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  ["project_title"]=>
  string(125) "Association between baseline cardiovascular risk and cardiovascular effect of abiraterone acetate in advanced prostate cancer"
  ["project_narrative_summary"]=>
  string(696) "Doctors often prescribe a medication called abiraterone acetate to treat advanced prostate cancer. While this drug helps fight cancer effectively, some research suggests it may increase the risk of heart problems. However, we do not fully understand how these heart-related risks might differ among different patients. This research project will analyze data from multiple clinical trials where patients received either abiraterone acetate or standard treatment to better understand this association. By examining detailed patient data, we hope to identify whether certain pre-existing health factors make some patients more likely to experience heart complications while taking this medication. "
  ["project_learn_source"]=>
  string(12) "scien_public"
  ["principal_investigator"]=>
  array(7) {
    ["first_name"]=>
    string(6) "Wataru"
    ["last_name"]=>
    string(9) "Fukuokaya"
    ["degree"]=>
    string(2) "MD"
    ["primary_affiliation"]=>
    string(39) "The Jikei University School of Medicine"
    ["email"]=>
    string(20) "wfukuokaya@gmail.com"
    ["state_or_province"]=>
    string(5) "Tokyo"
    ["country"]=>
    string(5) "Japan"
  }
  ["project_key_personnel"]=>
  array(3) {
    [0]=>
    array(6) {
      ["p_pers_f_name"]=>
      string(9) "Keiichiro"
      ["p_pers_l_name"]=>
      string(4) "Mori"
      ["p_pers_degree"]=>
      string(7) "MD, PhD"
      ["p_pers_pr_affil"]=>
      string(39) "The Jikei University School of Medicine"
      ["p_pers_scop_id"]=>
      string(0) ""
      ["requires_data_access"]=>
      string(2) "no"
    }
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      ["p_pers_f_name"]=>
      string(8) "Takahiro"
      ["p_pers_l_name"]=>
      string(6) "Kimura"
      ["p_pers_degree"]=>
      string(7) "MD, PhD"
      ["p_pers_pr_affil"]=>
      string(39) "The Jikei University School of Medicine"
      ["p_pers_scop_id"]=>
      string(0) ""
      ["requires_data_access"]=>
      string(2) "no"
    }
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      ["p_pers_f_name"]=>
      string(7) "Akihiro"
      ["p_pers_l_name"]=>
      string(8) "Hirakawa"
      ["p_pers_degree"]=>
      string(3) "PhD"
      ["p_pers_pr_affil"]=>
      string(26) "Institute of Science Tokyo"
      ["p_pers_scop_id"]=>
      string(0) ""
      ["requires_data_access"]=>
      string(3) "yes"
    }
  }
  ["project_ext_grants"]=>
  array(2) {
    ["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(1411) "Background

Meta-analyses suggest androgen receptor pathway inhibitors (ARPIs) increase cardiovascular risk in advanced prostate cancer patients. Among ARPIs, abiraterone acetate plus prednisone (AAP) shows higher cardiovascular event incidence. However, the association between baseline cardiovascular risk and AAP's cardiovascular effects remains unclear.



Objective

To evaluate whether AAP's cardiovascular effect versus placebo/observation varies with baseline cardiovascular risk in advanced prostate cancer patients.



Study design

Individual participant data meta-analysis and systematic review.



Participants

Advanced prostate cancer patients treated with AAP or standard-of-care in randomized controlled trials.



Primary and secondary measures

Primary outcome is cumulative incidence of major adverse cardiovascular events (MACE), defined as first occurrence of cardiovascular death, ischemic heart disease, heart failure, or cerebrovascular accident. A second enriched MACE (MACE2) includes arrhythmia, non-ischemic cardiomyopathies, valvular heart disease, and venous thromboembolism.



