Abstract 3009: A systematic review of the tumor growth metrics of patient-derived xenograft (PDX) models in the literature and in NCI PDXNet centers
Authors: Li Dali , Ha Min Jin , Evrard Yvonne A. , Chen Huiqin , McShane Lisa M. , Grover Jeffrey , Wang Jing , Fang Bingliang , DiPeri Timothy , Lewis Michael T. , Rubinstein Lawrence , Roth Jack A. , Chuang Jeffrey H. , Doroshow James H. , Moscow Jeffrey A. , Meric-Bernstam Funda 
Published: July 2021

Abstract
Background: Despite increasing utilization of patient-derived xenografts (PDXs) in early drug development, there are no agreed upon metrics for assessment of PDX growth inhibition for agents given alone or in combination. In the present study, we aim to investigate what metrics are being used in the literature, as well as among the National Cancer Institute PDX Development and Trial Centers Research Network (PDXNet) investigators.
Methods: Relevant PDX literature was identified and retrieved using an information retrieval tool, RetriLite, to search for articles that met following criteria: 1) Published between 01/2018 through 12/2019; 2) Published in a journal with impact factor of 10 or above; 3) Search terms included: Cancer, PDX(s), patient derived xenograft(s), and patient-derived xenograft(s). Exclusion criteria included: 1) Brain tumors; 2) Immune-oncology/non-solid tumors; 3) Studies with no detailed information; 4) studies from PDXNet investigators. In addition, a questionnaire regarding PDX analysis practices was distributed to NCI PDXNet investigators and responses were analyzed.
Results: Sixty-five studies with relevant information were included in this systematic literature review and 15 NCI PDXNet PIs from all six centers responded to the survey representing the general practice in the network. The most commonly used tumor growth assessment metric was comparisons in tumor volumes in different treatment arms, used by 33 (51%) of 65 PDX papers and 13 (87%) of 15 PDXNet investigators. Thirteen different growth metrics were reported in the PDX literature and ten different metrics were used by PDXNet investigators. PDXNet investigators were more likely to use growth metrics analogous to clinical endpoints compared to the PDX literature, including percent change of tumor volume (80% vs 17%), event-free survival (EFS: 40% vs 11%), and overall survival (33% vs 8%). PDXNet investigators were also more likely to assess objective response rate (ORR) compared to the PDX literature (60% vs 12%); several different cutoffs were used for defining response and progression. For combination therapy, most investigators and literature compared tumor volumes across treatment arms, with few looking at measures of synergy or dynamic effects and with variable utilization of other metrics such as OR and EFS. In PDX literature, of the 40 papers with combination therapies presented, at least one monotherapy control arm was missing in 7 (18%), and four (10%) only compared growth with the no treatment control arm.
Conclusions: In summary, there is great variability in growth metrics used in the PDX community. To better use PDXs as preclinical models and increase the reproducibility of treatment effect on PDXs, a joint effort is needed to harmonize approaches in PDX growth assessment.
Citation Format: Dali Li, Min Jin Ha, Yvonne A. Evrard, Huiqin Chen, Lisa M. McShane, Jeffrey Grover, Jing Wang, Bingliang Fang, Timothy DiPeri, Michael T. Lewis, Lawrence Rubinstein, Jack A. Roth, Jeffrey H. Chuang, James H. Doroshow, Jeffrey A. Moscow, Funda Meric-Bernstam. A systematic review of the tumor growth metrics of patient-derived xenograft (PDX) models in the literature and in NCI PDXNet centers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3009.