Controlling Nutritional Status (CONUT) as a Novel Postoperative Prognostic Marker in Breast Cancer Patients: A Retrospective Study

Purpose This investigation seeks to elucidate the potential prognostic significance as well as the clinical utility of the controlling nutritional status (CONUT) score in breast cancer patients. Methods Breast cancer patients managed in our center between January 2010 and December 2016 were recruited for our study. They comprised 187 patients who did not undergo neoadjuvant chemotherapy and 194 who did. A receiver operating characteristic curve (ROC) was utilized in identifying the ideal cut-off CONUT value. This cut-off score was then used to reclassify patients into those with high CONUT scores (≥1) and low CONUT scores (<1). The outcomes were analyzed by statistical methods. Results Univariate and multivariate Cox regression survival analyses revealed that a CONUT score cut-off of 1 was able to significantly predict duration of disease-free survival (DFS) (p < 0.001; hazard ratio [HR]: 3.184; 95% CI: 1.786-5.677; and p < 0.001; HR: 2.465; 95% CI: 1.642-3.700) and overall survival (OS) (p < 0.001; HR: 2.326; 95% CI: 1.578-3.429; and p < 0.001; HR: 2.775; 95% CI: 1.791-4.300). The mean DFS and OS in those with lower CONUT scores were 41.59 (95% CI: 37.66-45.51 months) and 77.34 months (95% CI: 71.79-82.90 months), respectively. On the other hand, the average DFS and OS for all individuals in the raised CONUT score group were 39.18 (95% CI: 34.41-43.95 months) and 71.30 months (95% CI: 65.47-77.12 months), respectively. Moreover, Kaplan-Meier survival analysis revealed that those in the raised CONUT score cohort had remarkably worse DFS and OS survival rates compared to individuals in the low CONUT score cohort (Log-rank test, DFS: χ2 = 12.900, p = 0.0003, and OS: χ2 = 16.270, p < 0.0001). Conclusion The survival times of breast cancer patients may be reliably predicted using the CONUT score. This score is an easy, convenient, readily accessible, and clinically significant means of prognosticating patients with breast cancer.


Introduction
The latest reported global cancer statistics data places breast cancer (BC) as the most frequently diagnosed malignancy around the world. BC is a notable contributor to cancerassociated morbidity and mortality in females globally, with the year 2020 yielding over 276,480 new cases and 63,220 deaths [1,2]. The development of BC is a multistep process involving a variety of cell types, and its treatment and prevention remain challenging. Despite advances in early diagnosis and continuously improving multidisciplinary treatment modalities and protocols, the clinical course of recurrent and metastatic BC remains unsatisfactory [3,4]. Surgery is the main treatment for BC. Key components of neoadjuvant BC treatment include chemoradiotherapy, hormonal therapy, molecular targeted therapy, and so on [5][6][7]. BC is a clinically heterogeneous disease, and currently available nutritional status markers have been found to be inadequate in stratifying patients according to their risk, thus limiting the extent of effective individualized treatment [8].
Treatment regimens tailored specifically to each patient will likely result in improved survival rates and prognosis. There is a need to develop more reliable biomarker panels that are able to accurately evaluate the impact of nutritional status on disease prognosis and treatment outcomes.
The Controlling Nutritional Status (CONUT) score takes into consideration both nutritional and immune status. The CONUT score is derived from three parameters total cholesterol (TC), total lymphocyte CONUT (TLC), and serum albumin concentration (ALB), and is reflective of host immune function, lipid, as well as protein metabolism [20]. The CONUT score has been shown to provide accurate prognostic and survival information in a variety of solid organ and hematological malignancies, such as gastric cancer, colorectal cancer, and multiple myeloma [21][22][23]. Cancer patients are often malnourished, which negatively impacts cancer progression, chemotherapy response, and postoperative outcomes. Despite these established links, the relationship between the immune system and nutritional state is not commonly explored in cancer patients. The use of the CONUT score is an immune-nutritional score with a good prognostic value that also highlights the importance of these two physiological parameters. Our investigation seeks to elaborate on the clinical utility of the CONUT score in breast cancer patients.

