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

医学 肿瘤科 内科学 腺癌 阶段(地层学) 多元分析 队列 疾病 接收机工作特性 辅助治疗 递归分区 癌症 生物 古生物学
作者
Wang Chun Kwok,Ting Fung,Jcm Ho,David Chi Leung Lam,Ko Yung Sit,Msm Ip,Timmy Wing Kuk Au,Terence Chi Chun Tam
出处
期刊:Respirology [Wiley]
卷期号:28 (7): 669-676 被引量:4
标识
DOI:10.1111/resp.14508
摘要

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.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.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).The model could categorize post-operative patients using readily available clinical information, and may help personalize a follow-up strategy and future adjuvant therapy.

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