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  string(1548) "Background:  Not all individuals with schizophrenia benefit from the antipsychotic drugs.  The majority experience immediate and long-term adverse effects raising risk/benefit dilemmas for the patients and for the prescribers. An alternative treatment scheme proposes a targeted or intermittent treatment approach, by which antipsychotic drugs are administered upon psychosis exacerbation and discontinued upon remission or stabilization, and renewed treatment in case of symptoms recurrence. However, there are currently no reliable biological or phenomenological markers able to predict which patients will maintain symptoms stability in absence of antipsychotic treatment.  
Objective: Identify markers that can help predict which patients maintain symptom stability in absence of antipsychotic treatment.
Study Design: Data from the requested studies will be merged into an integrated database to facilitate meta-analysis of individual participant data.
Participants: Six placebo-controlled antipsychotic trials with a double-blind phase of at least 8 months.
Primary and Secondary Outcome Measure(s); Time to: (1) relapse as measured on the PANSS, (2) discontinuation or (3) hospitalization. Secondary outcome measures time to relapse as measured on the CGI-S.
Statistical Analysis: Time to drop-out, relapse or hospitalization will be analyzed using Cox-regression. Predictor variables to be tested included routinely collected symptom, demographic and clinical variables in antipsychotic trials." ["project_brief_bg"]=> string(1367) "Current pharmacological treatment of schizophrenia employs drugs that interfere with dopamine neurotransmission, aiming to suppress acute exacerbation of psychosis and maintenance treatment to reduce the risk of psychosis recurrence. However, not all individuals who meet DSM criteria for schizophrenia benefit from the antipsychotic drugs and the majority experience immediate and long-term adverse effects raising risk/benefit dilemmas for the patients and for the prescribers. An alternative treatment scheme proposes a targeted or intermittent treatment approach, by which antipsychotic drugs are administered upon psychosis exacerbation and discontinued upon remission or stabilization, and renewed treatment in case of symptoms recurrence. However, there are currently no reliable biological or phenomenological markers able to predict which patients will maintain symptoms stability in absence of antipsychotic treatment and which patients are likely to experience symptoms worsening shortly after treatment discontinuation. A recent study has suggested that patients who experience high level of negative symptoms and low levels of symptoms related to agitation may be able to maintain symptoms stability and avoid hospitalization in absence of drugs which directly interfere with dopamine neurotransmission for at least 12 months (Rabinowitz et al, 2023). " ["project_specific_aims"]=> string(494) "The aim of this project is to identify markers that can help predict which patients maintain symptoms stability in absence of antipsychotic treatment. Based on previous work, I hypothesize that trial participants with predominantly negative symptoms and low agitation at baseline will sustain without relapse longer than patients without this symptom profile. Attempts will be made to develop and test other symptom typologies that predict stability in the absence of antipsychotic treatment." ["project_study_design"]=> array(2) { ["value"]=> string(7) "meta_an" ["label"]=> string(52) "Meta-analysis (analysis of multiple trials together)" } ["project_purposes"]=> array(3) { [0]=> array(2) { ["value"]=> string(22) "participant_level_data" ["label"]=> string(36) "Participant-level data meta-analysis" } [1]=> array(2) { ["value"]=> string(56) "participant_level_data_meta_analysis_from_yoda_and_other" ["label"]=> string(69) "Meta-analysis using data from the YODA Project and other data sources" } [2]=> array(2) { ["value"]=> string(50) "research_on_clinical_prediction_or_risk_prediction" ["label"]=> string(50) "Research on clinical prediction or risk prediction" } } ["project_research_methods"]=> string(480) "1. None.
2. Other studies from VIVILI
>Olanzapine Relapse Prevention Versus Placebo https://benmeg.com/archives/rxarchives.org/uploads/2/4/4/6/24466638/1960_online.pdf
IDs: F1D-MC-HGGI

>Intramuscular Depot Formulation of Aripiprazole as Maintenance Treatment in Patients With Schizophrenia (ASPIRE)
https://clinicaltrials.gov/study/NCT00705783

