Serum KL-6 Levels in Patients with Lung Cancer

Yoshimasu, Tatsuya

doi:10.4172/2161-105x.1000118

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…However, an increase in KL-6 does not always indicate the presence of IP. Yoshimatsu et al reported that KL-6 levels could increase by the existence of lung cancer itself, with a significant association with tumor size [ 10 ]. Several cases showed high pre-treatment KL-6 levels, although they did not have pre-existing IP (the bottom right example in Fig 5 ).…”

Section: Discussionmentioning

confidence: 99%

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Synergistic combination of a topologically invariant imaging signature and a biomarker for the accurate prediction of symptomatic radiation pneumonitis before stereotactic ablative radiotherapy for lung cancer: A retrospective analysis

et al. 2022

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Objectives We aimed to explore the synergistic combination of a topologically invariant Betti number (BN)-based signature and a biomarker for the accurate prediction of symptomatic (grade ≥2) radiation-induced pneumonitis (RP+) before stereotactic ablative radiotherapy (SABR) for lung cancer. Methods A total of 272 SABR cases with early-stage non-small cell lung cancer were chosen for this study. The occurrence of RP+ was predicted using a support vector machine (SVM) model trained with the combined features of the BN-based signature extracted from planning computed tomography (pCT) images and a pretreatment biomarker, serum Krebs von den Lungen-6 (BN+KL-6 model). In all, 242 (20 RP+ and 222 RP–(grade 1)) and 30 cases (8 RP+ and 22 RP–) were used for training and testing the model, respectively. The BN-based features were extracted from BN maps that characterize topologically invariant heterogeneous traits of potential RP+ lung regions on pCT images by applying histogram- and texture-based feature calculations to the maps. The SVM models were built to predict RP+ patients with a BN signature that was constructed based on the least absolute shrinkage and selection operator logistic regression model. The evaluation of the prediction models was performed based on the area under the receiver operating characteristic curves (AUCs) and accuracy in the test. The performance of the BN+KL-6 model was compared to the performance based on the BN, conventional original pCT, and wavelet decomposition (WD) models. Results The test AUCs obtained for the BN+KL-6, BN, pCT, and WD models were 0.825, 0.807, 0.642, and 0.545, respectively. The accuracies of the BN+KL-6, BN, pCT, and WD models were found to be 0.724, 0.708, 0.591, and 0.534, respectively. Conclusion This study demonstrated the comprehensive performance of the BN+KL-6 model for the prediction of potential RP+ patients before SABR for lung cancer.

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Section: Discussionmentioning

confidence: 99%

“…Therefore, prescreening of KL-6 is suggested to decide the strategy for SABR in lung cancer patients [ 5 – 7 ]. However, since KL-6 is associated with RP+ as well as the existence of lung cancer itself [ 10 , 11 ], the predictive performance of pretreatment KL-6 may not be sufficient ( S1 Table ).…”

Section: Introductionmentioning

confidence: 99%

Synergistic combination of a topologically invariant imaging signature and a biomarker for the accurate prediction of symptomatic radiation pneumonitis before stereotactic ablative radiotherapy for lung cancer: A retrospective analysis

et al. 2022

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“…KL-6 was first suggested as a serum biomarker for lung, breast and pancreatic cancers. In lung cancer, its serum levels could indicate malignancy progression 20 . However, KL-6 showed a lower diagnostic accuracy than other tumor markers, such as carcinoembryonic antigen, a reliable predictor of treatment response in NSCLC 21 .…”

Section: Peripheral Biomarkers Of Ipf and Lung Cancermentioning

confidence: 99%

Non-invasive Biomarkers of Idiopathic Pulmonary Fibrosis and Lung Cancer

Armati¹,

Michalczyszyn²,

Zaczyk³

et al. 2022

BRN

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Introduction:The aim of this article is to collect and summarize the evidence related to the role of non-invasive biomarkers in lung cancer and idiopathic pulmonary fibrosis (IPF), to better understand the point in common of these two conditions and the possible uses, and to better understand and define these diseases individually and together. Methods: The methodology for this study consisted of a systematic review searching on PubMed covering the period between 2000 and 2020. From this research, only 13 articles were considered as most relevant regarding this theme. Conclusion: This review provides a current state of knowledge regarding the use of non-invasive biomarkers in lung cancer and IPF to address clinical practice and research proposals to better understand the correlation between IPF and lung cancer and to give other possible information about the severity and the prognosis in IPF patients. (BRN Rev. 2021;7(2):109-14)

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Serum KL-6 Levels in Patients with Lung Cancer

Cited by 2 publications

References 17 publications

Synergistic combination of a topologically invariant imaging signature and a biomarker for the accurate prediction of symptomatic radiation pneumonitis before stereotactic ablative radiotherapy for lung cancer: A retrospective analysis

Synergistic combination of a topologically invariant imaging signature and a biomarker for the accurate prediction of symptomatic radiation pneumonitis before stereotactic ablative radiotherapy for lung cancer: A retrospective analysis

Non-invasive Biomarkers of Idiopathic Pulmonary Fibrosis and Lung Cancer

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