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

Author:

Yeh Celine1,Zhou Mengxi2,Sigel Keith3ORCID,Jameson Gayle4,White Ruth2,Safyan Rachael2,Saenger Yvonne2,Hecht Elizabeth5,Chabot John2,Schreibman Stephen2,Juzyna Béata6,Ychou Marc7,Conroy Thierry8,Fojo Tito29,Manji Gulam A2,Von Hoff Daniel1011,Bates Susan E29

Affiliation:

1. Department of Medicine, Columbia University Irving Medical Center , New York, NY , USA

2. Department of Medicine, Division of Hematology/Oncology, Columbia University Herbert Irving Comprehensive Cancer Center , New York, NY , USA

3. Department of Medicine, Icahn School of Medicine at Mount Sinai , New York, NY , USA

4. Department of Medical Oncology/Hematology, HonorHealth Research Institute , Scottsdale, AZ , USA

5. Department of Radiology, Weill Cornell Medicine , New York, NY , USA

6. R&D UNICANCER, Fédération Nationale des Centres de Lutte Contre le Cancer, Paris , France

7. Department of Medical Oncology, Institut Régional du Cancer de Montpellier (ICM) , Montpellier , France

8. Department of Medical Oncology, Institut de Cancérologie de Lorraine , Vandoeuvre-lès-Nancy Cedex , France

9. Hematology/Oncology, James J. Peters VA Medical Center , Bronx, NY , USA

10. Virginia G. Piper Cancer Center Clinical Trials, HonorHealth Research Institute , Scottsdale , AZ , USA

11. Translational Genomics Research Institute, Clinical Translational Research Division, Phoenix , AZ , USA

Abstract

Abstract Background Methods for screening agents earlier in development and strategies for conducting smaller randomized controlled trials (RCTs) are needed. 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 pancreatic ductal adenocarcinoma (PDAC) who were enrolled in 8 clinical trials or were included in 2 large real-world data sets. Results g correlated inversely with overall survival (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 more than 3-fold. 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.

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Oncology

Reference33 articles.

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