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      string(235) "NCT03201965 - A Randomized Phase 3 Study to Evaluate the Efficacy and Safety of Daratumumab in Combination With Cyclophosphamide, Bortezomib and Dexamethasone (CyBorD) Compared to CyBorD Alone in Newly Diagnosed Systemic AL Amyloidosis"
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  ["project_title"]=>
  string(119) "Bone Marrow Plasma Cell Burden and Clinical Outcomes in AL Amyloidosis: A Retrospective Analysis of the ANDROMEDA Trial"
  ["project_narrative_summary"]=>
  string(844) "AL amyloidosis is a plasma cell dyscrasia leading to the production of abnormal free light chains depositing in target organs. In multiple myeloma, a related plasma cell disorder, the burden of disease correlates to overall survival and characterizes disease biology. However, it is unknown if this has any prognostic importance in AL amyloidosis. This study will use data from the ANDROMEDA trial to evaluate whether baseline bone marrow plasma cell percentage is associated with outcomes. We hypothesize that plasma cell percentage is not independently associated with outcomes. Instead, disease biology is driven more by organ involvement and light chain burden than marrow plasmacytosis. If this hypothesis is incorrect, it offers an additional vantage point to help redefine AL amyloidosis staging and capture the patients at highest risk."
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    ["first_name"]=>
    string(5) "Giada"
    ["last_name"]=>
    string(7) "Bianchi"
    ["degree"]=>
    string(2) "MD"
    ["primary_affiliation"]=>
    string(28) "Dana-Farber Cancer Institute"
    ["email"]=>
    string(30) "Giada_Bianchi@DFCI.HARVARD.EDU"
    ["state_or_province"]=>
    string(2) "MA"
    ["country"]=>
    string(13) "United States"
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      string(8) "Shahrier"
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      string(7) "Hossain"
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      string(6) "PharmD"
      ["p_pers_pr_affil"]=>
      string(28) "Dana-Farber Cancer Institute"
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      string(5) "Grace"
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      string(5) "Ferri"
      ["p_pers_degree"]=>
      string(2) "MD"
      ["p_pers_pr_affil"]=>
      string(36) "Beth Israel Deaconess Medical Center"
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      string(4) "Redd"
      ["p_pers_degree"]=>
      string(2) "MS"
      ["p_pers_pr_affil"]=>
      string(28) "Dana-Farber Cancer Institute"
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      string(4) "Emre"
      ["p_pers_l_name"]=>
      string(7) "Karayol"
      ["p_pers_degree"]=>
      string(2) "MD"
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      string(21) "Mount Auburn Hospital"
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    ["label"]=>
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  ["property_scientific_abstract"]=>
  string(1685) "Background: In multiple myeloma, the burden of clonal plasma cells in the bone marrow has prognostic significance for the cancer. However, it is unknown if those holds true for AL amyloidosis, a related plasma cell disorder. The ANDROMEDA trial assigned patients with newly diagnosed AL amyloidosis to treatment with either bortezomib, cyclophosphamide, dexamethasone (VCD) or daratumumab with VCD. Patients were followed for a median of 61.4 months and thus provides a longitudinal view of patients and their outcomes.  

Objective: To evaluate whether baseline bone marrow plasma cell percentage is independently associated with clinical outcomes in patients with AL amyloidosis treated in the ANDROMEDA.

Study Design: Retrospective participant-level analysis of a randomized clinical trial.

Participants: All patients enrolled in the ANDROMEDA trial with available baseline bone marrow plasma cell percentage.

Primary Outcome Measure:

-Overall survival

Secondary Outcome Measures:

-Cardiac response (NT-proBNP reduction) and time to cardiac response

-Renal Response and time to organ response

-Progression-free survival

-Duration of hematologic response

-Time to hematological response

-Major Organ Deterioration Progression Free Survival (MOD PFS)

Statistical Analysis: Plasma cell percentage will be analyzed as both a continuous and categorical variable. Kaplan-Meier models will be used to assess time-to-event endpoints Cox proportional hazards models will evaluate associations with survival outcomes, adjusting for covariables. Logistic regression will assess binary response outcomes."
  ["project_brief_bg"]=>
  string(2316) "Multiple myeloma is a clonal plasma cell disorder characterized by end organ damage such as hypercalcemia, renal dysfunction, anemia, and bone disease. In this hematologic malignancy, the bone marrow plasma cell (BMPC) burden is correlated with clinical outcomes.  