3. We plan to pool the studies in VIVILI unless it can be done in YODA." ["project_main_outcome_measure"]=> string(177) "Primary outcome measures: Change on the PANSS total score, time to discontinuation and time to hospitalization. Secondary measures to be includes with be CGI-S, CGI-C and PSP." ["project_main_predictor_indep"]=> string(337) "The main independent variables will be symptomatology at baseline as measured on the PANSS items, subscales and total score, CGI-S, PSP and medical history (e.g., age of first illness, number of hospitalizations and medication history), smoking, tardive dyskinesia, akathisia, demographic variables (age, sex, race, ethnicity, region). " ["project_other_variables_interest"]=> string(333) "These variables will be used interchangeably as independent variables and as other variables used to adjust in multivariate models: and medical history (e.g., age of first illness, number of hospitalizations and medication history), smoking, tardive dyskinesia, akathisia, demographic variables (age, sex, race, ethnicity, region). " ["project_stat_analysis_plan"]=> string(1333) "The major mode of analysis will be Cox regression modeling. Separate models will be specified for time to drop-out, relapse (12 point increase on total PANSS, as per Siafis et al, 2023) or hospitalization. Predictor variables to be tested include symptomatology at baseline as measured on the PANSS items, subscales and total score, CGI-S, PSP and medical history (e.g., age of first illness, number of hospitalizations and medication history), smoking, tardive dyskinesia, akathisia, demographic variables (age, sex, race, ethnicity, region).

To test the hypothesis that patients who manifest primarily negative symptoms are less likely to relapse on placebo dichotomous variables of meeting criteria for negative symptoms will be created using known negative symptom population groupings (Rabinowitz et al 2013; Rabinowitz et al, 2023) and compared to the effect of this grouping variable for patients on active treatment. This will be done by testing interaction of placebo vs. active treatment and yes/no negative symptom patient and separate models for placebo and active treatment will also be run and effects of the negative symptom grouping variable will be compared.

Additional analysis will be done using network analysis to attempt to identify symptom cluster and propensity scoring. " ["project_software_used"]=> array(2) { ["value"]=> string(7) "rstudio" ["label"]=> string(7) "RStudio" } ["project_timeline"]=> string(238) "Anticipated start date: April 15, 2025
Analysis completion date: Sept 15, 2025
Date manuscript drafted and first submitted for publication: Nov. 15, 2025
Date results reported back to the YODA Project: Nov. 15, 2025" ["project_dissemination_plan"]=> string(129) "Conference poster at schizophrenia conference on early findings and journal article in specialty journal upon project completion." ["project_bibliography"]=> string(2345) "

Leucht S, Tardy M, Komossa K, Heres S, Kissling W, Salanti G, Davis JM. Antipsychotic drugs versus placebo for relapse prevention in schizophrenia: a systematic review and meta-analysis. Lancet. 2012 Jun 2;379(9831):2063-71. doi: 10.1016/S0140-6736(12)60239-6. Epub 2012 May 3. PMID: 22560607.

Rabinowitz J, Staner C, Saoud J, Weiser M, Kuchibhatla R, Davidson M, Harvey PD, Luthringer R. Long-term effects of Roluperidone on negative symptoms of schizophrenia. Schizophr Res. 2023 May;255:9-13. doi: 10.1016/j.schres.2023.03.028. Epub 2023 Mar 16. PMID: 36933291.

Rabinowitz J, Levine SZ, Barkai O, Davidov O. Dropout rates in randomized clinical trials of antipsychotics: a meta-analysis comparing first- and second-generation drugs and an examination of the role of trial design features. Schizophr Bull. 2009 Jul;35(4):775-88. doi: 10.1093/schbul/sbn005. Epub 2008 Feb 26. PMID: 18303093; PMCID: PMC2696366.

Siafis S, Brandt L, McCutcheon RA, Gutwinski S, Schneider-Thoma J, Bighelli I, Kane JM, Arango C, Kahn RS, Fleischhacker WW, McGorry P, Carpenter WT, Falkai P, Hasan A, Marder SR, Schooler N, Engel RR, Honer WG, Buchanan RW, Davidson M, Weiser M, Priller J, Davis JM, Howes OD, Correll CU, Leucht S. Relapse in clinically stable adult patients with schizophrenia or schizoaffective disorder: evidence-based criteria derived by equipercentile linking and diagnostic test accuracy meta-analysis. Lancet Psychiatry. 2024 Jan;11(1):36-46. doi: 10.1016/S2215-0366(23)00364-4. Epub 2023 Nov 30. PMID: 38043562.

Rabinowitz J, Werbeloff N, Caers I, Mandel FS, Stauffer V, Menard F, Kinon BJ, Kapur S. Negative symptoms in schizophrenia–the remarkable impact of inclusion definitions in clinical trials and their consequences. Schizophr Res. 2013 Nov;150(2-3):334-8. doi: 10.1016/j.schres.2013.06.023. Epub 2013 Jun 29. PMID: 23815975.

