Back to Search Start Over

Tumor Growth Rate Informs Treatment Efficacy in Metastatic Pancreatic Adenocarcinoma: Application of a Growth and Regression Model to Pivotal Trial and Real-World Data.

Authors :
Yeh C
Zhou M
Sigel K
Jameson G
White R
Safyan R
Saenger Y
Hecht E
Chabot J
Schreibman S
Juzyna B
Ychou M
Conroy T
Fojo T
Manji GA
Von Hoff D
Bates SE
Source :
The oncologist [Oncologist] 2023 Feb 08; Vol. 28 (2), pp. 139-148.
Publication Year :
2023

Abstract

Background: Methods for screening agents earlier in development and strategies for conducting smaller randomized controlled trials (RCTs) are needed.<br />Methods: We retrospectively applied a tumor growth model to estimate the rates of growth of pancreatic cancer using radiographic tumor measurements or serum CA 19-9 values from 3033 patients with stages III-IV PDAC who were enrolled in 8 clinical trials or were included in 2 large real-world data sets.<br />Results: g correlated inversely with OS and was consistently lower in the experimental arms than in the control arms of RCTs. At the individual patient level, g was significantly faster for lesions metastatic to the liver relative to those localized to the pancreas. Regardless of regimen, g increased toward the end of therapy, often by over 3-fold.<br />Conclusions: Growth rates of PDAC can be determined using radiographic tumor measurement and CA 19-9 values. g is inversely associated with OS and can differentiate therapies within the same trial and across trials. g can also be used to characterize changes in the behavior of an individual's PDAC, such as differences in the growth rate of lesions based on metastatic site, and the emergence of chemoresistance. We provide examples of how g can be used to benchmark phase II and III clinical data to a virtual reference arm to inform go/no go decisions and consider novel trial designs to optimize and accelerate drug development.<br /> (Published by Oxford University Press 2022.)

Details

Language :
English
ISSN :
1549-490X
Volume :
28
Issue :
2
Database :
MEDLINE
Journal :
The oncologist
Publication Type :
Academic Journal
Accession number :
36367377
Full Text :
https://doi.org/10.1093/oncolo/oyac217