| Abstract|| |
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.
Keywords: Chemoradiotherapy, CONUT Score, esophageal cancer, nutrition, prognosis
| Introduction|| |
Esophageal cancer (EC) is the sixth leading cause of cancer mortality worldwide and the case-fatality ratio is 84%., Treatment modalities are evolving, and higher rates of locoregional and distant metastases are observed with surgery alone. Thus, adjuvant and neoadjuvant treatment options have been adopted in many centers to improve survival outcomes.
Malnutrition is frequent in EC patients at diagnosis, which is related to poor prognosis. Gastrointestinal tract obstruction, gastrointestinal adverse events due to neoadjuvant therapy, and esophageal dysfunction after surgery are the main risk factors that can make nutrition maintenance challenging.,, Recently, the identification of malnutrition has been based on quantitative measurement of decreased fat-free mass and skeletal muscle mass., Systemic inflammation is also recognized as a poor prognostic factor in solid tumors. Several quantitative, nutritional, inflammatory indices, and their relations with survival, are well-defined in EC. These were the Controlling Nutritional Status (CONUT), prognostic nutritional index (PNI), advanced lung cancer inflammation index (ALI), systemic immune-inflammation index (SII), pan-immune-inflammation value (PIV), c-reactive protein (CRP)-to-albumin (CAR), lymphocyte-to-CRP ratio, platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR).,,,,,,,,
Several trials investigated the prognostic significance of nutritional and inflammatory indices and scores in EC patients treated with upfront surgery, whereas neoadjuvant chemoradiotherapy (CRT) or adjuvant or neoadjuvant chemotherapy (CT) are preferred worldwide. Moreover, patients may reject surgery due to symptomatic relief after neoadjuvant CRT. Therefore, prognostic markers are needed not only in patients who undergo surgery alone but also in those treated with different treatment approaches. We investigated the impact of the CONUT Score along with several indices on survival in EC patients treated with CRT.
| Patients and Methods|| |
We included non-metastatic EC patients older than 18 years, who were diagnosed in our center between 2009 and 2021 and whose CONUT Score was available. Patients with a primary tumor located in the cervical esophagus and below the esophagogastric junction and those who have recently had an infectious disease that might affect the laboratory parameters were excluded. The patient groups, which were defined according to a significant CONUT Score cut-off, were compared in terms of survival. Demographic characteristics, tumor location and stage, pathologic features, and treatment data were retrieved from patient files. Paraesophageal, subcarinal, paratracheal, pulmonary ligament, diaphragmatic, paracardial, left gastric, common hepatic, splenic, and celiac nodes were accepted as regional lymph nodes. Approval for the study was obtained from the independent ethics committee. Written informed consent was obtained from all participants for this study.
The CONUT Score was calculated by adding the scores of the following parameters: serum albumin concentration (SAC) [≥3.5 g/dl (0 points), 3.0–3.4 g/dl (2 points), 2.5–2.9 g/dl (4 points), or <2.5 g/dl (6 points)], total lymphocyte count (TLC) [≥1600 cells/mm3 (0 points), 1200–1599 cells/mm3 (1 point), 800–1199 cells/mm3 (2 points), or <800 cells/mm3 (3 points)], and total cholesterol (TC) level [≥180 mg/dl (0 point), 140–179 mg/dl (1 point), 100–139 mg/dl (2 points), or <100 mg/dl (3 points)]. PNI was calculated as follows: 10 × SAC (g/dl) + 0.005 × TLC (per mm3). ALI was calculated as follows: Body mass index (BMI) x SAC/NLR. SII was calculated by neutrophil count (per mm3) × platelet count (per mm3)/TLC (per mm3). SAC was measured in g/dl. The lymphocyte/CRP ratio was calculated by dividing the TLC (per mm3) by the CRP (mg/dl). The CRP/Albumin ratio was calculated by dividing the CRP (mg/dl) by SAC (g/dl). PIV was calculated as: (neutrophil count [per mm3] × platelet count [per mm3] × monocyte count [per mm3])/TLC (per mm3). The PLR and NLR ratios were obtained by dividing the platelet (per mm3) and neutrophil (per mm3) counts by TLC (per mm3), respectively.
