A Visualized Dynamic Prediction Model for Overall Survival in Elderly Patients With Pancreatic Cancer for Smart Medical Services

Abstract

BackgroundPancreatic cancer (PC) is a highly malignant tumor of the digestive system. The number of elderly patients with PC is increasing, and older age is related to a worse prognosis. Accurate prognostication is crucial in treatment decisions made for people diagnosed with PC. However, an accurate predictive model for the prognosis of these patients is still lacking. We aimed to construct nomograms for predicting the overall survival (OS) of elderly patients with PC.MethodsPatients with PC, older than 65 years old from 2010 to 2015 in the Surveillance, Epidemiology, and End Results database, were selected and randomly divided into training cohort (n = 4,586) and validation cohort (n = 1,966). Data of patients in 2016–2018 (n = 1,761) were used for external validation. Univariable and forward stepwise multivariable Cox analysis was used to determine the independent prognostic factors. We used significant variables in the training set to construct nomograms predicting prognosis. The performance of the models was evaluated for their discrimination and calibration power based on the concordance index (C-index), calibration curve, and the decision curve analysis (DCA).ResultsAge, insurance, grade, surgery, radiation, chemotherapy, T, N, and American Joint Commission on Cancer were independent predictors for OS and thus were included in our nomogram. In the training cohort and validation cohort, the C-indices of our nomogram were 0.725 (95%CI: 0.715–0.735) and 0.711 (95%CI: 0.695–0.727), respectively. The 1-, 3-, and 5-year areas under receiver operating characteristic curves showed similar results. The calibration curves showed a high consensus between observations and predictions. In the external validation cohort, C-index (0.797, 95%CI: 0.778–0.816) and calibration curves also revealed high consistency between observations and predictions. The nomogram-related DCA curves showed better clinical utility compared to tumor-node-metastasis staging. In addition, we have developed an online prediction tool for OS.ConclusionsA web-based prediction model for OS in elderly patients with PC was constructed and validated, which may be useful for prognostic assessment, treatment strategy selection, and follow-up management of these patients.

Development and external validation of a prognostic nomogram to predict survival in patients aged ≥60 years with pancreatic ductal adenocarcinoma

“…Many studies have shown that age is an independent variable affecting OS in PDAC patients ( 26 , 33 - 35 ). Since the clinical features and prognosis of elderly PDAC patients are different from those of younger patients ( 12 , 15 , 16 ), it is not accurate to rely solely on the traditional stage systems to estimate the prognosis of these patients. In the current study, we constructed a nomogram model based on a combination of independent prognostic factors to predict survival in PDAC patients aged ≥60 years.…”

“…Age is considered to be an independent prognostic factor for many cancers, including PC ( 12 - 14 ). Previous studies have shown that the clinical features and prognosis of elderly PC patients differ from those of younger patients ( 12 , 15 , 16 ).…”

“…Age is considered to be an independent prognostic factor for many cancers, including PC ( 12 - 14 ). Previous studies have shown that the clinical features and prognosis of elderly PC patients differ from those of younger patients ( 12 , 15 , 16 ). It is commonly believed that older patients are less tolerant to surgery, chemotherapy and radiation, leading to poorer adherence to anti-tumor treatment and increased side effects.…”

“…For patients with metastatic PDAC, the 5-year OS rate is less than 3% ( 28 ). Few studies have reported the clinical characteristics and prognosis of elderly patients with PDAC ( 12 , 29 ). As far as we know, there are no specific nomograms considering both OS and cancer-specific survival (CSS) for elderly PDAC patients.…”

“…Zhong et al developed a web-based prediction model for predicting OS in PC patients aged ≥65 years. However, the study included all pathological types of PC and the nomogram was not externally validated ( 12 ). Our study aimed to investigate the prognostic factors for OS and CSS in PDAC patients aged ≥60 years and further develop a population-based survival-predicting model with external validation.…”