A retrospective study completed by Al Saleh et al., showed patients had worse outcomes in patients with (BMPC) of ≥ 60% as compared to those with <60%. Progression free survival and overall survival in those with higher BMPC was noted to be 22.6 months and 53.4 months, respectively. This is in stark contrast to those with lower plasma cell burdens, 32.1 months and 75.4 months. This was found to be an independent risk factor even when adjusting for cytogenetics and across different time intervals (thus capturing the effect of novel therapies). A significantly higher initial plasma cell burden shows a reduction in PFS by nearly 10 months and shorter life expectancy of nearly 2 years. 

AL amyloidosis is a plasma cell dyscrasia characterized by the production of misfolded immunoglobulin light chains leading to multiorgan amyloid deposition. Unlike multiple myeloma, the degree of bone marrow plasma cell infiltration in AL amyloidosis is often modest, and its role in predicting outcomes remains uncertain. Current staging systems rely primarily on cardiac biomarkers (NT-proBNP, troponin) and free light chain burden rather than marrow plasma cell percentage. The ANDROMEDA trial provides an opportunity to evaluate this question in a large, prospective cohort of newly diagnosed patients treated with daratumumab plus standard-of-care therapy that have been followed over 5 years. Understanding whether bone marrow plasma cell burden adds prognostic information beyond established biomarkers could refine disease classification and risk stratification. This study will assess whether baseline plasma cell percentage is independently associated with hematologic response, organ response (cardiac), progression-free survival, and overall survival. We will also explore whether plasma cell burden modifies treatment effect or interacts with baseline disease stage. Findings will inform whether bone marrow plasmacytosis should be incorporated into future prognostic models or treatment decision frameworks in AL amyloidosis."
  ["project_specific_aims"]=>
  string(872) "Aim 1: To determine whether baseline bone marrow plasma cell percentage is associated with overall survival and progression-free survival in AL amyloidosis patients in the ANDROMEDA trial.

•	Hypothesis: Baseline plasma cell percentage has limited independent prognostic value for survival outcomes after adjustment for cardiac biomarkers and light chain burden. 



Aim 2: To evaluate the association between bone marrow plasma cell percentage and hematologic and organ responses.

•	Hypothesis: Baseline plasma cell percentage has limited association with hematologic CR/VGPR or organ response rates. 



Aim 3: To explore whether baseline bone marrow plasma cell percentage modifies treatment effect of daratumumab-based therapy.

•	Hypothesis: Limited interaction exists between plasma cell percentage and treatment arm."
  ["project_study_design"]=>
  array(2) {
    ["value"]=>
    string(14) "indiv_trial_an"
    ["label"]=>
    string(25) "Individual trial analysis"
  }
  ["project_purposes"]=>
  array(1) {
    [0]=>
    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(258) "All participants enrolled in the ANDROMEDA trial will be assessed for inclusion 

•	Inclusion: Confirmed AL amyloidosis, available baseline bone marrow plasma cell percentage, received at least one dose of study treatment 

•	Exclusion:  None"
  ["project_main_outcome_measure"]=>
  string(1194) "Primary Outcomes:

•	Overall survival (OS; time from randomization to death) 



Secondary Outcomes:

•	Hematologic response (CR, VGPR)  as well as depth of response – best response and time to response – (TTR; time from randomization to first response with death as a competing event)

•	Cardiac response (≥30% and ≥300 ng/L NT-proBNP reduction, if available), including Depth of response – best response and time to response – (TTR; time from randomization to first response with death as a competing event)

•	Renal response (standard criteria) including Depth of response – best response  and time to response (TTR; time from randomization to first response with death as a competing event)

•	Time to next therapy (TTNT; time from randomization to start of non-protocol therapy with death as a competing event)

•	Progression-free survival (PFS; time from randomization to hematologic progression or death) 

•	Major organ deterioration progression-free survival (MOD-PFS; time from randomization to hematologic progression, major organ deterioration including end-stage cardiac or renal failure, or death) "
  ["project_main_predictor_indep"]=>
  string(149) "•	Bone marrow plasma cell percentage at baseline 

•	Modeled as: Continuous (%)  and Categorical (e.g., <10%, 10–29%, ≥30% )

