Cargando…
Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules
The purpose of this study was to assess whether homology-based emphysema quantification (HEQ) is significantly associated with lung cancer risk. This retrospective study was approved by our institutional review board. We included 576 patients with lung nodules (317 men and 259 women; age, 66.8 ± 12....
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6342309/ https://www.ncbi.nlm.nih.gov/pubmed/30668605 http://dx.doi.org/10.1371/journal.pone.0210720 |
_version_ | 1783389104759635968 |
---|---|
author | Nishio, Mizuho Kubo, Takeshi Togashi, Kaori |
author_facet | Nishio, Mizuho Kubo, Takeshi Togashi, Kaori |
author_sort | Nishio, Mizuho |
collection | PubMed |
description | The purpose of this study was to assess whether homology-based emphysema quantification (HEQ) is significantly associated with lung cancer risk. This retrospective study was approved by our institutional review board. We included 576 patients with lung nodules (317 men and 259 women; age, 66.8 ± 12.3 years), who were selected from a database previously generated for computer-aided diagnosis. Of these, 283 were diagnosed with lung cancer, whereas the remaining 293 showed benign lung nodules. HEQ was performed and percentage of low-attenuation lung area (LAA%) was calculated on the basis of computed tomography scans. Statistical models were constructed to estimate lung cancer risk using logistic regression; sex, age, smoking history (Brinkman index), LAA%, and HEQ were considered independent variables. The following three models were evaluated: the base model (sex, age, and smoking history); the LAA% model (the base model + LAA%); and the HEQ model (the base model + HEQ). Model performance was assessed using receiver operating characteristic analysis and the associated area under the curve (AUC). Differences in AUCs among the models were evaluated using Delong’s test. AUCs of the base, LAA%, and HEQ models were 0.585, 0.593, and 0.622, respectively. HEQ coefficient was statistically significant in the HEQ model (P = 0.00487), but LAA% coefficient was not significant in the LAA% model (P = 0.199). Delong’s test revealed significant difference in AUCs between the LAA% and HEQ models (P = 0.0455). In conclusion, after adjusting for age, sex, and smoking history (Brinkman index), HEQ was significantly associated with lung cancer risk. |
format | Online Article Text |
id | pubmed-6342309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-63423092019-02-01 Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules Nishio, Mizuho Kubo, Takeshi Togashi, Kaori PLoS One Research Article The purpose of this study was to assess whether homology-based emphysema quantification (HEQ) is significantly associated with lung cancer risk. This retrospective study was approved by our institutional review board. We included 576 patients with lung nodules (317 men and 259 women; age, 66.8 ± 12.3 years), who were selected from a database previously generated for computer-aided diagnosis. Of these, 283 were diagnosed with lung cancer, whereas the remaining 293 showed benign lung nodules. HEQ was performed and percentage of low-attenuation lung area (LAA%) was calculated on the basis of computed tomography scans. Statistical models were constructed to estimate lung cancer risk using logistic regression; sex, age, smoking history (Brinkman index), LAA%, and HEQ were considered independent variables. The following three models were evaluated: the base model (sex, age, and smoking history); the LAA% model (the base model + LAA%); and the HEQ model (the base model + HEQ). Model performance was assessed using receiver operating characteristic analysis and the associated area under the curve (AUC). Differences in AUCs among the models were evaluated using Delong’s test. AUCs of the base, LAA%, and HEQ models were 0.585, 0.593, and 0.622, respectively. HEQ coefficient was statistically significant in the HEQ model (P = 0.00487), but LAA% coefficient was not significant in the LAA% model (P = 0.199). Delong’s test revealed significant difference in AUCs between the LAA% and HEQ models (P = 0.0455). In conclusion, after adjusting for age, sex, and smoking history (Brinkman index), HEQ was significantly associated with lung cancer risk. Public Library of Science 2019-01-22 /pmc/articles/PMC6342309/ /pubmed/30668605 http://dx.doi.org/10.1371/journal.pone.0210720 Text en © 2019 Nishio et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Nishio, Mizuho Kubo, Takeshi Togashi, Kaori Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules |
title | Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules |
title_full | Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules |
title_fullStr | Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules |
title_full_unstemmed | Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules |
title_short | Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules |
title_sort | estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6342309/ https://www.ncbi.nlm.nih.gov/pubmed/30668605 http://dx.doi.org/10.1371/journal.pone.0210720 |
work_keys_str_mv | AT nishiomizuho estimationoflungcancerriskusinghomologybasedemphysemaquantificationinpatientswithlungnodules AT kubotakeshi estimationoflungcancerriskusinghomologybasedemphysemaquantificationinpatientswithlungnodules AT togashikaori estimationoflungcancerriskusinghomologybasedemphysemaquantificationinpatientswithlungnodules |