ABSTRACT
BACKGROUND/AIMS: Pancreatic ductal adenocarcinoma (PDAC) is associated with high mortality, even after surgical resection. The existing predictive models for survival have limitations. This study aimed to develop better nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in PDAC patients after surgery. METHODS: A total of 6323 PDAC patients were retrospectively recruited from the Surveillance, Epidemiology, and End Results (SEER) database and randomly allocated into training, validation, and test cohorts. Multivariate Cox regression analysis was conducted to identify significant independent factors for OS and CSS, which were used for construction of nomograms. The performance was evaluated, validated, and compared with that of the 8th edition AJCC staging system. RESULTS: Ten independent factors were significantly correlated with OS and CSS. The 1-, 3-, and 5-year OS rates were 40%, 20%, and 15%, and 1-, 3-, and 5-year CSS rates were 45%, 24%, and 19%, respectively. The nomograms were calibrated well, with c-indexes of 0.640 for OS and 0.643 for CSS, respectively. Notably, relative to the 8th edition AJCC staging system, the nomograms were able to stratify each AJCC stage into three prognostic subgroups for more robust risk stratification. Furthermore, the nomograms achieved significant clinical validity, exhibiting wide threshold probabilities and high net benefit. Performance assessment also showed high predictive accuracy and reliability. CONCLUSIONS: The predictive ability and reliability of the established nomograms have been validated, and therefore, these nomograms hold potential as novel approaches to predicting survival and assessing survival risks for PDAC patients after surgery.
Subject(s)
Carcinoma, Pancreatic Ductal/surgery , Nomograms , Pancreatectomy , Pancreatic Neoplasms/surgery , Pancreaticoduodenectomy , Adolescent , Adult , Aged , Aged, 80 and over , Carcinoma, Pancreatic Ductal/mortality , Carcinoma, Pancreatic Ductal/pathology , Cause of Death , Ethnicity , Female , Humans , Kaplan-Meier Estimate , Male , Marital Status , Middle Aged , Multivariate Analysis , Neoplasm Grading , Neoplasm Staging , Pancreatic Neoplasms/mortality , Pancreatic Neoplasms/pathology , Proportional Hazards Models , Reproducibility of Results , SEER Program , Survival Rate , Young AdultABSTRACT
The aim of this study was to identify metabolite biomarkers associated with acute rejection after heart transplantation in rats using a LC-MS-based metabolomics approach. A model of heterotopic cardiac xenotransplantation was established in rats, with Wistar rats as donors and SD rats as recipients. Blood and cardiac samples were collected from blank control rats (Group A), rats 5 (Group B) and 7 days (Group C) after heart transplantation, and pretreated rats 5 (Group D) and 7 days (Group E) post-transplantation for pathological and metabolomics analyses. We assessed International Society for Heart and Lung Transplantation (ISHLT) grades 0, 3B, 4, 1 and 1 rejection in groups A to E. There were 15 differential metabolites between groups A and B, 14 differential metabolites between groups A and C, and 10 differential metabolites between groups B and C. In addition, four common differential metabolites, including D-tagatose, choline, C16 sphinganine and D-glutamine, were identified between on days 5 and 7 post-transplantation. Our findings demonstrate that the panel of D-tagatose, choline, C16 sphinganine and D-glutamine exhibits a high sensitivity and specificity for the early diagnosis of acute rejection after heart transplantation, and LC-MS-based metabolomics approach has a potential value for screening post-transplantation biomarkers.