Learn about the flu shot, COVID-19 vaccine, and our masking policy »
New to MyHealth?
Manage Your Care From Anywhere.
Access your health information from any device with MyHealth. You can message your clinic, view lab results, schedule an appointment, and pay your bill.
ALREADY HAVE AN ACCESS CODE?
DON'T HAVE AN ACCESS CODE?
NEED MORE DETAILS?
MyHealth for Mobile
Get the iPhone MyHealth app »
Get the Android MyHealth app »
Abstract
Responses to immuno-oncology agents are often subject to misinterpretation as apparent tumor growth due to immune infiltration leads to the appearance of progressive disease and can result in the discontinuation of effective therapeutic agents. Better statistical strategies to determine experimental outcomes are needed to distinguish between true and pseudoprogression. We applied time-to-event statistical analyses methods that account for study design features and capture the longitudinal and panoramic aspects of pseudoprogression to test superiority of a combination of RRx-001, a novel tumor-associated macrophage polarizing agent in Phase 2, and an anti-PD-L1 antibody in a myeloma preclinical model, comparing to traditional, mean-based mixed effects modeling approaches that did not show statistical significance. Nonparametric p values for the difference of cumulative incidence rates of time to =?50% tumor growth reduction and its associated restricted mean survival times are computed and found to be statistically significant. Kaplan-Meier description of time-to-volume reduction (=?50%) coupled with Cox's proportional hazards model follows the data longitudinally and therefore permits an analysis of immune infiltration resolution, making it an improved method for analysis of preclinical experiments with immuno-oncology agents.
View details for PubMedID 29404682