Xu Zhang1,2, Jin Yang1,2, Qiao Huang3, Jun Lyu1,2. 1. Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University , Xi'an , China. 2. School of Public Health, Xi'an Jiaotong University Health Science Center , Xi'an , China. 3. Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University , Wuhan , China.
Abstract
Background: Accurate prognostic factors for gastric adenocarcinoma are still lacking in clinical practice, which contributes to inappropriate treatment. Applying the widely used Cox-proportional hazards model to describe survival trends and identify prognostic factors has limitations that result in a risk of bias. A competing-risk model was therefore adopted in this study to identify the significant prognostic factors and evaluate the cumulative incidence of cause-specific death for gastric adenocarcinoma, which can be used to guide clinical treatments. Methods: All of the cases analyzed in this study were extracted from the SEER (Surveillance, Epidemiology, and End Results) database. Using the competing risk approach, we calculated the cumulative incidence function (CIF) for cause-specific death and death from other causes at each time point. The Fine and Gray's proportional subdistribution hazard model was then applied in the univariate analysis and multivariate analysis to test the differences in CIF between different groups and obtain independent prognostic factors. Results: The univariate analysis showed that patients with characteristics of advanced pathology grade, lymph node involvement, and metastasis, were at risk of increasing cancer-specific mortality. Primary-site surgery, radiation with surgery, and chemotherapy, were associated with decreased cancer-specific mortality. The multivariate analysis showed that pathology grade, primary-site surgery, radiation with surgery, and chemotherapy, could significantly affect the cancer-specific mortality and were independent prognostic factors in patients with gastric adenocarcinoma. Conclusions: Using a competing-risk model, this study obtained more-accurate estimates for the cumulative incidence of cancer-specific death and identified the prognostic factors more accurately for gastric adenocarcinoma.
Background: Accurate prognostic factors for gastric adenocarcinoma are still lacking in clinical practice, which contributes to inappropriate treatment. Applying the widely used Cox-proportional hazards model to describe survival trends and identify prognostic factors has limitations that result in a risk of bias. A competing-risk model was therefore adopted in this study to identify the significant prognostic factors and evaluate the cumulative incidence of cause-specific death for gastric adenocarcinoma, which can be used to guide clinical treatments. Methods: All of the cases analyzed in this study were extracted from the SEER (Surveillance, Epidemiology, and End Results) database. Using the competing risk approach, we calculated the cumulative incidence function (CIF) for cause-specific death and death from other causes at each time point. The Fine and Gray's proportional subdistribution hazard model was then applied in the univariate analysis and multivariate analysis to test the differences in CIF between different groups and obtain independent prognostic factors. Results: The univariate analysis showed that patients with characteristics of advanced pathology grade, lymph node involvement, and metastasis, were at risk of increasing cancer-specific mortality. Primary-site surgery, radiation with surgery, and chemotherapy, were associated with decreased cancer-specific mortality. The multivariate analysis showed that pathology grade, primary-site surgery, radiation with surgery, and chemotherapy, could significantly affect the cancer-specific mortality and were independent prognostic factors in patients with gastric adenocarcinoma. Conclusions: Using a competing-risk model, this study obtained more-accurate estimates for the cumulative incidence of cancer-specific death and identified the prognostic factors more accurately for gastric adenocarcinoma.