Prognostic Value of Preoperative Controlling Nutritional Status in Hypopharyngeal Cancer Patients Undergoing Surgery-Oriented Comprehensive Treatment

Abstract

Objectives

The preoperative controlling nutritional status (pCONUT) score has been shown correlated with the prognosis of some cancerous diseases; however, little is known about the effect of pCONUT score on hypopharyngeal cancer (HPC). Therefore, the objective of our study was to demonstrate the relationship between the pCONUT score and the clinical outcome of patients with HPC.

Patients and Methods

Ninety-four patients with HPC who underwent surgery between May 2012 and Dec 2020 were enrolled in this study. We evaluated retrospectively their pCONUT scores and calculated the cutoff value regarding the patients’ overall survival using the X-tile software. Kaplan–Meier and Cox proportional hazard regression model were used to determine how the pCONUT score affected overall survival.

Results

A cutoff level of 4 was determined to be optimal for the pCONUT score, by which the patients were grouped into high pCONUT score (≥4, n = 22, 23.4%) or low pCONUT score (<4, n = 72, 76.6%) groups. The univariate analysis showed that high pCONUT scores correlated with reduced overall survival (hazard ratio: 2.925, 95% confidence interval: 1.526-5.607, P = .001). Furthermore, the multivariate analysis also showed that high pCONUT scores increased the risk of overall death (hazard ratio: 2.639, 95% confidence interval: 1.365-5.101, P = .004).

Conclusions

The pCONUT score is considered a useful prognostic factor in patients with HPC.

Keywords

hypopharyngeal cancer controlling nutritional status surgery prognosis

Introduction

Hypopharyngeal cancer (HPC) is considered to be one of the most aggressive head and neck cancers. In spite of significant improvements in comprehensive HPC treatment, the 5-year overall survival (OS) rate remains poor, at approximately 40%.¹

HPC patients suffer from anorexia, dysphagia, odynophagia, and mechanical obstruction. They are often malnourished at diagnosis.² They may also exhibit underlying chronic malnutrition as a result of tobacco and alcohol abuse and poor dietary habits at presentation.³ Malnutrition has been observed in approximately 30%–50% of patients with head and neck squamous cell carcinoma.^4,5 Nutritional deficiencies impair the immune system,⁶ reduce vitality, and reduce disease resistance, as well as the ability to heal wounds.⁴ Malnutrition thus plays an important role in the occurrence of postoperative complications and worse oncology outcomes. Once postoperative complication occurs, malnutrition is further exacerbated by decreased oral food intake. In addition, postoperative complications can postpone postoperative radiotherapy or chemotherapy, increase hospitalization times, and impair quality of life.⁷ Therefore, it is essential to consider the nutritional status of the patients for their appropriate postoperative management.

Depending on the controlling nutritional status CONUT score, one can determine the patient’s overall health, including their nutritional condition.⁸ CONUT scores are calculated using serum albumin (Alb), total cholesterol, and lymphocyte count. Compared with standard nutritional assessments, the CONUT score offers a cost-effective and reliable approach to assessing the nutritional status of patients.^8,9 Numerous studies have demonstrated an association between preoperative CONUT (pCONUT) scores and prognosis of various cancers, such as colorectal cancer, glioblastoma, epithelial ovarian cancer, and gastric cancer.^10-13 Additionally, it may be possible to predict severe adverse events in patients with head and neck cancer treated by radiotherapy using the pCONUT score.¹⁴

As of yet, no research has examined the pCONUT score’s prognostic value in patients with HPC, nor the predictive value of pCONUT on postoperative complications. Hence, the purpose of this study is to demonstrate the prognostic and predictive value of pCONUT score on OS and postoperative complications of patients with HPC who underwent surgical-oriented comprehensive treatment.

