Exploring Stage I non-small-cell lung cancer: development of a prognostic model predicting 5-year survival after surgical resection†

医学 DLCO公司 分级(工程) 淋巴结切除术 阶段(地层学) 比例危险模型 内科学 肺癌 肿瘤科 列线图 外科 癌症 扩散能力 肺功能 古生物学 土木工程 工程类 生物
作者
Francesco Guerrera,Luca Errico,Andrea Evangelista,Pier Luigi Filosso,Enrico Ruffini,Elena Lisi,Giulia Bora,Elena Asteggiano,Stefania Olivetti,Paolo Olivo Lausi,Francesco Ardissone,A Oliaro
出处
期刊:European Journal of Cardio-Thoracic Surgery [Oxford University Press]
卷期号:47 (6): 1037-1043 被引量:35
标识
DOI:10.1093/ejcts/ezu410
摘要

Despite impressive results in diagnosis and treatment of non-small-cell lung cancer (NSCLC), more than 30% of patients with Stage I NSCLC die within 5 years after surgical treatment. Identification of prognostic factors to select patients with a poor prognosis and development of tailored treatment strategies are then advisable. The aim of our study was to design a model able to define prognosis in patients with Stage I NSCLC, submitted to surgery with curative intent.A retrospective analysis of two surgical registries was performed. Predictors of survival were investigated using the Cox model with shared frailty (accounting for the within-centre correlation). Candidate predictors were: age, gender, smoking habit, morbidity, previous malignancy, Eastern Cooperative Oncology Group performance status, clinical N stage, maximum standardized uptake value (SUV(max)), forced expiratory volume in 1 s, carbon monoxide lung diffusion capacity (DLCO), extent of surgical resection, systematic lymphadenectomy, vascular invasion, pathological T stage, histology and histological grading. The final model included predictors with P < 0.20, after a backward selection. Missing data in evaluated predictors were multiple-imputed and combined estimates were obtained from 10 imputed data sets.Analysis was performed on 848 consecutive patients. The median follow-up was 48 months. Two hundred and nine patients died (25%), with a 5-year overall survival (OS) rate of 74%. The final Cox model demonstrated that mortality was significantly associated with age, male sex, presence of cardiac comorbidities, DLCO (%), SUV(max), systematic nodal dissection, presence of microscopic vascular invasion, pTNM stage and histological grading. The final model showed a fair discrimination ability (C-statistic = 0.69): the calibration of the model indicated a good agreement between observed and predicted survival.We designed an effective prognostic model based on clinical, pathological and surgical covariates. Our preliminary results need to be refined and validated in a larger patient population, in order to provide an easy-to-use prognostic tool for Stage I NSCLC patients.

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