Construction and validation of a predictive model for the risk of three-month-postoperative malnutrition in patients with gastric cancer: a retrospective case-control study

Abstract

Background: This study analyzed both the influencing factors of malnutrition in patients with gastric cancer and established a multi-dimensional risk model to predict postoperative malnutrition three months after surgery. Methods:The clinical data of gastric cancer patients hospitalized for the first time and receiving laparoscopic surgery in the general surgery department of our hospital were retrospectively analyzed through the hospital information system and divided into a training set and a validation set in the ratio of 7:3. Nutritional status was assessed using the Patient Generated Subjective Global Assessment scale and follow-up records three months after surgery. Patients were divided into a non-malnutrition group and a malnutrition group, and a risk prediction model was established and displayed in the form of a nomogram. Results: A total of 344 patients were included, with 242 in the training and 102 in the validation set. Tumor node metastasis stage (TNM Stage, P=0.020), cardiac function grading (CFG, P=0.013), prealbumin (PAB, P<0.001), neutrophil-to-lymphocyte ratio (NLR, P=0.027), and enteral nutrition within 48 hours post-operation (EN 48h post-op, P=0.025) were independent risk factors. We established a prediction model with the above variables and displayed it via a nomogram, then verified its effectiveness through internal and external verification. This revealed a C-index of 0.84 (95% CI: 0.79-0.89), and the area under curve (AUC) areas of 0.840 (training set) and 0.854 (validation set), which was better than the nutritional risk screening 2002 (NRS2002) scale. The calibration curve brier scores were 0.159 and 0.195, and the Hosmer-Lemeshow test chi-square values were 14.070 and 1.989 (P>0.05). The decision curve analysis (DCA) of the training set model indicated the clinical applicability was good and within the threshold probability range of 10%-85%, which was also better than NRS2002. Conclusions: A clinical prediction model including multi-dimensional variables was established based on independent risk factors of malnutrition three months after gastrectomy in patients with gastric cancer. The model yields greater prediction accuracy of the risk of three-month-postoperative malnutrition in patients with gastric cancer, helps screen high-risk patients, formulates targeted nutritional prescriptions early, and improves the overall prognosis of patients.

Development of a nomogram for predicting malnutrition in elderly hospitalized cancer patients: a cross-sectional study in China

“…Tian and other researchers retrospectively collected the clinical data of 344 patients with gastric cancer who underwent laparoscopic surgery, and divided the data into a training set and a validation set in a 7:3 ratio ( 7 ). Using logistic regression, they established a nutritional risk assessment model for patients with gastric cancer post-gastrectomy.…”

“…Tian and his team conducted a retrospective study on clinical data from 344 patients with gastric cancer who underwent laparoscopic surgery, dividing the data into a training set and a validation set in a 7:3 ratio ( 7 ). They then developed a nutritional risk assessment model using logistic regression for patients post-gastrectomy.…”