Patients and Methods

Patients

According to the inclusion and exclusion criteria, eligible patients with HPC were selected. Here are the criteria for inclusion: patients with HPC who received surgery-oriented treatment, who had a pathological diagnosis of HPC, who had signed informed consent or obtained a waiver of consent, whose hematological parameters were routinely examined within 1 week preoperatively, and whose follow-up information was available. Patients with HPC who did not undergo any surgery, did not have histological diagnosis, had a history of other malignant diseases, and had obvious infections, autoimmune diseases, or chronic liver disease. This retrospective study included a consecutive series of patients with HPC who were surgically treated by the senior author at Beijing Friendship Hospital, Capital Medical University between May 2012 and Dec 2020. American Joint Committee on Cancer’s tumor-node-metastasis (TNM) staging system was used to stage the tumors.¹⁵

The pCONUT score indicates nutritional status, determined by the serum Alb, cholesterol, and lymphocyte counts obtained from the peripheral blood. Overall survival (OS) was defined as the time from surgical resection to death or last follow-up. The last follow-up was conducted in July 2022. The study protocol was approved by the authors’ institutions, Beijing Friendship Hospital, Capital Medical University; as this was a retrospective study and the analysis was anonymized, the requirement for patient consent was waived. All patients or their legal guardians provided written informed consent for undergoing the surgery.

Treatment

In total, 94 patients were included. All patients received surgical treatment, including primary site tumor resection, neck lymph node dissection, and/or defect reconstruction. All patients were scheduled to receive postoperative radiotherapy, preferably commencing within 6 weeks, delivered by intensity-modulated radiotherapy: 5 days a week, 2 Gy/day over 7 weeks, reaching a total dose of 60–70 Gy. Other forms of treatment, including chemotherapy, targeted therapy, immune therapy, or combinations of them, were to be administered according to clinicopathological risk factors such as N stage, extra-nodal extension, and/or perineural and perivascular invasion.

Parameters

The medical records of the patients were carefully reviewed to obtain general patient information and treatment details including patient demographics, medical history, hematological parameters, treatment, complications, and survival. A convenient, inexpensive, and readily available set of nutritional parameters were selected for the pre-therapeutic evaluation. Data collection was conducted before surgery. Body mass index (BMI, kg/m²) was assessed as the nutritional parameter. BMI were considered “low” when they were below 18.5 kg/m². A peripheral blood inflammation-based marker, neutrophil-to-lymphocyte ratio (NLR), was also calculated.¹⁶ Moreover, nutritional screening tools like Onodera’s Prognostic Nutrition Index (O-PNI), and pCONUT score, as well as Nutritional Risk Screening 2002 (NRS 2002), were evaluated. O-PNI is broadly applied for predicting surgical outcomes in oncology for esophageal and gastrointestinal cancer. O-PNI was calculated using the formula: Alb (g/L) + 5 × total lymphocyte count (10⁹/L). O-PNI and NLR were continuous variables. We calculated their cutoff values using “timeROC” package under R environment (http://cran.r-project.org/web/packages/timeROC).¹⁷ The package was used for analyzing time-dependent receiver operating characteristic (tROC), and tROC-based area under the curve (AUC) was plotted to calculate the best cutoff values. The cutoff values were 46.5 for O-PNI and 1.563 for NLR. The pCONUT score was calculated using the serum Alb level, total lymphocyte count, and total cholesterol level (Table 1).¹⁸ The optimal cutoff values of the pCONUT score were selected using X-tile software 3.6.1. Data from the Nutritional Status Survey 2002 is a combination of nutritional status, disease severity, and age.¹⁹ Total scores of NRS 2002 of ≥3 were considered to represent a poor nutritional status.

Table 1.

Definition of pCONUT.

Parameters	pCONUT
Parameters	Normal	Light	Moderate	Severe
Serum albumin (g/dL)	≥3.5	3.0-3.49	2.5-2.99	<2.5
Alb score	0	2	4	6
Total lymphocyte (count/mm³)	≥1600	1200-1599	800-1199	<800
TLC score	0	1	2	3
Total cholesterol (mg/dL)	≥180	140-179	100-139	<100
T-cho score	0	1	2	3
pCONUT score (total)	0	1-4	5-8	9-12
Assessment	Normal	Light	Moderate	Severe

pCONUT is calculated as the sum of the Alb score, TLC score, and T-cho score. Alb, albumin; TLC, total lymphocytes; T-cho, total cholesterol.

