Comparative Analysis of Immunoinflammatory and Nutritional Measures in Surgically Resected Esophageal Cancer: A Single-center Retrospective Study

Long-term nutrition in patients candidate to neoadjuvant and adjuvant treatments

To improve outcomes, to decrease the rate of local recurrence and development of distant metastases neoadjuvant and adjuvant therapies are employed in cancer patients in forms of radiation, chemo-, endocrine-, targeted-, and immunotherapy or their combination. Nutrition therapy plays important role in all phases of the cancer journey. From neoadjuvant therapy to prehabilitation, early postoperative nutrition, and long-term nutrition care during the adjuvant phase and survivorship determines the survival and quality of life of cancer patients. During the neoadjuvant phase patients may be in poor nutritional condition which can be aggravated by the applied oncological treatment. Beside this apparent threat this period also gives an excellent opportunity to maintain or even improve the nutritional status of the patients by nutrition therapy. After surgery the burdening effects of the operation may jeopardize the execution of adjuvant therapy. After early postoperative feeding a long-term nutrition strategy should be developed for cancer patients in order to avoid nutritional deterioration during the usually lengthy postoperative therapy. In this narrative review we discuss how preoperative nutritional status and medical nutrition therapy influence the results of surgery and after the operation what is the available evidence about nutritional status and outcome and the potentials to influence them by nutrition therapy.

Prognostic value of pretreatment Controlling Nutritional Status score in esophageal cancer: a meta-analysis

Background and purpose: The association between the pretreatment Controlling Nutritional Status (CONUT) score and the prognosis of esophageal cancer patients remains unclear. The aim of this meta-analysis was to further elucidate the prognostic role of the pretreatment CONUT score in esophageal cancer based on current evidence. Methods: The PubMed, Embase, Web of Science and CNKI databases were searched up to 27 September 2022. The primary and secondary outcomes were overall survival (OS) and progression-free survival (PFS)/cancer-specific survival (CSS), and the hazard ratio (HR) and 95% confidence interval (CI) were pooled for analysis. Results: A total of 11 retrospective studies involving 3,783 participants were included. The pooled results demonstrated that a higher pretreatment CONUT score was significantly related to poor OS (HR = 1.82, 95% CI: 1.31-2.54, p < 0.001), and subgroup analysis stratified by pathological type showed similar results. In addition, the pretreatment CONUT score was associated with poor PFS (HR = 1.19, 95% CI: 1.10-1.28, p < 0.001) and CSS (HR = 2.67, 95% CI: 1.77-4.02, p < 0.001). Conclusion: The pretreatment CONUT score was predictive of worse prognosis in esophageal cancer, and patients with a higher CONUT score showed worse survival.

The CONUT score is prognostic in esophageal cancer treated with chemoradiotherapy

Background

Malnutrition is a frequent issue in esophageal cancer (EC). The Controlling Nutritional Status (CONUT) Score has been established as a prognostic indicator in EC patients who underwent surgery. We aimed to investigate the role of the CONUT Score in EC patients treated with chemoradiotherapy (CRT).

Methods

The trial included 101 non-metastatic EC patients. Receiver operating characteristic (ROC) curve analyses were used to determine cut-off values for the CONUT Score and other indices. Cox regression analyses were performed to determine prognostic markers.

Results

Of 101 patients, 59.4% (n = 60) and 40.6% (n = 41) of patients were treated with CRT alone and CRT plus surgery, respectively. ROC curve analyses determined an optimal cut-off for CONUT Score in overall survival (OS), which was 3.5 (AUC = 0.63, CI 95%: 0.51-0.76, P = 0.05). The sensitivity and specificity of CONUT were 66% and 61%, respectively. Low CONUT (≤3.5) patients had significantly longer median OS than high CONUT (>3.5) patients (57.1 vs. 23 months; P = 0.009). Multivariate regression analysis revealed a CONUT Score hazard ratio (HR) of 1.96 for OS (CI 95%: 1.03-3.75, P = 0.04).

