Prediction model on disease recurrence for low risk resected stage I lung adenocarcinoma

Abstract Background and Objective Although stage I non‐small cell lung carcinoma (NSCLC) typically carries a good prognosis following complete resection, early disease recurrence can occur. An accurate survival prediction model would help refine a follow‐up strategy and personalize future adjuvant therapy. We developed a post‐operative prediction model based on readily available clinical information for patients with stage I adenocarcinoma. Methods We retrospectively studied the disease‐free survival (DFS) of 408 patients with pathologically confirmed low‐risk stage I adenocarcinoma of lung who underwent curative resection from 2013 to 2017. A tree‐based method was employed to partition the cohort into subgroups with distinct DFS outcome and stepwise risk ratio. These covariates were included in multivariate analysis to build a scoring system to predict disease recurrence. The model was subsequently validated using a 2011–2012 cohort. Results Non‐smoker status, stage IA disease, epidermal‐growth factor receptor mutants and female gender were associated with better DFS. Multivariate analysis identified smoking status, disease stage and gender as factors necessary for the scoring system and yielded 3 distinct risk groups for DFS [99.4 (95% CI 78.3–125.3), 62.9 (95% CI 48.2–82.0), 33.7 (95% CI 24.6–46.1) months, p < 0.005]. External validation yielded an area under the curve by receiver operating characteristic analysis of 0.863 (95% CI 0.755–0.972). Conclusion The model could categorize post‐operative patients using readily available clinical information, and may help personalize a follow‐up strategy and future adjuvant therapy.