Statistical Analysis

The X-tile program is a bioinformatics tool for optimizing cut-point of certain biomarker based on survival outcome. It identifies the cutoff value with minimum P values from log-rank chi-square statistics based on OS. Patients were divided into different groups based on every possible cutoff point. We used X-tile software 3.6.1 to select the optimal cutoff values of the pCONUT score, as described previously.²⁰ A cutoff level of 4 was determined to be optimal for the pCONUT score, by which the patients were grouped into high pCONUT score (≥4, n = 22, 23.4%) or low pCONUT score (<4, n = 72, 76.6%) groups. The cutoff values of O-PNI and NLR were calculated using “timeROC” package under R environment. The cutoff values were 46.5 for O-PNI and 1.563 for NLR.

The possible associations between the pCONUT score and other parameters were evaluated by chi-square test or Fisher exact test. The effects of pCONUT score on OS were examined by Kaplan–Meier method. Cox proportional hazards regression models were used for univariate and multivariate survival analyses of clinical and serum parameters and to calculate the hazard ratio (HR) and 95% confidence interval (CI). Covariates with significant P values (<.05) in univariate analysis were included in the multivariable analysis. Categorized variables were assessed in multivariate models using Cox proportional hazard regression models with a stepwise forward selection method. A two-tailed P-value of <.05 was considered significant. All statistical analyses were performed by SPSS version 26.0.

Results

Patient Characteristics

This retrospective study included 88 men and 6 women with a median age of 60.5 years (range, 41–83 years). The most common subsite of tumors was the pyriform sinus (n = 65, 69.1%), followed by the posterior hypopharyngeal wall (n = 20, 21.3%) and the postcricoid region (n = 9, 9.6%). Approximately three-quarters of the patients (n = 70) had locally advanced disease (T3-4). 87 patients (92.6%) had an advanced overall clinical stage (Ⅲ-Ⅳ) (Table 2). All patients underwent primary surgery, including tumor resection, neck lymph node dissection, and/or defect reconstruction. The laryngeal function was preserved in 48 patients. Owing to disease progression or other social reasons, 6 patients did not undergo any postsurgical adjuvant therapy, whereas the others managed to receive comprehensive adjuvant therapy. The 3-year OS of all 94 patients was 55.62%, whereas the 5-year OS was 51.2% (Figure 1A).

Table 2.

Characteristics of Our Cohort of Patients With Hypopharyngeal Cancer.

Variables	N	%
Age (years)
<60	44	46.8
≥60	50	53.2
Gender
Male	88	93.6
Female	6	6.4
Primary site
Pyriform sinus	65	69.1
Posterior hypopharyngeal wall	20	21.3
Postcricoid area	9	9.6
T stage
1–2	24	25.5
3–4	70	74.5
N stage
0–1	41	43.6
2–3	53	56.4
Clinical stage
I-II	7	7.4
III-IV	87	92.6
BMI
≥18.5	82	87.2
<18.5	12	12.8
O-PNI
≥46.5	54	57.4
<46.5	40	42.6
NLR
≥1.563	78	83.0
<1.563	16	17.0
pCONUT
≥4	22	23.4
<4	72	76.6
NRS 2002
≥3	34	36.2
<3	60	63.8

Figure 1.

Kaplan–Meier survival curves for overall survival among all patients (A) without stratification, or stratified by (B) preoperative controlling nutritional status (pCONUT) cutoff value. The hazard ratios (HR), 95% confidence intervals (CI), and log-rank P values are shown.

The Cutoff Values of the pCONUT, O-PNI, and NLR

X-tile software was applied to identifying the cutoff value of the pCONUT score. A cutoff level of 4 was determined to be optimal for the pCONUT score, by which the patients were grouped into high pCONUT score (≥4, n = 22, 23.4%) or low pCONUT score (<4, n = 72, 76.6%) groups. O-PNI and NLR were continuous variables. We calculated their cutoff values using “timeROC” package under R environment. The package was used for analyzing time-dependent receiver operating characteristic (tROC), and tROC-based area under the curve (AUC) was plotted to calculate the best cutoff values. The cutoff values were 46.5 for O-PNI and 1.563 for NLR.

