Cargando…
Predictive Nomogram for Hyperprogressive Disease During Anti-PD-1/PD-L1 Treatment in Patients with Advanced Non-Small Cell Lung Cancer
INTRODUCTION: Various studies have reported that anti-PD-1/PD-L1 treatment may lead to the rapid development of tumors called hyperprogressive disease (HPD). A nomogram for HPD prediction in NSCLC patients is urgently needed. METHODS: This retrospective cohort study included 176 cases for establishi...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9828302/ https://www.ncbi.nlm.nih.gov/pubmed/36632330 http://dx.doi.org/10.2147/ITT.S373866 |
_version_ | 1784867241437691904 |
---|---|
author | Wang, Xueping Guo, Zhixing Wu, Xingping Chen, Da Wang, Fang Yang, Lewei Luo, Min Wu, Shaocong Yang, Chuan Huang, Lamei Fu, Liwu |
author_facet | Wang, Xueping Guo, Zhixing Wu, Xingping Chen, Da Wang, Fang Yang, Lewei Luo, Min Wu, Shaocong Yang, Chuan Huang, Lamei Fu, Liwu |
author_sort | Wang, Xueping |
collection | PubMed |
description | INTRODUCTION: Various studies have reported that anti-PD-1/PD-L1 treatment may lead to the rapid development of tumors called hyperprogressive disease (HPD). A nomogram for HPD prediction in NSCLC patients is urgently needed. METHODS: This retrospective cohort study included 176 cases for establishing a model of HPD prediction and 85 cases for validation in advanced NSCLC patients treated with PD-1/PD-L1 inhibitors. HPD was defined as tumor growth rate (TGR, ≥ 2), tumor growth kinetics (TGK, ≥ 2) or time to treatment failure (TTF, ≤ 2 months). Univariate and multivariate logistic regression were used to estimate the specified factors associated with HPD. Then, the nomogram was developed and validated. RESULTS: Anti-PD-1/PD-L1 therapy resulted in a 9.66% (17/176) incidence of HPD in advanced NSCLC. The overall survival (OS) and progression-free survival (PFS) in patients with HPD were significantly shorter than those in patients without HPD (OS: 7.00 vs 12.00 months, P<0.01; PFS: 2.00 vs 5.00 months, P<0.001, respectively). The HPD prediction nomogram included APTT (P<0.01), CD4+ CD25+ CD127-low cells (Treg cells) (P<0.01), the presence of liver metastasis (P<0.05), and more than two metastatic sites (P<0.05). Then, patients were divided into two groups by the “HPD score” calculated by the nomogram. The C-index was 0.845, while the area under the curve (AUC) was 0.830 (sensitivity 75.00%, specificity 91.70%). The calibration plot of HPD probability showed an optimal agreement between the actual observation and prediction by the nomogram. In the validation cohort, the AUC was up to 0.960 (sensitivity 88.70%, specificity 89.80%). CONCLUSIONS: The nomogram was constructed with the presence of liver metastasis, more than two metastatic sites, lengthened APTT and a high level of Treg cells, which could be used to predict HPD risk. |
format | Online Article Text |
id | pubmed-9828302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-98283022023-01-10 Predictive Nomogram for Hyperprogressive Disease During Anti-PD-1/PD-L1 Treatment in Patients with Advanced Non-Small Cell Lung Cancer Wang, Xueping Guo, Zhixing Wu, Xingping Chen, Da Wang, Fang Yang, Lewei Luo, Min Wu, Shaocong Yang, Chuan Huang, Lamei Fu, Liwu Immunotargets Ther Original Research INTRODUCTION: Various studies have reported that anti-PD-1/PD-L1 treatment may lead to the rapid development of tumors called hyperprogressive disease (HPD). A nomogram for HPD prediction in NSCLC patients is urgently needed. METHODS: This retrospective cohort study included 176 cases for establishing a model of HPD prediction and 85 cases for validation in advanced NSCLC patients treated with PD-1/PD-L1 inhibitors. HPD was defined as tumor growth rate (TGR, ≥ 2), tumor growth kinetics (TGK, ≥ 2) or time to treatment failure (TTF, ≤ 2 months). Univariate and multivariate logistic regression were used to estimate the specified factors associated with HPD. Then, the nomogram was developed and validated. RESULTS: Anti-PD-1/PD-L1 therapy resulted in a 9.66% (17/176) incidence