"
  ["project_other_variables_interest"]=>
  string(351) "•	Age 

•	Sex 

•	Baseline cardiac stage (I–IIIA) 

•	Baseline NT-proBNP 

•	Baseline Cardiac troponin 

•	dFLC

•	EGFR

•	Treatment arm (daratumumab vs. control)

•	Cytogenetics - 1q gain, t(11;14), del17p, t( 4;14), t(14;16), t(14;20), del(1p32) 

•	Involved organs

"
  ["project_stat_analysis_plan"]=>
  string(3639) "Based on the 112 deaths and median follow-up of 60+ months reported in the final ANDROMEDA analysis, we would have approximately 80% power to detect a minimum hazard ratio of 1.3 per standard-deviation (SD) increase in baseline bone marrow plasma cell percentage, assuming a two-sided 5% significance level and similar number of events in the analysis cohort. However, since SD units are less intuitive, HRs will be reported per 10 percentage point increase and by discrete percentage groups (<10, 10-29, ≥30%). Since variability of plasma cell percentage is not available from the published data, the calculation will be updated using the observed distribution and OS events in the final analysis cohort. The primary analysis will evaluate the association between baseline plasma cell percentage, modeled continuously and reported as 10 percentage point increase, and OS using a multivariable Cox regression adjusted for treatment arm and pre-specified clinically relevant prognostic factors. Baseline demographics will be reported for the final analysis cohort using descriptive statistics and stratified by plasma cell burden with univariate tests of association (Wilcoxon/Kruskal-Wallis rank-sum for continuous variables, and Fisher’s exact test for discrete variables where appropriate). Between-group differences may be summarized using standardized differences. Median follow-up for the final analysis cohort will be estimated using the reverse Kaplan-Meier (KM) method. OS, PFS, and MOD-PFS outcomes will be assessed using the KM method, and discrete group differences will be assessed with log-rank tests. Uni- and multi-variable Cox regressions will be summarized with hazard ratios, 95% confidence intervals, and Wald p-values for plasma cell percentage and other model covariates. Time-to-response and next treatment outcomes will be evaluated using cumulative incidence and competing risks regressions with death as a competing event. Gray’s test will be used to assess group differences in incidences, and regressions will be summarized for the event of interest with subdistribution HRs, 95% confidence intervals, and Wald p-values for each covariate. Logistic regressions will be fit for binary outcomes including hematologic and organ response and summarized with odds ratios, 95% confidence intervals, and Wald p-values for each covariate. Multi-variable Cox, competing risks, and logistic models may be adjusted for clinical factors including stage, biomarkers, and treatment arm. Variable selection techniques may be used; however, we will prefer adjustment variables to be selected based primarily on clinical relevance while considering the number of observed events and model complexity.

Exploratory analyses of interaction terms of plasma cell percentage by treatment arm will be evaluated; however, these models may be underpowered and will be interpreted with caution.

Models will be fit using complete case analysis with respect to plasma cell percentage. The extent and patterns of missing covariate data will be summarized. Complete-case analysis may be used when missingness is limited. We will prefer sensitivity analyses to evaluate the impact of missing data on clinical outcomes before multiple imputation is considered. However, if imputation is used, models will be fit using the mice R package, and results will be pooled using Rubin’s rules. Imputation will not be used on the primary exposure itself. Additional sensitivity analyses evaluating extreme plasma cell values, alternative cut points, and non-linear modeling of continuous plasma cell values will also be explored."
  ["project_software_used"]=>
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    [0]=>
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      ["value"]=>
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      ["label"]=>
      string(1) "R"
    }
    [1]=>
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      ["value"]=>
      string(7) "rstudio"
      ["label"]=>
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  ["project_timeline"]=>
  string(275) "•	Month 0–1: Data access + cleaning  

•	Month 2: Primary analysis (OS/PFS models), secondary + sensitivity analyses, manuscript drafting 

•	Month 3: Internal revision + submission, conference abstract submission

•	Month 4-5+: Revisions 

"
  ["project_dissemination_plan"]=>
  string(364) "Results will be submitted as a full manuscript to a hematology/oncology journal such as Blood or Blood Advances. Findings will also be presented at major conferences such as ASH. Target audience includes hematologists, amyloidosis specialists, and clinical trialists. Results may inform future risk stratification models and trial design in AL amyloidosis.