Relationship Between pCONUT Score and Other Clinical Characteristics

Table 3 shows the correlations between pCONUT scores and other clinical characteristics. The statistical analysis denied any significant difference between CONUT score (<4 vs ≥4) and other parameters, such as age (<60 years vs ≥60 years), sex, N stage (0–1 vs 1–2), clinical stage (I-II vs III-IV), postoperative complication, BMI, NLR, and NRS 2002. The results of the chi-square test indicated that the CONUT score (<4 vs ≥4) was related to the T stage and O-PNI (P < .05).

Table 3.

Relationship Between pCONUT Score and Other Clinical Characteristics.

Variables	pCONUT Score <4 (n = 72)	pCONUT Score ≥4 (n = 22)	p
Age (years)			1.000
<60	34 (47.2)	10 (45.5)
≥60	38 (52.8)	12 (54.5)
Gender			.924
Male	68 (94.4)	20 (90.9)
Female	4 (5.6)	2 (9.1)
T stage			.021
1–2	23 (31.9)	1 (4.5)
3–4	49 (68.1)	21 (95.5)
N stage			.303
0–1	36 (47.2)	7 (31.8)
2–3	38 (52.8)	15 (68.2)
Clinical stage			.194
I-II	8 (9.7)	0 (0)
III-IV	65 (90.3)	22 (100.0)
Postoperative complication	20 (27.8)	9 (40.9)	.366
BMI			.822
≥18.5	62 (86.1)	20 (90.9)
<18.5	10 (13.9)	2 (9.1)
O-PNI			<.001
≥46.5	52 (72.2)	2 (9.1)
<46.5	20 (27.8)	20 (90.9)
NLR			.289
≥1.563	56 (77.8)	20 (90.9)
<1.563	16 (22.2)	2 (9.1)
NRS 2002			.434
≥3	24 (33.3)	10 (45.5)
<3	48 (66.7)	12 (54.5)

Impact of pCONUT Score and Other Clinical Characteristics on OS

The results of univariate analysis of the Cox regression model indicated that a high pCONUT score (P = .001), a high O-PNI score (P = .014), an advanced T-stage (T3-4) (P = .025), and N-stage (N2-3) (P = .001) were associated with poor survival outcome (Table 4). Furthermore, multivariate analysis showed that N stage and pCONUT score were independent predictive factors for patients with HPC. In the Kaplan–Meier plots, the OS curve in the high pCONUT score group was lower than that of the low pCONUT score group, with a statistical significance (P = .0007, Figure 1B).

Table 4.

Univariate and Multivariate Cox Regression Analysis Regarding OS.

Variables	Univariate			Multivariate^a
Variables	HR	95% CI	P-value	HR	95%CI	P-value
Age (years)	1.083	.581-2.020	.801
Gender	.741	.178-3.079	.680
T stage	2.913	1.141-7.440	.025
N stage	3.473	1.686-7.153	.001	3.243	1.565-6.722	.002
Clinical stage	3.979	.546-28.997	.173
BMI <18.5	1.262	.527-3.025	.602
O-PNI <46.5	2.200	1.171-4.133	.014
NLR ≥1.563	1.746	.731-4.168	.210
pCONUT ≥4	2.925	1.526-5.607	.001	2.639	1.365-5.101	.004
NRS 2002 ≥3	1.673	.899-3.115	.104

HR, hazard ratio; CI, confidence interval.

^aVariables entered in the model but excluded after stepwise forward Cox proportional hazards regression analysis include T stage and O-PNI.

Discussion

In this study, we examined the prognostic value of some index of nutritional status, including BMI, O-PNI, NLR, NRS 2002, and the pCONUT score, in 94 patients with HPC. The results showed that for patients with HPC, the pCONUT score was related to OS, whereas the others factors were not related. Furthermore, high T stage, N stage, O-PNI score, and pCONUT scores were associated with poor OS according to our results. The multivariate Cox regression analysis further showed that the pCONUT score together with N stage were independent prognostic factors for OS. It seemed that the pCONUT tended to be superior to the other popular scoring systems such as T stage, O-PNI, and NRS 2002 for the prediction of 5-year OS. Moreover, we found that a high pCONUT score was associated with an advanced T stage and O-PNI. O-PNI is also a nutritional status index calculated from patients’ serum Alb level and total lymphocyte count. The correlation between pCONUT and O-PNI was reasonable to some extent. One possible reason for the relation between pCONUT and T stage may be that the degree of impaired swallowing function mainly depends on the tumor’s primary site and size, which reflects the tumor’s T stage.