Patients.
All of 381 patients treated at the Cancer Hospital Chinese Academy of Medical Sciences between January 2010 to December 2016 were retrospectively examined in this investigation. All patients had stage III histologically confirmed breast cancer and underwent a radical mastectomy. Of all, 194 cases received neoadjuvant chemotherapy, while 187 cases did not (controls). All personal data was handled in strict compliance with ethical guidelines stipulated by the 1964 Declaration of Helsinki (including its later amendments or similar ethical frameworks) and were also in line with standards upheld by the ethics committee of the Cancer Hospital Chinese Academy of Medical Sciences.

Eligibility Criteria and Exclusion
Criteria. Eligibility criteria were: (1) patients with pathologically diagnosed with breast cancer; (2) patients who underwent primary tumor resection; (3) patients with complete clinical and follow-up medical records; (4) patients with Zubrod-ECOG-WHO (ZPS) between 0 and 2 and Karnofsky Performance Scores ðKPSÞ ≥ 80; (5) patients with pretreatment laboratory results of peripheral blood samples (such as serum TLC, TC, and ALB).
Exclusion criteria were: (1) patients who received antitumor therapy, such as radiotherapy, chemotherapy, and targeted therapy before treatment in control group; (2) patients diagnosed with inflammatory or autoimmune diseases; (3) those found to have incomplete clinicopathological data; (4) patients who were transfused with blood products within a month prior to data collection.
2.3. Data Collection and Assessment. The 8th edition AJCC (American Joint Committee on Cancer) and the Union for International Cancer Control (UICC) TNM stage classification were used to assess patients' demographic and clinicopathologic parameters, which were extracted from their respective medical records [24,25]. The following demographic parameters were collected: age, marital status, occupation, weight, height, BMI, family history, menarche age, menopause status, and so forth. The following clinicopathologic parameters were collected: hematologic parameters, imaging parameters, pathological parameters, treatment parameters, and so on. The Response Evaluation Criteria in Solid Tumors (RECIST) guidelines and Miller and Payne grade (MPG) were used to determine the degree of histological response [26,27]. The National Cancer Institute Common Toxicity Criteria (NCI-CTC) was used to evaluate chemotherapy toxicity [28].

Calculation of the CONUT Score and Other Markers.
Peripheral venous blood specimens were obtained within seven days before treatment in all enrolled patients. An immune-nutritional status marker, the CONUT score, was derived using TC, TLC, and ALB values. All individuals were placed into four cohorts in line with their degree of malnourishment: Normal (0-1), Light (2-4), Moderate (5)(6)(7)(8), and Severe (9)(10)(11)(12). The detailed information is shown in Table 1 Univariate and multivariate Cox proportional hazards regression models were used to discern potential prognostic factors. Hazard ratios (HRs) and 95% confidence intervals (CIs) were used to determine the association between various parameters and breast cancer prognosis. The nomogram was conducted by the multivariate analyses, matched every prognostic variable with the corresponding score, and the sum of the scores of all potential variables is defined as the total score. The calibration curve was performed to predict the performance for DFS and OS after curative resection. And the decision curve analysis (DCA) to test predictive clinical utility. A two-tailed p value that was <0.05 was interpreted as achieving statistical significance. In control group, we noted that lymphocyte, MLR, PLR, SII, and PNI in the preoperative high CONUT group were significantly different from those in the low CONUT group (p < 0:05). In the treatment group, we noted TC, white blood cell, lymphocyte, monocyte, eosinophils, basophils, platelets, MLR, PLR, SIRI, SII, and PNI in the preoperative high CONUT group were significantly different from those in the low CONUT group (p < 0:05) ( Table 3).

