Literature DB >> 31526256

Cancer Risk in Subsolid Nodules in the National Lung Screening Trial.

Mark M Hammer1, Lauren L Palazzo1, Chung Yin Kong1, Andetta R Hunsaker1.   

Abstract

Background Subsolid pulmonary nodules, comprising pure ground-glass nodules (GGNs) and part-solid nodules (PSNs), have a high risk of indolent malignancy. Lung Imaging Reporting and Data System (Lung-RADS) nodule management guidelines are based on expert opinion and lack independent validation. Purpose To evaluate Lung-RADS estimates of the malignancy rates of subsolid nodules, using nodules from the National Lung Screening Trial (NLST), and to compare Lung-RADS to the NELSON trial classification as well as the Brock University calculator. Materials and Methods Subsets of GGNs and PSNs were selected from the NLST for this retrospective study. A thoracic radiologist reviewed the baseline and follow-up CT images, confirmed that they were true subsolid nodules, and measured the nodules. The primary outcome for each nodule was the development of malignancy within the follow-up period (median, 6.5 years). Nodules were stratified according to Lung-RADS, NELSON trial criteria, and the Brock model. For analyses, nodule subsets were weighted on the basis of frequency in the NLST data set. Nodule stratification models were tested by using receiver operating characteristic curves. Results A total of 622 nodules were evaluated, of which 434 nodules were subsolid. At baseline, 304 nodules were classified as Lung-RADS category 2, with a malignancy rate of 3%, which is greater than the 1% in Lung-RADS (P = .004). The malignancy rate for GGNs smaller than 10 mm (two of 129, 1.3%) was smaller than that for GGNs measuring 10-19 mm (11 of 153, 6%) (P = .01). The malignancy rate for Lung-RADS category 3 was 14% (13 of 67), which is greater than the reported 2% in Lung-RADS (P < .001). The Brock model predicted malignancy better than Lung-RADS and the NELSON trial scheme (area under the receiver operating characteristic curve = 0.78, 0.70, and 0.67, respectively; P = .02 for Brock model vs NELSON trial scheme). Conclusion Subsolid nodules classified as Lung Imaging Reporting and Data System (Lung-RADS) categories 2 and 3 have a higher risk of malignancy than reported. The Brock risk calculator performed better than measurement-based classification schemes such as Lung-RADS. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Kauczor and von Stackelberg in this issue.

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Year:  2019        PMID: 31526256      PMCID: PMC6823608          DOI: 10.1148/radiol.2019190905

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  19 in total

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Authors:  Paul A Harris; Robert Taylor; Robert Thielke; Jonathon Payne; Nathaniel Gonzalez; Jose G Conde
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2.  A method of comparing the areas under receiver operating characteristic curves derived from the same cases.

Authors:  J A Hanley; B J McNeil
Journal:  Radiology       Date:  1983-09       Impact factor: 11.105

3.  Probability of cancer in pulmonary nodules detected on first screening CT.

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Journal:  N Engl J Med       Date:  2013-09-05       Impact factor: 91.245

4.  Lung-RADS Category 4X: Does It Improve Prediction of Malignancy in Subsolid Nodules?

Authors:  Kaman Chung; Colin Jacobs; Ernst T Scholten; Jin Mo Goo; Helmut Prosch; Nicola Sverzellati; Francesco Ciompi; Onno M Mets; Paul K Gerke; Mathias Prokop; Bram van Ginneken; Cornelia M Schaefer-Prokop
Journal:  Radiology       Date:  2017-03-24       Impact factor: 11.105

5.  Reduced lung-cancer mortality with low-dose computed tomographic screening.

Authors:  Denise R Aberle; Amanda M Adams; Christine D Berg; William C Black; Jonathan D Clapp; Richard M Fagerstrom; Ilana F Gareen; Constantine Gatsonis; Pamela M Marcus; JoRean D Sicks
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Authors:  Eduardo J Mortani Barbosa
Journal:  Acad Radiol       Date:  2015-03-13       Impact factor: 3.173

7.  Estimating overdiagnosis in low-dose computed tomography screening for lung cancer: a cohort study.

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8.  Persistent pure ground-glass opacity lung nodules ≥ 10 mm in diameter at CT scan: histopathologic comparisons and prognostic implications.

Authors:  Hyun-Ju Lim; Soomin Ahn; Kyung Soo Lee; Joungho Han; Young Mog Shim; Sookyoung Woo; Jae-Hun Kim; Miyeon Yie; Ho Yun Lee; Chin A Yi
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9.  Delta radiomic features improve prediction for lung cancer incidence: A nested case-control analysis of the National Lung Screening Trial.

Authors:  Dmitry Cherezov; Samuel H Hawkins; Dmitry B Goldgof; Lawrence O Hall; Ying Liu; Qian Li; Yoganand Balagurunathan; Robert J Gillies; Matthew B Schabath
Journal:  Cancer Med       Date:  2018-12-01       Impact factor: 4.452

10.  Malignancy estimation of Lung-RADS criteria for subsolid nodules on CT: accuracy of low and high risk spectrum when using NLST nodules.

Authors:  Kaman Chung; Colin Jacobs; Ernst T Scholten; Onno M Mets; Irma Dekker; Mathias Prokop; Bram van Ginneken; Cornelia M Schaefer-Prokop
Journal:  Eur Radiol       Date:  2017-04-24       Impact factor: 5.315

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4.  Strategies for Reducing False-Positive Screening Results for Intermediate-Size Nodules Evaluated Using Lung-RADS: A Secondary Analysis of National Lung Screening Trial Data.

Authors:  Mark M Hammer; Andetta R Hunsaker
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5.  Cost-Effectiveness of Management Algorithms for Lung-RADS Category 4 Nodules.

Authors:  Mark M Hammer; Sumit Gupta; Chung Yin Kong
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6.  Use of relative CT values to evaluate the invasiveness of pulmonary subsolid nodules in patients with emphysema.

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7.  Lung cancer screening in patients with previous malignancy: Is this cohort at increased risk for malignancy?

Authors:  Elisabeth O'Dwyer; Darragh F Halpenny; Michelle S Ginsberg
Journal:  Eur Radiol       Date:  2020-07-29       Impact factor: 5.315

8.  Developing an understanding of artificial intelligence lung nodule risk prediction using insights from the Brock model.

Authors:  Madhurima R Chetan; Nicholas Dowson; Noah Waterfield Price; Sarim Ather; Angus Nicolson; Fergus V Gleeson
Journal:  Eur Radiol       Date:  2022-03-03       Impact factor: 7.034

9.  Initial Results from Mobile Low-Dose Computerized Tomographic Lung Cancer Screening Unit: Improved Outcomes for Underserved Populations.

Authors:  Derek Raghavan; Mellisa Wheeler; Darcy Doege; John D Doty; Henri Levy; Kia A Dungan; Lauren M Davis; James M Robinson; Edward S Kim; Kathryn F Mileham; James Oliver; Daniel Carrizosa
Journal:  Oncologist       Date:  2019-11-26

10.  Preliminary recommendations for lung surgery during COVID-19 epidemic period.

Authors:  Xin Li; Minghui Liu; Qingchun Zhao; Renwang Liu; Hongbing Zhang; Ming Dong; Song Xu; Jinghao Liu; Honglin Zhao; Sen Wei; Zuoqing Song; Gang Chen; Jun Chen
Journal:  Thorac Cancer       Date:  2020-04-14       Impact factor: 3.500

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