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European Radiology

, Volume 29, Issue 4, pp 1674–1683 | Cite as

A simple prediction model using size measures for discrimination of invasive adenocarcinomas among incidental pulmonary subsolid nodules considered for resection

  • Hyungjin Kim
  • Jin Mo Goo
  • Chang Min ParkEmail author
Chest
  • 107 Downloads

Abstract

Objectives

To develop and validate a concise prediction model using simple size measures for the discrimination of invasive pulmonary adenocarcinomas (IPAs) among incidentally detected subsolid nodules (SSNs) considered for resection and to compare its diagnostic performance with the Brock model.

Methods

This retrospective institutional review board-approved study included 427 surgically resected SSNs (121 preinvasive lesions/minimally invasive adenocarcinomas [MIAs] and 306 IPAs) from 407 patients. After stratified random splitting of the study population into the training and validation sets (3:1), a simple logistic model was constructed using nodule size, solid proportion, and type for the differentiation of IPAs. Diagnostic performance of this model was compared with the original and modified Brock models using the DeLong method for area under the receiver-operating characteristic curve (AUC) and McNemar test for diagnostic sensitivity and specificity.

Results

Our proposed model had an AUC of 0.859 in the validation set, while the original Brock model showed an AUC of 0.775 (p = 0.035) and the modified Brock model exhibited an AUC of 0.787 (p = 0.006). At equally high specificity of 90%, our proposed model exhibited significantly higher sensitivity (65.8%) than the original and modified Brock models (38.2% and 50.0%; p < 0.001 and 0.008, respectively).

Conclusions

Our study results demonstrated that the proposed concise model outperformed both Brock models, demonstrating its potential to be utilized as a specific tool to differentiate IPAs from preinvasive lesions and MIAs, which were considered for resection. External validation studies are warranted for the population with incidentally detected SSNs including small SSNs to confirm our observations.

Key Points

• Size measures provided sufficient information for the risk stratification of surgical candidate incidental subsolid nodules.

• Our proposed concise model showed higher diagnostic performance than the Brock model for incidentally detected subsolid nodules.

• Our proposed model can specifically differentiate invasive adenocarcinomas among incidentally detected subsolid nodules and reduce overtreatment for indolent subsolid nodules.

Keywords

Non-small-cell lung carcinoma Adenocarcinoma Multidetector computed tomography Logistic models Differential diagnosis 

Abbreviations

AAH

Atypical adenomatous hyperplasia

AIS

Adenocarcinoma-in-situ

AUC

Area under the receiver-operating characteristic curve

BTS

British Thoracic Society

IPA

Invasive pulmonary adenocarcinoma

MIA

Minimally invasive adenocarcinoma

NPV

Negative predictive value

PPV

Positive predictive value

PSN

Part-solid nodule

ROC

Receiver-operating characteristic

SSN

Subsolid nodule

Notes

Acknowledgements

We express our gratitude to Sunkyung Jeon, Jong Hyuk Lee, Su Yeon Ahn, Roh-Eul Yoo, Hyun-ju Lim, Juil Park, and Woo Hyeon Lim for data acquisition. We also thank Chris Woo for the manuscript editing.

Funding

This study was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT & Future Planning (grant no. 2017R1A2B4008517).

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Chang Min Park.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

Some study subjects or cohorts have been previously reported in journal articles (Eur Radiol 2016 26:4465-4474; Eur J Radiol 2016 85:1174-1180; Eur Radiol 2017 27:3266-3274; Eur Radiol 2017 10.1007/s00330-017-5171-7; Eur Radiol 2017 27:1369-1376).

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

Supplementary material

330_2018_5739_MOESM1_ESM.docx (14 kb)
ESM 1 (DOCX 14 kb)

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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  1. 1.Department of RadiologySeoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research CenterSeoulKorea
  2. 2.Cancer Research InstituteSeoul National UniversitySeoulKorea

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