Establishment and validation of the survival prediction risk model for appendiceal cancer - Liu, Tao; Mi, Junli; Wang, Yafeng; Qiao, Wenjie; Wang, Chenxiang; Ma, Zhijun; Wang, Cheng (Frontiers in Medicine, 2022)
Objective To establish a risk model of the survival situation of appendix cancer to accurately identify high-risk patients and develop individualized treatment plans. Methods The SEER*Stat software was used to extract 4691 patients diagnosed with primary appendix cancer from 2010 to 2016, and the total sample size was divided into a modeling set of 3283 cases and a validation set of 1408 cases according to 7:3. Univariate Cox risk regression, Lasso regression, and multivariate Cox risk regression were used to analyze the risk factors for OS in patients with appendix cancer. The nomogram model was established according to the risk factors affecting the OS of the appendix cancer, and was evaluated by using the consistency index, the ROC curve and the drawing calibration curve. The survival differences between high and low risk groups were analyzed using Kaplan-Meier survival analysis and log-rank test. Result：Multivariate outcome The Cox risk regression analysis revealed that age, tumor stage, surgery, lymphadenectomy, T stage, N stage, M stage, and CEA were independent risk factors affecting the OS of appendiceal cancer. A nomogram model was established for the multi-factor statistically significant indicators. The area under the ROC curve of the modeling set 1,3, and 5 years is 0.808 (95%CI: 0.777 0.839), 0.824 (95%CI: 0.804 0.845), and 0.786 (95%CI: 0.759 0.813), (Figure 4); The validation set C index was 0.803, The area under the ROC curves in 1,3 and 5 years are 0.823 (95%CI: 0.781 0.864), 0.832 (95%CI: 0.801 0.863), and 0.817 (95%CI: 0.781 0.855) (Figure 5). Further risk stratification according to the nomogram model, Kaplan-Meier survival analysis showed, the prognosis of the low-risk group in the modeling set and validation set was significantly better than that of the high-risk group (P<0.001).Conclusion The established appendix cancer survival model can be used to predict 1,3, and 5 years of OS, by identifying high-risk patients to develop individualized treatment plans for them.