Factors associated with the costs of hospitalization after esophagectomy: a retrospective observational study at a three-tertiary cancer hospital in China

Background: This prospective cohort study, conducted at a high-volume esophageal cancer center from July 2019 to July 2022, aimed to investigate the link between the right gastroepiploic artery (RGEA) length and anastomotic leakage (AL) rates following minimally invasive esophagectomy (MIE). Real-world data on stomach blood supply in the Chinese population were examined. Materials and Methods: A total of 516 cases were enrolled, categorized into two groups based on the Youden index-determined optimal cut-off value for the relative length of RGEA (length of RGEA/length of gastric conduit, 64.69%) through ROC analysis: Group SR (short RGEA) and Group LR (long RGEA). The primary observation parameter was the relationship between AL incidence and the ratio of direct blood supply from RGEA. Secondary parameters included the mean length of the right gastroepiploic artery, greater curvature, and the connection type between right and left gastroepiploic vessels. Patient data were prospectively recorded in electronic case report forms. Results: The study revealed median lengths of 43.60 cm for greater curvature, 43.16 cm for the gastric conduit, and 26.75 cm for RGEA. AL, the most common postoperative complication, showed a significant difference between groups (16.88% vs. 8.84%, P=0.01). Multivariable binary logistic regression identified Group SR and LR (Odds ratio: 2.651, 95% CI: 1.124–6.250, P=0.03) and Neoadjuvant therapy (Odds ratio: 2.479, 95% CI: 1.374–4.473, P=0.00) as independent predictors of AL. Conclusions: The study emphasizes the crucial role of RGEA length in determining AL incidence in MIE for esophageal cancer. Preserving RGEA and fostering capillary arches between RGEA and LGEA are recommended strategies to mitigate AL risk.

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Prediction and the influencing factor study of colorectal cancer hospitalization costs in China based on machine learning-random forest and support vector regression: a retrospective study

Gao,

Liu

2024

Front. Public Health

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AimsAs people’s standard of living improves, the incidence of colorectal cancer is increasing, and colorectal cancer hospitalization costs are relatively high. Therefore, predicting the cost of hospitalization for colorectal cancer patients can provide guidance for controlling healthcare costs and for the development of related policies.MethodsThis study used the first page of medical record data on colorectal cancer inpatient cases of a tertiary first-class hospital in Shenzhen from 2018 to 2022. The impacting factors of hospitalization costs for colorectal cancer were analyzed. Random forest and support vector regression models were used to establish predictive models of the cost of hospitalization for colorectal cancer patients and to compare and evaluate.ResultsIn colorectal cancer inpatients, major procedures, length of stay, level of procedure, Charlson comorbidity index, age, and medical payment method were the important influencing factors. In terms of the test set, the R2 of the Random forest model was 0.833, the R2 of the Support vector regression model was 0.824; the root mean square error (RMSE) of the Random forest model was 0.029, and the RMSE of the Support vector regression model was 0.032. In the Random Forest model, the weight of the major procedure was the highest (0.286).ConclusionMajor procedures and length of stay have the greatest impacts on hospital costs for colorectal cancer patients. The random forest model is a better method to predict the hospitalization costs for colorectal cancer patients than the support vector regression.

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Factors associated with the costs of hospitalization after esophagectomy: a retrospective observational study at a three-tertiary cancer hospital in China

Cited by 3 publications

References 20 publications

Cost analysis of robot-assisted versus open transthoracic esophagectomy for resectable esophageal cancer. Results of the ROBOT randomized clinical trial

Cost analysis of robot-assisted versus open transthoracic esophagectomy for resectable esophageal cancer. Results of the ROBOT randomized clinical trial

Right gastroepiploic artery length determined anastomotic leakage after minimally invasive esophagectomy for esophageal cancer: a prospective cohort study

Prediction and the influencing factor study of colorectal cancer hospitalization costs in China based on machine learning-random forest and support vector regression: a retrospective study

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