Statistical analysis

After systematic database search, we will evaluate AAP's cardiovascular effects versus placebo/observation based on predicted cardiovascular risk using the MACE risk prediction model."
  ["project_brief_bg"]=>
  string(1331) "Treatment for patients with advanced prostate cancer has evolved significantly with the introduction of androgen receptor pathway inhibitors (ARPIs) to standard-of-care (SOC), including androgen deprivation therapy (ADT) (Armstrong et al., 2022; Attard et al., 2022; Beer et al., 2014; Chi et al., 2019; Davis et al., 2019; de Bono et al., 2011; Fizazi et al., 2017, 2020, 2022; James et al., 2017; Ryan et al., 2013; Scher et al., 2012; Smith et al., 2018; Sternberg et al., 2020). While this new therapy has improved oncological outcomes in this population, meta-analyses suggest that adding ARPIs to SOC increases cardiovascular risk (El-Taji et al., 2024). Among ARPIs, previous studies have indicated that AAP is associated with a higher risk of cardiovascular events compared with other ARPIs (Conover et al., 2023; Liu et al., 2023). However, Despite these known risks, a knowledge gap exists regarding how the cardiovascular effects of AAP may vary among different populations based on underlying characteristics and cardiovascular risk factors. Investigating the association between baseline cardiovascular risk and cardiovascular outcomes would enable more personalized risk-benefit assessments and could inform the identification of patients who might require more careful monitoring or alternative treatment strategies."
  ["project_specific_aims"]=>
  string(226) "In patients with advanced prostate cancer who are receiving ADT (with or without prednisone), this study aims to determine whether the effects of AAP on cardiovascular outcomes differ according to baseline cardiovascular risk."
  ["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(56) "new_research_question_to_examine_treatment_effectiveness"
      ["label"]=>
      string(114) "New research question to examine treatment effectiveness on secondary endpoints and/or within subgroup populations"
    }
    [1]=>
    array(2) {
      ["value"]=>
      string(49) "new_research_question_to_examine_treatment_safety"
      ["label"]=>
      string(49) "New research question to examine treatment safety"
    }
  }
  ["project_research_methods"]=>
  string(543) "This study will include patients with advanced prostate cancer who are randomized to either AAP or placebo / observation, both with SOC, in clinical trials. Randomized controlled trials (RCTs) will be eligible when patients with advanced prostate cancer are randomized to receive AAP compared with placebo / observation, both with SOC. Non-RCT studies and studies without available IPD will be excluded. To minimize measurement bias, RCTs that did not measure severe adverse events after study treatment discontinuation will also be excluded. "
  ["project_main_outcome_measure"]=>
  string(1095) "The primary outcome measure is the cumulative incidence of major adverse cardiovascular events (MACEs), defined as the composite of the first occurrence of death from cardiovascular causes, ischemic heart disease, heart failure, or cerebrovascular accident. These events are defined according to Common Terminology Criteria for Adverse Events. Treatment effect will be measured by the subdistribution hazard ratio estimated by the Fine‐Gray subdistribution hazard model and the difference in restricted mean time lost (RMTL) based on cumulative incidence function plots. A cardiovascular disease death is defined as a death due to cardiovascular disease if cardiovascular disease represents the cause of death or if death occurs within 1 month of a cardiovascular disease hospitalization, irrespective of the stated cause of death. Non-cardiovascular disease death will be used for competing risk. Additionally, a second enriched MACE (MACE2) will include arrhythmia, non-ischemic cardiomyopathies, valvular heart disease, and venous thromboembolism in addition to the primary MACE components."
  ["project_main_predictor_indep"]=>
  string(30) "Predicted cardiovascular risk."
  ["project_other_variables_interest"]=>
  string(908) "Age (continuous), body mass index (continuous), systolic blood pressure (continuous), total cholesterol (continuous), high-density lipoprotein cholesterol (continuous), sex (categorical), ethnic group (categorical), smoking status (categorical), atypical antipsychotic use (categorical), glucocorticoid use (categorical), history of migraine (categorical), history of rheumatoid arthritis (categorical), history of atrial fibrillation (categorical), history of chronic kidney disease (categorical), history of severe mental illness (categorical), history of systemic lupus erythematosus (categorical), history of erectile dysfunction (categorical), antihypertensive use (categorical), history of diabetes (categorical), and family history of heart disease (categorical). If a continuous variable is coded as a categorical variable during the data anonymization process, the variable will be used accordingly."
  ["project_stat_analysis_plan"]=>
  string(4082) "Literature Search

