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Early on-treatment tumor growth rate (EOT-TGR) determines treatment outcomes of advanced non-small-cell lung cancer patients treated with programmed cell death protein 1 axis inhibitor

BACKGROUND: Tumor growth rate (TGR), denoted as percentage change in tumor size per month, is a well-established indicator of tumor growth kinetics. The predictive value of early on-treatment TGR (EOT-TGR) for immunotherapy remains unclear. We sought to establish and validate the association of EOT-...

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Autores principales: He, L.-N., Fu, S., Ma, H., Chen, C., Zhang, X., Li, H., Du, W., Chen, T., Jiang, Y., Wang, Y., Zhou, Y., Lin, Z., Yang, Y., Huang, Y., Zhao, H., Fang, W., Zhang, H., Zhang, L., Hong, S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9808481/
https://www.ncbi.nlm.nih.gov/pubmed/36442353
http://dx.doi.org/10.1016/j.esmoop.2022.100630
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author He, L.-N.
Fu, S.
Ma, H.
Chen, C.
Zhang, X.
Li, H.
Du, W.
Chen, T.
Jiang, Y.
Wang, Y.
Wang, Y.
Zhou, Y.
Lin, Z.
Yang, Y.
Huang, Y.
Zhao, H.
Fang, W.
Zhang, H.
Zhang, L.
Hong, S.
author_facet He, L.-N.
Fu, S.
Ma, H.
Chen, C.
Zhang, X.
Li, H.
Du, W.
Chen, T.
Jiang, Y.
Wang, Y.
Wang, Y.
Zhou, Y.
Lin, Z.
Yang, Y.
Huang, Y.
Zhao, H.
Fang, W.
Zhang, H.
Zhang, L.
Hong, S.
author_sort He, L.-N.
collection PubMed
description BACKGROUND: Tumor growth rate (TGR), denoted as percentage change in tumor size per month, is a well-established indicator of tumor growth kinetics. The predictive value of early on-treatment TGR (EOT-TGR) for immunotherapy remains unclear. We sought to establish and validate the association of EOT-TGR with treatment outcomes in patients with advanced non-small-cell lung cancer (aNSCLC) undergoing anti-PD-1/PD-L1 (programmed cell death protein 1/programmed death-ligand 1) therapy. PATIENTS AND METHODS: This bicenter retrospective cohort study included a training cohort, a contemporaneously treated internal validation cohort, and an external validation cohort. Computed tomography images were retrieved to calculate EOT-TGR, denoted as tumor burden change per month during a period between baseline and the first imaging evaluation after immunotherapy. Kaplan–Meier methodology and Cox regression analysis were conducted for survival analyses. RESULTS: In the pooled cohort (n = 172), 125 patients (72.7%) were males; median age at diagnosis was 58 (range 28-79) years. Based on the training cohort, we determined the optimal cut-off value for EOT-TGR as 10.4%/month. Higher EOT-TGR was significantly associated with inferior overall survival [OS; hazard ratio (HR) 2.93, 95% confidence interval (CI) 1.47-5.83; P = 0.002], worse progression-free survival (PFS; HR 2.44, 95% CI 1.46-4.08; P = 0.001), and lower objective response rate (3.3% versus 20.9%; P = 0.040) and durable clinical benefit rate (6.7% versus 41.9%; P = 0.001). Results were reproducible in the two validation cohorts for OS and PFS. Among 43 patients who had a best response of progressive disease in the training cohort, those with high EOT-TGR had worse OS (HR 2.64; P = 0.041) and were more likely to progress due to target lesions at the first tumor evaluation (85.2% versus 0.0%; P <0.001). CONCLUSIONS: Higher EOT-TGR was associated with inferior OS and immunotherapeutic response in patients with aNSCLC undergoing anti-PD-1/PD-L1 therapy. This easy-to-calculate radiologic biomarker may help evaluate the abilities of immunotherapy to prolong survival and assist in tailoring patients’ management. TRIAL REGISTRATION: ClinicalTrials.govNCT04722406; https://clinicaltrials.gov/ct2/show/NCT04722406
