|Table of Contents|

Risk factors of lung GGN patients diagnosed with early invasive adenocarcinoma and prediction model construction

Journal Of Modern Oncology[ISSN:1672-4992/CN:61-1415/R]

Issue:
2024 06
Page:
1070-1074
Research Field:
Publishing date:

Info

Title:
Risk factors of lung GGN patients diagnosed with early invasive adenocarcinoma and prediction model construction
Author(s):
SONG Yan; ZHANG Gaochao; ZHANG Xuemin; CHEN Zhengfu; FU Wei
Department of Nuclear Medicine,Hanzhong 3201 Hospital,Shaanxi Hanzhong 723000,China.
Keywords:
ground glass nodules; lung adenocarcinoma; invasive carcinoma; PET/CT; model
PACS:
R734.2
DOI:
10.3969/j.issn.1672-4992.2024.06.015
Abstract:
Objective:To investigate the risk factors of lung GGN patients diagnosed with early invasive adenocarcinoma and construct prediction model to provide more reference for the early differential diagnosis and treatment of invasive lung adenocarcinoma.Methods:Clinical data of 171 patients with lung GGN for 194 nodules were retrospectively analyzed in the period from January 2017 to January 2023.All patients were divided into invasion group (158 nodules) and non-invasion group (36 nodules) according to pathological diagnosed results of invasive lung adenocarcinoma.The clinicopathological and imaging characteristics of 2 groups were compared and the independent risk factors for early invasive adenocarcinoma diagnosed by lung GGN were evaluated by univariate factor and multivariate factor method.Construction and efficacy analysis of risk prediction model for early invasive adenocarcinoma diagnosed with lung GGN were performed.Results:A total of 158 nodules (81.44%) of 194 nodules in 171 cases were confirmed as infiltrating lung adenocarcinoma by histopathological examination.There were significant differences in the proportion of pleural depression sign,proportion of solid nodules and SUV index between the two combinations (P＜0.05).There was no significant difference in other clinicopathological and imaging characteristics between the two groups (P＞0.05).The results of multi-factor analysis showed that the combination of pleural depression sign,the proportion of solid nodular component and SUV index were independent risk factors for the diagnosis of early invasive adenocarcinoma of lung GGN (P＜0.05).Independent influencing factors of regression model and P-value prediction probability were used to predict the risk of early invasive adenocarcinoma diagnosed by lung GGN.The Yoden index was 52.55%,94.13%,70.72% and 96.66%,respectively.Conclusion:The invasive adenocarcinoma of lung GGN was closely related to pleural depression,the proportion of solid nodular components and SUV index and the prediction model based on the above indexes can accurately guide the early differential diagnosis of invasive lung adenocarcinoma.

References:

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