The Relationship between Pathological
Parameters and the CONUT Score. We uncovered statistically significant variances in molecular subtypes, Ki-67 status, PR status, ER status, and TOP2A status (p < 0:05). And these variables were found to be significantly worse in the high CONUT group than in the low CONUT group. In control group, statistical analysis of the relationship between pathological parameters and CONUT scores demonstrated that ER status, PR status, P53 status, and TOP2A status were all related to the CONUT score (p < 0:05). However, there was only a molecular subtypes in the preoperative high CONUT group was significantly different from this in the low CONUT group in the treatment group (p < 0:05) ( Table 4).   4 BioMed Research International             a) and 1(b)). The prognostic value of the CONUT score was also evaluated in the Treatment and Control cohorts. There were 76 patients with high CONUT scores and 111 patients with low CONUT scores in the Control cohort. Kaplan Meier survival analysis revealed that patients with higher CONUT scores having significantly poorer survival outcomes in contrast to those with lower CONUT scores in terms of DFS

Establishing CONUT-Based Nomograms in Predicting
Survival Outcomes. Univariate and multivariate Cox regression analyses revealed that postoperative chemotherapy, postoperative radiotherapy, TC, CONUT, and lymph vessel invasion were identified as candidate prognostic factors affecting DFS. For OS, the potential prognostic factors were postoperative chemotherapy, postoperative radiotherapy, TC, and CONUT. These prognostic factors were used to generate a DFS-and OS-predicting nomogram (Figures 2(a) and 2(b)). 28.82%, 1.75%, and 96.94%, 83.84%, 72.05%, and 17.47%, respectively. The corresponding DFS and OS in the high CONUT score group were 80.26%, 47.37%, 23.68%, 0.66%, and 96.05%, 81.58%, 67.11%, and 11.18%, respectively. Although with high CONUT score had worse 1-, 3-, 5-, and 10-year rates of DFS and OS than those with low CONUT scores, yet there were no significant difference between the two groups (p > 0:05) (Figures 3(a) and 3(b)). In the Control group, only the 5-and 10-year OS rates of those with high CONUT scores were lower in contrast to those with lower CONUT scores, but the 1-and 3-year OS rates in the high CONUT group were higher than those in the low CONUT group. However, these differences failed to achieve statistical significance (p > 0:05), except in 10year rates of OS (p < 0:05). Conversely, the 1-, 3-, 5-, and 10-year DFS rates of those in the high CONUT group were lower in contrast to those with lower CONUT scores (Figures 3(c) and 3(d)). In the treatment group, the 1-, 3-, 5-, and 10-year DFS and OS rates were raised in the low CONUT group in contrast to those with higher CONUT scores. However, there were no significant difference between the two groups (p > 0:05) (Figures 3(e) and 3(f)).

Calibration Curve and Decision Curve Analysis for
Predicting Clinical Utility. The calibration curve was performed to predict the performance for DFS and OS after curative resection. In this study, the calibration curve shown good agreement between predicted and the actual probability at different survival time points, including 1-, 3-, and 5year DFS and OS ( Figure 4). Moreover, we also used the decision curve analysis (DCA) to test predictive clinical utility, and the result shows that compared to only CONUT, the constructed nomogram model (the nomogram incorporating the potential independent prognostic factors of OS and DFS by the multivariate analysis) yielded the best net benefit across in the range of threshold probability for 3-, 5-year DFS and OS. Furthermore, the nomogram predictive clinical utility for clinical decision-making was better than only CONUT ( Figure 5).

