BackgroundAdenocarcinoma of esophagogastric junction (AEG) was initially proposed in 1999 by Siewert. During recent decades, the incidence and prevalence of AEG were arising globally whereas the incidence of gastric cancer is gradually declining. Complete blood counting and liver function tests, as the routine examination of immune and nutritional status, were reported to be the predictors of overall survival (OS) in some tumors. However, little is known about the prognostic significance of these indexes in AEG patients. The purpose of this study was to assess the prediction of preoperative pre-albumin, hemoglobin, and prognostic nutritional index (PNI) for survival outcomes in AEG patients.MethodsA retrospective cohort of 101 AEG patients followed by radical surgery was recruited between January and July 2010. Clinical and laboratory data were obtained and used to evaluate the predictive value through survival analysis. Receiver operating characteristic (ROC) curve analysis determined 200 mg/L, 120 g/L, 5 cm, and 51 as the cutoff values of pre-albumin, hemoglobin, tumor size, and PNI, respectively.ResultsUnivariate analysis revealed that AEG patients with hemoglobin ≥120 g/L, albumin ≥40 g/L, pre-albumin ≥200 g/L, PNI ≥51, and tumor size <5 cm had longer OS (P < 0.05). Additionally, pre-albumin, tumor size, and TNM stage were demonstrated to be independent prognostic indicators by multivariate analysis with Cox regression, and the performance of pre-albumin for predicting OS in AEG patients was further identified by ROC curves (P = 0.006).ConclusionsPreoperative pre-albumin was an independent prognostic factor, and a high level of pre-albumin predicted longer OS in AEG patients.

Background The prognosis of colon cancer (CC) is challenging to predict due to its highly heterogeneous nature. Ferroptosis, an iron-dependent form of cell death, has roles in various cancers; however, the correlation between ferroptosis-related genes (FRGs) and prognosis in CC remains unclear. Methods The expression profiles of FRGs and relevant clinical information were retrieved from the Cancer Genome Atlas (TCGA) database. Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression model were performed to build a prognostic model in TCGA cohort. Results Ten FRGs, five of which had mutation rates ≥ 3%, were found to be related to the overall survival (OS) of patients with CC. Patients were divided into high- and low-risk groups based on the results of Cox regression and LASSO analysis. Patients in the low-risk group had a significantly longer survival time than patients in the high-risk group (P < 0.001). Enrichment analyses in different risk groups showed that the altered genes were associated with the extracellular matrix, fatty acid metabolism, and peroxisome. Age, risk score, T stage, N stage, and M stage were independent predictors of patient OS based on the results of Cox analysis. Finally, a nomogram was constructed to predict 1-, 3-, and 5-year OS of patients with CC based on the above five independent factors. Conclusion A novel FRG model can be used for prognostic prediction in CC and may be helpful for individualized treatment.

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