C-reactive protein to albumin ratio is a key indicator in a predictive model for anastomosis leakage after esophagectomy: Application of classification and regression tree analysis

Sex differences in survival following surgery for esophageal cancer: A systematic review and meta-analysis

The impact of sex on the prognosis of patients with esophageal cancer remains unclear. Evidence supports that sex- based disparities in esophageal cancer survival could be attributed to sex- specific risk exposures, such as age at diagnosis, race, socioeconomic status, smoking, drinking, and histological type. The aim of our study is to investigate the role of sex disparities in survival of patients who underwent surgery for esophageal cancer. A systematic review and meta-analysis of the existing literature in PubMed, EMBASE, and CENTRAL from December 1966 to February 2023, was held. Studies that reported sex-related differences in survival outcomes of patients who underwent esophagectomy for esophageal cancer were identified. A total of 314 studies were included in the quantitative analysis. Statistically significant results derived from 1-year and 2-year overall survival pooled analysis with Relative Risk (RR) 0.93 (95% Confidence Interval (CI): 0.90-0.97, I2 = 52.00) and 0.90 (95% CI: 0.85-0.95, I2 = 0.00), respectively (RR < 1 = favorable for men). In the postoperative complications analysis, statistically significant results concerned anastomotic leak and heart complications, RR: 1.08 (95% CI: 1.01-1.16) and 0.62 (95% CI: 0.52-0.75), respectively. Subgroup analysis was performed among studies with <200 and > 200 patients, histology types, study continent and publication year. Overall, sex tends to be an independent prognostic factor for esophageal carcinoma. However, unanimous results seem rather obscure when multivariable analysis and subgroup analysis occurred. More prospective studies and gender-specific protocols should be conducted to better understand the modifying role of sex in esophageal cancer prognosis.

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.

Complication Prediction after Esophagectomy with Machine Learning

Esophageal cancer can be treated effectively with esophagectomy; however, the postoperative complication rate is high. In this paper, we study to what extent machine learning methods can predict anastomotic leakage and pneumonia up to two days in advance. We use a dataset with 417 patients who underwent esophagectomy between 2011 and 2021. The dataset contains multimodal temporal information, specifically, laboratory results, vital signs, thorax images, and preoperative patient characteristics. The best models scored mean test set AUROCs of 0.87 and 0.82 for leakage 1 and 2 days ahead, respectively. For pneumonia, this was 0.74 and 0.61 for 1 and 2 days ahead, respectively. We conclude that machine learning models can effectively predict anastomotic leakage and pneumonia after esophagectomy.

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.

Machine learning applications in upper gastrointestinal cancer surgery: a systematic review

BACKGROUND

Machine learning (ML) has seen an increase in application, and is an important element of a digital evolution. The role of ML within upper gastrointestinal surgery for malignancies has not been evaluated properly in the literature. Therefore, this systematic review aims to provide a comprehensive overview of ML applications within upper gastrointestinal surgery for malignancies.

METHODS

A systematic search was performed in PubMed, EMBASE, Cochrane, and Web of Science. Studies were only included when they described machine learning in upper gastrointestinal surgery for malignancies. The Cochrane risk-of-bias tool was used to determine the methodological quality of studies. The accuracy and area under the curve were evaluated, representing the predictive performances of ML models.

RESULTS

From a total of 1821 articles, 27 studies met the inclusion criteria. Most studies received a moderate risk-of-bias score. The majority of these studies focused on neural networks (n = 9), multiple machine learning (n = 8), and random forests (n = 3). Remaining studies involved radiomics (n = 3), support vector machines (n = 3), and decision trees (n = 1). Purposes of ML included predominantly prediction of metastasis, detection of risk factors, prediction of survival, and prediction of postoperative complications. Other purposes were predictions of TNM staging, chemotherapy response, tumor resectability, and optimal therapy.

CONCLUSIONS

Machine Learning algorithms seem to contribute to the prediction of postoperative complications and the course of disease after upper gastrointestinal surgery for malignancies. However, due to the retrospective character of ML studies, these results require trials or prospective studies to validate this application of ML.

Development of Pharyngocutaneous Fistula after Total Laryngectomy: The Predictive Value of C-reactive Protein/Albumin Ratio

BACKGROUND

We aimed to evaluate whether C-reactive protein(CRP)/ Albumin ratio (CAR) performed in the early postoperative period after total laryngectomy could be a predictive factor for the development of pharyngocutaneous fistula (PCF).

METHODS

The files of patients with laryngeal squamous cell carcinoma who underwent total laryngectomy between January 2005 and January 2019 were retrospectively reviewed. Patients were divided into two groups: patients with PCF (PCF group) and without (Non-PCF group). CAR values and risk factors were compared between groups.

RESULTS

The overall incidence of PCF was 23.2%. There was a statistically significant difference between the two groups in terms of CRP and CAR levels (p = 0.001). The CAR value of 27.05 (sensitivity = 75.0% , specificity 68.2%, area under curve (AUC) = 0.742, 95% confidence interval 0.616-0.868) was determined as a cutoff value to describe the development of fistula in the early postoperative period. In multiple linear regression analysis, there was an independent relationship between presence of PCF and previous RT and CAR value.

CONCLUSIONS

CAR, performed in the early postoperative period, may be a new and useful marker for predicting PCF after total laryngectomy.

