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The R code for Machine Learning Based on Blood Test Biomarkers Predicts Fast Progression in Advanced NSCLC Patients Treated with Immunotherapy

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The R code for Machine Learning Based on Blood Test Biomarkers Predicts Fast Progression in Advanced NSCLC Patients Treated with Immunotherapy

Machine Learning Based on Blood Test Biomarkers Predicts Fast Progression in Advanced NSCLC Patients Treated with Immunotherapy

Jian-Guo Zhou1,2,3,4*#, Jie Yang5*, Haitao Wang6, Ada Hang-Heng Wong7, Fangya Tan8, Xiaofei Chen9, Si-Si He1, Gang Shen1, Yun-Jia Wang1, Benjamin Frey2,3,4, Rainer Fietkau3,4, Markus Hecht3,4, Wen-Zhao Zhong5#, Hu Ma1# and Udo S. Gaipl2,3,4#

1 Department of Oncology, The second affiliated Hospital of Zunyi Medical University, Zunyi, China 2 Translational Radiobiology, Department of Radiation Oncology, Universitätsklinikum Erlangen, Erlangen, Germany 3 Department of Radiation Oncology, Universitätsklinikum Erlangen, Erlangen, Germany 4 Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany 5 Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China. 6 Thoracic Surgery Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA 7 AW Medical Company Limited, Macau SAR, China 8 Department of Analytics, Harrisburg University of Science & Technology, Harrisburg, Pennsylvania, USA 9 Department of Biostat & programming, Sanofi, New Jersey, USA.

JGZ and JY contributed equally as first authors.

### JGZ, WZZ, HM and USG contributed equally as senior authors.

Correspondence:

Prof. Dr. Udo Gaipl: Head of Translational Radiobiology Department of Radiation Oncology Universitätsklinikum Erlangen Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Universitätsstraße 27, 91054 Erlangen, Germany Tel Office: +49 (0)9131-85-44258 Fax: +49 (0)9131-85-39335 E-mail address: [email protected]

Prof. Dr. Hu Ma: Director of Department of Oncology Vice President of the second affiliated Hospital of Zunyi Medical University Intersection of Xinlong And Xinpu Avenue, 563000, Zunyi, China E-mail address: [email protected]

Dr. Jian-Guo Zhou Department of Oncology the second affiliated Hospital of Zunyi Medical University Intersection of Xinlong And Xinpu Avenue, 563000, Zunyi, China E-mail address: [email protected]

Dr. Wen-Zhao Zhong Guangdong Lung Cancer Institute, Guangdong Provincial People's. Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China. E-mail address: [email protected]

Acknowledgments

We would like to thank all of the patients, investigators and staff involved in the FIR, BIRCH, POPLAR and OAK studies who released and shared their data. This publication is based on research using data from data contributors, Roche, that has been made available through Vivli, Inc. (Data Request ID: 5935; Lead Investigator: Dr. Jian-Guo Zhou). Vivli has not contributed to or approved, and is not in any way responsible for, the contents of this publication.

Funding

This research was funded by the National Natural Science Foundation of China (Grant No. 81660512), the National Natural Science Foundation of Guizhou Province (Grant No. ZK2021-YB435), Research Programs of Science and Technology Commission Foundation of Zunyi City (Grant Nos. HZ2019-11, HZ2019-07), Research Programs of Health Commission Foundation of Guizhou Province (Grant Nos. gzwjkj2019-1-073, gzwjkj2019-1-172), Lian Yun Gang Shi Hui Lan Public Foundation (Grant No. HL-HS2020-92).

Zhou J, Yang J, Wang H, et alMachine learning based on blood test biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapyBMJ Oncology 2024;3:e000128. doi: 10.1136/bmjonc-2023-000128

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