Objective: To investigate the prognostic factors of small cell lung cancer (SCLC) and establish a reliable model of clinical prognostic index.
Methods: Kaplan-Meier and Cox regression were used to analyze the relationship between survival time and prognostic factors in 60 cases of SCLC. The prognostic factors included clinical and laboratory parameters, serum cytokeratin fragment 19 (CYFRA21-1), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), CA125, interleukin-2 (IL-2) and soluble interleukin-2 receptors (sIL-2R).
Results: Kaplan-Meier analysis showed that poor prognosis was in patients with KPS < 80 or extensive disease and unrelated to other clinical parameters such as age, sex and smoking index, and in patients with serum NSE > 30 micro g/L, CEA > 5.0 micro g/L, CA125 > 37 KU/L and sIL-2R > 500 KU/L. Serum IL-2 and CYFRA21-1 were also elevated, but had no significant prognostic value. Multivariate analysis indicated that serum NSE, stage and treatment of disease were independent prognostic factors. The three prognostic factors enabled establishment of a prognostic index (PI) based on a simple algorithm: PI = NSE (0 if < or = 30 micro g/L, 1 if > 30 microg/L) + stage (0 = LD, 1 = ED) + CEA (0 if < or = 5.0 microg/L, 1 if > 5.0 microg/L).
Conclusion: The stage of disease, systemic treatment and the level of serum NSE are independent prognostic factors. Without considering the influence of treatment-related factors on survival, the levels of serum CEA, NSE and stage of disease before treatment are significant independent prognostic factors. PI calculated on the basis of CEA, NSE and stage is recommended to predict the survival of SCLC.