The variables were investigated using visual (histogram, probability plots) and analytical methods (Kolmogorov-Smirnov and Shapiro-Wilk's tests) to determine whether or not they were normally distributed. Descriptive analyses were presented using means and standard deviations for normally distributed non-categorical variables and the Student's t-test was used to compare these parameters. Descriptive analyses of non-normally distributed non-categorical variables were presented using medians and minimum-maximum values, and the Mann-Whitney U test was used to compare them between groups. Categorical variables were compared using the Chi-square or Fisher's exact test, as appropriate. The capacity of the CONUT Score and other indices in predicting survival was analyzed using receiver operating characteristic (ROC) curve analyses. When a significant cut-off value was observed, the sensitivity and specificity were presented. A cut-off for CONUT is calculated to show a survival difference in Kaplan-Meier analyses. Overall survival (OS) and progression-free survival (PFS) were analyzed. PFS was defined as the time from the last treatment date to progression. OS is defined as the time from the date of diagnosis to death. Survival estimates were calculated by Kaplan-Meier analyses and median survival times were compared by the log-rank test. Possible prognostic factors determined in univariate Cox regression analyses with a P value of ≤0.20 were further entered into multivariate Cox regression analysis, with entry selection, to determine independent predictors of survival. Among strongly correlated factors with similar effects on survival, only those with clinical significance were included. A P value less than 0.05 was considered to denote statistical significance. The SPSS Software Version 26 (IBM, Chicago, Illinois, USA) was used for the analysis.
| Results|| |
Clinicopathologic characteristics of patients
A total of 101 patients were included in the study, with a median age of diagnosis of 59 years (35-84); 44 (43.6%) were male and 57 (56.4%) were female. Ninety-four (93%) patients had esophageal squamous cell carcinoma (ESCC). In 45 patients (44.6%), the tumour was found in the lower esophagus; 40 (39.6%) and 39 (38.6%) patients had an ECOG performance status of 0 and 1, respectively. The majority of patients had cT3 (n = 87, 86.1%) and cN0 (n = 93, 50.3%) disease. Thirty-one (30.7%) patients received systemic treatment after diagnosis. Sixty (60%) patients were treated with CRT alone, while 41 patients were treated with CRT plus surgery. Other clinicopathologic features of the entire population are summarized in [Table 1].
ROC curve analyses for indices
ROC curve analyses were performed for CONUT, PNI, ALI, SII, Lymphocyte/CRP, CRP/Albumin, PIV, PLR, and NLR in predicting OS. The ROC Curve analysis determined the optimal cut-off value, which was 3.5 (AUC = 0.63, CI 95%: 0.51-0.76, P = 0.05), for the CONUT Score [Figure 1]. The ROC Curve analyses did not establish any optimal cut-off value for PNI, ALI, SII, Lymphocyte/CRP, CRP/Albumin, PIV, PLR, and NLR [Table 2]. The sensitivity and specificity of CONUT in the observed cut-off value were 66% and 61%, respectively. The ROC Curve analyses did not show a significant cut-off in predicting PFS in the CONUT Score (AUC = 0.54, CI 95%:41-67, P = 0.55).
|Figure 1: ROC Curve of different indices and scores for OS. CONUT: Controlling Nutritional Status; PNI: Prognostic Nutritional Index; ALII: Advanced Lung Cancer Inflammation Index; SII: Systemic Immune-Inflammation Index; CRP: C-Reactive Protein; PIV: Pan-Immune-Inflammation Value; PLR: Platelet-Lymphocyte Ratio; NLR: Neutrophil Lymphocyte Ratio|
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Clinicopathologic variables and survival outcomes
The median duration of follow-up was 47.9 months. The median PFS and OS of the entire population were 7.7 and 44.8 months, respectively. We divided the patients into two groups: 50 (49.5%) patients were classified as low (≤3.5) and 51 (50.5%) patients were classified as high (>3.5) CONUT. The median age of these patients was 62 and 59, respectively. High CONUT was significantly related to high CRT alone (n = 36, 70.6%) and death (n = 32, 62.7%). High CONUT patients had lower mean PNI (p = 0.009), TLC (p = 0.02), TC (p < 0.001), SAC (p = 0.009), and median ALI (p = 0.03) than low CONUT patients. Other features were equally distributed between low and high CONUT [Table 3].
|Table 3: Clinicopathological features of non-metastatic EC patients according to low (≤3.5) and high (>3.5) CONUT|
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Low CONUT patients had significantly longer median OS than high CONUT patients (57.1; [CI 95%: not calculated] vs. 23 months; [CI 95%: 15.5-30.5], P = 0.009) [Figure 2]a. Median PFS was not significantly different between low and high CONUT (8.5; [CI 95%: 0.9-16.1] vs. 6.4 months; [CI 95%: 2.7-10.1], P = 0.83) [Figure 2]b. In addition to age at diagnosis and surgery, CONUT Score was also an independent predictor of OS based on multivariate Cox regression analysis (HR 1.96 [CI 95%: 1.03-3.75], P = 0.04) [Table 4].
