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Review
. 2021 Sep 20;24(9):660-667.
doi: 10.3779/j.issn.1009-3419.2021.102.29. Epub 2021 Aug 30.

[Advances and Clinical Application of Malignant Probability Prediction Models for Solitary Pulmonary Nodule]

[Article in Chinese]
Affiliations
Review

[Advances and Clinical Application of Malignant Probability Prediction Models for Solitary Pulmonary Nodule]

[Article in Chinese]
Zhaojue Wang et al. Zhongguo Fei Ai Za Zhi. .

Abstract

With the popularization of computed tomography (CT) examinations, the incidence of solitary pulmonary nodules (SPNs) has increased significantly. The assessment of benign and malignant pulmonary nodules is crucial to the diagnosis and treatment of lung nodules. Many models for predicting the malignant probability of lung nodules have been developed. These models assess the malignant probability of lung nodules based on the clinical and imaging characteristics of patients. In recent years, malignant probability prediction models have gradually attracted attention in China. Based on the researches on the malignant probability prediction model of pulmonary nodule, focusing on the establishment or verification of the model in the Chinese patient population, this paper reviews the research progress and clinical application of the malignant probability prediction model of pulmonary nodule, and proposes ideas for the future development. .

【中文题目:孤立性肺结节恶性概率预测模型 的研究进展及临床应用】 【中文摘要:随着计算机断层扫描(computed tomography, CT)的普及,孤立性肺结节(solitary pulmonary nodule, SPN)发病率明显上升。肺结节良恶性评估对肺结节诊治决策至关重要。许多肺结节恶性概率预测模型已被开发,这些模型基于患者临床和影像学特征来评估肺结节恶性概率。近年来,肺结节恶性概率预测模型在国内逐渐引起关注。本文基于肺结节恶性概率预测模型研究,重点关注在中国患者群体中模型的建立或验证情况,综述肺结节恶性概率预测模型的研究进展和临床应用情况,并为模型未来发展提出思路。 】 【中文关键词:模型;肺结节;肺肿瘤】.

Keywords: Lung neoplasms; Models; Pulmonary nodules.

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References

    1. Swensen SJ, Silverstein MD, Ilstrup DM, et al. The probability of malignancy in solitary pulmonary nodules: Application to small radiologically indeterminate nodules. Arch Intern Med. 1997;157(8):849–855. doi: 10.1001/archinte.1997.00440290031002. - DOI - PubMed
    1. Herder GJ, van Tinteren H, Golding RP, et al. Clinical prediction model to characterize pulmonary nodules: validation and added value of 18F-fluorodeoxyglucose positron emission tomography. Chest. 2005;128(4):2490–2496. doi: 10.1378/chest.128.4.2490. - DOI - PubMed
    1. McWilliams A, Tammemagi MC, Mayo JR, et al. Probability of cancer in pulmonary nodules detected on first screening CT. N Engl J Med. 2013;369(10):910–919. doi: 10.1056/NEJMoa1214726. - DOI - PMC - PubMed
    1. Gould MK, Ananth L, Barnett PG, et al. A clinical model to estimate the pretest probability of lung cancer in patients with solitary pulmonary nodules. Chest. 2007;131(2):383–388. doi: 10.1378/chest.06-1261. - DOI - PMC - PubMed
    1. Li Y, Chen KZ, Sui XC, et al. Establishment of a mathematical prediction model to evaluate the probability of malignancy or benign in patients with solitary pulmonary nodules. Beijing Da Xue Xue Bao: Yi Xue Ban. 2011;43(3):450–454. - PubMed
    2. 李 运, 陈 克终, 隋 锡朝, et al. 孤立性肺结节良恶性判断数学预测模型的建立. 北京大学学报: 医学版. 2011;43(3):450–454. doi: 10.3969/j.issn.1671-167X.2011.03.027. - DOI - PubMed

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