Clinical Factors Influencing Long-Term Survival in a Real-Life Cohort of Early Stage Non-Small-Cell Lung Cancer Patients

Abstract BACKGROUND Current prognosis in oncology is reduced to the tumour stage and performance status, leaving out many other factors that may impact the patient´s management. Prognostic stratification of early stage non-small-cell lung cancer (NSCLC) patients with poor prognosis after surgery is of considerable clinical relevance. The objective of this study was to identify clinical factors associated with long-term overall survival in a real-life cohort of patients with stage I-II NSCLC and develop a prognostic model that identifies features associated with poor prognosis and stratifies patients by risk. METHODS This is a cohort study including 505 patients, diagnosed with stage I-II NSCLC, who underwent curative surgical procedures at a tertiary hospital in Madrid, Spain. RESULTS Median OS (in months) was 63.7 (95% CI, 58.7–68.7) for the whole cohort, 62.4 in patients submitted to surgery and 65 in patients submitted to surgery and adjuvant treatment. The univariate analysis estimated that a female diagnosed with NSCLC has a 0.967 (95% CI 0.936–0.999) probability of survival one year after diagnosis and a 0.784 (95% CI 0.712–0.863) five years after diagnosis. For males, these probabilities drop to 0.904 (95% CI 0.875–0.934) and 0.613 (95% CI 0.566–0.665), respectively. Multivariable analysis shows that sex, age at diagnosis, type of treatment, ECOG-PS, and stage are statistically significant variables (p < 0.10). According to the Cox regression model, age over 50, ECOG-PS 1 or 2, and stage ll are risk factors for survival (HR > 1) while adjuvant chemotherapy is a good prognostic variable (HR < 1). The prognostic model identified a high-risk profile defined by males over 71 years old, former smokers, treated with surgery, ECOG-PS 2. CONCLUSIONS Surgery plus adjuvant chemotherapy was associated with the best long-term OS in our patients. The prognostic model identified Age, Sex, Stage and ECOG-PS as significant factors to explain the probability of survival.