Abstract Number:
2868
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Speed
Participants:
Marzana Chowdhury (1), Shubhadeep Chakraborty (1), Izumi Hamada (1), Kshitij Aggarwal (1), Chuanpu Hu (1), Anna Kondic (1), David Palucchi (1), Arun Kumar (1), Kaushal Mishra (1), Ram Tiwari (1), Mariann Micsinai Balan (1), Kalyanee Viraswami-Appanna (1)
Institutions:
(1) Bristol Myers Squibb, USA
Co-Author(s):
First Author:
Presenting Author:
Abstract Text:
In Oncology drug development, overall response rate (ORR), is commonly used as an early measure to assess the activity of a new drug. However, ORR, often is not very informative about longer-term clinical benefit depending upon specific indication and class of therapy. The existing endpoints in literature based on tumor growth dynamics (TGD) i.e., continuous longitudinal tumor size data provides better predictions for overall survival (OS) than ORR. But those have limitations such as requiring a minimum duration of follow-up for a patient to be included in the analysis, leading to biased results. We aim to address this gap by 1) proposing multiple TGD-based endpoints with an imputation mechanism so that all available data from all the patients can be utilized 2) developing a broad framework to simulate clinical trials with a variety of tumor growth and reduction rates, to perform unbiased comparison of proposed endpoints and ORR. Extensive simulations and validation indicate that some TGD endpoints dominate ORR consistently by having a comparable or higher correlation with long term OS than ORR. Thus, the TGD endpoints are recommended as an alternative to ORR across indications.
Keywords:
Oncology|Overall response rate|Tumor growth dynamics|Overall survival | |
Sponsors:
Biopharmaceutical Section
Tracks:
Biomarkers and Endpoint Validation
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