Georgios Schoretsanitis, John M Kane, Christoph U Correll, Jose M Rubio, Predictors of Lack of Relapse After Random Discontinuation of Oral and Long-acting Injectable Antipsychotics in Clinically Stabilized Patients with Schizophrenia: A Re-analysis of Individual Participant Data, Schizophrenia Bulletin, Volume 48, Issue 2, March 2022, Pages 296–306, https://doi.org/10.1093/schbul/sbab091

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2025-0120

Research Proposal

Project Title: Identifying predictors of symptom stability in absence of antipsychotic treatment

Scientific Abstract: Background: Not all individuals with schizophrenia benefit from the antipsychotic drugs. The majority experience immediate and long-term adverse effects raising risk/benefit dilemmas for the patients and for the prescribers. An alternative treatment scheme proposes a targeted or intermittent treatment approach, by which antipsychotic drugs are administered upon psychosis exacerbation and discontinued upon remission or stabilization, and renewed treatment in case of symptoms recurrence. However, there are currently no reliable biological or phenomenological markers able to predict which patients will maintain symptoms stability in absence of antipsychotic treatment.
Objective: Identify markers that can help predict which patients maintain symptom stability in absence of antipsychotic treatment.
Study Design: Data from the requested studies will be merged into an integrated database to facilitate meta-analysis of individual participant data.
Participants: Six placebo-controlled antipsychotic trials with a double-blind phase of at least 8 months.
Primary and Secondary Outcome Measure(s); Time to: (1) relapse as measured on the PANSS, (2) discontinuation or (3) hospitalization. Secondary outcome measures time to relapse as measured on the CGI-S.
Statistical Analysis: Time to drop-out, relapse or hospitalization will be analyzed using Cox-regression. Predictor variables to be tested included routinely collected symptom, demographic and clinical variables in antipsychotic trials.

Brief Project Background and Statement of Project Significance: Current pharmacological treatment of schizophrenia employs drugs that interfere with dopamine neurotransmission, aiming to suppress acute exacerbation of psychosis and maintenance treatment to reduce the risk of psychosis recurrence. However, not all individuals who meet DSM criteria for schizophrenia benefit from the antipsychotic drugs and the majority experience immediate and long-term adverse effects raising risk/benefit dilemmas for the patients and for the prescribers. An alternative treatment scheme proposes a targeted or intermittent treatment approach, by which antipsychotic drugs are administered upon psychosis exacerbation and discontinued upon remission or stabilization, and renewed treatment in case of symptoms recurrence. However, there are currently no reliable biological or phenomenological markers able to predict which patients will maintain symptoms stability in absence of antipsychotic treatment and which patients are likely to experience symptoms worsening shortly after treatment discontinuation. A recent study has suggested that patients who experience high level of negative symptoms and low levels of symptoms related to agitation may be able to maintain symptoms stability and avoid hospitalization in absence of drugs which directly interfere with dopamine neurotransmission for at least 12 months (Rabinowitz et al, 2023).

Specific Aims of the Project: The aim of this project is to identify markers that can help predict which patients maintain symptoms stability in absence of antipsychotic treatment. Based on previous work, I hypothesize that trial participants with predominantly negative symptoms and low agitation at baseline will sustain without relapse longer than patients without this symptom profile. Attempts will be made to develop and test other symptom typologies that predict stability in the absence of antipsychotic treatment.

Study Design: Meta-analysis (analysis of multiple trials together)

What is the purpose of the analysis being proposed? Please select all that apply.: Participant-level data meta-analysis Meta-analysis using data from the YODA Project and other data sources Research on clinical prediction or risk prediction

Software Used: RStudio

Data Source and Inclusion/Exclusion Criteria to be used to define the patient sample for your study: 1. None.
2. Other studies from VIVILI
>Olanzapine Relapse Prevention Versus Placebo https://benmeg.com/archives/rxarchives.org/uploads/2/4/4/6/24466638/1960_online.pdf
IDs: F1D-MC-HGGI

>Intramuscular Depot Formulation of Aripiprazole as Maintenance Treatment in Patients With Schizophrenia (ASPIRE)
https://clinicaltrials.gov/study/NCT00705783

3. We plan to pool the studies in VIVILI unless it can be done in YODA.

Primary and Secondary Outcome Measure(s) and how they will be categorized/defined for your study: Primary outcome measures: Change on the PANSS total score, time to discontinuation and time to hospitalization. Secondary measures to be includes with be CGI-S, CGI-C and PSP.

Main Predictor/Independent Variable and how it will be categorized/defined for your study: The main independent variables will be symptomatology at baseline as measured on the PANSS items, subscales and total score, CGI-S, PSP and medical history (e.g., age of first illness, number of hospitalizations and medication history), smoking, tardive dyskinesia, akathisia, demographic variables (age, sex, race, ethnicity, region).

Other Variables of Interest that will be used in your analysis and how they will be categorized/defined for your study: These variables will be used interchangeably as independent variables and as other variables used to adjust in multivariate models: and medical history (e.g., age of first illness, number of hospitalizations and medication history), smoking, tardive dyskinesia, akathisia, demographic variables (age, sex, race, ethnicity, region).