C reactive protein to albumin ratio (CAR) as predictor of anastomotic leakage in colorectal surgery

BACKGROUND

Anastomotic leakage (AL) is one of the most severe complications in colorectal surgery. Currently, no predictive biomarkers of AL are available. The aim of this study was to investigate the role of C reactive protein (CRP) to albumin ratio (CAR) as a predictor of AL in patients undergoing elective surgery for colorectal cancer.

MATERIALS AND METHODS

Data on 1183 consecutive patients surgically treated for histologically proven colorectal cancer in the surgical units involved in the study were collected. Data included sex, age, BMI, ASA score, Charlson comorbidity index, localization, histology and stage of the disease, as well as blood tests including albumin and CRP at the 4th postoperative day. Differences in CAR between patients who developed AL and those who did not were analyzed, and the ability of CAR to predict AL was investigated with ROC analysis.

RESULTS

CAR was significantly higher in patients with AL in comparison to those without, at the 4th postoperative day. In ROC analysis CAR showed a good ability in detecting AL (AUC 0.825, 95%CI: 0,786-0,859), greater than those of CRP and albumin alone. CAR also showed a high ability in detecting postoperative deaths (AUC 0.750, 95% CI 0,956-0,987). These findings were confirmed in multivariate analysis including the most relevant risk factors for AL.

CONCLUSION

Our study evidenced that CAR, an inexpensive and widely available laboratory biomarker, adequately predicts AL and death in patients who underwent elective surgery for colorectal cancer.

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

Objective

The purpose of this study was to investigate a newly constructed risk prediction model for anastomotic leakage after esophageal cancer resection.

Methods

A retrospective survey of 205 patients who underwent esophageal cancer resection was conducted using a self-designed questionnaire. The influencing factors were explored by single factor analysis, and a logistic regression analysis was performed to construct the prediction equation. A receiver operating characteristic curve was used to evaluate the model.

Results

The incidence of anastomotic leakage after esophageal cancer resection was 11.73%. There were five independent risk factors entered into the regression equation. The risk prediction equation was Z = 0.108 × age + 2.011 × preoperative chemotherapy history + 3.007 ×incision redness/exudation + 2.632 × pleural effusion + 1.934 × increased white blood cell count − 12.304. According to the receiver operating characteristic curve test, the area under the curve was 0.946, the sensitivity was 0.833, the specificity was 0.912, and the Youden index was 0.745.

Conclusion

The risk model of anastomotic leakage after esophageal cancer resection had a good predictive effect that was of significance for guiding clinical observation and early-screening.

Diagnosing anastomotic leak post-esophagectomy: a systematic review

Esophagectomy is the gold-standard treatment for esophageal cancer; however, postoperative anastomotic leakage remains the primary concern for surgeons. No consensus exists on the optimal investigations to predict an anastomotic leak. This systematic review aims to identify a single test or combination of tests with acceptable sensitivity and specificity to identify anastomotic leak after esophagectomy and to formulate a diagnostic algorithm to facilitate surgical decision-making. A systematic review of PubMed and EMBASE databases was undertaken to evaluate diagnostic investigations for anastomotic leak post-esophagectomy. Each study was reviewed and where possible, the sensitivity, specificity, positive predictive value, and negative predictive value were extracted. The review identified 3,204 articles, of which 49 met the inclusion criteria. Investigations most commonly used for diagnosis of anastomotic leak were: C-reactive protein (CRP), oral contrast imaging, computed tomography (CT), pleural drain amylase concentration, and the 'NUn score'. The sensitivity of CRP for detecting anastomotic leak varied from 69.2% to 100%. Oral contrast studies sensitivities varied between 16% and 87.5% and specificity varied from 20% to 100%. Pleural drain amylase sensitivities ranged between 75% and 100% and specificity ranged from 52% to 95.5%. The NUn score sensitivities ranged from 0% to 95% and specificity from 49% to 94.4%. No single investigation was identified to rule out anastomotic leak in asymptomatic patients. However, the authors propose a diagnostic algorithm incorporating CRP, pleural drain amylase concentration, and CT with oral contrast to aid clinicians in predicting anastomotic leak to facilitate safe, timely discharge post-esophagectomy.

Preoperative C-reactive protein-to-albumin ratio predicts anastomotic leak in elderly patients after curative colorectal surgery

BACKGROUND

Anastomotic leak (AL), as one of the most devastating complications, is the leading cause of mortality in colorectal cancer (CRC) patients after resection. This study was aimed to investigate potential risk factors for AL in elderly surgical CRC patients.

METHODS

A total of 1068 elderly subjects who underwent elective curative colorectal surgery from 2012 to 2018 were retrospectively evaluated and enrolled into this study population. The predictive value of C-reactive protein-to-albumin ratio (CAR) for AL in surgical CRC patients was evaluated by receiver operating characteristic (ROC) curve analysis. Potential risk factors for AL were assessed by the univariate and multivariate logistic regression analyses.

RESULTS

Of all the 1068 enrolled patients, 81 patients have developed AL with an incidence of 7.6% (81/1068). Preoperative CAR was an effective predictor for AL with an area under the curve (AUC) of 0.758, 95% CI of 0.700-0.817, a cut-off value of 2.44, a sensitivity of 61.09% and a specificity of 80.25%, respectively (P< 0.001). Duration of operation (OR: 2.05, 95% CI: 1.21-3.44, P= 0.013) and preoperative CAR (OR: 1.94, 95% CI: 1.21-3.11, P= 0.007) were two independent risk factors for AL by the multivariate logistic regression analysis.

CONCLUSIONS

Our study indicate that preoperative CAR level and duration of operation were two independent predictors for AL among elderly surgical CRC patients.