The morbidity of GC was shown to increase with age and older age in GC patients often means a poor prognosis . Accurately predicting the survival of elderly GC patients is still imperative and a grand challenge for clinicians because it could effectively improve elderly patients’ prognosis. Chinese average life span in 2019 was 76.1 years showed in the data released by the World Health OrganizationIn (WHO); therefore, we define patients older than 75 years as elderly patients which is more representative to predict their short-term survival. In the study, we developed and validated a prognostic nomogram to predict survival of elderly GC patients based on the SEER database. The nomogram involving five variables of histologic grade, AJCC stage T, N, M and surgery showed excellent discrimination and calibration in both internal and external validation, which manifested the nomogram could assist with the clinical prognostic prediction.
In our study, we discovered that the proportion of elderly GC patients with poor histologic grade, T4, N3, M1 were higher than the reported proportion of early cases , and elderly GC patients had a lower OS than early-onset gastric cancer (EOGC) . In addition, we confirmed five variables associated with the OS of elderly GC patients. A foregoing study by Li et al. showed that BMI, tumor site, T stage and N stage were connected with the OS of GC patients who received neoadjuvant chemotherapy . Roberto et al. reported that age, T stage, N stage, tumor residual after surgery, and pre-operatory ECOG-PS (performance status of Eastern Cooperative Oncology Group) were risk factors for prognosis of elderly GC patients after surgery; in addition, GC patients undergoing surgery perform0ed better survival results . Most studies indicated that elderly GC patients had worse survival outcomes than younger GC patients. These studies were consistent with our findings.
Taking the influence of the risk factors mentioned above into account, the traditional AJCC staging system may not predict the survival of elderly GC patients well. Due to this reason, we developed a prognostic nomogram incorporating clinicopathological risk factors to predict survival of the elderly GC patients. Notably, Yu et al.  published a nomogram to evaluate the prognosis of EOGC, by including tumor size and tumor site as significant risk factors of survival of EOGC; however, in our study, they did not show sufficient predictive performance in the multivariate Cox model related to the prognosis of elderly GC patients. This may be due to the collinearity with other variables or the potential influencing factors different from EOGC in elderly GC patients.
As can be found in our nomogram, surgery emerged as the most significant predictor which could be expressed by the length of the axis standing for this. Despite several related research have reported that surgical resection could control elderly patients’ condition and improve their prognosis [19–21], there remains controversial [22, 23]. In view of its high surgical risk, poor prognosis, low quality of life and low survival rate, many clinicians are reluctant to offer surgery to advanced aged patients [24, 25]. Currently there is no strong evidence to draw robust conclusions in this population. There was a report that age alone should not preclude gastrectomy in elderly patients . They think that elderly patients should undergo operation because the benefit is the same as for young patients from short-term and long-term prognosis. On the other hand, Choo et al.  found elderly patients aged 80–85 years could have a large benefit from the surgical resection and for elderly patients aged over 86 years, especially those with cardiovascular and renal system diseases, the risks and benefits of the procedure should be weighed before surgery. Surgery and chemotherapy should be the recommended treatment strategy in elderly patients which can effectively improve patients’ survival compared with conservative treatment . Consistent with previous reports, our study suggested that surgery could improve the prognosis of elderly GC patients. The patients older than 74 years who underwent surgery had a good outcome, 96% of which improve quality of life and resume daily activities . Therefore, we should adapt active treatment strategies including surgery or chemotherapy to improve patients’ quality of life. For patients with poor physical conditions or comorbidities, we need to weigh their surgical risk and survival benefit.
The validation of the nomogram including C-index, the ROC curves and calibration curves all showed good results, which means that the nomogram was discriminative and reliable in predicting 3- and 5-year survival of elderly GC patients. However, the discrimination and calibration could not response the clinical consequences of extent of miscalibration that could affect a model’s clinical utility . To evaluate its clinical effectiveness, the DCA curves was applied in our study by comparing the net benefits with the traditional AJCC stage model. The DCA curves showed that using the nomogram in this study for predicting the short-term survival of elderly GC patients is more beneficial than the AJCC staging system. In order to get a better performance in the clinical prediction, we used the nomogram to calculate the patients’ total risk score for death. Elderly patients were divided into different classification through X-tile analysis, which could facilitate the personal health management of elderly patients. In addition, the clinicopathological variables building the nomogram were relatively accessible, hence, the nomogram can be applied universally to clinical work. This system also can give clinicians and patients an approximate range of survival at the time of diagnosis. Prognostication is not a targeted result during disease development, as it might change with the adjustment of the patients’ treatment plan and subsequent treatment response. We believe that our nomogram could assist clinicians quantify the risk factors associated with cancer death, so as to develop a suitable personalized treatment plan for elderly GC patients.
There are some potential limitations that need to be acknowledged in our study. Firstly, this was a retrospective analysis based on the SEER database, among which the recruited patients were predominantly white race. There may be potential racial heterogeneity. Secondly, several factors that are closely related to prognosis are not available in the SEER database, such as tumor markers (CEA, CA 199), surgery details (surgical approach, lymphadenectomy extent, digestive tract reconstruction) and follow-up treatment (radiotherapy, and chemotherapy). Thirdly, we did not build a nomogram to predict cancer-specific survival (CSS) of elderly GC patients. It is important to note that gastric cancer is not the only factor affecting prognosis in this population group. Deaths due to other comorbidities account for 34%-37% of the total deaths in GC patients over eighty years . Fourthly, some patients with missing data were excluded from the development and the validation sets, which may lead to selection bias.
In conclusion, we developed and validated a nomogram to predict 3- and 5-year survival rate of elderly GC patients based on a large sample cohort, which could improve the performance of the AJCC staging system. This might be extremely beneficial in assisting the prediction of survival and formulating individualized treatment protocols for elderly GC patients.