Browsing by Subject "Endpoint"

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    Comparisons of Metabolic Measures to Predict T1D vs Detect a Preventive Treatment Effect in High-Risk Individuals
    (Oxford University Press, 2024) Sims, Emily K.; Cuthbertson, David; Jacobsen, Laura; Ismail, Heba M.; Nathan, Brandon M.; Herold, Kevan C.; Redondo, Maria J.; Sosenko, Jay; Pediatrics, School of Medicine
    Context: Metabolic measures are frequently used to predict type 1 diabetes (T1D) and to understand effects of disease-modifying therapies. Objective: Compare metabolic endpoints for their ability to detect preventive treatment effects and predict T1D. Methods: Six-month changes in metabolic endpoints were assessed for (1) detecting treatment effects by comparing placebo and treatment arms from the randomized controlled teplizumab prevention trial, a multicenter clinical trial investigating 14-day intravenous teplizumab infusion and (2) predicting T1D in the TrialNet Pathway to Prevention natural history study. For each metabolic measure, t-Values from t tests for detecting a treatment effect were compared with chi-square values from proportional hazards regression for predicting T1D. Participants in the teplizumab prevention trial and participants in the Pathway to Prevention study selected with the same inclusion criteria used for the teplizumab trial were studied. Results: Six-month changes in glucose-based endpoints predicted diabetes better than C-peptide-based endpoints, yet the latter were better at detecting a teplizumab effect. Combined measures of glucose and C-peptide were more balanced than measures of glucose alone or C-peptide alone for predicting diabetes and detecting a teplizumab effect. Conclusion: The capacity of a metabolic endpoint to detect a treatment effect does not necessarily correspond to its accuracy for predicting T1D. However, combined glucose and C-peptide endpoints appear to be effective for both predicting diabetes and detecting a response to immunotherapy. These findings suggest that combined glucose and C-peptide endpoints should be incorporated into the design of future T1D prevention trials.
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    Summary of the 2019 Blood and Marrow Transplant Clinical Trials Network Myeloma Intergroup Workshop on Minimal Residual Disease and Immune Profiling
    (Elsevier, 2020-10) Holstein, Sarah A.; Howard, Alan; Avigan, David; Bhutani, Manisha; Cohen, Adam D.; Costa, Luciano J.; Dhodapkar, Madhav V.; Gay, Francesca; Gormley, Nicole; Green, Damian J.; Hillengass, Jens; Korde, Neha; Li, Zihai; Mailankody, Sham; Neri, Paola; Parekh, Samir; Pasquini, Marcelo C.; Puig, Noemi; Roodman, G. David; Samur, Mehmet Kemal; Shah, Nina; Shah, Urvi A.; Shi, Qian; Spencer, Andrew; Suman, Vera J.; Usmani, Saad Z.; McCarthy, Philip L.; Medicine, School of Medicine
    The Blood and Marrow Transplant Clinical Trials Network (BMT CTN) Myeloma Intergroup has organized an annual workshop focused on minimal residual disease (MRD) testing and immune profiling (IP) in multiple myeloma since 2016. In 2019, the workshop took place as an American Society of Hematology (ASH) Friday Scientific Workshop entitled “Immune Profiling and Minimal Residual Disease Testing in Multiple Myeloma”. This workshop focused on four main topics: the molecular and immunological evolution of plasma cell disorders, the development of new laboratory- and imaging-based MRD assessment approaches, chimeric antigen receptor T-cell therapy research, and the statistical and regulatory issues associated with novel clinical endpoints. In this report, we provide a summary of the workshop and discuss future directions.