Literature DB >> 29110848

Relationship between nodule count and lung cancer probability in baseline CT lung cancer screening: The NELSON study.

Marjolein A Heuvelmans1, Joan E Walter2, Robin B Peters3, Geertruida H de Bock4, Uraujh Yousaf-Khan5, Carlijn M van der Aalst5, Harry J M Groen6, Kristiaan Nackaerts7, Peter Ma van Ooijen2, Harry J de Koning5, Matthijs Oudkerk2, Rozemarijn Vliegenthart2.   

Abstract

OBJECTIVES: To explore the relationship between nodule count and lung cancer probability in baseline low-dose CT lung cancer screening.
MATERIALS AND METHODS: Included were participants from the NELSON trial with at least one baseline nodule (3392 participants [45% of screen-group], 7258 nodules). We determined nodule count per participant. Malignancy was confirmed by histology. Nodules not diagnosed as screen-detected or interval cancer until the end of the fourth screening round were regarded as benign. We compared lung cancer probability per nodule count category.
RESULTS: 1746 (51.5%) participants had one nodule, 800 (23.6%) had two nodules, 354 (10.4%) had three nodules, 191 (5.6%) had four nodules, and 301 (8.9%) had>4 nodules. Lung cancer in a baseline nodule was diagnosed in 134 participants (139 cancers; 4.0%). Median nodule count in participants with only benign nodules was 1 (Inter-quartile range [IQR]: 1-2), and 2 (IQR 1-3) in participants with lung cancer (p=NS). At baseline, malignancy was detected mostly in the largest nodule (64/66 cancers). Lung cancer probability was 62/1746 (3.6%) in case a participant had one nodule, 33/800 (4.1%) for two nodules, 17/354 (4.8%) for three nodules, 12/191 (6.3%) for four nodules and 10/301 (3.3%) for>4 nodules (p=NS).
CONCLUSION: In baseline lung cancer CT screening, half of participants with lung nodules have more than one nodule. Lung cancer probability does not significantly change with the number of nodules. Baseline nodule count will not help to differentiate between benign and malignant nodules. Each nodule found in lung cancer screening should be assessed separately independent of the presence of other nodules.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Computed tomography; Lung neoplasms; Mass screening; Pulmonary nodule

Mesh:

Year:  2017        PMID: 29110848     DOI: 10.1016/j.lungcan.2017.08.023

Source DB:  PubMed          Journal:  Lung Cancer        ISSN: 0169-5002            Impact factor:   5.705


  23 in total

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Journal:  Transl Lung Cancer Res       Date:  2021-05

10.  Features for Predicting Absorbable Pulmonary Solid Nodules as Depicted on Thin-Section Computed Tomography.

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