The pCONUT score was initially proposed as a comprehensive system for assessing nutrition and immunity of patients and was demonstrated to be related to hospitalization length.²¹ Besides the function of nutrition assessment, pCONUT can serve as a prognostic factor for some chronic diseases.^22,23 The progression of cancer and its prognosis is associated with the nutritional and inflammation statuses of the patient,²⁴ and pCONUT was predictive of patients’ survival in various cancers.^10-12

The X-tile software was applied to calculate the optimal cutoff values of pCONUT derived from the highest chi-square value (minimum P value) analyzed by the Kaplan–Meier method and log-rank test.²⁰ The pCONUT cutoff value of our cohort was calculated as 4, in accordance with several previous studies.^13,25 On the basis, the pCONUT score was found to be related to the OS of the patients with resected HPC independently. Therefore, we should lay emphasis on HPC patients with a high pCONUT score.

The prognosis of patients with malignant tumor is linked with an individual’s nutritional or inflammatory functional status.²⁴ Approximately 80% of patients with head and neck cancer suffer from malnutrition due to their lifestyle and risk factors.²⁶ pCONUT was initially used to appraise the nutritional status of patients,⁸ which was decent and convenient to determine from serum Alb level, total cholesterol level and total lymphocyte count. To our knowledge, the present study is the first to explore the relationship between pCONUT score and OS for patients with HPC who underwent curative resection and to thus assess the prognostic value of the pCONUT score in patients with HPC. Further study should be done to analyze the importance of perioperative nutrition interventions for patients with HPC according to their pCONUT scores, which might be a promising treatment plan to improve their survival and prognosis. This study emphasized again the concept of individualized therapy, for we should evaluate individual status of each patient and provide specific recommendation. Our findings may contribute to the knowledge base, improve treatment designs, and enhance the accuracy of HPC prognoses.

Regarding the 3 components of pCONUT, serum Alb level has twice the weight of other parameters. Serum Alb level reflects the degree of malnutrition and correlates with the prognosis in patients with head and neck squamous cell carcinoma.²⁷ Total cholesterol level is correlated with tumor progression and survival in patients with various malignancies.²⁸ There was a negative correlation between high-density lipoprotein or low-density lipoprotein cholesterol and increased risk of cancers, including nasopharyngeal cancer,^29,30 but some studies have different results.³¹ Total lymphocyte count is an indicator of immunological status.^32,33 Low peripheral lymphocyte count leads to insufficient host immune response to cancer cells and intolerance to chemotherapy. Above all, the 3 parameters reflect an individual’s nutrition from many aspects, and thus accurately assess the general conditions of patients.

We acknowledge that there were some limitations and shortcomings in this study. First, it was a retrospective study from just one institution, and the cohort was ethnically homogeneous. Second, for patients suffered from relapsed disease and underwent salvage therapies, the prognostic effect of pCONUT score still lacks evidence. Third, intravenous and enteral nutritional support was routinely administered after surgery in our cohort, so we did not concentrate on the postoperative pCONUT score and determine its significance. Numerous measurements and evaluation of pCONUT before, during, and after the planned therapy may be used to identify a dynamic nutritional status for the patient. Next, the absence of chemokine or cytokine measurements hindered us from elucidating the mechanistic link between the data and the underlying basic molecular interactions.

Conclusion

In conclusion, the present study shows that the pCONUT score has potential application as a predictor of prognosis in patients with HPC. Thus, perioperative nutrition interventions are recommended to patients with HPC according to their pCONUT scores, which might be a promising treatment plan to improve their survival and prognosis.

