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  ["property_scientific_abstract"]=>
  string(2179) "Background:
Surrogate endpoints are used to replace clinical endpoints in evaluating new treatments, but their validity requires demonstration of their reliability in predicting treatment effects. Statistical approaches, such as individual and trial level association assessments can help determine the strength of evidence for surrogacy. Clinical trials in multiple myeloma (MM) typically use progression-free survival (PFS) or time to progression (TTP) as primary endpoints, but the identification of alternative surrogate endpoints, such as Minimal Residual Disease (MRD) negativity is increasing in interest due to its strong correlation with both PFS and overall survival (OS). There are some meta-analyses attempting to demonstrate the association between MRD and OS, but standard statistical methods were not used for evaluation.
Objective:
To validate MRD as surrogate endpoint in MM with standard statistical surrogate evaluation method.
Study Design and Participants:
Subjects will be pooled into two subgroups: NCT02076009, NCT02136134 and NCT03180736 will be Relapsed or Refractory Multiple Myeloma (RRMM) group, while NCT02195479 and NCT02252172 will be newly diagnosed multiple myeloma (NDMM) group.
Primary and Secondary Outcome Measure(s):
Individual level and trial level coefficients of determination to evaluate MRD negativity rate as surrogate endpoint for OS in RRMM and NDMM.
Individual level and trial level coefficients of determination to evaluate MRD negativity with CR rate as surrogate endpoint for OS in RRMM and NDMM.
Individual level and trial level coefficients of determination to evaluate longitudinal MRD result as surrogate endpoint for OS in RRMM and NDMM.
Statistical Analysis:
Surrogacy of MRD negativity rate and MRD negativity with CR rate will be evaluated with two-stage model by Burzykowski, in which, one marginal distribution can be a proportional odds logistic regression, while the other is a proportional hazards model. While Surrogacy of longitudinal MRD result will be evaluated with joint modeling of longitudinal measurements and event time data by Henderson." ["project_brief_bg"]=> string(3183) "The development of new drugs is hindered by the slow and costly clinical development process, and the choice of endpoint used to assess drug efficacy plays an important role in this process. Surrogate endpoints or biomarkers can be used to measure drug efficacy more cheaply, conveniently, frequently, or earlier than the true clinical endpoint. However, historical failures have led to controversies about the use of surrogate endpoints in medical research, and the effect of treatment on the surrogate endpoint must reliably predict the effect on the clinical endpoint [1-6].
The use of biomarkers as surrogate endpoints for drug approval has become increasingly important in oncology due to the desire to quickly approve new drugs. Shortening clinical trials and using surrogate endpoints, such as disease-free survival and progression-free survival, may decrease evaluation costs and potential problems with noncompliance and missing data. However, the value of these endpoints as surrogate endpoints for overall survival has been questioned, particularly in advanced disease.
Advancements in therapeutic options for multiple myeloma, including proteasome inhibitors, immunomodulators, and antibody therapies, have greatly improved patient prognosis. However, traditional endpoint measures such as PFS may delay the development of better therapies. Surrogate endpoints, such as MRD status, have been explored as a potential alternative. Studies have shown that MRD monitoring provides a more sensitive determination of disease burden than complete response (CR), and MRD-negative responses are associated with superior survival outcomes [7, 8]. The use of MRD status as a potential endpoint for clinical trials in multiple myeloma has been the subject of an FDA symposium. In order for an endpoint to be considered a surrogate "reasonably likely to predict clinical benefit" (that is, potentially acceptable for accelerated drug approval), it needs to meet two key criteria proposed by Prentice [9]: a surrogate endpoint must, (1) be correlated at a patient level with the clinical benefit endpoint independent of treatment, and (2) fully capture the net effect of treatment on the clinical benefit endpoint. That is, the treatment effect on the surrogate endpoint must reliably predict the treatment effect on the clinical benefit endpoint and not be merely a correlate of activity between two endpoint measurements.
The preferred method for validating surrogate endpoints is through a meta-analytic, multi-trial approach, a two-stage model [10] to derive both trial-level and individual-level surrogacy. However, in multiple myeloma, most published meta-analyses have only addressed the first of the two Prentice criteria, which is demonstrating correlation between MRD status and PFS or OS at the trial level. Therefore, with the individual-level data I?ve requested, both trial-level and individual-level surrogacy of MRD to OS in RRMM and NDMM can be validated. This will potentially change the FDA's perspective on the use of MRD as a surrogate endpoint for multiple myeloma, which may accelerate the drug approval process while ensuring robust surrogacy." ["project_specific_aims"]=> string(760) "Specific aims:
The overall objective of this study is to find out whether MRD negativity can be a statistically validated surrogate endpoint for RRMM and NDMM.
Specific hypotheses:
1. MRD negativity rate can serve as the surrogate endpoint both on individual level (coefficients of determination > 0.75) and trial level (coefficients of determination > 0.75).
2. MRD negativity with CR rate can serve as the surrogate endpoint both on individual level (coefficients of determination > 0.75) and trial level (coefficients of determination > 0.75).
3. Longitudinal MRD result can serve as the surrogate endpoint both on individual level (coefficients of determination > 0.75) and trial level (coefficients of determination > 0.75)." ["project_study_design"]=> array(2) { ["value"]=> string(5) "other" ["label"]=> string(5) "Other" } ["project_study_design_exp"]=> string(0) "" ["project_purposes"]=> array(1) { [0]=> array(2) { ["value"]=> string(5) "Other" ["label"]=> string(5) "Other" } } ["project_purposes_exp"]=> string(0) "" ["project_software_used"]=> array(2) { ["value"]=> string(1) "R" ["label"]=> string(1) "R" } ["project_software_used_exp"]=> string(0) "" ["project_research_methods"]=> string(118) "1. ITT flag as "Y" (all randomized subjects);
2. with at least 1 MRD result (numeric value or categorical value)" ["project_main_outcome_measure"]=> string(522) "Primary Outcome Measure:
1. Individual level and trial level coefficients of determination to evaluate MRD negativity rate as surrogate endpoint for OS in RRMM and NDMM.
Secondary Outcome Measure:
1. Individual level and trial level coefficients of determination to evaluate MRD negativity with CR rate as surrogate endpoint for OS in RRMM and NDMM.
2. Individual level and trial level coefficients of determination to evaluate longitudinal MRD result as surrogate endpoint for OS in RRMM and NDMM." ["project_main_predictor_indep"]=> string(476) "No predictors will be included in the study, since the main point of the study is to evaluate the surrogacy of MRD for OS. However, some stratification variables may be included as independent variables, such as ISS, Age and cytogenetic risk (stratification variables for most of DARA studies, however it depends on the specific design of each study).
Category:
ISS stage: I, II, III
Age: prefer continuous variable
cytogenetic risk: High, Low, Unknown" ["project_other_variables_interest"]=> string(285) "1. Analysis set flags: ITTFL, SAFFL, etc.
2. Demographic information: age, sex, race, baseline ECOG
3. Baseline disease characteristics: type of measurable disease, other baseline information
4. Efficacy related results: PFS, best overall response, OS, MRD negativity" ["project_stat_analysis_plan"]=> string(735) "1. Data from different studies will be integrated and cleaned.
2. Descriptive statistical analysis will be performed for overall and with subgroups (eg, RRMM, NDMM).
3. MRD negativity rate will be derived for each study.
4. MRD negativity with CR rate will be derived for each study.
5. Longitudinal MRD result will be derived as BDS data.
6. OS will be derived.
7. Evaluation method by Burzykowski will be used to validate binary surrogate endpoint (MRD negativity rate /MRD negativity with CR rate) and time-to-event true endpoint (OS).
8. Evaluation method by Henderson will be used to validate longitudinal surrogate endpoint (Longitudinal MRD result) and time-to-event true endpoint (OS)." ["project_timeline"]=> string(257) "1. Completion of contract: Feb 2023
2. Obtain de-identified dataset: Feb 2023
3. Analysis and report submitted to YODA: March 2023
4. Submitting manuscript to targeting Journal: April 2023
5. Adding the result to PhD thesis: May 2023" ["project_dissemination_plan"]=> string(469) "Target journals:
Journal of Clinical Oncology/Blood/Blood reviews/British journal of haematology/Clin Lymphoma Myeloma Leuk, etc.
Other publish:
PhD thesis will be published on www.cnki.net 1 year after graduation (2024)
Online R Shiny APP to predict treatment effect of MM with MRD (if MRD has been validated as robust surrogate endpoint, then a model to predict the treatment effect with MRD will be established and published as an online APP)" ["project_bibliography"]=> string(1785) "

