C-reactive protein identifies patients at low risk of anastomotic leak after esophagectomy

C-reactive protein and digestive pathologies: A narrative review for daily clinical use

The aim of this narrative review is to familiarize clinicians, especially digestive surgeons, to adequately use of serum C-reactive protein as a reliable noninvasive biomarker in diverse practical clinical situations. We hope that the review will help clinicians for their decision-making when facing various digestive diseases including operative and nonoperative pathologies such as anastomotic leakage, pancreatitis, emergency situation, and digestive cancer management and prognosis.

Biomarkers associated with anastomotic leakage after esophagectomy: a systematic review

PURPOSE

Anastomotic leakage (AL) is one of the most important complications that occurs after upper gastrointestinal surgery, registering rates of 20-30% after esophagectomy. The role of systemic inflammatory biomarkers to predict anastomotic leaks is controversial and needs systematization.

METHODS

A systematic review based on the PRISMA guidelines criteria was performed. PubMed, Scopus, and Embase were queried using MESH Terms and All Fields key words to identify studies investigating a range of immune-inflammatory factors in predicting AL.

RESULTS

Twenty-four studies were included in this review. The total number of included patients was 5903, ranging in each study from 42 to 612. The included studies reported patients that underwent different techniques of esophagectomy (Ivor Lewis, McKeown, Orringer or thoracoabdominal esophagectomy) and 23 out of 24 studies included patients that underwent neoadjuvant treatment. While different biomarkers at different timepoints were analyzed, most studies have indicated postoperative biomarkers, between day 3 and day 5 to reach statistical significance.

CONCLUSIONS

Systemic inflammatory biomarkers represent potential risk stratification and predicting tools for AL after esophageal surgery, but more studies need to be conducted to validate their clinical utility.

Prediction of Anastomotic Leakage in Esophageal Cancer Surgery: A Multimodal Machine Learning Model Integrating Imaging and Clinical Data

RATIONALE AND OBJECTIVES

Surgery in combination with chemo/radiotherapy is the standard treatment for locally advanced esophageal cancer. Even after the introduction of minimally invasive techniques, esophagectomy carries significant morbidity and mortality. One of the most common and feared complications of esophagectomy is anastomotic leakage (AL). Our work aimed to develop a multimodal machine-learning model combining CT-derived and clinical data for predicting AL following esophagectomy for esophageal cancer.

MATERIAL AND METHODS

A total of 471 patients were prospectively included (Jan 2010-Dec 2022). Preoperative computed tomography (CT) was used to evaluate celia trunk stenosis and vessel calcification. Clinical variables, including demographics, disease stage, operation details, postoperative CRP, and stage, were combined with CT data to build a model for AL prediction. Data was split into 80%:20% for training and testing, and an XGBoost model was developed with 10-fold cross-validation and early stopping. ROC curves and respective areas under the curve (AUC), sensitivity, specificity, PPV, NPV, and F1-scores were calculated.

RESULTS

A total of 117 patients (24.8%) exhibited post-operative AL. The XGboost model achieved an AUC of 79.2% (95%CI 69%-89.4%) with a specificity of 77.46%, a sensitivity of 65.22%, PPV of 48.39%, NPV of 87.3%, and F1-score of 56%. Shapley Additive exPlanation analysis showed the effect of individual variables on the result of the model. Decision curve analysis showed that the model was particularly beneficial for threshold probabilities between 15% and 48%.

CONCLUSION

A clinically relevant multimodal model can predict AL, which is especially valuable in cases with low clinical probability of AL.

Early postoperative systemic inflammatory response as predictor of anastomotic leakage after esophagectomy: a systematic review and meta-analysis

BACKGROUND AND PURPOSE

Postesophagectomy anastomotic leakage occurs in up to 16% of patients and is the main cause of morbidity and mortality. The leak severity is determined by the extent of contamination and the degree of sepsis, both of which are related to the time from onset to treatment. Early prediction based on inflammatory biomarkers such as C-reactive protein (CRP) levels, white blood cell counts, albumin levels, and combined Noble-Underwood (NUn) scores can guide early management. This review aimed to determine the diagnostic accuracy of these biomarkers.