Conclusion

The CONUT Score might be a useful prognostic tool in EC patients treated with CRT. Appropriate nutritional support might provide a better prognosis, which underlines the importance of multidisciplinary assessment of malnutrition in EC patients.

Usefulness of Nutrition and Inflammation Assessment Tools in Esophageal Cancer Treatment

Multidisciplinary treatment for esophageal cancer leads to nutritional and inflammatory changes. Recent studies showed that nutritional and inflammatory changes during multidisciplinary treatment affect both short and long-term oncological outcomes in esophageal cancer treatment. Therefore, evaluation of the nutritional and inflammatory status during treatment is necessary in order to optimize and utilize multidisciplinary therapy for esophageal cancer. If patients with esophageal cancer are able to determine their nutritional and inflammatory status, they will be able to select the optimal esophageal cancer, anti-inflammation, and nutritional treatments. Various types of nutrition and inflammation assessment tools have been developed and reported for esophageal cancer, with each tool having its own clinical characteristics, which must be understood before being applied in clinical practice. This review summarizes the background, current status, and future perspectives on the application of nutrition and inflammation assessment tools in esophageal cancer treatment.

Controlling Nutritional Status Score Serves as a Prognosticator in Esophageal Squamous Cell Carcinoma: Optimal Timing of Evaluation of Patients Undergoing Neoadjuvant Treatment

BACKGROUND

Usefulness of various nutritional indices for management of patients with esophageal squamous cell carcinoma (ESCC) has been reported. Although Controlling Nutritional Status (CONUT) score is among promising indices to predict outcome, the optimal timing for its measurement during the perioperative period remains unknown. Here the prognostic value of the CONUT score was assessed among patients with ESCC.

METHODS

We analyzed 464 patients who underwent subtotal esophagectomy of ESCC, of which 276 patients were treated with neoadjuvant treatment (NAT). The significance of the associations between candidate parameters including the CONUT score and postoperative prognosis were evaluated.

RESULT

Among the 25 candidate predictors, the preoperative CONUT score had the highest correlation with overall survival (OS) after surgery. Patients were categorized as follows: normal, mild, and moderate or severe, on the basis of the preoperative CONUT score. OS was significantly shortened as the CONUT score worsened. Multivariable analysis revealed that the CONUT scores of the subgroups mild (Hazard ratio [HR] 1.69) and moderate or severe (HR 2.18) were independent predictors of poor prognosis for OS. Furthermore, in an analysis limited to patients who underwent NAT, OS was significantly shortened as the preoperative CONUT score worsened. On the contrary, there was no significant difference in RFS among patient groups stratified by the CONUT score determined before NAT.

CONCLUSIONS

Our study indicates that the preoperative CONUT score serves as a prognosticator in resectable ESCC. The preoperative CONUT value was more useful than that before NAT in patients administered NAT.

Clinlabomics: leveraging clinical laboratory data by data mining strategies

The recent global focus on big data in medicine has been associated with the rise of artificial intelligence (AI) in diagnosis and decision-making following recent advances in computer technology. Up to now, AI has been applied to various aspects of medicine, including disease diagnosis, surveillance, treatment, predicting future risk, targeted interventions and understanding of the disease. There have been plenty of successful examples in medicine of using big data, such as radiology and pathology, ophthalmology cardiology and surgery. Combining medicine and AI has become a powerful tool to change health care, and even to change the nature of disease screening in clinical diagnosis. As all we know, clinical laboratories produce large amounts of testing data every day and the clinical laboratory data combined with AI may establish a new diagnosis and treatment has attracted wide attention. At present, a new concept of radiomics has been created for imaging data combined with AI, but a new definition of clinical laboratory data combined with AI has lacked so that many studies in this field cannot be accurately classified. Therefore, we propose a new concept of clinical laboratory omics (Clinlabomics) by combining clinical laboratory medicine and AI. Clinlabomics can use high-throughput methods to extract large amounts of feature data from blood, body fluids, secretions, excreta, and cast clinical laboratory test data. Then using the data statistics, machine learning, and other methods to read more undiscovered information. In this review, we have summarized the application of clinical laboratory data combined with AI in medical fields. Undeniable, the application of Clinlabomics is a method that can assist many fields of medicine but still requires further validation in a multi-center environment and laboratory.

