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In vivo growth of 60 non-screening detected lung cancers: a computed tomography study

Authors :
Pim A. de Jong
Kaman Chung
Onno M. Mets
Cornelia M. Schaefer-Prokop
Ernst T. Scholten
Wouter B. Veldhuis
Pieter Zanen
Bram van Ginneken
Mathias Prokop
Source :
The European Respiratory Journal, European Respiratory Journal, 51,, European Respiratory Journal, 51, 4, pp., European Respiratory Journal, 51(4). European Respiratory Society
Publication Year :
2018
Publisher :
European Respiratory Society, 2018.

Abstract

Current pulmonary nodule management guidelines are based on nodule volume doubling time, which assumes exponential growth behaviour. However, this is a theory that has never been validated in vivo in the routine-care target population. This study evaluates growth patterns of untreated solid and subsolid lung cancers of various histologies in a non-screening setting. Growth behaviour of pathology-proven lung cancers from two academic centres that were imaged at least three times before diagnosis (n=60) was analysed using dedicated software. Random-intercept random-slope mixed-models analysis was applied to test which growth pattern most accurately described lung cancer growth. Individual growth curves were plotted per pathology subgroup and nodule type. We confirmed that growth in both subsolid and solid lung cancers is best explained by an exponential model. However, subsolid lesions generally progress slower than solid ones. Baseline lesion volume was not related to growth, indicating that smaller lesions do not grow slower compared to larger ones. By showing that lung cancer conforms to exponential growth we provide the first experimental basis in the routine-care setting for the assumption made in volume doubling time analysis.<br />Lung cancers in vivo conform to an exponential growth pattern http://ow.ly/eNqB30iUL7D

Details

Language :
English
ISSN :
13993003 and 09031936
Volume :
51
Issue :
4
Database :
OpenAIRE
Journal :
The European Respiratory Journal
Accession number :
edsair.doi.dedup.....6f61991bc1a711a5bc4ff4a84e96160c