Preoperative risk modelling for oesophagectomy: A systematic review

Risk prediction model for postoperative pneumonia in esophageal cancer patients: A systematic review

Background

Numerous studies have developed or validated prediction models to estimate the likelihood of postoperative pneumonia (POP) in esophageal cancer (EC) patients. The quality of these models and the evaluation of their applicability to clinical practice and future research remains unknown. This study systematically evaluated the risk of bias and applicability of risk prediction models for developing POP in patients undergoing esophageal cancer surgery.

Methods

PubMed, Embase, Web of Science, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), WanFang Database and Chinese Biomedical Literature Database were searched from inception to March 12, 2024. Two investigators independently screened the literature and extracted data. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was employed to evaluate both the risk of bias and applicability.

Result

A total of 14 studies involving 23 models were included. These studies were mainly published between 2014 and 2023. The applicability of all studies was good. However, all studies exhibited a high risk of bias, primarily attributed to inappropriate data sources, insufficient sample size, irrational treatment of variables and missing data, and lack of model validation. The incidence of POP in patients undergoing esophageal cancer surgery ranged from 14.60% to 39.26%. The most frequently used predictors were smoking, age, chronic obstructive pulmonary disease(COPD), diabetes mellitus, and methods of thoracotomy. Inter-model discrimination ranged from 0.627 to 0.850, sensitivity ranged between 60.7% and 84.0%, and specificity ranged from 59.1% to 83.9%.

Conclusion

In all included studies, good discrimination was reported for risk prediction models for POP in patients undergoing esophageal cancer surgery, indicating stable model performance. However, according to the PROBAST checklist, all studies had a high risk of bias. Future studies should use the predictive model assessment tool to improve study design and develop new models with larger samples and multicenter external validation.

Systematic review registration

https://www.crd.york.ac.uk/prospero, identifier CRD42024527085.

Prediction of Morbidity and Mortality After Esophagectomy: A Systematic Review

BACKGROUND

Esophagectomy for esophageal cancer has a complication rate of up to 60%. Prediction models could be helpful to preoperatively estimate which patients are at increased risk of morbidity and mortality. The objective of this study was to determine the best prediction models for morbidity and mortality after esophagectomy and to identify commonalities among the models.

PATIENTS AND METHODS

A systematic review was performed in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and was prospectively registered in PROSPERO ( https://www.crd.york.ac.uk/prospero/ , study ID CRD42022350846). Pubmed, Embase, and Clarivate Analytics/Web of Science Core Collection were searched for studies published between 2010 and August 2022. The Prediction model Risk of Bias Assessment Tool was used to assess the risk of bias. Extracted data were tabulated and a narrative synthesis was performed.

RESULTS

Of the 15,011 articles identified, 22 studies were included using data from tens of thousands of patients. This systematic review included 33 different models, of which 18 models were newly developed. Many studies showed a high risk of bias. The prognostic accuracy of models differed between 0.51 and 0.85. For most models, variables are readily available. Two models for mortality and one model for pulmonary complications have the potential to be developed further.

CONCLUSIONS

The availability of rigorous prediction models is limited. Several models are promising but need to be further developed. Some models provide information about risk factors for the development of complications. Performance status is a potential modifiable risk factor. None are ready for clinical implementation.

The influence of postoperative outcomes on survival after esophageal cancer surgery: validation of a consensus-based updated textbook outcome parameter

BACKGROUND

Esophagectomy in combination with perioperative multimodal therapy is the cornerstone of modern curative treatment for esophageal adenocarcinoma. The primary aim of this study was to assess the influence of textbook outcome (TO) as a composite quality performance indicator (QPI) and its perioperative parameters on survival in patients who underwent esophagectomy with curative intent.

METHODS

Consecutive patients who underwent an esophagectomy between January 2014 and December 2022 at Christchurch Hospital were identified from a prospectively maintained hospital database. Univariable and multivariable analyses were performed to assess prognostic factors for each composite and individual postoperative outcome. Survival analysis was performed to evaluate the influence of these outcomes on overall survival.

RESULTS

A total of 108 patients underwent an esophagectomy during the study period. The overall and Clavien-Dindo (CD) grade ≥ 3 postoperative complication rates were 62% and 26%, respectively. The anastomotic leak rate was 6.5% (n = 7). The TO rate, 30-day readmission rate, and 30-day mortality rate were 20%, 13%, and 1%, respectively. Resection margin and nodal disease were found to be independent prognostic factors for reduced survival.

CONCLUSION

TO as originally defined and its postoperative parameters of 30-day postoperative complications and 30-day readmission are validated QPIs of esophageal cancer surgery. Updating the postoperative complication parameter to include CD grade ≥ 3 complications resulted in a positive association between achieving TO and increased survival. Our findings support the call to redefine TO based on an update to this parameter, making it a more precise QPI of esophageal cancer surgery.