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spelling pubmed-98084812023-01-04 Early on-treatment tumor growth rate (EOT-TGR) determines treatment outcomes of advanced non-small-cell lung cancer patients treated with programmed cell death protein 1 axis inhibitor He, L.-N. Fu, S. Ma, H. Chen, C. Zhang, X. Li, H. Du, W. Chen, T. Jiang, Y. Wang, Y. Wang, Y. Zhou, Y. Lin, Z. Yang, Y. Huang, Y. Zhao, H. Fang, W. Zhang, H. Zhang, L. Hong, S. ESMO Open Original Research BACKGROUND: Tumor growth rate (TGR), denoted as percentage change in tumor size per month, is a well-established indicator of tumor growth kinetics. The predictive value of early on-treatment TGR (EOT-TGR) for immunotherapy remains unclear. We sought to establish and validate the association of EOT-TGR with treatment outcomes in patients with advanced non-small-cell lung cancer (aNSCLC) undergoing anti-PD-1/PD-L1 (programmed cell death protein 1/programmed death-ligand 1) therapy. PATIENTS AND METHODS: This bicenter retrospective cohort study included a training cohort, a contemporaneously treated internal validation cohort, and an external validation cohort. Computed tomography images were retrieved to calculate EOT-TGR, denoted as tumor burden change per month during a period between baseline and the first imaging evaluation after immunotherapy. Kaplan–Meier methodology and Cox regression analysis were conducted for survival analyses. RESULTS: In the pooled cohort (n = 172), 125 patients (72.7%) were males; median age at diagnosis was 58 (range 28-79) years. Based on the training cohort, we determined the optimal cut-off value for EOT-TGR as 10.4%/month. Higher EOT-TGR was significantly associated with inferior overall survival [OS; hazard ratio (HR) 2.93, 95% confidence interval (CI) 1.47-5.83; P = 0.002], worse progression-free survival (PFS; HR 2.44, 95% CI 1.46-4.08; P = 0.001), and lower objective response rate (3.3% versus 20.9%; P = 0.040) and durable clinical benefit rate (6.7% versus 41.9%; P = 0.001). Results were reproducible in the two validation cohorts for OS and PFS. Among 43 patients who had a best response of progressive disease in the training cohort, those with high EOT-TGR had worse OS (HR 2.64; P = 0.041) and were more likely to progress due to target lesions at the first tumor evaluation (85.2% versus 0.0%; P <0.001). CONCLUSIONS: Higher EOT-TGR was associated with inferior OS and immunotherapeutic response in patients with aNSCLC undergoing anti-PD-1/PD-L1 therapy. This easy-to-calculate radiologic biomarker may help evaluate the abilities of immunotherapy to prolong survival and assist in tailoring patients’ management. TRIAL REGISTRATION: ClinicalTrials.govNCT04722406; https://clinicaltrials.gov/ct2/show/NCT04722406 Elsevier 2022-11-25 /pmc/articles/PMC9808481/ /pubmed/36442353 http://dx.doi.org/10.1016/j.esmoop.2022.100630 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Research
He, L.-N.
Fu, S.
Ma, H.
Chen, C.
Zhang, X.
Li, H.
Du, W.
Chen, T.
Jiang, Y.
Wang, Y.
Wang, Y.
Zhou, Y.
Lin, Z.
Yang, Y.
Huang, Y.
Zhao, H.
Fang, W.
Zhang, H.
Zhang, L.
Hong, S.
Early on-treatment tumor growth rate (EOT-TGR) determines treatment outcomes of advanced non-small-cell lung cancer patients treated with programmed cell death protein 1 axis inhibitor
title Early on-treatment tumor growth rate (EOT-TGR) determines treatment outcomes of advanced non-small-cell lung cancer patients treated with programmed cell death protein 1 axis inhibitor
title_full Early on-treatment tumor growth rate (EOT-TGR) determines treatment outcomes of advanced non-small-cell lung cancer patients treated with programmed cell death protein 1 axis inhibitor
title_fullStr Early on-treatment tumor growth rate (EOT-TGR) determines treatment outcomes of advanced non-small-cell lung cancer patients treated with programmed cell death protein 1 axis inhibitor
title_full_unstemmed Early on-treatment tumor growth rate (EOT-TGR) determines treatment outcomes of advanced non-small-cell lung cancer patients treated with programmed cell death protein 1 axis inhibitor
title_short Early on-treatment tumor growth rate (EOT-TGR) determines treatment outcomes of advanced non-small-cell lung cancer patients treated with programmed cell death protein 1 axis inhibitor
title_sort early on-treatment tumor growth rate (eot-tgr) determines treatment outcomes of advanced non-small-cell lung cancer patients treated with programmed cell death protein 1 axis inhibitor
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9808481/
https://www.ncbi.nlm.nih.gov/pubmed/36442353
http://dx.doi.org/10.1016/j.esmoop.2022.100630
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