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Metabolic phenotypes, serum tumor markers, and histopathological subtypes in predicting bone metastasis: analysis of 695 patients with lung cancer in China

BACKGROUND: Patients with lung cancer who develop bone metastasis (BM) generally have an adverse prognosis. Although several clinical models have been used to predict BM in patients with lung cancer, the results are unsatisfactory. In this retrospective study, we investigated the role of (18)F-2-flu...

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Autores principales: Jiang, Maoqing, Chen, Ping, Zhang, Xiaohui, Guo, Xiuyu, Gao, Qiaoling, Ma, Lijuan, Mei, Weiqi, Zhang, Jingfeng, Zheng, Jianjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006154/
https://www.ncbi.nlm.nih.gov/pubmed/36915307
http://dx.doi.org/10.21037/qims-22-741
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author Jiang, Maoqing
Chen, Ping
Zhang, Xiaohui
Guo, Xiuyu
Gao, Qiaoling
Ma, Lijuan
Mei, Weiqi
Zhang, Jingfeng
Zheng, Jianjun
author_facet Jiang, Maoqing
Chen, Ping
Zhang, Xiaohui
Guo, Xiuyu
Gao, Qiaoling
Ma, Lijuan
Mei, Weiqi
Zhang, Jingfeng
Zheng, Jianjun
author_sort Jiang, Maoqing
collection PubMed
description BACKGROUND: Patients with lung cancer who develop bone metastasis (BM) generally have an adverse prognosis. Although several clinical models have been used to predict BM in patients with lung cancer, the results are unsatisfactory. In this retrospective study, we investigated the role of (18)F-2-fluoro-2-deoxyglucose (FDG) metabolic activity, serum tumor markers, and histopathological subtypes in predicting BM in patients with lung cancer. METHODS: This study included 695 consecutive patients with lung cancer who underwent (18)F-FDG positron emission tomography/computed tomography (PET/CT) and in whom serum tumor markers were detected prior to treatment. The maximum standardized uptake value of primary tumors (pSUV(max)), metastatic lymph nodes (nSUV(max)) and distant metastases (mSUV(max)), 8 serum tumor markers [carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), squamous cell carcinoma-related antigen (SCCA), cytokeratin 19 fragment (CYFRA21-1), carbohydrate antigen (CA) 125, CA50, CA72-4, and ferritin], and histopathological subtypes were compared between patients with and without BM. Receiver operating characteristic (ROC) curve and multiple logistic regression analyses were performed to identify predictors of BM in patients with lung cancer. RESULTS: BM was identified in 133 (19.1%) patients and not in 562 (80.9%). Patients with BM had significantly higher pSUV(max), nSUV(max), and mSUV(max) than did those without BM. High concentrations of 6 serum tumor markers (i.e., CEA, ferritin, NSE, CA50, CA125, and CYFRA21-1) were significantly associated with BM. There were significant differences in the proportion of histopathological subtypes between patients with and without BM (χ(2)=32.35; P<0.001). The area under ROC-derived curve based on metabolic parameters was 0.737 (95% CI: 0.644–0.829) and 0.884 (95% CI: 0.825–0.943) when combined with the 6 serum tumor markers and histopathological subtypes, respectively. CONCLUSIONS: High pSUV(max), nSUV(max), and mSUV(max) favor the presence of BM in patients with lung cancer, and serum tumor markers and histopathological subtypes are important factors for predicting BM in these patients.
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spelling pubmed-100061542023-03-12 Metabolic phenotypes, serum tumor markers, and histopathological subtypes in predicting bone metastasis: analysis of 695 patients with lung cancer in China Jiang, Maoqing Chen, Ping Zhang, Xiaohui Guo, Xiuyu Gao, Qiaoling Ma, Lijuan Mei, Weiqi Zhang, Jingfeng Zheng, Jianjun Quant Imaging Med Surg Original Article BACKGROUND: Patients with lung cancer who develop bone metastasis (BM) generally have an adverse prognosis. Although several clinical models have been used to predict BM in patients with lung cancer, the results are unsatisfactory. In this retrospective study, we investigated the role of (18)F-2-fluoro-2-deoxyglucose (FDG) metabolic activity, serum tumor markers, and histopathological subtypes in predicting BM in patients with lung cancer. METHODS: This study included 695 consecutive patients with lung cancer who underwent (18)F-FDG positron emission tomography/computed tomography (PET/CT) and in whom serum tumor markers were detected prior to treatment. The maximum standardized uptake value of primary tumors (pSUV(max)), metastatic lymph nodes (nSUV(max)) and distant metastases (mSUV(max)), 8 serum tumor markers [carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), squamous cell carcinoma-related antigen (SCCA), cytokeratin 19 fragment (CYFRA21-1), carbohydrate antigen (CA) 125, CA50, CA72-4, and ferritin], and histopathological subtypes were compared between patients with and without BM. Receiver operating characteristic (ROC) curve and multiple logistic regression analyses were performed to identify predictors of BM in patients with lung cancer. RESULTS: BM was identified in 133 (19.1%) patients and not in 562 (80.9%). Patients with BM had significantly higher pSUV(max), nSUV(max), and mSUV(max) than did those without BM. High concentrations of 6 serum tumor markers (i.e., CEA, ferritin, NSE, CA50, CA125, and CYFRA21-1) were significantly associated with BM. There were significant differences in the proportion of histopathological subtypes between patients with and without BM (χ(2)=32.35; P<0.001). The area under ROC-derived curve based on metabolic parameters was 0.737 (95% CI: 0.644–0.829) and 0.884 (95% CI: 0.825–0.943) when combined with the 6 serum tumor markers and histopathological subtypes, respectively. CONCLUSIONS: High pSUV(max), nSUV(max), and mSUV(max) favor the presence of BM in patients with lung cancer, and serum tumor markers and histopathological subtypes are important factors for predicting BM in these patients. AME Publishing Company 2023-02-01 2023-03-01 /pmc/articles/PMC10006154/ /pubmed/36915307 http://dx.doi.org/10.21037/qims-22-741 Text en 2023 Quantitative Imaging in Medicine and Surgery. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Jiang, Maoqing
Chen, Ping
Zhang, Xiaohui
Guo, Xiuyu
Gao, Qiaoling
Ma, Lijuan
Mei, Weiqi
Zhang, Jingfeng
Zheng, Jianjun
Metabolic phenotypes, serum tumor markers, and histopathological subtypes in predicting bone metastasis: analysis of 695 patients with lung cancer in China
title Metabolic phenotypes, serum tumor markers, and histopathological subtypes in predicting bone metastasis: analysis of 695 patients with lung cancer in China
title_full Metabolic phenotypes, serum tumor markers, and histopathological subtypes in predicting bone metastasis: analysis of 695 patients with lung cancer in China
title_fullStr Metabolic phenotypes, serum tumor markers, and histopathological subtypes in predicting bone metastasis: analysis of 695 patients with lung cancer in China
title_full_unstemmed Metabolic phenotypes, serum tumor markers, and histopathological subtypes in predicting bone metastasis: analysis of 695 patients with lung cancer in China
title_short Metabolic phenotypes, serum tumor markers, and histopathological subtypes in predicting bone metastasis: analysis of 695 patients with lung cancer in China
title_sort metabolic phenotypes, serum tumor markers, and histopathological subtypes in predicting bone metastasis: analysis of 695 patients with lung cancer in china
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006154/
https://www.ncbi.nlm.nih.gov/pubmed/36915307
http://dx.doi.org/10.21037/qims-22-741
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