 5.6 ns haloperidol 4 mg BID 14.6 20 5.4 0.02 Reprintziprasidone 160 mg QD 7.1 12.3 5.2 <0.05 For Not 2006 20 319982000 NA 2 NA2001 NA 33.5 33.3 NA NA2005 102.4 NA 3 NA NA paliperidone NA mg ER9-12 93.12005 6 3 92 NA asenapine 27.2 NA2005 4 asenapine 93.7 NA NA 25 NA 86.8 asenapine NA2005 4 4.35 NA 5 mg BID 25 asenapine2005 92 NA 3.68 6 5.3 5–10 mg 3 20 NA 41 NA asenapine 15.9 4 5 NA 5 mg BID NA 89.2 10.6 20.4 6 11.1 <0.005 NA asenapine 91.7 28.8 14.5 5 mg BID iloperidone 95.5 14.6 24 mg QD 3.4 iloperidone 21.3 NA 7.1 4 mg QD 12 6.7 4.6 0.004 4.9 9 <0.01 4.4 0.097 11 12 12 13 12 12 14 15 16 Szegedi 2008 Szegedi 2008 Potkin 2007 Szegedi 2008 Potkin 2008 Canuso 2009 Szegedi 2008 Kane 2008 Cutler 2008

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SIGNAL DETECTION IN SCHIZOPHRENIA ALUE P V AN- AGE* ADV T - T TREA MENT CHANGE* PLACEBO CHANGE* QD 7.6 14 6.4 0.005 DOSE

68 Mallinckrodt, Zhang, Prucka, et al. DRUG risperidone 4–8 mg QD 3.5 16.6 13.1 0.001 bifeprunoxbifeprunox 10 mg QD 20 mg QD 5.3bifeprunox 5.3 40 mg QD 5 11.3 7.7 –0.3 6 10.3 1 <0.05 2.6 0.156 iloperidoneiloperidone 8 mg QD 12 mg QD 4.6 4.6 7.8 9.9 3.2 5.3 0.227 0.047 iloperidone 10–16 mg QD 3.5iloperidone 11.1 20–24 mg 7.6 0.002 haloperidol 15 mg QD 4.6 13.9 9.3 <0.001 Reprintrisperidone 6–8 mg QD 7.6risperidone 18.8 6 mg QDrisperidone 11.2 5.3 <0.001 6 mg QD 15.7 7.7 10.4 19.5 <0.001 11.8 0.0011 BASELINE

% FEMALE For TION DURA- (WEEKS) # OF ARM . %

NotEXP RAND. TO PLACEBO ) ART YEAR ST 2005 252005 4 22.2 6 42002 29.5 20 6 94.4 38.4 52005 iloperidone 25 94.8 4–8 mg QD 6 iloperidone2005 3.5 4 12–16 mg QD 25 25 7.6 9.5 6 92.1 4 11 bifeprunox 28 6 6 5 mg QD 3.4 93.5 0.017 NA 0.101 5.3 bifeprunox NA 30 mg QD 9.7 bifeprunox 7.7 20 mg QD 4.4 13.5 10.7 0.128 5.8 13.8 0.02 3.1 ns

CONTINUED 16 16 17 18 19 Potkin 2008 STUDY Potkin 2008 Casey 2008 Rapaport 2007 Barbato 2006 APPENDIX (

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SIGNAL DETECTION IN SCHIZOPHRENIA ) ( continued J Clin Psychiatry . Nat Med .Nat 2007;13(9):1102–1107. clinical trial. pine); IR = immediate release; = extended ER lue indicates a better response. Then the advantage was QDQD 20.2QD 20.5 18.8QD 18.8 24.8 0.3 18.8 30.9 ns 6 31.3 12.1 0.03 <0.001 12.5 <0.001

69 Mallinckrodt, Zhang, Prucka, et al. olanzapine 15 mg QD 10.7 22 11.3 <0.05 olanzapine 15 mg QD 12.6 31.5 18.9 <0.001 bifeprunox 30 mg QD 10.7 13.1 2.4 ns sonepiprazolesonepiprazole 10 mg QD 60 mg QD 12.6 12.6 17.1 7.8 4.5 –4.8 0.23 0.22 quetiapine 400–600 mg quetiapinequetiapine XR600 mg Reprintquetiapine XR800 mg IR200 mg BID 18.8 26.6 7.8 0.004 For 2008;69(5):790–799. nist at the mGlu2/3 receptor for the treatment of schizophrenia. for the treatment nist at the mGlu2/3 receptor Conference (ICOSR) of Schizophrenia International Research Congress

Not J Clin Psychiatry 2000 20 52003 20 62004 3 34.3 20 NA 2 5 sonepiprazole 34.3 1.5 mg QD 6 95.8 12.6 39.8 risperidone 10.9 4–6 mg QD 96.5 –1.7 20.2 quetiapine 0.64 XR400 mg 27.7 7.5 <0.01 20 21 22 Patil ST,Patil Zhang L, Martenyi F, et al. schizophrenia: as a new to treat of mGlu2/3 receptors approach Activation a randomized Phase 2 Kinon B. monohydrate: LY2140023 an ago Lauriello J,T, Lambert Andersen S, Lin D, CC, Taylor McDonnell D. An 8-week, double-blind, randomized, study of olanzapine placebo-controlled long-acting injection in acutely Kane JM,WH, Carson Saha AR, et al. Efficacy and safety of aripiprazole and haloperidol versus placebo in patients with schizophrenia and schizoaffective disorder. Corrigan 2004 Kahn 2007 Potkin 2006 Abbreviations: ns = not significant; = not available; NA BID = twice daily; QD = once daily, wk = week; (paliperidone);release (quetia XR = extended release = olanzapine OL LAI long-acting injection. interpretation purpose,*For by (–1) so that a higher positive va multiplied baseline were change from the placebo and treatment calculated minus placebo, by treatment a higher positive advantage indicates a better signal detection. 1 2 2009. 2009 Mar 29. San Diego, CA, USA. 3 ill patients with schizophrenia. 4 2002;63(9):763–771.

