METHOD: This international multi-center prospective study across 137 hospitals in 41 countries included patients who underwent an esophagectomy for esophageal cancer, with 90-day follow-up. The main explanatory variable was country income, defined according to the World Bank Data classification. The primary outcome was 90-day postoperative mortality, and secondary outcomes were composite leaks (anastomotic leak or conduit necrosis) and major complications (Clavien-Dindo Grade III - V). Multivariable generalized estimating equation models were used to produce adjusted odds ratios (ORs) and 95% confidence intervals (CI95%).
RESULTS: Between April 2018 to December 2018, 2247 patients were included. Patients from HIC were more significantly older, with higher ASA grade, and more advanced tumors. Patients from LMIC had almost three-fold increase in 90-day mortality, compared to HIC (9.4% vs 3.7%, p
METHODS: Patients undergoing curative resection for oesophageal cancer were identified from the international Oesophagogastric Anastomosis Audit (OGAA) from April 2018-December 2018. Definitions for AL and CN were those set out by the Oesophageal Complications Consensus Group. Univariate and multivariate analyses were performed to identify risk factors for both AL and CN. A risk score was then produced for both AL and CN using the derivation set, then internally validated using the validation set.
RESULTS: This study included 2247 oesophagectomies across 137 hospitals in 41 countries. The AL rate was 14.2% and CN rate was 2.7%. Preoperative factors that were independent predictors of AL were cardiovascular comorbidity and chronic obstructive pulmonary disease. The risk scoring model showed insufficient predictive ability in internal validation (area under the receiver-operating-characteristic curve [AUROC] = 0.618). Preoperative factors that were independent predictors of CN were: body mass index, Eastern Cooperative Oncology Group performance status, previous myocardial infarction and smoking history. These were converted into a risk-scoring model and internally validated using the validation set with an AUROC of 0.775.
CONCLUSION: Despite a large dataset, AL proves difficult to predict using preoperative factors. The risk-scoring model for CN provides an internally validated tool to estimate a patient's risk preoperatively.
METHODS: Decision-analytic models were constructed using best available evidence sourced from unbundled data of an ongoing pilot trial assessing the effectiveness of high FiO2, published literature, and a cost survey in Nigeria, India, and South Africa. Effectiveness was measured as percentage of SSIs at 30 days after surgery, a healthcare perspective was adopted, and costs were reported in US dollars ($).
RESULTS: High FiO2 may be cost-effective (cheaper and effective). In Nigeria, the average cost for high FiO2 was $216 compared with $222 for low FiO2 leading to a -$6 (95% confidence interval [CI]: -$13 to -$1) difference in costs. In India, the average cost for high FiO2 was $184 compared with $195 for low FiO2 leading to a -$11 (95% CI: -$15 to -$6) difference in costs. In South Africa, the average cost for high FiO2 was $1164 compared with $1257 for low FiO2 leading to a -$93 (95% CI: -$132 to -$65) difference in costs. The high FiO2 arm had few SSIs, 7.33% compared with 8.38% for low FiO2, leading to a -1.05 (95% CI: -1.14 to -0.90) percentage point reduction in SSIs.
CONCLUSION: High FiO2 could be cost-effective at preventing SSIs in the three countries but further data from large clinical trials are required to confirm this.