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      string(242) "NCT00236431 - A Randomized Double-Blind Placebo-Controlled Trial to Evaluate the Efficacy and Safety of Galantamine in Patients With Mild Cognitive Impairment (MCI) Clinically at Risk for Development of Clinically Probable Alzheimer's Disease"
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      string(256) "NCT00574132 - A Phase 3, Multicenter, Randomized, Double-Blind, Placebo-Controlled, Parallel-Group, Efficacy and Safety Trial of Bapineuzumab (AAB-001, ELN115727) In Patients With Mild to Moderate Alzheimer's Disease Who Are Apolipoprotein E4 Non- Carriers"
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      string(251) "NCT00575055 - A Phase 3, Multicenter, Randomized, Double-Blind, Placebo-Controlled, Parallel-Group, Efficacy and Safety Trial of Bapineuzumab (AAB-001, ELN115727) In Patients With Mild to Moderate Alzheimer's Disease Who Are Apolipoprotein E4 Carriers"
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  ["project_title"]=>
  string(106) "Integrated Reanalysis of Phase III Disease-Modifying Therapy Trials in Early to Mild Alzheimer’s Disease"
  ["project_narrative_summary"]=>
  string(753) "We will reanalyze de-identified data from three completed, randomized placebo-controlled Alzheimer’s disease trials available through the YODA Project (NCT00236431, NCT00574132, NCT00575055). Our goal is to understand why results can differ across studies and across patients. Specifically, we will (1) test whether some types of patients benefit more or less than others, based on baseline disease severity and other characteristics; (2) describe how symptoms change over time in the placebo groups; and (3) examine whether differences in study design (who was enrolled, which outcomes were used, visit schedules, and missing data/dropout) may help explain outcome differences. No new participants will be recruited and no new data will be collected."
  ["project_learn_source"]=>
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  ["principal_investigator"]=>
  array(7) {
    ["first_name"]=>
    string(7) "Yoonsuk"
    ["last_name"]=>
    string(3) "Cho"
    ["degree"]=>
    string(3) "PhD"
    ["primary_affiliation"]=>
    string(23) "Sungkyunkwan University"
    ["email"]=>
    string(19) "openadmed@gmail.com"
    ["state_or_province"]=>
    string(11) "Gyeonggi-do"
    ["country"]=>
    string(11) "South Korea"
  }
  ["project_key_personnel"]=>
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    [0]=>
    array(6) {
      ["p_pers_f_name"]=>
      string(10) "Seung Hyun"
      ["p_pers_l_name"]=>
      string(4) "Baek"
      ["p_pers_degree"]=>
      string(3) "PhD"
      ["p_pers_pr_affil"]=>
      string(23) "Sungkyunkwan University"
      ["p_pers_scop_id"]=>
      string(0) ""
      ["requires_data_access"]=>
      string(3) "yes"
    }
  }
  ["project_ext_grants"]=>
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    ["value"]=>
    string(2) "no"
    ["label"]=>
    string(68) "No external grants or funds are being used to support this research."
  }
  ["project_date_type"]=>
  string(18) "full_crs_supp_docs"
  ["property_scientific_abstract"]=>
  string(1530) "Background: Placebo-controlled Alzheimer’s disease (AD) trials provide an opportunity to understand why outcomes vary across studies and participants.

Objective: Using de-identified IPD from YODA trials NCT00236431, NCT00574132, and NCT00575055, we will (1) evaluate heterogeneity of treatment response by baseline severity and key characteristics, (2) characterize placebo progression, and (3) assess whether design/analytic factors (visit schedules, missingness) are associated with outcome variability.

Study Design: Retrospective secondary analysis using participant-level IPD meta-analysis with explicit trial structure.

Participants: All randomized participants in the shared IPD; longitudinal analyses require baseline and ≥1 post-baseline assessment of the analyzed endpoint.

Primary and Secondary Outcome Measure(s): Primary: trial-defined continuous cognitive/functional endpoints and prespecified heterogeneity metrics (interaction effects). Secondary: placebo progression metrics, missing-data sensitivity analyses, and exploratory comparisons of trial design features.

