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Dynamic serum biomarkers to predict the efficacy of PD-1 in patients with nasopharyngeal carcinoma
BACKGROUND: There is a lack of effective treatments for recurrent or metastatic nasopharyngeal carcinoma (RM-NPC). Furthermore, the response rate of NPC patients to programmed death 1 (PD-1) inhibitors is approximately 20% to 30%. Thus, we aimed to explore reliable and minimally invasive prognostic...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8480072/ https://www.ncbi.nlm.nih.gov/pubmed/34583688 http://dx.doi.org/10.1186/s12935-021-02217-y |
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author | Zhang, Ao Zhong, Guanqing Wang, Luocan Cai, Rongzeng Han, Runkun Xu, Caixia Chen, Shulin Sun, Peng Chen, Hao |
author_facet | Zhang, Ao Zhong, Guanqing Wang, Luocan Cai, Rongzeng Han, Runkun Xu, Caixia Chen, Shulin Sun, Peng Chen, Hao |
author_sort | Zhang, Ao |
collection | PubMed |
description | BACKGROUND: There is a lack of effective treatments for recurrent or metastatic nasopharyngeal carcinoma (RM-NPC). Furthermore, the response rate of NPC patients to programmed death 1 (PD-1) inhibitors is approximately 20% to 30%. Thus, we aimed to explore reliable and minimally invasive prognostic indicators to predict the efficacy of PD-1 inhibitors combination therapy in RM-NPC. METHODS: The serum markers of 160 RM-NPC patients were measured before and three weeks after the first anti-PD-1 treatment. The least absolute shrinkage and selection operator (LASSO) logistic regression was carried out to select dynamic serum indicators and construct a prediction model. Furthermore, we carried out univariate, multivariate, nomogram and survival analyses to identify independent prognostic factors that were associated with 1-year progression-free survival (PFS). RESULTS: Based on two markers that were screened by Lasso logistic regression, we constructed a risk score prediction model for the prediction of anti-PD-1 efficacy at 8–12 weeks with an AUC of 0.737 in the training cohort and 0.723 in the validation cohort. Risk score and metastases were included in the nomogram, and the Kaplan–Meier survival curves demonstrated that the high-risk group has shorter PFS compared to the low-risk group. The concordance index (C-index) of the nomogram for PFS is higher than that of the TNM stage in the training and validation cohort. CONCLUSION: We proposed a strategy to monitor dynamic changes in the biochemistry markers and emphasized their importance as potential prognostic biomarkers for the treatment of advanced NPC treated with PD-1 inhibitors. Our risk score prediction model was based on the dynamic change of LDH and AST/ALT, which has predictive and prognostic value for NPC patients who were treated with PD-1 inhibitors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02217-y. |
format | Online Article Text |
id | pubmed-8480072 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84800722021-09-30 Dynamic serum biomarkers to predict the efficacy of PD-1 in patients with nasopharyngeal carcinoma Zhang, Ao Zhong, Guanqing Wang, Luocan Cai, Rongzeng Han, Runkun Xu, Caixia Chen, Shulin Sun, Peng Chen, Hao Cancer Cell Int Primary Research BACKGROUND: There is a lack of effective treatments for recurrent or metastatic nasopharyngeal carcinoma (RM-NPC). Furthermore, the response rate of NPC patients to programmed death 1 (PD-1) inhibitors is approximately 20% to 30%. Thus, we aimed to explore reliable and minimally invasive prognostic indicators to predict the efficacy of PD-1 inhibitors combination therapy in RM-NPC. METHODS: The serum markers of 160 RM-NPC patients were measured before and three weeks after the first anti-PD-1 treatment. The least absolute shrinkage and selection operator (LASSO) logistic regression was carried out to select dynamic serum indicators and construct a prediction model. Furthermore, we carried out univariate, multivariate, nomogram and survival analyses to identify independent prognostic factors that were associated with 1-year progression-free survival (PFS). RESULTS: Based on two markers that were screened by Lasso logistic regression, we constructed a risk score prediction model for the prediction of anti-PD-1 efficacy at 8–12 weeks with an AUC of 0.737 in the training cohort and 0.723 in the validation cohort. Risk score and metastases were included in the nomogram, and the Kaplan–Meier survival curves demonstrated that the high-risk group has shorter PFS compared to the low-risk group. The concordance index (C-index) of the nomogram for PFS is higher than that of the TNM stage in the training and validation cohort. CONCLUSION: We proposed a strategy to monitor dynamic changes in the biochemistry markers and emphasized their importance as potential prognostic biomarkers for the treatment of advanced NPC treated with PD-1 inhibitors. Our risk score prediction model was based on the dynamic change of LDH and AST/ALT, which has predictive and prognostic value for NPC patients who were treated with PD-1 inhibitors. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02217-y. BioMed Central 2021-09-28 /pmc/articles/PMC8480072/ /pubmed/34583688 http://dx.doi.org/10.1186/s12935-021-02217-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Primary Research Zhang, Ao Zhong, Guanqing Wang, Luocan Cai, Rongzeng Han, Runkun Xu, Caixia Chen, Shulin Sun, Peng Chen, Hao Dynamic serum biomarkers to predict the efficacy of PD-1 in patients with nasopharyngeal carcinoma |
title | Dynamic serum biomarkers to predict the efficacy of PD-1 in patients with nasopharyngeal carcinoma |
title_full | Dynamic serum biomarkers to predict the efficacy of PD-1 in patients with nasopharyngeal carcinoma |
title_fullStr | Dynamic serum biomarkers to predict the efficacy of PD-1 in patients with nasopharyngeal carcinoma |
title_full_unstemmed | Dynamic serum biomarkers to predict the efficacy of PD-1 in patients with nasopharyngeal carcinoma |
title_short | Dynamic serum biomarkers to predict the efficacy of PD-1 in patients with nasopharyngeal carcinoma |
title_sort | dynamic serum biomarkers to predict the efficacy of pd-1 in patients with nasopharyngeal carcinoma |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8480072/ https://www.ncbi.nlm.nih.gov/pubmed/34583688 http://dx.doi.org/10.1186/s12935-021-02217-y |
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