Data were expressed as means ± SD. Categorical variables were analyzed using the chi-squared test or Fisher's exact test where appropriate and continuous variables were compared using Student's t-test or the Mann-Whitney U test. All variables were considered as risk factors with a P value <0.10 in univariate analysis that were entered into the multivariate model. Multivariate logistic regression analysis was performed to identify independent factors for predicting one-year survival. Receiver operating characteristic (ROC) curves were plotted and the area under the curve was compared with several serum biomarkers measured in this study. The cutoff value of serum biomarkers for predicting one-year survival among lung cancer patients was analyzed according to ROC curves. The proportion of patients over time was estimated by means of Kaplan-Meier analysis comparing subjects identified as independent factors by multivariate method as well as first-line treatment status.
Results were presented as absolute numbers (percentage) or mean ± standard deviation (SD). Odds ratios and 95% confidence intervals (CIs) were reported for logistic regression analysis. A two-tailed P value of <0.05 was considered significant. All statistical analysis was performed using the SPSS 14.0 software package (SPSS Inc., Chicago, IL, USA).
Results were presented as absolute numbers (percentage) or mean ± standard deviation (SD). Odds ratios and 95% confidence intervals (CIs) were reported for logistic regression analysis. A two-tailed P value of <0.05 was considered significant. All statistical analysis was performed using the SPSS 14.0 software package (SPSS Inc., Chicago, IL, USA).