Statistical Analysis Plan: The major mode of analysis will be Cox regression modeling. Separate models will be specified for time to drop-out, relapse (12 point increase on total PANSS, as per Siafis et al, 2023) or hospitalization. Predictor variables to be tested include symptomatology at baseline as measured on the PANSS items, subscales and total score, CGI-S, PSP and medical history (e.g., age of first illness, number of hospitalizations and medication history), smoking, tardive dyskinesia, akathisia, demographic variables (age, sex, race, ethnicity, region).

To test the hypothesis that patients who manifest primarily negative symptoms are less likely to relapse on placebo dichotomous variables of meeting criteria for negative symptoms will be created using known negative symptom population groupings (Rabinowitz et al 2013; Rabinowitz et al, 2023) and compared to the effect of this grouping variable for patients on active treatment. This will be done by testing interaction of placebo vs. active treatment and yes/no negative symptom patient and separate models for placebo and active treatment will also be run and effects of the negative symptom grouping variable will be compared.

Additional analysis will be done using network analysis to attempt to identify symptom cluster and propensity scoring.

Narrative Summary: Not all individuals with schizophrenia benefit from antipsychotic drugs. The majority experience immediate and long-term adverse effects raising risk/benefit dilemmas for patients and for prescribers. An alternative treatment scheme proposes a targeted or intermittent treatment approach, by which antipsychotic drugs are administered upon psychosis exacerbation and discontinued upon remission or stabilization, and renewed treatment in case of symptoms recurrence. However, there are currently no reliable biological or phenomenological markers able to predict which patients will maintain symptom stability in absence of antipsychotic treatment.

Project Timeline: Anticipated start date: April 15, 2025
Analysis completion date: Sept 15, 2025
Date manuscript drafted and first submitted for publication: Nov. 15, 2025
Date results reported back to the YODA Project: Nov. 15, 2025

Dissemination Plan: Conference poster at schizophrenia conference on early findings and journal article in specialty journal upon project completion.

Bibliography:

Leucht S, Tardy M, Komossa K, Heres S, Kissling W, Salanti G, Davis JM. Antipsychotic drugs versus placebo for relapse prevention in schizophrenia: a systematic review and meta-analysis. Lancet. 2012 Jun 2;379(9831):2063-71. doi: 10.1016/S0140-6736(12)60239-6. Epub 2012 May 3. PMID: 22560607.

Rabinowitz J, Staner C, Saoud J, Weiser M, Kuchibhatla R, Davidson M, Harvey PD, Luthringer R. Long-term effects of Roluperidone on negative symptoms of schizophrenia. Schizophr Res. 2023 May;255:9-13. doi: 10.1016/j.schres.2023.03.028. Epub 2023 Mar 16. PMID: 36933291.

Rabinowitz J, Levine SZ, Barkai O, Davidov O. Dropout rates in randomized clinical trials of antipsychotics: a meta-analysis comparing first- and second-generation drugs and an examination of the role of trial design features. Schizophr Bull. 2009 Jul;35(4):775-88. doi: 10.1093/schbul/sbn005. Epub 2008 Feb 26. PMID: 18303093; PMCID: PMC2696366.

Siafis S, Brandt L, McCutcheon RA, Gutwinski S, Schneider-Thoma J, Bighelli I, Kane JM, Arango C, Kahn RS, Fleischhacker WW, McGorry P, Carpenter WT, Falkai P, Hasan A, Marder SR, Schooler N, Engel RR, Honer WG, Buchanan RW, Davidson M, Weiser M, Priller J, Davis JM, Howes OD, Correll CU, Leucht S. Relapse in clinically stable adult patients with schizophrenia or schizoaffective disorder: evidence-based criteria derived by equipercentile linking and diagnostic test accuracy meta-analysis. Lancet Psychiatry. 2024 Jan;11(1):36-46. doi: 10.1016/S2215-0366(23)00364-4. Epub 2023 Nov 30. PMID: 38043562.

Rabinowitz J, Werbeloff N, Caers I, Mandel FS, Stauffer V, Menard F, Kinon BJ, Kapur S. Negative symptoms in schizophrenia–the remarkable impact of inclusion definitions in clinical trials and their consequences. Schizophr Res. 2013 Nov;150(2-3):334-8. doi: 10.1016/j.schres.2013.06.023. Epub 2013 Jun 29. PMID: 23815975.

Georgios Schoretsanitis, John M Kane, Christoph U Correll, Jose M Rubio, Predictors of Lack of Relapse After Random Discontinuation of Oral and Long-acting Injectable Antipsychotics in Clinically Stabilized Patients with Schizophrenia: A Re-analysis of Individual Participant Data, Schizophrenia Bulletin, Volume 48, Issue 2, March 2022, Pages 296--306, https://doi.org/10.1093/schbul/sbab091