[1] Cardiac Arrhythmia Suppression Trial (CAST) Investigators (1989). Preliminary Report: effect of encainide and flecainide on mortality in a randomized trial of arrhythmia suppression after myocardial infraction. New England Journal of Medicine 321, 406?412.
[2] Fleming, T. R. and DeMets, D. L. (1996). Surrogate end points in clinical trials: are we being misled? Annals of Internal Medicine 125, 605?613.
[3] DeGruttola, V. and Tu, X. M. (1994). Modelling progression of CD-4 lymphocyte count and its relationship to survival time. Biometrics 50, 1003?1014.
[4] Lagakos, S. W. and Hoth, D. F. (1992). Surrogate markers in AIDS: where are we? Where are we going? Annals of Internal Medicine 116, 599?601.
[5] Fleming, T. R. (1994). Surrogate markers in AIDS and cancer trials. Statistics in Medicine 13, 1423?1435.
[6] Ferentz, A. E. (2002). Integrating pharmacogenomics into drug development. Pharmacogenomics 3, 453?467.
[7] Rawstron AC, Child JA, de Tute RM, et al. (2013). Minimal residual disease assessed by multiparameter flow cytometry in multiple myeloma: impact on outcome in the Medical Research Council Myeloma IX Study. J Clin Oncol. 31:2540?2547.
[8] Martinez-Lopez J, Lahuerta JJ, Pepin F, et al. (2014). Prognostic value of deep sequencing method for minimal residual disease detection in multiple myeloma. Blood. 123:3073?3079.
[9] Prentice RL. (1989). Surrogate endpoints in clinical trials: definition and operational criteria. Stat Med. 8:431?440.
[10] Burzykowski, T., Molenberghs, G. and Buyse, M. (2004). The validation of surrogate endpoints using data from randomized clinical trials: a case-study in advanced colorectal cancer. Journal of the Royal Statistical Society, Series A 167, 103?124.