Albumin and Derived Neutrophil-to-Lymphocyte Ratio is a Novel Prognostic Factor for Patients with Esophageal Squamous Cell Carcinoma

BACKGROUND

Multidisciplinary treatment combining neoadjuvant treatment (NAT) and surgery has slightly improved the prognosis of patients with esophageal squamous cell carcinoma (ESCC). Although various biomarkers targeting nutrition and inflammation are associated with cancer prognosis, most studies have focused on conditions prior to NAT. Developing real-time and sensitive biomarkers that monitor changes in systemic conditions during NAT is important. We established a novel nutritional and inflammatory index, represented as the albumin to derived neutrophil-to-lymphocyte ratio (Alb-dNLR), and calculated the change in Alb-dNLR (ΔAlb-dNLR) during neoadjuvant chemotherapy (nCT). In this study, we aimed to evaluate whether ΔAlb-dNLR is associated with prognosis in patients with ESCC.

METHODS

We investigated 172 patients who underwent nCT before esophagectomy between April 2010 and March 2018. The dNLR was calculated as the ratio of neutrophil count to (white blood cell count - neutrophil count), Alb-dNLR was calculated by dividing the serum albumin level by the dNLR, and ΔAlb-dNLR was evaluated by dividing the post-Alb-dNLR by the pre-Alb-dNLR. Patients were divided into 'high' and 'low' groups according to the ΔAlb-dNLR.

RESULTS

Thirty-nine patients (22.7%) had a low ΔAlb-dNLR (≤ 0.8), and the 5-year overall survival (OS) rates in patients with low and high ΔAlb-dNLR were 38.1% and 53.6%, respectively (p = 0.0072). Multivariate analyses demonstrated that estimated blood loss (p = 0.044), pathological T stage (p = 0.0005), pathological N stage (p = 0.017), and ΔAlb-dNLR (p = 0.005) were independent prognostic factors for OS.

CONCLUSIONS

ΔAlb-dNLR is a useful prognostic factor for OS in patients with ESCC receiving nCT.

Clinical Significance of Nutrition and Inflammation in Esophageal Cancer Patients with Surgery: A Meta-Analysis

Many studies have reported that the geriatric nutritional risk index (GNRI) and C-reactive protein to albumin ratio (CAR) may be associated with prognosis of esophageal cancer (EC); however, the results are inconsistent. Therefore, we performed a meta-analysis to evaluate the effect of preoperative GNRI and CAR on the prognosis of EC. PubMed, Embase, Cochrane Library, and Web of Science databases were searched. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were used to analyze the relationship between GNRI/CAR and prognosis. Publication bias was estimated using Begg's funnel plot asymmetry test and Egger's test. A total of 21 studies comprising 5,018 patients were included in the meta-analysis. A decreased GNRI was significantly associated with poorer overall survival (OS) (HR = 1.808, 95% CI: 1.489-2.196, P < 0.001) and cancer-specific survival (CSS) (HR = 1.769, 95% CI: 1.193-2.624, P = 0.005), and an increased CAR was significantly associated with lower OS (HR = 2.179, 95% CI: 1.587-2.992, P < 0.001), CSS (HR = 1.733, 95% CI: 1.333-2.253, P < 0.001), and recurrence-free survival (HR = 2.178, 95% CI: 1.328-3.573, P = 0.002). Thus, preoperative GNRI and CAR may be noninvasive and powerful tools for predicting survival outcomes in patients with EC.

Impact of the Ratio of Visceral Fat Area (VFA) to Psoas Muscle Area (PMA) (V/P Ratio) on Survival for Surgically Resected Esophageal Cancer

BACKGROUND

The synergic effects of muscle mass reduction with excess body adiposity in surgically resected esophageal cancer (EC) patients remains controversial, especially in non-obese patients.