of HPD in advanced NSCLC. The overall survival (OS) and progression-free survival (PFS) in patients with HPD were significantly shorter than those in patients without HPD (OS: 7.00 vs 12.00 months, P<0.01; PFS: 2.00 vs 5.00 months, P<0.001, respectively). The HPD prediction nomogram included APTT (P<0.01), CD4+ CD25+ CD127-low cells (Treg cells) (P<0.01), the presence of liver metastasis (P<0.05), and more than two metastatic sites (P<0.05). Then, patients were divided into two groups by the “HPD score” calculated by the nomogram. The C-index was 0.845, while the area under the curve (AUC) was 0.830 (sensitivity 75.00%, specificity 91.70%). The calibration plot of HPD probability showed an optimal agreement between the actual observation and prediction by the nomogram. In the validation cohort, the AUC was up to 0.960 (sensitivity 88.70%, specificity 89.80%). CONCLUSIONS: The nomogram was constructed with the presence of liver metastasis, more than two metastatic sites, lengthened APTT and a high level of Treg cells, which could be used to predict HPD risk. Dove 2023-01-04 /pmc/articles/PMC9828302/ /pubmed/36632330 http://dx.doi.org/10.2147/ITT.S373866 Text en © 2023 Wang et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution– Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Wang, Xueping Guo, Zhixing Wu, Xingping Chen, Da Wang, Fang Yang, Lewei Luo, Min Wu, Shaocong Yang, Chuan Huang, Lamei Fu, Liwu Predictive Nomogram for Hyperprogressive Disease During Anti-PD-1/PD-L1 Treatment in Patients with Advanced Non-Small Cell Lung Cancer |
title | Predictive Nomogram for Hyperprogressive Disease During Anti-PD-1/PD-L1 Treatment in Patients with Advanced Non-Small Cell Lung Cancer |
title_full | Predictive Nomogram for Hyperprogressive Disease During Anti-PD-1/PD-L1 Treatment in Patients with Advanced Non-Small Cell Lung Cancer |
title_fullStr | Predictive Nomogram for Hyperprogressive Disease During Anti-PD-1/PD-L1 Treatment in Patients with Advanced Non-Small Cell Lung Cancer |
title_full_unstemmed | Predictive Nomogram for Hyperprogressive Disease During Anti-PD-1/PD-L1 Treatment in Patients with Advanced Non-Small Cell Lung Cancer |
title_short | Predictive Nomogram for Hyperprogressive Disease During Anti-PD-1/PD-L1 Treatment in Patients with Advanced Non-Small Cell Lung Cancer |
title_sort | predictive nomogram for hyperprogressive disease during anti-pd-1/pd-l1 treatment in patients with advanced non-small cell lung cancer |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9828302/ https://www.ncbi.nlm.nih.gov/pubmed/36632330 http://dx.doi.org/10.2147/ITT.S373866 |
work_keys_str_mv | AT wangxueping predictivenomogramforhyperprogressivediseaseduringantipd1pdl1treatmentinpatientswithadvancednonsmallcelllungcancer AT guozhixing predictivenomogramforhyperprogressivediseaseduringantipd1pdl1treatmentinpatientswithadvancednonsmallcelllungcancer AT wuxingping predictivenomogramforhyperprogressivediseaseduringantipd1pdl1treatmentinpatientswithadvancednonsmallcelllungcancer AT chenda predictivenomogramforhyperprogressivediseaseduringantipd1pdl1treatmentinpatientswithadvancednonsmallcelllungcancer AT wangfang predictivenomogramforhyperprogressivediseaseduringantipd1pdl1treatmentinpatientswithadvancednonsmallcelllungcancer AT yanglewei predictivenomogramforhyperprogressivediseaseduringantipd1pdl1treatmentinpatientswithadvancednonsmallcelllungcancer AT luomin predictivenomogramforhyperprogressivediseaseduringantipd1pdl1treatmentinpatientswithadvancednonsmallcelllungcancer AT wushaocong predictivenomogramforhyperprogressivediseaseduringantipd1pdl1treatmentinpatientswithadvancednonsmallcelllungcancer AT yangchuan predictivenomogramforhyperprogressivediseaseduringantipd1pdl1treatmentinpatientswithadvancednonsmallcelllungcancer AT huanglamei predictivenomogramforhyperprogressivediseaseduringantipd1pdl1treatmentinpatientswithadvancednonsmallcelllungcancer AT fuliwu predictivenomogramforhyperprogressivediseaseduringantipd1pdl1treatmentinpatientswithadvancednonsmallcelllungcancer |