|Figure 2: Progression Free Survival (a) and Overall Survival (b) in Low and High CONUT Patients. CONUT: Controlling Nutritional Score|
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|Table 4: Univariate and multivariate cox regression analyses for overall survival|
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| Discussion|| |
Increasing evidence suggests that nutrition and inflammation have a prognostic impact on survival in EC patients. In the present study, we investigated a significant cut-off value for each index in predicting OS. We established a significant cut-off for CONUT and have shown that nutritional status established by the CONUT Score was significantly prognostic for OS. This effect was evident in patients treated with CRT, and the CONUT Score was a useful tool to estimate prognosis at initial assessment.
The CONUT Score was first validated by Ulibarri et al. and is calculated using TC, SAC, and TLC. The CONUT Score is different than other inflammatory-based markers due to the inclusion of TC. TC is an indicator of the calorie reserve of a patient., Hypocholesterolemia was associated with worse survival outcomes in several malignancies such as renal cell carcinoma and lung cancer, and it was hypothesized that this was possibly induced by tumor proliferation, migration, and invasion.,,,, A lower TC level was associated with poorer survival in a recent study which enrolled ESCC patients. In previous trials, it has been proposed that hypocholesterolemia was associated with lower T cell counts and decreased antigen-presenting features of monocytes., These demonstrate that cholesterol plays an important role as a host factor beyond tumor cell proliferation.
SAC is related to both nutritional status and systemic inflammation. Fuhrman argued that SAC may be affected by several factors, and this condition may lead to low sensitivity and specificity for the CONUT Score.
Lymphocytes are involved in cell-mediated immune responses, and the balance between neutrophilic and lymphocytic infiltration in the tumor microenvironment is important at this point. The tumor microenvironment includes many types of inflammatory cells such as neutrophils which can suppress cytotoxic anti-tumor lymphocytes., There has been increasing evidence that cancer-associated inflammation is a major determinant of survival in malignancies. The CONUT can be considered as a comprehensive score in terms of including both nutritional and inflammatory-based biomarkers according to all the present findings.
We showed the cut-off value as 3.5 for the CONUT Score in predicting OS of EC patients, with a sensitivity and specificity of 66% and 61%, respectively. This cut-off was similar to that determined in a locally advanced gastric cancer study. Low CONUT patients had significantly higher OS than high CONUT patients (57.1 vs. 23 months, P = 0.009), respectively. The CONUT Score was an independent prognostic factor (p = 0.04), although treatment modalities were significantly different in the low and high CONUT groups (p = 0.02). Yoshida et al. advocated that the CONUT Score has a prognostic value rather than being an indicator of malnutrition. To date, there has not been sufficient information regarding this point. Another problem which might be present in such a study is multicollinearity in multivariate analyses. Several indices carrying multicollinearity risk were excluded in multivariate analysis and our latest model was obtained. To the best of our knowledge, this is the first study which represents the utility of the CONUT Score in EC patients treated with CRT. Our study also included patients treated with surgery or CT and reflects real life scenario. Therefore, we can also conclude that the CONUT Score is useful in such a mixed patient population regardless of treatment modality.
Our limitations were the relatively small sample size, retrospective nature of the trial, absence of a validation cohort, and absence of cancer-specific survival data. The vast majority of patients were clinically staged with PET and the absence of EUS may result in lower accuracy of locoregional staging. Tumor grade, lymphovascular invasion, and perineural invasion data were missing in a vast majority of patients.
In conclusion, accurate detection of malnutrition provide better prognosis in EC patients treated with CRT. Our findings showed that EC patients with good and poor prognosis can be identified even in the untreated period with the CONUT Score, which is a nutrition and inflammatory-based score. Dietitian evaluation and feeding interventions such as enteral or parenteral support, if essential, should be a part of the multidisciplinary assessment for these patients. This will help clinicians to manage EC patients in the completion of preplanned treatment, including CT, CRT, or surgery. In malnutrition risk assessment, we presented that the CONUT Score is a useful, cheap, comprehensive, and bedside tool for each EC patient treated with CRT.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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Department of Medical Oncology, Erzurum Regional Training and Research Hospital, 25100, Yakutiye, Erzurum
Source of Support: None, Conflict of Interest: None
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]