METHODS

One hundred and six patients with EC who underwent surgery between 2006 and 2014 were included in this study. Reduction in muscle mass and excess body adiposity were defined as the ratio of visceral fat area (VFA) to psoas muscle area (PMA) (V/P ratio) on the same axial computed tomography (CT) slice at the third lumbar vertebra (L3).

RESULTS

A high V/P ratio was associated with greater age (p = 0.03), higher body mass index (BMI) (p < 0.001), higher VFA (p < 0.001), and increased age-adjusted Charlson comorbidity index (ACCI) (p = 0.005). Multivariate analysis revealed a high V/P ratio to be an independent prognostic factor for poor overall survival (OS) in EC patients who underwent surgery (p = 0.003). The prognostic value of the V/P ratio was still significant in EC patients with a BMI < 25.

CONCLUSIONS

A high V/P ratio was associated with poor survival in surgically resected EC patients, even in non-obese patients. The V/P ratio as a surrogate marker of relative muscle mass reduction and fat accumulation may have prognostic value in EC patients regardless of body composition differences.

Albumin-Derived NLR Score is a Novel Prognostic Marker for Esophageal Squamous Cell Carcinoma

BACKGROUND

Multidisciplinary treatment for esophageal squamous cell carcinoma (ESCC) has improved outcomes, but the prognosis for ESCC remains poor. Nutritional and inflammatory indicators are reported to be associated with cancer prognosis. The combination of albumin and the derived neutrophil-to-lymphocyte ratio (Alb-dNLR) score was established to measure the immune system and nutritional status. The authors hypothesized that the Alb-dNLR score could be a new reliable prognostic factor for ESCC patients.

METHODS

The study evaluated 269 patients who underwent esophagectomy between April 2010 and March 2018, including 185 patients who received neoadjuvant chemotherapy. The Alb-dNLR score was calculated using serum albumin and the dNLR. The dNLR was calculated as neutrophils to (leukocyte-neutrophil count). The cutoff values of the albumin and dNLR for overall survival (OS) were determined using the receiver operating characteristic curve. Patients were divided into "high" and "low" groups according to the Alb-dNLR score.

RESULTS

A high Alb-dNLR score was found in 61 cases (22.7%). The 5-year OS was 34% in the high Alb-dNLR group and 66.2% in the low Alb-dNLR group (p < 0.0001). The 5-year cause-specific survival (CSS) was 51.5% in the high Alb-dNLR group and 74.7% in the low Alb-dNLR group (p < 0.0001). Multivariate analyses demonstrated that the Alb-dNLR score was an independent prognostic factor for OS (hazard ratio [HR], 2.198; 95% confidence interval [CI], 1.460-3.263; p = 0.0002) and CSS (HR, 1.733; 95% CI, 1.035-2.835; p = 0.0371).

CONCLUSIONS

The Alb-dNLR score is an extremely useful, easy-to-use parameter to predict OS and CSS for ESCC patients.

Prognostic Value of C-Reactive Protein, Glasgow Prognostic Score, and C-Reactive Protein-to-Albumin Ratio in Colorectal Cancer

Background: Emerging evidence suggests that inflammatory response biomarkers are predictive factors that can improve the accuracy of colorectal cancer (CRC) prognoses. We aimed to evaluate the prognostic significance of C-reactive protein (CRP), the Glasgow Prognostic Score (GPS), and the CRP-to-albumin ratio (CAR) in CRC. Methods: Overall, 307 stage I-III CRC patients and 72 colorectal liver metastases (CRLM) patients were enrolled between October 2013 and September 2019. We investigated the correlation between the pretreatment CRP, GPS, and CAR and the clinicopathological characteristics. The Cox proportional hazards model was used for univariate or multivariate analysis to assess potential prognostic factors. A receiver operating characteristic (ROC) curve was constructed to evaluate the predictive value of each prognostic score. We established CRC survival nomograms based on the prognostic scores of inflammation. Results: The optimal cutoff levels for the CAR for overall survival (OS) in all CRC patients, stage I-III CRC patients, and CRLM patients were 0.16, 0.14, and 0.25, respectively. Kaplan-Meier analysis and log-rank tests demonstrated that patients with high CRP, CAR, and GPS had poorer OS in CRC, both in the cohorts of stage I-III patients and CRLM patients. In the different cohorts of CRC patients, the area under the ROC curve (AUC) of these three markers were all high. Multivariate analysis indicated that the location of the primary tumor, pathological differentiation, and pretreatment carcinoembryonic antigen (CEA), CRP, GPS, and CAR were independent prognostic factors for OS in stage I-III patients and that CRP, GPS, and CAR were independent prognostic factors for OS in CRLM patients. The predictors in the prediction nomograms included the pretreatment CRP, GPS, and CAR. Conclusions: CRP, GPS, and CAR have independent prognostic values in patients with CRC. Furthermore, the survival nomograms based on CRP, GPS, and CAR can provide more valuable clinical significance.

