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

Abstract

OBJECTIVES: 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. METHODS: 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 (SUVmax), 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. RESULTS: 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 (%), SUVmax, 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. CONCLUSIONS: 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.