Discussion
BC cancer prognosis appears to be closely related to the degree of systemic inflammation and nutritional status [29,30]. Although the use of CONUT was previously confined to assessing nutritional status only, more and more evidence has highlighted its ability to predict cancer patient survival [31][32][33]. The various components of the CONUT score-TLC, ALB, and TC, reflect impaired immune defenses, protein reserves, and caloric depletion, respectively.
Ignacio de Ulíbarri et al. were the first to characterize the CONUT score in 2005 as a means of assessing patients' nutritional and immune status [20]. The CONUT score has been useful in several chronic diseases, including endstage liver disease, congestive heart failure, and cancer [34][35][36]. A study by Shiihara et al. demonstrates that the CONUT score may be used to predict the risk of postoperative complications in pancreatic cancer patients planned for surgery, with a higher CONIT score correlating to increased risks of postoperative complications and shorter OS as well as relapse-free survival [37]. A study by Hirahara et al. linked the pTNM stage and CONUT score together as complementary parameters that predicted esophageal cancer patient survival [38]. Another investigation also indicated  18 BioMed Research International that the CONUT score provided invaluable prognostic information regarding stage II-III gastric cancer patients planned for curative resection and adjuvant chemotherapy and may be useful in guiding the selection of adequate preoperative nutritional interventions [39]. What is more, there are some studies predicting the similar results between CONUT score and breast cancer. A study by Huang et al. pointed out that patients in the high-CONUT score group had shorter OS and recurrence-free survival (RFS) in comparison with those in the low-CONUT score group in surgically treated breast cancer patients [40]. But they only focused on preoperative health status and failed to renew data during the whole process. Another study by Li et al. told us that breast cancer patients with high CONUT predicted the shorter DFS and OS [41]. However, the study only focused on breast cancer patients who did not receive chemotherapy before the surgery.
Our study demonstrated that a higher CONUT score was strongly linked to several clinical characteristics (weight and tumor size) and blood parameters (TC, CA153, white blood cell, hemoglobin, lymphocyte, monocyte, eosinophils, basophils, platelet, MLR, PLR, SIRI, SII, and PNI) of all enrolled patients. We also analyzed the relationship between the CONUT score and other pathological variables and found that the molecular subtype, Ki-67 status, ER status, PR status, and TOP2A status were remarkably worse in those with elevated CONUT scores.
Univariate and multivariate Cox proportional hazards regression model analyses both concurred that the CONUT score functioned as an independent prognosticator of OS and DFS. Individuals possessing lower CONUT scores demonstrated longer mean DFS and OS in contrast to those with higher scores. Moreover, we also successfully constructed a nomogram as a visual tool that is useful in predicting BC 19 BioMed Research International patient prognosis according to the multivariate Cox proportional hazard regression analysis on DFS and OS. Moreover, the calibration curve shown a good agreement between predicted and the actual probability at different survival time points, including 1-, 3-, and 5-year DFS and OS rates. Furthermore, the DCA was used to quantify the net benefits at different threshold probabilities, and nomograms predictive clinical utility for clinical decision-making was better than only CONUT. These results lay the foundation for the use of novel immune-nutrition evaluation tools in guiding postoperative BC patient management.
The biological mechanism of CONUT as a prognostic indicator of BC has not been clearly explained. We seek to provide a brief explanation of the relevance of each component of this score. Cholesterol is metabolized by the liver and represents a key cell membrane molecule that actively takes

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BioMed Research International part in cellular metabolism [42,43]. Gao et al. found that low circulating cholesterol concentration was associated with enhanced cancer morbidity and mortality and appeared to be a good prognostic marker in diffuse large B-cell lymphoma (DLBCL) [44]. Other investigations suggest that lower cholesterol levels may alter immune cell membranes, thus limiting their immune function and ultimately translating to poorer cancer patient prognosis [45]. Serum albumin level is widely used as a marker of nutritional and immunological status, with lower levels reflecting poorer nutrition and immune states [46,47]. One study by Fujii et al. links low serum albumin levels to poorer BC prognosis [48]. Total lymphocyte CONUT, on the other hand, is a critical mediator of cell-mediated immunity. Lymphocytes, which can be divided into T lymphocytes (T-cells), B lymphocytes (Bcells), and natural killer (NK) cells, and played an essential role in mediating response to the proliferation, invasion, and metastasis of cancer cells [49]. A low total lymphocyte CONUT reflects suboptimal immune status and is an independent factor of poor cancer patient prognosis [50]. All CONUT score components relate to an individual's nutritional status and immune capacity, with each parameter exerting important influence over tumor initiation, occurrence, and progression. Several limitations in this study require consideration upon the interpretation of study results. Firstly, this analysis is a retrospective study and has a relatively small sample size. Thus, further studies with prospective and multicenter studies are needed. Secondly, selection bias cannot be underestimated, and further prospective study with a larger sample size is imperative to validate this study's results. Thirdly, it is important to consider that the cut-off CONUT score value determined from this study was based on our patient cohort and may not be applicable in other cohorts.
The CONUT represents a novel independent prognostic factor in BC patients that may aid in predicting survival rates. The CONUT score is an easily replicable, convenient, and accessible parameter that can be used in daily practice.

Data Availability
The data used to support the findings of this study are available from the corresponding author upon request.

Ethical Approval
The studies involving human participants were reviewed and approved by National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College (reference NCC2018-034). The patients/participants provided their written informed consent to participate in this study.