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2023-5162

Research Proposal

Project Title: Is minimal residual disease a valid surrogate endpoint for survival in multiple myeloma?

Scientific Abstract: Background:
Surrogate endpoints are used to replace clinical endpoints in evaluating new treatments, but their validity requires demonstration of their reliability in predicting treatment effects. Statistical approaches, such as individual and trial level association assessments can help determine the strength of evidence for surrogacy. Clinical trials in multiple myeloma (MM) typically use progression-free survival (PFS) or time to progression (TTP) as primary endpoints, but the identification of alternative surrogate endpoints, such as Minimal Residual Disease (MRD) negativity is increasing in interest due to its strong correlation with both PFS and overall survival (OS). There are some meta-analyses attempting to demonstrate the association between MRD and OS, but standard statistical methods were not used for evaluation.
Objective:
To validate MRD as surrogate endpoint in MM with standard statistical surrogate evaluation method.
Study Design and Participants:
Subjects will be pooled into two subgroups: NCT02076009, NCT02136134 and NCT03180736 will be Relapsed or Refractory Multiple Myeloma (RRMM) group, while NCT02195479 and NCT02252172 will be newly diagnosed multiple myeloma (NDMM) group.
Primary and Secondary Outcome Measure(s):
Individual level and trial level coefficients of determination to evaluate MRD negativity rate as surrogate endpoint for OS in RRMM and NDMM.
Individual level and trial level coefficients of determination to evaluate MRD negativity with CR rate as surrogate endpoint for OS in RRMM and NDMM.
Individual level and trial level coefficients of determination to evaluate longitudinal MRD result as surrogate endpoint for OS in RRMM and NDMM.
Statistical Analysis:
Surrogacy of MRD negativity rate and MRD negativity with CR rate will be evaluated with two-stage model by Burzykowski, in which, one marginal distribution can be a proportional odds logistic regression, while the other is a proportional hazards model. While Surrogacy of longitudinal MRD result will be evaluated with joint modeling of longitudinal measurements and event time data by Henderson.

