Constructing a risk prediction model for anastomotic leakage after esophageal cancer resection

Sun, Zhongwen; Du, Hui; Jia-rui, LI; Qin, Huiying

doi:10.1177/0300060519896726

Cited by 8 publications

(5 citation statements)

References 19 publications

(18 reference statements)

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“…30 Studies believe that as the age increases, the likelihood of postoperative complications will increase, especially if the age is older than 65. 31 This is the same as the results of our study. The increase in patient age is an independent risk factor for early postoperative complications.…”

supporting

confidence: 88%

A Novel Nomogram for Prediction of Early Postoperative Complications of Total Gastrectomy for Gastric Cancer

Zhang

Jiang

Zhu

2021

CMAR

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Background: Accurate prediction of postoperative complications is especially important for the formulation of treatment plans for patients with total gastrectomy (TG) for gastric cancer (GC). The purpose of this study was to establish a risk assessment model for early postoperative complications. Methods: This retrospective study involved 363 patients with GC who underwent TG from January 2019 to December 2020. The influencing factors were explored by univariate and multivariable logistic regression; then, a nomogram was established and verified by internal verification. Results: Linear stapler (OR=2.501, P=0.030), age (OR=1.052, P =0.024), blood transfusion (yes) (OR=2.450, P =0.021), one-time consumables for surgery (or=1.000, P =0.022), number of total lymph nodes (OR=1.060, P =0.011) and number of positive lymph nodes (OR=1.054, P =0.029) were independent risk factors for early postoperative complications in TG, and nomogram model was constructed. The C-index of primary cohort, modeling cohort and validation cohort was 0.787, 0.754 and 0.912. The calibration curves showed good accuracy. Conclusion:This study used the indicators available before and during surgery to establish a nomogram model for early postoperative complications of total gastrectomy for gastric cancer, which found that linear stapler (LS), blood transfusion, one-time consumables for surgery, number of total lymph nodes and number of positive lymph nodes were factors.

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confidence: 88%

A Novel Nomogram for Prediction of Early Postoperative Complications of Total Gastrectomy for Gastric Cancer

Zhang

Jiang

Zhu

2021

CMAR

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“…Factors affecting the gastrectomy complications included age, BMI, tumor stage, etc. ( 27 , 28 ) In this study, large IBL was found to increase complications. The possible reason was that large IBL reduced the body’s immunity, thereby increasing the incidence of complications ( 29 ).…”

Section: Discussionmentioning

confidence: 48%

Does Intraoperative Blood Loss Affect the Short-Term Outcomes and Prognosis of Gastric Cancer Patients After Gastrectomy? A Meta-Analysis

2022

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PurposeThe purpose of the current meta-analysis was to analyze whether intraoperative blood loss (IBL) influenced the complications and prognosis of gastric cancer patients after gastrectomy.MethodsWe systematically searched the PubMed, Embase and Cochrane library databases on November 29, 2021. The Newcastle-Ottawa scale was used to evaluate the quality of included studies. This meta-analysis uses RevMan 5.3 for data analysis.ResultsA total of nine retrospective studies were included in this meta-analysis, involving 4653 patients. In terms of short-term outcomes, the Larger IBL group has a higher complication rate (OR = 1.94, 95% CI, 1.44 to 2.61, P < 0.0001) and a longer operation time (OR = 77.60, 95% CI, 41.95 to 113.25, P < 0.0001) compared with the smaller IBL group, but the Larger IBL group had higher total retrieved lymph nodes (OR = 3.68, 95% CI, 1.13 to 6.24, P = 0.005). After pooling up all the HRs, the Larger IBL group has worse overall survival (OS) (HR = 1.80, 95% CI, 1.27 to 2.56, P = 0.001) and disease-free survival (DFS) (HR = 1.48, 95% CI, 1.28 to 1.72, P < 0.00001).ConclusionLarger IBL increased operation time and postoperative complications, and decreased OS and DFS of gastric cancer patients. Therefore, surgeons should be cautious about IBL during operation.

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“…In recent years, with the popularization of statistical methods for clinical prediction models, more and more surgeons have applied them to the prediction of postoperative complications. Huang et al and Sun et al analyzed various indicators of the perioperative period, including the general state of patients, anastomosis site and method, postoperative blood inflammation index, and complications, to establish a risk prediction model for anastomotic leakage after esophagectomy, respectively ( 12 , 13 ). In this case, the researcher systematically identified and rated their performance, a presentation we have not found in previous literature.…”

Section: Discussionmentioning

confidence: 99%

Development of nomograms predictive of anastomotic leakage in patients before minimally invasive McKeown esophagectomy

Xu¹,

He²,

Hu³

et al. 2023

Front. Surg.

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PurposeThe present study aims to identify factors related to anastomotic leakage before esophagectomy and to construct a prediction model.MethodsA retrospective analysis of 285 patients who underwent minimally invasive esophagectomy (MIE). An absolute shrinkage and selection operator was applied to screen the variables, and predictive models were developed using binary logistic regression.ResultsA total of 28 variables were collected in this study. LASSO regression analysis, combined with previous literature and clinical experience, finally screened out four variables, including aortic calcification, heart disease, BMI, and FEV1. A binary logistic regression was conducted on the four predictors, and a prediction model was established. The prediction model showed good discrimination and calibration, with a C-statistic of 0.67 (95% CI, 0.593–0.743), a calibration curve fitting a 45° slope, and a Brier score of 0.179. The DCA demonstrated that the prediction nomogram was clinically useful. In the internal validation, the C-statistic still reaches 0.66, and the calibration curve has a good effect.ConclusionsWhen patients have aortic calcification, heart disease, obesity, and a low FEV1, the risk of anastomotic leakage is higher, and relevant surgical techniques can be used to prevent it. Therefore, the clinical prediction model is a practical tool to guide surgeons in the primary prevention of anastomotic leakage.

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Constructing a risk prediction model for anastomotic leakage after esophageal cancer resection

Cited by 8 publications

References 19 publications

A Novel Nomogram for Prediction of Early Postoperative Complications of Total Gastrectomy for Gastric Cancer

A Novel Nomogram for Prediction of Early Postoperative Complications of Total Gastrectomy for Gastric Cancer

Does Intraoperative Blood Loss Affect the Short-Term Outcomes and Prognosis of Gastric Cancer Patients After Gastrectomy? A Meta-Analysis

Development of nomograms predictive of anastomotic leakage in patients before minimally invasive McKeown esophagectomy

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