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Brock malignancy risk calculator for pulmonary nodules : validation outside a lung cancer screening population

Authors :
Bram van Ginneken
Ernst T. Scholten
Onno M. Mets
Kaman Chung
Paul K. Gerke
Colin Jacobs
Annemarie M. den Harder
Mathias Prokop
Pim A. de Jong
Cornelia M. Schaefer-Prokop
Radiology and Nuclear Medicine
Source :
Thorax, 73, 857. BMJ Publishing Group, Thorax, 73, 9, pp. 857-863, Thorax, 73(9), 857-863. BMJ Publishing Group, Thorax, 73, 857-863
Publication Year :
2018

Abstract

ObjectiveTo assess the performance of the Brock malignancy risk model for pulmonary nodules detected in routine clinical setting.MethodsIn two academic centres in the Netherlands, we established a list of patients aged ≥40 years who received a chest CT scan between 2004 and 2012, resulting in 16 850 and 23 454 eligible subjects. Subsequent diagnosis of lung cancer until the end of 2014 was established through linking with the National Cancer Registry. A nested case–control study was performed (ratio 1:3). Two observers used semiautomated software to annotate the nodules. The Brock model was separately validated on each data set using ROC analysis and compared with a solely size-based model.ResultsAfter the annotation process the final analysis included 177 malignant and 695 benign nodules for centre A, and 264 malignant and 710 benign nodules for centre B. The full Brock model resulted in areas under the curve (AUCs) of 0.90 and 0.91, while the size-only model yielded significantly lower AUCs of 0.88 and 0.87, respectively (p99%.DiscussionThe Brock model shows high predictive discrimination of potentially malignant and benign nodules when validated in an unselected, heterogeneous clinical population. The high NPV may be used to decrease the number of nodule follow-up examinations.

Details

Language :
English
ISSN :
00406376
Database :
OpenAIRE
Journal :
Thorax, 73, 857. BMJ Publishing Group, Thorax, 73, 9, pp. 857-863, Thorax, 73(9), 857-863. BMJ Publishing Group, Thorax, 73, 857-863
Accession number :
edsair.doi.dedup.....36f3921d93e37acd845fe097c3b1f7f4