Statistical Analysis: Within each trial, estimate treatment effects using MMRM/mixed models with treatment, visit/time, treatment×time, and baseline endpoint (plus prespecified covariates when available). Assess heterogeneity via treatment×covariate terms. Cross-trial synthesis will use one-stage models including trial and trial×treatment terms and/or two-stage meta-analysis of trial-specific estimates."
  ["project_brief_bg"]=>
  string(1323) "Alzheimer’s disease (AD) is a progressive neurodegenerative disorder for which disease-modifying strategies have been extensively investigated. From the late 2000s to mid-2010s, several large-scale randomized controlled trials evaluated therapies targeting amyloid or tau pathology. These studies marked a pivotal transition toward pathology-driven therapeutic development.

While primary endpoints were not consistently achieved, these trials provided critical empirical evidence regarding feasibility, effect size expectations, and methodological challenges in DMT development. Notably, these trials occurred before biomarker-based enrollment became standardized, relying instead on broader clinical diagnostic standards.



Reanalysis of these trials at the individual participant level provides an opportunity to:

* Clarify whether heterogeneity of treatment response influenced overall outcomes

* Examine disease-stage–specific effects across early to mild–moderate AD populations

* Evaluate placebo-group progression patterns

* Assess whether methodological design elements contributed to observed results

The findings may contribute to generalizable scientific and medical knowledge regarding clinical trial methodology in AD and inform future trial design."
  ["project_specific_aims"]=>
  string(346) "Aim 1. To evaluate heterogeneity of treatment effects across disease stage and baseline clinical characteristics.

Aim 2. To characterize placebo progression trajectories across trials.

Aim 3. To assess whether differences in trial design, endpoint structure, or participant selection may have influenced observed treatment outcomes."
  ["project_study_design"]=>
  array(2) {
    ["value"]=>
    string(7) "meta_an"
    ["label"]=>
    string(52) "Meta-analysis (analysis of multiple trials together)"
  }
  ["project_purposes"]=>
  array(2) {
    [0]=>
    array(2) {
      ["value"]=>
      string(22) "participant_level_data"
      ["label"]=>
      string(36) "Participant-level data meta-analysis"
    }
    [1]=>
    array(2) {
      ["value"]=>
      string(37) "participant_level_data_only_from_yoda"
      ["label"]=>
      string(51) "Meta-analysis using only data from the YODA Project"
    }
  }
  ["project_research_methods"]=>
  string(1678) "The data source will consist exclusively of de-identified individual participant-level data (IPD) from three completed, randomized, placebo-controlled Phase III Alzheimer’s disease (AD) trials: NCT00236431, NCT00574132, and NCT00575055. These data were originally collected for primary efficacy and safety analyses and will be reused for secondary research within the YODA secure analytic environment. No new data collection, participant contact, or external data linkage will occur.



The analytic population will include randomized participants meeting the following criteria based solely on available trial data:

Inclusion Criteria

1. Randomized to active investigational therapy or placebo.

2. Availability of baseline demographic data.

3. Availability of at least one baseline cognitive assessment (e.g., ADAS-Cog, CDR-SB, or MMSE).

4. At least one post-baseline efficacy assessment to permit longitudinal modeling.



Exclusion Criteria

1. Absence of baseline cognitive data required for prespecified analyses.

2. No post-baseline efficacy data.

3. Participants from trial arms not relevant to placebo versus active comparisons (if applicable).



Because this is a secondary analysis, original trial diagnostic definitions, eligibility criteria, and disease classifications will not be modified. Disease stage groupings (e.g., early vs. mild AD) will be derived from original protocol-defined criteria and baseline severity ranges. No additional clinical inclusion or exclusion criteria will be imposed beyond data availability requirements necessary for statistical modeling."
  ["project_main_outcome_measure"]=>
  string(1204) "Primary Outcome Measures: Trial-specific cognitive endpoint (available across trials)

Primary outcomes will be analyzed as continuous longitudinal variables using prespecified mixed-effects modeling approaches. The primary estimand will be the difference in mean change trajectory between active treatment and placebo over time within each trial and, where appropriate, across trials with adjustment for trial identifier.



Secondary Outcome Measures

1. Clinically meaningful decline thresholds defined using established cutoffs where supported by published literature and available data (e.g., ≥4-point worsening in ADAS-Cog), analyzed as binary outcomes.

2. Time to cognitive worsening based on prespecified thresholds.

3. Longitudinal trajectories within placebo arms to characterize progression patterns descriptively.

4. Functional measures (e.g., ADL scales) where available, analyzed continuously.



Outcome harmonization will be conducted using prespecified rules limited to variables directly available in the original datasets. No novel composite endpoints will be created unless clearly derivable from existing validated measures."
  ["project_main_predictor_indep"]=>
  string(904) "Main Predictor / Independent Variable

The primary independent variable is randomized treatment assignment within each trial.