METHODS

This study was designed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and registered in the PROSPERO (International Prospective Register of Systematic Reviews) database. Two reviewers independently conducted searches across PubMed, MEDLINE, Web of Science, and Embase. Sources of bias were assessed, and a meta-analysis was performed.

RESULTS

Data from 5348 patients were analyzed, and 13% experienced leakage. The diagnostic accuracy of the serum biomarkers was analyzed, and pooled cutoff values were identified. CRP levels were found to have good diagnostic accuracy on days 2 to 5. The best discrimination was identified on day 2 for a cutoff value < 222 mg/L (area under the curve = 0.824, sensitivity = 81%, specificity = 88%, positive predictive value = 38.6%, and negative predictive value = 98%). A NUn score of >10 on day 4 correlated with poor diagnostic accuracy.

CONCLUSION

The NUn score failed to achieve adequate accuracy. CRP seems to be the only valuable biomarker and is a negative predictor of postesophagectomy leakage. Patients with a CRP concentration of <222 mg/L on day 2 are unlikely to develop a leak, and patients can safely proceed through their enhanced recovery after surgery protocol. Patients with a CRP concentration of <127 mg/L on day 5 can be safely discharged when clinically possible.

Systemic Inflammatory Response and the Noble and Underwood (NUn) Score as Early Predictors of Anastomotic Leakage after Esophageal Reconstructive Surgery

Anastomotic leakage (AL) remains the main cause of post-esophagectomy morbidity and mortality. Early detection can avoid sepsis and reduce morbidity and mortality. This study evaluates the diagnostic accuracy of the Nun score and its components as early detectors of AL. This single-center observational cohort study included all esophagectomies from 2010 to 2020. C-reactive protein (CRP), albumin (Alb), and white cell count (WCC) were analyzed and NUn scores were calculated. The area under the curve statistic (AUC) was used to assess their predictive accuracy. A total of 74 of the 668 patients (11%) developed an AL. CRP and the NUn-score proved to be good diagnostic accuracy tests on postoperative day (POD) 2 (CRP AUC: 0.859; NUn score AUC: 0.869) and POD 4 (CRP AUC: 0.924; NUn score AUC: 0.948). A 182 mg/L CRP cut-off on POD 4 yielded a 87% sensitivity, 88% specificity, a negative predictive value (NPV) of 98%, and a positive predictive value (PPV) of 47.7%. A NUn score cut-off > 10 resulted in 92% sensitivity, 95% specificity, 99% NPV, and 68% PPV. Albumin and WCC have limited value in the detection of post-esophagectomy AL. Elevated CRP and a high NUn score on POD 4 provide high accuracy in predicting AL after esophageal cancer surgery. Their high negative predictive value allows to select patients who can safely proceed with enhanced recovery protocols.

CRP as an early indicator for anastomotic leakage after esophagectomy for cancer: a single tertiary gastro-esophageal center study

PURPOSE

To determine the relationship between postoperative C-reactive protein (CRP) as an early indicator of anastomotic leakage (AL) after esophagectomy for esophageal cancer.

METHODS

We reviewed patients diagnosed with esophageal or esophagogastric junctional cancer who underwent esophagectomy between 2006 and 2022 at the Karolinska University Hospital, Stockholm, Sweden. Multivariable logistic regression models estimated relative risk for AL by calculating the odds ratio (OR) with a 95% confidence interval (CI). The cut-off values for CRP were based on the maximum Youden's index using receiver operating characteristic curve analysis.

RESULTS

In total, 612 patients were included, with 464 (75.8%) in the non-AL (N-AL) group and 148 (24.2%) in the AL group. Preoperative body mass index and the proportion of patients with the American Society of Anesthesiologists physical status classification 3 were significantly higher in the AL group than in the N-AL group. The median day of AL occurrence was the postoperative day (POD) 8. Trends in CRP levels from POD 2 to 3 and POD 3 to 4 were significantly higher in the AL than in the N-AL group. An increase in CRP of ≥ 4.65% on POD 2 to 3 was an independent risk factor for AL with the highest OR of 3.67 (95% CI 1.66-8.38, p = 0.001) in patients with CRP levels on POD 2 above 211 mg/L.

CONCLUSION

Early changes in postoperative CRP levels may help to detect AL early following esophageal cancer surgery.