Zhang Xu, Yang Jin, Huang Qiao, Lyu Jun
Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University , Xi'an , China.
School of Public Health, Xi'an Jiaotong University Health Science Center , Xi'an , China.
Scand J Gastroenterol. 2019 Aug;54(8):1015-1021. doi: 10.1080/00365521.2019.1649456. Epub 2019 Aug 6.
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. 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. 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. 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.
在临床实践中，仍缺乏用于胃腺癌的准确预后因素，这导致了不恰当的治疗。应用广泛使用的Cox比例风险模型来描述生存趋势并确定预后因素存在局限性，可能导致偏倚风险。因此，本研究采用竞争风险模型来确定胃腺癌的显著预后因素，并评估特定病因死亡的累积发生率，以指导临床治疗。本研究分析的所有病例均取自SEER（监测、流行病学和最终结果）数据库。使用竞争风险方法，我们计算了每个时间点特定病因死亡和其他原因死亡的累积发生率函数（CIF）。然后，将Fine和Gray的比例子分布风险模型应用于单变量分析和多变量分析，以检验不同组之间CIF的差异，并获得独立的预后因素。单变量分析表明，具有高级别病理分级、淋巴结受累和转移特征的患者，癌症特异性死亡率增加的风险较高。原发部位手术、手术联合放疗和化疗，与癌症特异性死亡率降低相关。多变量分析表明，病理分级、原发部位手术、手术联合放疗和化疗，可显著影响胃腺癌患者的癌症特异性死亡率，是独立的预后因素。本研究使用竞争风险模型，更准确地估计了癌症特异性死亡的累积发生率，并更准确地确定了胃腺癌的预后因素。
