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Predictors of pathological non-invasive lung cancer with pure-solid appearance on computed tomography to identify possible candidates for sublobar resection

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This study aimed to establish favorable predictors for patients with clinical stage IA radiological pure-solid lung cancer to identify possible candidates for sublobar resection.


We examined 275 patients with surgically resected clinical stage IA radiological pure-solid lung cancer. Pathological grade PL0, Ly0, V0, or N0 disease was defined as non-invasive pure-solid lung cancer (NIPS).


Nodal involvement was observed in 63 (23 %) patients with clinical stage IA pure-solid lung cancer, while NIPS was identified in 77 (28 %). Multivariate analysis revealed that air bronchogram (p = 0.0328), clinical T1a (p = 0.0041), and SUVmax (p = 0.0002) were significant clinical predictors of NIPS. When these clinical predictors were combined and the relevant patients’ disease was classified as favorable, the frequency of nodal involvement was only 4 %. Furthermore, the 3-year overall survival (OS) of the patients with “favorable” clinical stage IA pure-solid lung cancer was 100 % despite their operative modes. In contrast, the 3-year OS even for patients with clinical stage IA disease, if they had neither of these clinical predictors, was 74.1 %.


Tumor size, the presence of air bronchogram, and the SUVmax level were significant favorable predictors of pathological non-invasive status, and patients with these clinical predictors could be candidates for sublobar resection for clinical stage IA pure-solid lung cancers.

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This work was supported in part by a Grant-in-Aid for Cancer Research from the Ministry of Health, Labour and Welfare, Japan, the Smoking Research Foundation, and the National Cancer Center Research and Development Fund (26-A-4).

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Aritoshi Hattori and his co-authors have no conflicts of interest.

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Correspondence to Kenji Suzuki.

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Hattori, A., Maeyashiki, T., Matsunaga, T. et al. Predictors of pathological non-invasive lung cancer with pure-solid appearance on computed tomography to identify possible candidates for sublobar resection. Surg Today 46, 102–109 (2016).

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