Development of a New Recurrence-Free Survival Prediction Nomogram for Patients with Primary Non-Muscle-Invasive Bladder Cancer Based on Preoperative Controlling Nutritional Status Score

Background

Bladder cancer is the second most prevalent neoplasm in the urogenital system in terms of morbidity and mortality, and there is an urgent need for a more accurate assessment of individual prognosis in patients with primary non-muscle-invasive bladder cancer (NMIBC). The Controlling Nutritional Status (CONUT) score is an emerging biomarker score which has been confirmed to have prognostic value in various malignant tumors. The study attempted to systematically identify the prognostic role of preoperative CONUT score on posttreatment recurrence-free survival (RFS) in patients with NMIBC, and determine the predictive value and feasibility of the new prognostic prediction model.

Methods

A total of 94 patients with NMIBC were analyzed retrospectively between January 2011 and December 2015. Statistical analysis was conducted using the nonparametric method. The Kaplan-–Meier method was used to assess recurrence-free survival (RFS), and Log rank tests was used to analyze the equivalences of survival curves. We used univariate and multivariate Cox proportional hazards regression model to identify important predictors of RFS. Discrimination of nomogram was measured by the concordance index. Predictive accuracy of the model was evaluated using the internal validation.

Results

In univariate analysis, age, history of smoking, pathological T stage, tumor grade, tumor size, and CONUT score were significantly correlated with RFS. Multivariate analysis indicated that CONUT score (HR =3.855, 95% CI 1.242–11.970, p=0.020) was an independent predictor of RFS in patients with NMIBC. Based on significant parameters in multivariate analysis and reliable recurrence predictors determined in predictive models and relevant guidelines, a new age-, history of smoking-, pathologic factors- and the CONUT score-based scoring model was developed to predict recurrence of NMBIC. In addition, we internally validated the nomogram using the consistency index and calibration plots, which demonstrated that the model has high prediction accuracy (c-index= 0.851).

Conclusion

The development of a new nomogram based on CONUT score could increase the accuracy of recurrence prediction and improve individualized treatment plans for patients with NMIBC.

Preoperative C-Reactive Protein/Albumin Ratio as a Predictive Factor for Gallbladder Carcinoma

BACKGROUND/AIM

The C-reactive protein (CRP) to albumin ratio (CAR) is associated with outcomes in patients with sepsis. We aimed to evaluate the significance of preoperative CAR in therapeutic outcomes after gallbladder carcinoma (GBC) resection.

PATIENTS AND METHODS

Fifty-three patients who underwent surgical resection for GBC between January 2008 and September 2019 were enrolled. We retrospectively investigated the relation between preoperative CAR and overall and disease-free survival.

RESULTS

The optimal cut-off CAR was 0.07. Multivariate analysis showed that i) R1 or R2 resection (p=0.033), ii) advanced tumor stage (p=0.047), iii) CAR≥0.07 (p=0.011), and iv) postoperative complications (p=0.028) were significant independent predictors of overall survival; moreover, higher carbohydrate antigen levels (p=0.036) and R1 or R2 resection (p<0.001) were significant independent predictors of disease-free survival.

CONCLUSION

Preoperative CAR may be a significant independent predictor of long-term outcomes after GBC resection.