Analyses will estimate treatment effects using models that include treatment, time, and treatment-by-time interaction terms. Randomization will be preserved, and no reclassification of treatment groups will occur.

Exploratory effect-modification analyses will evaluate whether treatment effects differ by baseline disease stage (as defined by original protocol criteria), baseline cognitive severity, age, and sex. These subgroup analyses will be prespecified and interpreted cautiously, recognizing limited power for interaction testing.

In pooled analyses, a categorical trial identifier will be included to account for between-study heterogeneity. Cross-trial comparisons will be interpreted as exploratory and descriptive rather than confirmatory."
  ["project_other_variables_interest"]=>
  string(1298) "Other Variables of Interest

The following variables, if available in the requested datasets, will be included for adjustment and descriptive analyses:

Demographic Variables

 * Age (continuous; secondary categorical stratification).

 * Sex (male/female as recorded).

 * Race/ethnicity (categorized per original trial reporting).



Baseline Clinical Variables

 * Baseline ADAS-Cog, CDR-SB, and MMSE (continuous).

 * Baseline disease stage derived from original eligibility ranges.

Concomitant Treatment Variables

 * Use of symptomatic AD medications (e.g., cholinesterase inhibitors, memantine) coded as binary indicators where available.



Trial-Level Variables

 * Trial identifier (three-level categorical variable).

 * Scheduled visit timing (time since randomization).

 * Study duration.



These variables will be used for descriptive summaries, covariate adjustment, and prespecified subgroup analyses. Harmonization procedures will be limited to aligning variable definitions across trials without altering original measurement constructs. All analyses will remain within the scope of the approved Specific Aims and will not extend beyond the available dataset structure."
  ["project_stat_analysis_plan"]=>
  string(3094) "We will conduct analyses using de-identified IPD from NCT00236431, NCT00574132, and NCT00575055.

Descriptive analyses: For each trial and arm, summarize baseline demographics and clinical variables (mean/SD or median/IQR; n/%), baseline endpoint distributions, and follow-up completeness by visit. Describe discontinuation and missingness by visit/arm; if time-to-dropout is available, provide Kaplan–Meier descriptive curves.

Primary within-trial longitudinal models: For each trial-defined continuous endpoint (e.g., CDR-SB and/or ADAS-Cog 11, as available), estimate treatment effects using MMRM/linear mixed models with fixed effects for treatment, visit/time, treatment×time, baseline endpoint value, and prespecified baseline covariates (e.g., age, sex, baseline severity measures) when consistently available. Report model-estimated active vs placebo differences at prespecified follow-up windows (aligned to each trial schedule) and/or longitudinal contrasts, with 95% CIs.

Heterogeneity (effect modification): Evaluate prespecified effect modifiers (baseline disease severity/stage measures, baseline endpoint value, age, sex, and other consistently available baseline characteristics) via interaction terms (treatment×covariate and, where relevant, treatment×time×covariate). Report interaction estimates with 95% CIs and prespecified subgroup summaries. For bapineuzumab trials, preserve the original ApoE4 cohort structure (carrier vs non-carrier trials) and report stratified results as applicable.

Placebo progression: Using placebo participants, estimate mean change from baseline over time and/or trajectory parameters using the same repeated-measures framework. Summarize progression metrics by trial and compare patterns across trials descriptively; where appropriate, compute harmonized metrics (e.g., annualized change or standardized change).

Participant-level IPD meta-analysis (cross-trial): We will synthesize evidence across trials while accounting for trial structure. One-stage IPD meta-analysis will pool participants but include trial indicators and trial-by-treatment terms (and trial-by-time structure where applicable); hierarchical/random-effects components will be used where feasible. Two-stage IPD meta-analysis will derive trial-specific treatment and interaction estimates from IPD and combine them using fixed/random-effects models depending on heterogeneity. Because interventions and endpoints may differ, we will not interpret results as a single class effect; endpoint-specific results will be emphasized and synthesis will be limited to harmonized effect measures when appropriate.

Missing data: Characterize missingness mechanisms by trial/arm/visit. Primary repeated-measures models rely on principled approaches consistent with MAR assumptions; sensitivity analyses will include alternative model specifications/covariance structures and multiple imputation for key endpoints/covariates where feasible. Subgroup/interaction analyses will be clearly labeled and interpreted with multiplicity caution."
  ["project_software_used"]=>
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    [0]=>
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      ["value"]=>
      string(6) "python"
      ["label"]=>
      string(6) "Python"
    }
    [1]=>
    array(2) {
      ["value"]=>
      string(1) "r"
      ["label"]=>
      string(1) "R"
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  ["project_timeline"]=>
  string(1168) "Month 0 (Start): Immediately after YODA approval, DUA execution, and data access.