We will perform a systematic search of PubMed, Web of Science, MEDLINE, and Cochrane Library to identify RCTs comparing the addition of AAP to SOC in patients with advanced prostate cancer published through December 31, 2024. The references of identified studies will be searched for additional relevant studies. 



Eligible Research Identification

RCTs will be eligible to the following analysis when patients with advanced prostate cancer are randomized to receive AAP or placebo, both with SOC. Non-RCT studies and studies without available IPD will be excluded. To minimize measurement bias, RCTs that did not measure serious adverse events after study treatment discontinuation will also be excluded. For multiple publications of the same trial, the most recent, complete, and updated data will be included in the final analysis.



Heterogeneity of Treatment Effect Analysis

This analysis plan adheres the PRISMA-IPD statement and TRIPOD-cluster checklist (Debray et al., 2023; Stewart et al., 2015). There are two statistical approaches for conducting an IPD meta-analysis to account for clustering within each of the trials: one-stage and two-stage (Riley, 2021). We will implement both approaches but will default to one-stage analysis when low event rates and small sample sizes of the included trials make two-stage analysis unfeasible (Burke et al., 2017).



1. Overview

A risk modeling-based investigation will examine the heterogeneity of cardiovascular effects of AAP versus SOC on MACEs in patients with advanced prostate cancer (Kent et al., 2020). Because non-cardiovascular disease death could act as a competing risk for MACE and bias the results (Austin et al., 2016), Fine-Grey subdistribution hazard regression model, with non-cardiovascular disease death as a competing risk, will be performed. Developing a cardiovascular risk model internally using the pooled IPD dataset presents challenges because the incidence of MACEs is expected to be rare in published data of major, large-scale RCTs (Attard et al., 2022; de Bono et al., 2011; Fizazi et al., 2017, 2022; James et al., 2017; Ryan et al., 2013), and approximately 40 to 50 events per variable are needed to ensure accurate estimation of regression coefficients and associated quantities in the Fine-Grey subdistribution hazard model (Austin et al., 2017). Therefore, externally developed, well-established cardiovascular risk models, which have been validated for performance in patients with prostate cancer, will be used to calculate cardiovascular risk. The Framingham Risk Score (FRS) will be used if all variables needed to calculate FRS are available in the IPD dataset (D’Agostino et al., 2008). If there is at least one completely missing variable in the dataset, other cardiovascular risk models including QRISK3 (Hippisley-Cox et al., 2017) and SCORE2/SCORE-OP (SCORE2-OP working group and ESC Cardiovascular risk collaboration, 2021; SCORE2 working group and ESC Cardiovascular risk collaboration, 2021) will be used. 



2. Missing Covariate Imputation

Missing baseline covariate values will be multiply imputed using a multivariate imputation by chained equations (MICE) algorithm (van Buuren & Groothuis-Oudshoorn, 2011). Two-stage multilevel imputation will address systematic or sporadic missing values in the clustered data (Riley, 2021).



