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Efficacy of a new surgical indicator for lung cancer with interstitial lung disease based on the gender–age–physiology staging system

Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Selecting the optimal surgical strategy for lung cancer patients with interstitial lung disease (ILD) remains difficult. This study evaluated the prognostic value of a newly proposed surgical indicator-the predicted ILD Gender-Age-Physiology (GAP) stage-which incorporates predicted postoperative pulmonary function into the conventional ILD-GAP stage. METHODS: This study retrospectively analyzed 125 patients with clinical stage 1 lung cancer and ILD who underwent surgery during 2011-2023. Postoperative outcomes were compared according to surgical procedure and predicted ILD-GAP stage. RESULTS: The 5-year overall survival (OS) rate was markedly superior in patients who underwent anatomical resection with a predicted ILD-GAP stage ≤ 2 than in those who underwent wedge resection (75.0% vs. 21.3%, p < 0.001). In contrast, survival did not differ between anatomical resection with a predicted ILD-GAP stage 3 and wedge resection (27.8% vs. 21.3%, p = 0.934). Multivariate analysis identified diffusing capacity of carbon monoxide (p = 0.043), anatomical resection with a predicted ILD-GAP stage ≤ 2 (p = 0.009), and pathological stage 1 (p = 0.035) as independent predictors of prognosis. Furthermore, the predicted ILD-GAP stage provided superior prognostic accuracy for 5-year OS compared with the original ILD-GAP stage (area under the curve: 0.735 vs. 0.653; p = 0.040). CONCLUSIONS: The proposed surgical indicator enhanced prognostic stratification in lung cancer patients with ILD. In particular, anatomical lung resection in patients with a predicted ILD-GAP stage ≤ 2 was identified as an independent favorable prognostic factor for 5-year OS, highlighting the importance of surgical planning.
Institution: Nagoya University
Language: English
Field: Medicine
Open Access status: hybrid
Estimated APC paid: $4,590
OpenAlex ID: W7203887792
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Cites: 26
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