Cited 5 times in
Validation Study of New IASLC Histology Grading System in Stage I Non-Mucinous Adenocarcinoma Comparing With Minimally Invasive Adenocarcinoma
DC Field | Value | Language |
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dc.contributor.author | 문덕환 | - |
dc.contributor.author | 이성수 | - |
dc.contributor.author | 차윤진 | - |
dc.contributor.author | 김봉준 | - |
dc.contributor.author | 우원기 | - |
dc.date.accessioned | 2023-03-10T01:13:06Z | - |
dc.date.available | 2023-03-10T01:13:06Z | - |
dc.date.issued | 2022-11 | - |
dc.identifier.issn | 1525-7304 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/193068 | - |
dc.description.abstract | Background: A new histologic grading system for pulmonary non-mucinous invasive adenocarcinoma was proposed by the International Association for the Study of Lung Cancer (IASLC). We evaluated its clinical impact on prognosis in stage I patients, including minimally invasive adenocarcinoma (MIA). Patients and methods: 919 patients underwent surgery for lung adenocarcinoma between 2012 and 2019. Stage I patients (n = 500) were retrospectively reviewed. They were divided into 4 categories: MIA and 3 new IASLC grades (grades 1-3). Cox proportional hazards analysis was performed to identify risk factors associated with recurrence and mortality. Furthermore, we compared the predictability of the IASLC grading system with different models that are based on the clinicopathologic characteristics (baseline model), TNM staging, and predominant histologic pattern. The area under the receiver operating characteristic curve (AUC) was calculated for comparison. Results: Recurrence-free survival (RFS) and overall survival (OS) were significantly stratified by the IASLC grading system in patients with stage I adenocarcinoma (P < .001 and P = .003, respectively). In multivariate analyses, IASLC grade 3 was a significant factor for RFS (hazard ratio [HR] 3.18, P < .001) and OS (HR 2.31, P = .013). The AUCs of the new IASLC model were 0.781 for recurrence and 0.770 for mortality, compared with those of the predominant pattern (0.769 for recurrence, 0.747 for death) and TNM staging (0.762 for recurrence, 0.747 for death). Conclusion: The IASLC grading system effectively predicted the prognosis of early-stage adenocarcinoma compared with previous models. The IASLC classification appears to improve the current system; therefore, precise pathologic examination for early-stage adenocarcinoma is warranted. | - |
dc.description.statementOfResponsibility | restriction | - |
dc.language | English | - |
dc.publisher | Elsevier | - |
dc.relation.isPartOf | CLINICAL LUNG CANCER | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.subject.MESH | Adenocarcinoma of Lung* / pathology | - |
dc.subject.MESH | Adenocarcinoma of Lung* / surgery | - |
dc.subject.MESH | Adenocarcinoma* | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Lung Neoplasms* | - |
dc.subject.MESH | Neoplasm Recurrence, Local / pathology | - |
dc.subject.MESH | Neoplasm Staging | - |
dc.subject.MESH | Prognosis | - |
dc.subject.MESH | Retrospective Studies | - |
dc.title | Validation Study of New IASLC Histology Grading System in Stage I Non-Mucinous Adenocarcinoma Comparing With Minimally Invasive Adenocarcinoma | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Thoracic and Cardiovascular Surgery (흉부외과학교실) | - |
dc.contributor.googleauthor | Wongi Woo | - |
dc.contributor.googleauthor | Yoon-Jin Cha | - |
dc.contributor.googleauthor | Bong Jun Kim | - |
dc.contributor.googleauthor | Duk Hwan Moon | - |
dc.contributor.googleauthor | Sungsoo Lee | - |
dc.identifier.doi | 10.1016/j.cllc.2022.06.004 | - |
dc.contributor.localId | A05708 | - |
dc.contributor.localId | A02866 | - |
dc.contributor.localId | A04001 | - |
dc.relation.journalcode | J03603 | - |
dc.identifier.eissn | 1938-0690 | - |
dc.identifier.pmid | 35945128 | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S1525730422001486 | - |
dc.subject.keyword | Histologic subtype | - |
dc.subject.keyword | Lung adenocarcinoma | - |
dc.subject.keyword | Lung cancer | - |
dc.subject.keyword | Predictive model | - |
dc.contributor.alternativeName | Moon, Duk Hwan | - |
dc.contributor.affiliatedAuthor | 문덕환 | - |
dc.contributor.affiliatedAuthor | 이성수 | - |
dc.contributor.affiliatedAuthor | 차윤진 | - |
dc.citation.volume | 23 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | e435 | - |
dc.citation.endPage | e442 | - |
dc.identifier.bibliographicCitation | CLINICAL LUNG CANCER, Vol.23(7) : e435-e442, 2022-11 | - |
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