"
  ["project_bibliography"]=>
  string(1776) "

Sanchorawala V. Systemic Light Chain Amyloidosis. N Engl J Med. 2024;390(24):2295-2307. doi:10.1056/NEJMra2304088
Muchtar E, Gertz MA, Kourelis TV, et al. Bone marrow plasma cells 20% or greater discriminate presentation, response, and survival in AL amyloidosis. Leukemia. 2020;34(4):1135-1143. doi:10.1038/s41375-019-0655-x
Kourelis TV, Kumar SK, Gertz MA, et al. Coexistent multiple myeloma or increased bone marrow plasma cells define equally high-risk populations in patients with immunoglobulin light chain amyloidosis. J Clin Oncol. 2013;31(34):4319-4324. doi:10.1200/JCO.2013.50.8499
Dittus C, Uwumugambi N, Sun F, Sloan JM, Sanchorawala V. The Effect of Bone Marrow Plasma Cell Burden on Survival in Patients with Light Chain Amyloidosis Undergoing High-Dose Melphalan and Autologous Stem Cell Transplantation. Biol Blood Marrow Transplant. 2016;22(9):1729-1732. doi:10.1016/j.bbmt.2016.05.027
Tovar N, Rodríguez-Lobato LG, Cibeira MT, et al. Bone marrow plasma cell infiltration in light chain amyloidosis: impact on organ involvement and outcome. Amyloid. 2018;25(2):79-85. doi:10.1080/13506129.2018.1443439
Kastritis E, Palladini G, Minnema MC, et al. Daratumumab-Based Treatment for Immunoglobulin Light-Chain Amyloidosis. N Engl J Med. 2021;385(1):46-58. doi:10.1056/NEJMoa2028631
Al Saleh AS, Parmar HV, Visram A, Muchtar E, Buadi FK, Go RS, Dispenzieri A, Kapoor P, Warsame R, Lacy MQ, Dingli D, Leung N, Gonsalves WI, Kourelis TV, Gertz MA, Kyle RA, Rajkumar SV, Kumar SK. Increased Bone Marrow Plasma-Cell Percentage Predicts Outcomes in Newly Diagnosed Multiple Myeloma Patients. Clin Lymphoma Myeloma Leuk. 2020 Sep;20(9):596-601. doi: 10.1016/j.clml.2020.03.012. Epub 2020 Apr 7.

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    ["filesize"]=>
    int(108113)
    ["url"]=>
    string(100) "https://yoda.yale.edu/wp-content/uploads/2026/07/YODA-Project-Due-Diligence-Assessment-2026-0572.pdf"
    ["link"]=>
    string(93) "https://yoda.yale.edu/data-request/2026-0572/yoda-project-due-diligence-assessment-2026-0572/"
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    ["name"]=>
    string(47) "yoda-project-due-diligence-assessment-2026-0572"
    ["status"]=>
    string(7) "inherit"
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    string(15) "application/pdf"
    ["type"]=>
    string(11) "application"
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    string(3) "pdf"
    ["icon"]=>
    string(62) "https://yoda.yale.edu/wp/wp-includes/images/media/document.png"
  }
  ["project_title_link"]=>
  array(21) {
    ["ID"]=>
    int(20195)
    ["id"]=>
    int(20195)
    ["title"]=>
    string(44) "YODA Project Protocol - 2026-0572 - 26-09-21"
    ["filename"]=>
    string(44) "YODA-Project-Protocol-2026-0572-26-09-21.pdf"
    ["filesize"]=>
    int(127908)
    ["url"]=>
    string(93) "https://yoda.yale.edu/wp-content/uploads/2026/07/YODA-Project-Protocol-2026-0572-26-09-21.pdf"
    ["link"]=>
    string(86) "https://yoda.yale.edu/data-request/2026-0572/yoda-project-protocol-2026-0572-26-09-21/"
    ["alt"]=>
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    ["caption"]=>
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    ["name"]=>
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    ["status"]=>
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    ["uploaded_to"]=>
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    ["date"]=>
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  }
  ["project_review_link"]=>
  array(21) {
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    ["id"]=>
    int(20196)
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    ["filesize"]=>
    int(1321159)
    ["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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}


res
array(1) {
  [0]=>
  string(1) "3"
}