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Differential Network Analysis of Severity of Adverse Events in Immunotherapy Clinical Trial Patients

Abstract Number:

3557 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Speed 

Participants:

Amarise Little (1), Michael Wu (2)

Institutions:

(1) Fred Hutchinson Research Center, N/A, (2) Fred Hutchinson Cancer Center, N/A

Co-Author:

Michael Wu  
Fred Hutchinson Cancer Center

First Author:

Amarise Little  
Fred Hutchinson Research Center

Presenting Author:

Amarise Little  
Fred Hutchinson Research Center

Abstract Text:

Patients in anti-cancer clinical trials differentially experience toxicity to due to the treatment by race (Labriola & George, ASCO, 2021; Mizusawa, Cancer Med, 2023). We aim to better understand what the differences are in severity of toxicities (or adverse events) by estimating the difference network for severity of toxicities of Black race and white race samples during their time on immunotherapy clinical trials. The nature of the problem introduces several challenges including rare occurrences of adverse events, potential recurrence of adverse events, and adverse events' dependence on the type of treatments. We address these challenges by extending current graphical model frameworks to accommodate our specific data characteristics.

Keywords:

probit graphical model|adverse events| | | |

Sponsors:

Biometrics Section

Tracks:

Miscellaneous

Can this be considered for alternate subtype?

Yes

Are you interested in volunteering to serve as a session chair?

No

I have read and understand that JSM participants must abide by the Participant Guidelines.

Yes

I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.

I understand