One-off low-dose CT screening of positive nodules in lung cancer: A prospective community-based cohort study

Xiao, Huang; Z, Shi; Zou, Yan-Hua; Xu, Ke-Kui; Yu, Xiaoping; Li, Wen; Liu, Yang; Chen, Haiyan; Long, Huajun; Chen, Jihuai; Liu, Yanling; Cao, Shiyu; Li, Can; Hu, Yingyun; Liao, Xianzhen; Yan, Shipeng

doi:10.1016/j.lungcan.2023.01.005

Cited by 5 publications

(3 citation statements)

References 23 publications

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“…The role of lung nodules as a risk factor for lung cancer has been widely studied [ 39 - 41 ]. Beyond that, our study also found that the existence of lung nodules combined with emphysema can further increase the lung cancer risk.…”

Section: Discussionmentioning

confidence: 99%

Association of Lung Cancer Risk With the Presence of Both Lung Nodules and Emphysema in a Lung Cancer Screening Trial

Liu,

Feng,

Liu

et al. 2024

World J Oncol

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Background The coexistence of emphysema and lung nodules could interact with each other and then lead to potential higher lung cancer risk. The study aimed to explore the association between emphysema combined with lung nodules and lung cancer risk. Methods A total of 21,949 participants from the National Lung Screening Trial (NLST) who underwent low-dose computed tomography (LDCT) examination were included. Participants were categorized into four groups (NENN group (non-emphysema and non-nodules), E group (emphysema without nodules), N group (nodules without emphysema), and E + N group (nodules with emphysema)) according to whether there were lung nodules and emphysema. Multivariable Cox regression and stratified analyses were performed to estimate the association between the four groups and lung cancer risk. Results Among the 21,949 participants, there were 9,040 (41.2%), 5,819 (26.5%), 4,737 (21.6%), and 2,353 (10.7%) participants in the NENN group, E group, N group, and E + N group. The risk of lung cancer incidence increased in turn in NENN group, E group, N group and E + N group. Compared with NENN group, the age-adjusted hazard ratios (HRs) (95% confidence intervals (CIs)) of lung cancer incidence were 2.07 (1.69 - 2.54) for E group, 4.13 (3.47 - 5.05) for N group, and 6.26 (5.14 - 7.62) for E + N group. The association was robust to adjustment for potential confounders (1.83 (1.47 - 2.27) for E group, 3.97 (3.24 - 4.86) for N group, and 5.23 (4.28 - 6.48) for E + N group). Comparable results as the lung cancer incidence were observed for lung cancer mortality, whether in age-adjusted model (E group: 1.85 (1.39 - 2.46), N group: 2.49 (1.89 - 3.29), E + N group: 4.27 (3.21 - 5.68)) or fully adjusted model (E group: 1.56 (1.15 - 2.11), N group: 2.43 (1.81 - 3.26), E + N group: 3.39 (2.50 - 4.61)). However, the trend of all-cause mortality risk among the four groups was somewhat different from that of lung cancer risk, whether in age-adjusted model (1.37 (1.21 - 1.54) for E group, 1.06 (0.92 - 1.21) for N group, and 1.75 (1.51 - 2.02) for E + N group) or fully adjusted model (1.26 (1.10 - 1.44) for E group, 1.09 (0.94 - 1.27) for N group, and 1.52 (1.30 - 1.79) for E + N group). Conclusion Based on a large-scale lung cancer screening trial in the United States, this study demonstrated that either emphysema or lung nodules can increase lung cancer risk, and lung nodules combined with emphysema can further increase the lung cancer risk and all-cause mortality. The significance of these findings for lung cancer screening should be evaluated.

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Section: Discussionmentioning

confidence: 99%

Association of Lung Cancer Risk With the Presence of Both Lung Nodules and Emphysema in a Lung Cancer Screening Trial

Liu,

Feng,

Liu

et al. 2024

World J Oncol

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“…It found that chest radiotherapy targeting the lung was the only independent risk factor for lung cancer. Authors such as Xiao et al [82] discussed procedures such as single-use low-dose spiral computed tomography (LDCT) for improving early-stage diagnosis and reducing lung cancer mortality. The analysis covered the period 2021-2018 and was based on a competing risk model used to develop the nomogram.…”

Section: Literature Reviewmentioning

confidence: 99%

New Regional Dynamic Cancer Model across the European Union

Negoiță

Ionescu

Zlati

et al. 2023

Cancers

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Background: Can increasing levels of economic wealth significantly influence changes in cancer incidence and mortality rates? Methods: We investigated this issue by means of regression analyses based on the study of incidence and mortality indicators for lip, oral cavity, and pharyngeal; colon; pancreatic; lung; leukaemia; brain and central nervous system cancers in correlation with the levels of economic welfare and financial allocations to health at the level of the European Union member states, with the exception of Luxembourg and Cyprus for which there are no official statistical data reported. Results: The results of the study showed that there were significant disparities both regionally and by gender, requiring corrective public policy measures that were formulated in this study. Conclusions: The conclusions highlight the main findings of the study in terms of the evolution of the disease, present the significant aspects that characterise the evolution of each type of cancer during the period analysed (1993–2021), and highlight the novelty and limitations of the study and future directions of research. As a result, increasing economic welfare is a potential factor in halting the effects of cancer incidence and mortality at the population level, while the financial allocations to health of EU member countries’ budgets are a drawback due to large regional disparities.

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“…Based on the advantages and disadvantages of the above models, this paper proposes a prediction model that combines an attention mechanism-based convolutional neural network (CNN) (Lu et al, 2022) and a recurrent gated unit (GRU) (Xiao et al, 2023). First, the historical data and other predictive indicators are input into the CNN for convolutional processing to extract their important features.…”

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confidence: 99%

CNN-GRU model based on attention mechanism for large-scale energy storage optimization in smart grid

2023

Front. Energy Res.

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Introduction: Smart grid (SG) technologies have a wide range of applications to improve the reliability, economics, and sustainability of power systems. Optimizing large-scale energy storage technologies for smart grids is an important topic in smart grid optimization. By predicting the historical load and electricity price of the power system, a reasonable optimization scheme can be proposed.Methods: Based on this, this paper proposes a prediction model combining a convolutional neural network (CNN) and gated recurrent unit (GRU) based on an attention mechanism to explore the optimization scheme of large-scale energy storage in a smart grid. The CNN model can extract spatial features, and the GRU model can effectively solve the gradient explosion problem in long-term forecasting. Its structure is simpler and faster than LSTM models with similar prediction accuracy. After the CNN-GRU extracts the data, the features are finally weighted by the attention module to improve the prediction performance of the model further. Then, we also compared different forecasting models.Results and Discussion: The results show that our model has better predictive performance and computational power, making an important contribution to developing large-scale energy storage optimization schemes for smart grids.

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One-off low-dose CT screening of positive nodules in lung cancer: A prospective community-based cohort study

Cited by 5 publications

References 23 publications

Association of Lung Cancer Risk With the Presence of Both Lung Nodules and Emphysema in a Lung Cancer Screening Trial

Association of Lung Cancer Risk With the Presence of Both Lung Nodules and Emphysema in a Lung Cancer Screening Trial

New Regional Dynamic Cancer Model across the European Union

CNN-GRU model based on attention mechanism for large-scale energy storage optimization in smart grid

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