Brief Project Background and Statement of Project Significance: The development of new drugs is hindered by the slow and costly clinical development process, and the choice of endpoint used to assess drug efficacy plays an important role in this process. Surrogate endpoints or biomarkers can be used to measure drug efficacy more cheaply, conveniently, frequently, or earlier than the true clinical endpoint. However, historical failures have led to controversies about the use of surrogate endpoints in medical research, and the effect of treatment on the surrogate endpoint must reliably predict the effect on the clinical endpoint [1-6].
The use of biomarkers as surrogate endpoints for drug approval has become increasingly important in oncology due to the desire to quickly approve new drugs. Shortening clinical trials and using surrogate endpoints, such as disease-free survival and progression-free survival, may decrease evaluation costs and potential problems with noncompliance and missing data. However, the value of these endpoints as surrogate endpoints for overall survival has been questioned, particularly in advanced disease.
Advancements in therapeutic options for multiple myeloma, including proteasome inhibitors, immunomodulators, and antibody therapies, have greatly improved patient prognosis. However, traditional endpoint measures such as PFS may delay the development of better therapies. Surrogate endpoints, such as MRD status, have been explored as a potential alternative. Studies have shown that MRD monitoring provides a more sensitive determination of disease burden than complete response (CR), and MRD-negative responses are associated with superior survival outcomes [7, 8]. The use of MRD status as a potential endpoint for clinical trials in multiple myeloma has been the subject of an FDA symposium. In order for an endpoint to be considered a surrogate "reasonably likely to predict clinical benefit" (that is, potentially acceptable for accelerated drug approval), it needs to meet two key criteria proposed by Prentice [9]: a surrogate endpoint must, (1) be correlated at a patient level with the clinical benefit endpoint independent of treatment, and (2) fully capture the net effect of treatment on the clinical benefit endpoint. That is, the treatment effect on the surrogate endpoint must reliably predict the treatment effect on the clinical benefit endpoint and not be merely a correlate of activity between two endpoint measurements.
The preferred method for validating surrogate endpoints is through a meta-analytic, multi-trial approach, a two-stage model [10] to derive both trial-level and individual-level surrogacy. However, in multiple myeloma, most published meta-analyses have only addressed the first of the two Prentice criteria, which is demonstrating correlation between MRD status and PFS or OS at the trial level. Therefore, with the individual-level data I?ve requested, both trial-level and individual-level surrogacy of MRD to OS in RRMM and NDMM can be validated. This will potentially change the FDA's perspective on the use of MRD as a surrogate endpoint for multiple myeloma, which may accelerate the drug approval process while ensuring robust surrogacy.

Specific Aims of the Project: Specific aims:
The overall objective of this study is to find out whether MRD negativity can be a statistically validated surrogate endpoint for RRMM and NDMM.
Specific hypotheses:
1. MRD negativity rate can serve as the surrogate endpoint both on individual level (coefficients of determination > 0.75) and trial level (coefficients of determination > 0.75).
2. MRD negativity with CR rate can serve as the surrogate endpoint both on individual level (coefficients of determination > 0.75) and trial level (coefficients of determination > 0.75).
3. Longitudinal MRD result can serve as the surrogate endpoint both on individual level (coefficients of determination > 0.75) and trial level (coefficients of determination > 0.75).