Footnotes

Authors’ contributions

TD, YD and LL conceived and designed the research. WL, YL and LL performed the surgeries. TD, WL and YL retrieved patients’ data. TD and YD prepared figures and tables. WL, YD and LL drafted, edited and revised manuscript. All authors read and approved the manuscript and agree to be accountable for all aspects of the research in ensuring that the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Beijing Friendship Hospital Seed Project, Capital Medical University [grant number YYZZ202125], Key Science and Technology Program of Beijing Municipal Commission of Education [grant number KZ202110025035], Research and Development Project of Scientific Research Instruments and Equipment of Chinese Academy of Sciences-major instruments project [grant number YJKYYQ20180039] and Digestive Medical Coordinated Development Center of Beijing Municipal Administration of Hospitals [grant number XXZ0604].

Ethical approval

Ethics approval for the study was given by ethics committee of Beijing Friendship Hospital, Capital Medical University. Consent to participate was acquired.

Informed consent

Patient consent for publication was acquired.

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

ORCID iDs

Wanxin Li

Liangfa Liu

Yanbo Dong

References

Newman

Connolly

Illing

Kilgore

Locher

Carroll

. Survival trends in hypopharyngeal cancer: a population-based review. Laryngoscope. 2015;125(3):624-629.

Ravasco

Monteiro-Grillo

Vidal

Camilo

. Nutritional deterioration in cancer: the role of disease and diet. Clinical oncology (Royal College of Radiologists (Great Britain)). 2003;15(8):443-450.

Righini

Timi

Junet

Bertolo

Reyt

Atallah

. Assessment of nutritional status at the time of diagnosis in patients treated for head and neck cancer. European annals of otorhinolaryngology, head and neck diseases. 2013;130(1):8-14.

Magnano

Mola

Machetta

, et al. The nutritional assessment of head and neck cancer patients. Eur Arch Oto-Rhino-Laryngol : Official Journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : Affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery. 2015;272(12):3793-3799.

Mekhail

Adelstein

Rybicki

Larto

Saxton

Lavertu

. Enteral nutrition during the treatment of head and neck carcinoma: is a percutaneous endoscopic gastrostomy tube preferable to a nasogastric tube? Cancer. 2001;91(9):1785-1790.

Chandra

. Nutrition and the immune system: an introduction. The American journal of clinical nutrition. 1997;66(2):460s-463s.

Dong

Bradley

Liu

. Survival and swallowing function outcome impact factors analysis of surgery-oriented comprehensive treatment for hypopharyngeal cancer in a series of 122 patients. Ear Nose Throat J. 2021;101:532-541.

Ignacio de Ulíbarri

González-Madroño

de Villar

, et al. CONUT: a tool for controlling nutritional status. First validation in a hospital population. Nutr Hosp. 2005;20(1):38-45.

González-Madroño

Mancha

Rodríguez

Culebras

de Ulibarri

. Confirming the validity of the CONUT system for early detection and monitoring of clinical undernutrition: comparison with two logistic regression models developed using SGA as the gold standard. Nutr Hosp. 2012;27(2):564-571.

10.

Takagi

Domagala

Polak

Buettner

Wijnhoven

BPL

Ijzermans

JNM

. Prognostic significance of the controlling nutritional status (CONUT) score in patients undergoing gastrectomy for gastric cancer: a systematic review and meta-analysis. BMC Surg. 2019;19(1):129.

11.

Ahiko

Shida

Horie

, et al. Controlling nutritional status (CONUT) score as a preoperative risk assessment index for older patients with colorectal cancer. BMC Cancer. 2019;19(1):946.

12.

Zhang

, et al. Prognostic significance of the controlling nutritional status (CONUT) score in epithelial ovarian cancer. Int J Gynecol Cancer : Official Journal of the International Gynecological Cancer Society. 2020;30(1):74-82.

13.

Chen

Tang

. Prognostic value of preoperative controlling nutritional status in patients with glioblastoma. Clin Neurol Neurosurg. 2020;198:106129.

14.

Kono

Sakamoto

Shinden

Ogawa

. Pre-therapeutic nutritional assessment for predicting severe adverse events in patients with head and neck cancer treated by radiotherapy. Clinical nutrition (Edinburgh, Scotland). 2017;36(6):1681-1685.

15.

Edge

Compton

. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 2010;17(6):1471-1474.