Month 0–1: Obtain/access trial documentation; build analysis datasets; define endpoint visit windows; finalize harmonization plan and analysis code skeleton.

Month 2–3: Complete descriptive tables; missingness/discontinuation characterization; placebo progression analyses (Aim 2).

Month 3–5: Complete within-trial primary longitudinal models and treatment effect estimates; prespecified heterogeneity analyses (Aim 1).

Month 5–6: Complete cross-trial participant-level meta-analysis (one-stage and/or two-stage); sensitivity analyses (missing data/model specifications).

Month 6–7: Complete exploratory design/analytic feature comparisons (Aim 3); finalize figures/tables.

Month 7–8: Draft manuscript; internal review.

Month 9: First submission to journal and/or conference abstract submission.

Month 10–12: Respond to peer review (if applicable); finalize a written results report and provide results/status update to the YODA Project prior to the end of the 12-month access period (extension requested if needed)."
  ["project_dissemination_plan"]=>
  string(671) "We plan to disseminate findings through peer-reviewed publication and scientific meetings. Potential target journals include Alzheimer’s & Dementia, JAMA Neurology, Neurology, Trials, Clinical Trials, Statistics in Medicine, and Pharmaceutical Statistics (final selection will depend on study emphasis and scope). Potential conferences include the Alzheimer’s Association International Conference (AAIC), Clinical Trials on Alzheimer’s Disease (CTAD), AD/PD, and methods-focused meetings such as the Society for Clinical Trials annual meeting and ENAR/IBS meetings. We will provide the YODA Project with a results report and publication/abstract status updates."
  ["project_bibliography"]=>
  string(1285) "
1. Hendrix, S. B. et al. Meta-analysis of Alzheimer’s disease clinical trial time savings results. Alzheimer’s & Dementia 20, e093562 (2024).

2. Cai, W., Zhang, H., Wu, Y., Yao, Y. & Zhang, J. Comparative the efficacy and safety of Gosuranemab, Semorinemab, Tilavonemab, and Zagotenemab in patients with Alzheimer’s disease: a systematic review and network meta-analysis of randomized controlled trials. Front Aging Neurosci 16, 1465871 (2024).

3. Li, D. D., Zhang, Y. H., Zhang, W. & Zhao, P. Meta-Analysis of Randomized Controlled Trials on the Efficacy and Safety of Donepezil, Galantamine, Rivastigmine, and Memantine for the Treatment of Alzheimer’s Disease. Front Neurosci 13, 472 (2019).

4. Abushouk, A.I., Elmaraezy, A., Aglan, A., Salama, R., Fouda, S., Fouda, R., and AlSafadi, A.M. Bapineuzumab for mild to moderate Alzheimer’s disease: a meta-analysis of randomized controlled trials. BMC Neurol 17, 66 (2017).

5. Salloway, S., Sperling, R., Fox Nick, C., Blennow, K., Klunk, W., Raskind, M., Sabbagh, M., Honig Lawrence, S., Porsteinsson Anton, P., Ferris, S., et al. Two Phase 3 Trials of Bapineuzumab in Mild-to-Moderate Alzheimer’s Disease. New England Journal of Medicine 370, 322-333 (2014).
"
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    ["id"]=>
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    ["url"]=>
    string(95) "https://yoda.yale.edu/wp-content/uploads/2026/02/YODA-Project-Protocol-2026-0148-2026-04-08.pdf"
    ["link"]=>
    string(88) "https://yoda.yale.edu/data-request/2026-0148/yoda-project-protocol-2026-0148-2026-04-08/"
    ["alt"]=>
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    ["author"]=>
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    ["description"]=>
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    ["caption"]=>
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    ["uploaded_to"]=>
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    ["id"]=>
    int(19077)
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    string(38) "YODA-Project-Review-2026-0148_site.pdf"
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    int(1074857)
    ["url"]=>
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    ["link"]=>
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data partner
array(1) {
  [0]=>
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}


pi country
array(0) {
}


pi affil
array(0) {
}


products
array(0) {
}


num of trials
array(1) {
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  string(1) "0"
}


res
array(1) {
  [0]=>
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}