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SIGNAL DETECTION IN SCHIZOPHRENIA Biol Psychiatry. 2007;90(1–3);147–161. . 2008;28(2 Suppl 1):S4–S11. azole in schizophrenia: a placebo- al dopamine D2 receptor agonist,al dopamine D2 receptor in J Clin Psychiatry . 2007;68(10):1492–1500. Schizophr Res. Schizophr apine in inpatients with recently exacerbated ia: a randomized, from results double-blind, Drug Evaluation Unit, 48th Annual Meeting. cebo-controlled study. cebo-controlled can College of Neuropsychopharmacology 45th ed trial. phrenia: a randomized, double-blind, placebo-con- J Clin Psychopharmacol s. New Clinical Drug Evaluation Unit, 48th Annual

70 Mallinckrodt, Zhang, Prucka, et al. . 2007;41(11):895–905. Reprint J Psychiatr Res . 2008;200(3):317–331. For chopharmacology. 2006;31(Suppl 1s):S251. at: Presented Ameri Psychopharmacology (Berl) 2006;85(1–3):254–265. 2008; 28(2 Suppl 1): S20–S28. Schizophr Res. Schizophr Not . 2007;68(6):832–842. 2007;93:117–130. ) Biol Psychiatry . 2004;55(5):445–451. Am J Psychiatry . 2009;166(6):691–701. J Clin Psychopharmacol. Schizophr Res. Schizophr J Clin Psychiatry

CONTINUED Arch Gen Psychiatry . 2003;60(7):681–690. Corrigan MH, Gallen CC, Bonura ML, KM, and Merchant Sonepiprazole Study Group. Effectiveness of the selective D4 antagonist sonepipr Marder SR, Kramer M, L, Ford et al. Efficacy and safety of paliperidonetablets: extended-release of a 6-week, results randomized, pla Canuso CM, B, Dirks J, Carothers et al. Randomized, double-blind, study of paliperidoneand queti placebo-controlled extended-release Szegedi A, S, Portkin Kane JM, et al. Placebo clinical in antipsychotic response trials: overview and case of the literature example SG,Potkin Cohen M, J. Panagides Efficacy and tolerability of asenapine in acute schizophrenia: a placebo- and risperidone-controll Kane JM, Zhao J, Cohen M, J. Panagides Efficacy and safety of asenapine in patients with acute schizophrenia. at New Clinical Poster Cutler AJ, Kalali AH, P, Weiden Hamilton J, CD. Wolfgang Four-week, double-blind, placebo- and ziprasidone-controlled trial of iloperidone in patients with acute exacerbations of SG,Potkin Litman RE, R, Torres CD. Wolfgang Efficacy of iloperidoneschizophrenia in the treatment initial phase 3 studies. Casey DE, Sands EE, Heisterberg J, HM. Yang Efficacy and safety of bifeprunox in patients with an acute exacerbation of schizophren Rapaport M, Barbato LM, Heisterberg J, PP, Yeung Shapira NA. Efficacy and safety of pa tients with acute exacerations of bifeprunox of schizophre- versus placebo in the treatment Barbato LM, SG, Potkin Heisterberg J, PP, Yeung Shapira NA. A randomized, double-blind, study of bifeprunox, placebo-controlled a parti SG,Potkin Gharabawi GM, AJ, Greenspan et al. A double-blind comparison of risperidone, quetiapine and placebo in patients with schizophrenia experiencing an acute exacerba- Kahn RS, Schulz SC,VD, Palazov et al. Efficacy and tolerability of once-daily quetiapine fumarate in acute schizo extended release Potkin SG,Potkin Saha AR, Kujawa, MJ, et al. Aripiprazole, mechanism of action, with a novel an antipsychotic and risperidone vs placebo in patients with schizophrenia and schizoaffective JP,McEvoy Daniel DG,WH Jr, Carson McQuade RD, RN. Marcus A randomized, double-blind, placebo-controlled, study of the efficacy and sa fety of aripiprazole 10, 15 or 20 CTR April 2005. A multicenter, randomized, double-blind, study of 3 fixed doses aripiprazole placebo-controlled of patients with acute schizophrenia. in the treatment Kane J, Canas F, Kramer M, et al. of schizophrenia with paliperidonetablets: extended-release Treatment trial. A 6-week placebo-controlled Davidson M, Emsley R, Kramer M, et al. Efficacy, safety and early of paliperidonetablets (paliperidone response extended-release ER): Results of a 6-week, randomized, placebo-con- May 27–30, 2008. 5 disorder. 6 of patients with acute exacerbationsmg/day for the treatment of schizophrenia. 7 Aripiprazole CN138113 BMS-337039/OPC-14597 Clinical Study Report. 8 9 study. trolled 10 11 schizophrenia. 12 Meeting. 2008 May 27–30. Phoenix, AZ. 13 14 15 schizophrenia. 16 17 placebo-controlled, multicenter, dose-finding study. 18 nia. at: session presented Poster on SchizophreniaMar 30; 11th International Congress Research;2007 Colorado Springs,19 CO. patients with acute exacerbations of schizophrenia [abstract]. Neuropsy Annual Meeting: December 3–7, 2006; Hollywood,20 FL. 21 tion requiring hospitalization. 22 study. trolled controlled trial. 2007;62(12):1363–1370. APPENDIX (

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