16.

Asano

Kashiwagi

Onoda

, et al. Predictive Value of Neutrophil/Lymphocyte Ratio for Efficacy of Preoperative Chemotherapy in Triple-Negative Breast Cancer. Ann Surg Oncol. 2016;23(4):1104-1110.

17.

Blanche

Dartigues

Jacqmin-Gadda

. Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks. Stat Med. 2013;32(30):5381-5397.

18.

de Ulíbarri Pérez

Fernández

Rodríguez Salvanés

Díaz López

. Nutritional screening; control of clinical undernutrition with analytical parameters. Nutr Hosp. 2014;29(4):797-811.

19.

Kondrup

Rasmussen

Hamberg

Stanga

. Nutritional risk screening (NRS 2002): a new method based on an analysis of controlled clinical trials. Clinical nutrition (Edinburgh, Scotland). 2003;22(3):321-336.

20.

Camp

Dolled-Filhart

Rimm

X-tile . a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization. Clin Cancer Res : An Official Journal of the American Association for Cancer Research. 2004;10(21):7252-7259.

21.

Cabré

Ferreiro

Arus

Roca

Palomera

Serra-Prat

. Evaluation of CONUT for Clinical Malnutrition Detection and Short-Term Prognostic Assessment in Hospitalized Elderly People. J Nutr Health Aging. 2015;19(7):729-733.

22.

Fukushima

Ueno

Kawagishi

, et al. The nutritional index 'CONUT' is useful for predicting long-term prognosis of patients with end-stage liver diseases. Tohoku J Exp Med. 2011;224(3):215-219.

23.

Nakagomi

Kohashi

Morisawa

, et al. Nutritional Status is Associated with Inflammation and Predicts a Poor Outcome in Patients with Chronic Heart Failure. J Atherosclerosis Thromb. 2016;23(6):713-727.

24.

Elinav

Nowarski

Thaiss

Jin

Flavell

. Inflammation-induced cancer: crosstalk between tumours, immune cells and microorganisms. Nat Rev Cancer. 2013;13(11):759-771.

25.

Kuroda

Sawayama

Kurashige

, et al. Controlling Nutritional Status (CONUT) score is a prognostic marker for gastric cancer patients after curative resection. Gastric Cancer : Official Journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association. 2018;21(2):204-212.

26.

Müller-Richter

Betz

Hartmann

Brands

. Nutrition management for head and neck cancer patients improves clinical outcome and survival. Nutr Res (NY). 2017;48:1-8.

27.

Lim

Roh

Kim

Choi

Nam

Kim

. Pretreatment albumin level predicts survival in head and neck squamous cell carcinoma. Laryngoscope. 2017;127(12):E437-e442.

28.

Okuyama

Ichikawa

Sun

Hamazaki

Lands

. Cancer and all-cause mortalities are lower in the higher total cholesterol groups among general populations. World Rev Nutr Diet. 2007;96:37-54.

29.

Liu

Lin

Chen

, et al. High-density lipoprotein cholesterol as a predictor of poor survival in patients with nasopharyngeal carcinoma. Oncotarget. 2016;7(28):42978-42987.

30.

Tang

Piao

Hua

. Correlation between pretreatment serum LDL-cholesterol levels and prognosis in nasopharyngeal carcinoma patients. OncoTargets Ther. 2016;9:2585-2591.

31.

Wilms

Boldrup

Coates

Sgaramella

Nylander

. High Levels of Low-Density Lipoproteins Correlate with Improved Survival in Patients with Squamous Cell Carcinoma of the Head and Neck. Biomedicines. 2021;9(5).

32.

Liang

Zhu

Jia

, et al. Predictive value of pretreatment lymphocyte count in stage II colorectal cancer and in high-risk patients treated with adjuvant chemotherapy. Oncotarget. 2016;7(1):1014-1028.

33.

Schueneman

Sugar

Uram

, et al. Low total lymphocyte count is associated with poor survival in patients with resected pancreatic adenocarcinoma receiving a GM-CSF secreting pancreatic tumor vaccine. Ann Surg Oncol. 2013;20(suppl 30 3):S725-S730.