Study Design: Other

What is the purpose of the analysis being proposed? Please select all that apply.: Other

Software Used: R

Data Source and Inclusion/Exclusion Criteria to be used to define the patient sample for your study: 1. ITT flag as "Y" (all randomized subjects);
2. with at least 1 MRD result (numeric value or categorical value)

Primary and Secondary Outcome Measure(s) and how they will be categorized/defined for your study: Primary Outcome Measure:
1. Individual level and trial level coefficients of determination to evaluate MRD negativity rate as surrogate endpoint for OS in RRMM and NDMM.
Secondary Outcome Measure:
1. Individual level and trial level coefficients of determination to evaluate MRD negativity with CR rate as surrogate endpoint for OS in RRMM and NDMM.
2. Individual level and trial level coefficients of determination to evaluate longitudinal MRD result as surrogate endpoint for OS in RRMM and NDMM.

Main Predictor/Independent Variable and how it will be categorized/defined for your study: No predictors will be included in the study, since the main point of the study is to evaluate the surrogacy of MRD for OS. However, some stratification variables may be included as independent variables, such as ISS, Age and cytogenetic risk (stratification variables for most of DARA studies, however it depends on the specific design of each study).
Category:
ISS stage: I, II, III
Age: prefer continuous variable
cytogenetic risk: High, Low, Unknown

Other Variables of Interest that will be used in your analysis and how they will be categorized/defined for your study: 1. Analysis set flags: ITTFL, SAFFL, etc.
2. Demographic information: age, sex, race, baseline ECOG
3. Baseline disease characteristics: type of measurable disease, other baseline information
4. Efficacy related results: PFS, best overall response, OS, MRD negativity

Statistical Analysis Plan: 1. Data from different studies will be integrated and cleaned.
2. Descriptive statistical analysis will be performed for overall and with subgroups (eg, RRMM, NDMM).
3. MRD negativity rate will be derived for each study.
4. MRD negativity with CR rate will be derived for each study.
5. Longitudinal MRD result will be derived as BDS data.
6. OS will be derived.
7. Evaluation method by Burzykowski will be used to validate binary surrogate endpoint (MRD negativity rate /MRD negativity with CR rate) and time-to-event true endpoint (OS).
8. Evaluation method by Henderson will be used to validate longitudinal surrogate endpoint (Longitudinal MRD result) and time-to-event true endpoint (OS).

Narrative Summary: Drug development is slow and expensive, but surrogate endpoints or biomarkers can be used to measure drug efficacy more cheaply and faster then true endpoint. For multiple myeloma, MRD has been explored as a potential surrogate endpoint to traditional endpoint such as PFS and OS. The proposed study aims to validate MRD as a surrogate endpoint for multiple myeloma at both trial and individual levels. This may potentially change the FDA's perspective on the use of MRD as a surrogate endpoint for multiple myeloma, which could accelerate the drug approval process while ensuring robust surrogacy.

Project Timeline: 1. Completion of contract: Feb 2023
2. Obtain de-identified dataset: Feb 2023
3. Analysis and report submitted to YODA: March 2023
4. Submitting manuscript to targeting Journal: April 2023
5. Adding the result to PhD thesis: May 2023

Dissemination Plan: Target journals:
Journal of Clinical Oncology/Blood/Blood reviews/British journal of haematology/Clin Lymphoma Myeloma Leuk, etc.
Other publish:
PhD thesis will be published on www.cnki.net 1 year after graduation (2024)
Online R Shiny APP to predict treatment effect of MM with MRD (if MRD has been validated as robust surrogate endpoint, then a model to predict the treatment effect with MRD will be established and published as an online APP)

Bibliography:

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[7] Rawstron AC, Child JA, de Tute RM, et al. (2013). Minimal residual disease assessed by multiparameter flow cytometry in multiple myeloma: impact on outcome in the Medical Research Council Myeloma IX Study. J Clin Oncol. 31:2540?2547.
[8] Martinez-Lopez J, Lahuerta JJ, Pepin F, et al. (2014). Prognostic value of deep sequencing method for minimal residual disease detection in multiple myeloma. Blood. 123:3073?3079.
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[10] Burzykowski, T., Molenberghs, G. and Buyse, M. (2004). The validation of surrogate endpoints using data from randomized clinical trials: a case-study in advanced colorectal cancer. Journal of the Royal Statistical Society, Series A 167, 103?124.