• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

Accuracy of Models to Identify Lung Nodule Cancer Risk in the National Lung Screening Trial.

作者信息

Nair Viswam S, Sundaram Vandana, Desai Manisha, Gould Michael K

机构信息

1 University of South Florida Morsani College of Medicine Tampa, Florida.

2 Moffitt Cancer Center and Research Institute Tampa, Florida.

出版信息

Am J Respir Crit Care Med. 2018 May 1;197(9):1220-1223. doi: 10.1164/rccm.201708-1632LE.

DOI:10.1164/rccm.201708-1632LE
PMID:29064264
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5955070/
Abstract
摘要

相似文献

1
Accuracy of Models to Identify Lung Nodule Cancer Risk in the National Lung Screening Trial.国家肺癌筛查试验中识别肺结节癌症风险模型的准确性
Am J Respir Crit Care Med. 2018 May 1;197(9):1220-1223. doi: 10.1164/rccm.201708-1632LE.
2
Nodule size and overdiagnosis in lung cancer CT screening.肺癌CT筛查中的结节大小与过度诊断
J Natl Cancer Inst. 2014 Oct 18;106(11). doi: 10.1093/jnci/dju325. Print 2014 Nov.
3
Lung cancer screening-low dose CT for lung cancer screening: recent trial results and next steps.肺癌筛查——用于肺癌筛查的低剂量CT：近期试验结果及后续步骤
Br J Radiol. 2018 Oct;91(1090):20170460. doi: 10.1259/bjr.20170460. Epub 2017 Oct 17.
4
Computed tomography screening for lung cancer.计算机断层扫描筛查肺癌。
Ann Thorac Surg. 2008 Feb;85(2):S699-700. doi: 10.1016/j.athoracsur.2007.09.054.
5
Maximizing Benefits and Minimizing Harms of Lung Cancer Screening: A Teachable Moment.最大化肺癌筛查的益处并最小化危害：一个可汲取经验教训的时刻。
JAMA Intern Med. 2017 Aug 1;177(8):1197-1198. doi: 10.1001/jamainternmed.2017.2349.
6
Relationship between nodule count and lung cancer probability in baseline CT lung cancer screening: The NELSON study.基线 CT 肺癌筛查中结节数量与肺癌概率的关系：NELSON 研究。
Lung Cancer. 2017 Nov;113:45-50. doi: 10.1016/j.lungcan.2017.08.023. Epub 2017 Sep 1.
7
Relationship between the number of new nodules and lung cancer probability in incidence screening rounds of CT lung cancer screening: The NELSON study.CT 肺癌筛查中发病筛查轮中新结节数量与肺癌概率之间的关系：NELSON 研究。
Lung Cancer. 2018 Nov;125:103-108. doi: 10.1016/j.lungcan.2018.05.007. Epub 2018 May 14.
8
Early lung cancer action project: annual screening using single-slice helical CT.早期肺癌行动项目：使用单层螺旋CT进行年度筛查。
Ann N Y Acad Sci. 2001 Dec;952:124-34. doi: 10.1111/j.1749-6632.2001.tb02733.x.
9
Difficulty of early diagnosis in patients with solitary pulmonary nodule.孤立性肺结节患者的早期诊断困难。
J Thorac Cardiovasc Surg. 2005 May;129(5):1196; author reply 1196-7. doi: 10.1016/j.jtcvs.2004.10.028.
10
Screening for lung cancer using sub-millisievert chest CT with iterative reconstruction algorithm: image quality and nodule detectability.使用亚毫希沃特胸部CT及迭代重建算法进行肺癌筛查：图像质量与结节可检测性
Br J Radiol. 2018 Oct;91(1090):20170658. doi: 10.1259/bjr.20170658. Epub 2017 Dec 5.