3. Assessing Heterogeneity in Cardiovascular Effect from Cardiovascular Risk Scores

Subgroups will be defined based on the distribution of cardiovascular risk scores. A cardiovascular effect of AAP will be estimated for each risk group. The effect will be quantified based on subdistribution hazard ratio and the difference in RMTL as appropriate. The subdistribution hazard ratios will be calculated using an extension of the Fine-Gray subdistribution hazards regression model that accounts for within-trial patient correlations (Zhou et al., 2012). Alternative models may be applied if convergence issues arise."
  ["project_software_used"]=>
  array(2) {
    ["value"]=>
    string(1) "r"
    ["label"]=>
    string(1) "R"
  }
  ["project_timeline"]=>
  string(193) "Day 0: Approval of the project

Day 30: Data transfer

Day 60: Data processing

Day 120: Data analysis

Day 150: Manuscript writing

Day 180: Manuscript submission"
  ["project_dissemination_plan"]=>
  string(240) "The results of this project are expected to result in the development of a manuscript suitable for publication in a uro-oncology or cardiovascular journal. Results will be presented at appropriate uro-oncology or cardiovascular conferences."
  ["project_bibliography"]=>
  string(19232) "
Armstrong, A. J., Azad, A. A., Iguchi, T., Szmulewitz, R. Z., Petrylak, D. P., Holzbeierlein, J., Villers, A., Alcaraz, A., Alekseev, B., Shore, N. D., Gomez-Veiga, F., Rosbrook, B., Zohren, F., Yamada, S., Haas, G. P., & Stenzl, A. (2022). Improved survival with enzalutamide in patients with metastatic hormone-sensitive prostate cancer. Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology, 40(15), 1616–1622.
Attard, G., Murphy, L., Clarke, N. W., Cross, W., Jones, R. J., Parker, C. C., Gillessen, S., Cook, A., Brawley, C., Amos, C. L., Atako, N., Pugh, C., Buckner, M., Chowdhury, S., Malik, Z., Russell, J. M., Gilson, C., Rush, H., Bowen, J., … Systemic Therapy in Advancing or Metastatic Prostate cancer: Evaluation of Drug Efficacy (STAMPEDE) investigators. (2022). Abiraterone acetate and prednisolone with or without enzalutamide for high-risk non-metastatic prostate cancer: a meta-analysis of primary results from two randomised controlled phase 3 trials of the STAMPEDE platform protocol. Lancet, 399(10323), 447–460.
Austin, P. C., Allignol, A., & Fine, J. P. (2017). The number of primary events per variable affects estimation of the subdistribution hazard competing risks model. Journal of Clinical Epidemiology, 83, 75–84.
Austin, P. C., Lee, D. S., & Fine, J. P. (2016). Introduction to the analysis of survival data in the presence of competing risks. Circulation, 133(6), 601–609.
Beer, T. M., Armstrong, A. J., Rathkopf, D. E., Loriot, Y., Sternberg, C. N., Higano, C. S., Iversen, P., Bhattacharya, S., Carles, J., Chowdhury, S., Davis, I. D., de Bono, J. S., Evans, C. P., Fizazi, K., Joshua, A. M., Kim, C.-S., Kimura, G., Mainwaring, P., Mansbach, H., … PREVAIL Investigators. (2014). Enzalutamide in metastatic prostate cancer before chemotherapy. The New England Journal of Medicine, 371(5), 424–433.
Burke, D. L., Ensor, J., & Riley, R. D. (2017). Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ. Statistics in Medicine, 36(5), 855–875.
Chi, K. N., Agarwal, N., Bjartell, A., Chung, B. H., Pereira de Santana Gomes, A. J., Given, R., Juárez Soto, Á., Merseburger, A. S., Özgüroğlu, M., Uemura, H., Ye, D., Deprince, K., Naini, V., Li, J., Cheng, S., Yu, M. K., Zhang, K., Larsen, J. S., McCarthy, S., … TITAN Investigators. (2019). Apalutamide for metastatic, castration-sensitive prostate cancer. The New England Journal of Medicine, 381(1), 13–24.
Conover, M. M., Weaver, J., Fan, B., Leitz, G., Richarz, U., Li, Q., & Gifkins, D. (2023). Cardiovascular outcomes among patients with castration-resistant prostate cancer: A comparative safety study using US administrative claims data. The Prostate, 83(7), 729–739.
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