Nomogram based on clinical characteristics for predicting overall survival in gastric cancer patients with preoperative anemia

BACKGROUNDPreoperative anemia is associated with increased postoperative morbidity and mortality and increased perioperative transfusion risk. For surgical patients, this affects physical and cognitive ability and quality of life, but it is an important and modifiable risk factor.AIMTo determine the effect of preoperative anemia on the prognosis of gastric cancer (GC) patients and generate a prognostic nomogram to predict the postoperative overall survival (OS) of GC patients with preoperative anemia.METHODSClinicopathological and follow-up data of GC patients treated at Zhejiang Provincial People's Hospital (China) from 2010 to 2015 were collected. Independent prognostic factors were screened by univariate and multivariate Cox regression analyses. Then, these factors were used to construct a nomogram to predict 1-, 3-, and 5-year postoperative OS in preoperative anemic GC patients. The nomogram was assessed by calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).RESULTSNine hundred and sixty GC patients were divided into two groups (preoperatively anemic and nonanemic), and postoperative survival analysis was performed on both groups, yielding a shorter postoperative survival for preoperatively anemic patients than for nonanemic patients. A total of 347 GC patients with preoperative anemia were included. Age, preoperative alpha-fetoprotein level, monocyte count, lymphocyte count, clinicopathological stage, liver metastasis, and GC type were identified as independent prognostic factors for OS. The area under the ROC curve (AUC) of the nomogram for predicting 1-, 3-, and 5-year OS was 0.831, 0.845, and 0.840, respectively, for the training cohort, and the corresponding AUC values in the validation cohort were 0.827, 0.829, and 0.812, respectively. Calibration curves and DCA indicated good performance of the nomogram.CONCLUSIONIn all, we have successfully produced and verified a useful nomogram for predicting OS in GC patients with preoperative anemia. This nomogram based on a variety of clinicopathological indices can provide an effective prognostic assessment and help clinicians choose an appropriate treatment strategy for GC patients with preoperative anemia.