引用本文的文献

1
Lung Cancer Risk Prediction in Patients with Persistent Pulmonary Nodules Using the Brock Model and Sybil Model.使用布罗克模型和西比尔模型预测持续性肺结节患者的肺癌风险
Cancers (Basel). 2025 Apr 29;17(9):1499. doi: 10.3390/cancers17091499.
2
A clinically effective model based on cell-free DNA methylation and low-dose CT for risk stratification of pulmonary nodules.基于无细胞游离 DNA 甲基化和低剂量 CT 的临床有效模型用于肺结节的风险分层。
Cell Rep Med. 2024 Oct 15;5(10):101750. doi: 10.1016/j.xcrm.2024.101750. Epub 2024 Sep 27.
3
The Lung Cancer Prediction Model "Stress Test": Assessment of Models' Performance in a High-Risk Prospective Pulmonary Nodule Cohort.肺癌预测模型“压力测试”：在高危前瞻性肺结节队列中对模型性能的评估
CHEST Pulm. 2024 Mar;2(1). doi: 10.1016/j.chpulm.2023.100033. Epub 2023 Dec 26.
4
Lung nodules: sorting the wheat from the chaff.肺部结节：去芜存菁。
Br J Radiol. 2023 Feb;96(1142):20220963. doi: 10.1259/bjr.20220963. Epub 2023 Jan 17.
5
Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification.基于整合血清代谢指纹的多模态平台用于肺腺癌早期检测和肺结节分类。
Adv Sci (Weinh). 2022 Dec;9(34):e2203786. doi: 10.1002/advs.202203786. Epub 2022 Oct 18.
6
Comparison of Brock University, Mayo Clinic and Herder models for pretest probability of cancer in solid pulmonary nodules.实体性肺结节癌前概率的布鲁克大学、梅奥诊所和赫尔德模型比较。
Clin Respir J. 2022 Nov;16(11):740-749. doi: 10.1111/crj.13546. Epub 2022 Oct 7.
7
A new classifier constructed with platelet features for malignant and benign pulmonary nodules based on prospective real-world data.基于前瞻性真实世界数据构建的一种利用血小板特征区分恶性和良性肺结节的新型分类器。
J Cancer. 2022 May 9;13(8):2515-2527. doi: 10.7150/jca.67428. eCollection 2022.
8
Incidental chest findings on coronary CT angiography: a pictorial essay and management proposal.冠状动脉 CT 血管造影中的偶然胸部发现：影像学描述和处理建议。
J Bras Pneumol. 2022 May 13;48(4):e20220015. doi: 10.36416/1806-3756/e20220015. eCollection 2022.
9
Advances in lung cancer screening and early detection.肺癌筛查与早期检测的进展
Cancer Biol Med. 2022 May 11;19(5):591-608. doi: 10.20892/j.issn.2095-3941.2021.0690.
10
Comprehensive Analysis of Clinical Logistic and Machine Learning-Based Models for the Evaluation of Pulmonary Nodules.基于临床逻辑和机器学习的肺结节评估模型的综合分析
JTO Clin Res Rep. 2022 Feb 22;3(4):100299. doi: 10.1016/j.jtocrr.2022.100299. eCollection 2022 Apr.

本文引用的文献

1
Probability of cancer in pulmonary nodules detected on first screening CT.首次筛查 CT 检测到的肺结节的癌症概率。
N Engl J Med. 2013 Sep 5;369(10):910-9. doi: 10.1056/NEJMoa1214726.
2
Reduced lung-cancer mortality with low-dose computed tomographic screening.低剂量计算机断层扫描筛查可降低肺癌死亡率。
N Engl J Med. 2011 Aug 4;365(5):395-409. doi: 10.1056/NEJMoa1102873. Epub 2011 Jun 29.
3
Assessing the performance of prediction models: a framework for traditional and novel measures.评估预测模型的性能：传统和新型指标的框架。
Epidemiology. 2010 Jan;21(1):128-38. doi: 10.1097/EDE.0b013e3181c30fb2.
4
Validation of two models to estimate the probability of malignancy in patients with solitary pulmonary nodules.两种用于估计孤立性肺结节患者恶性概率模型的验证
Thorax. 2008 Apr;63(4):335-41. doi: 10.1136/thx.2007.084731. Epub 2007 Oct 26.
5
A clinical model to estimate the pretest probability of lung cancer in patients with solitary pulmonary nodules.一种用于估计孤立性肺结节患者肺癌预测试验概率的临床模型。
Chest. 2007 Feb;131(2):383-8. doi: 10.1378/chest.06-1261.
6
The probability of malignancy in solitary pulmonary nodules. Application to small radiologically indeterminate nodules.孤立性肺结节的恶性概率。应用于放射学上难以确定的小结节。
Arch Intern Med. 1997 Apr 28;157(8):849-55.
7
Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.比较两条或多条相关的受试者工作特征曲线下的面积：一种非参数方法。
Biometrics. 1988 Sep;44(3):837-45.