Editorial Open Access
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Dec 15, 2024; 16(12): 4537-4542
Published online Dec 15, 2024. doi: 10.4251/wjgo.v16.i12.4537
Is nutritional status a new indicator to use in clinical practice for colorectal cancer patients?
Rossana Berardi, Rebecca Chiariotti, Giulia Mentrasti, Department of Medical Oncology, Università Politecnica delle Marche, Azienda Ospedaliero-Universitaria delle Marche, Ancona 60126, Marche, Italy
ORCID number: Rossana Berardi (0000-0002-9529-2960); Rebecca Chiariotti (0009-0009-1465-7154).
Co-first authors: Rossana Berardi and Rebecca Chiariotti.
Author contributions: Berardi R, Chiariotti R, and Mentrasti G contributed to conception, design and manuscript writing.
Conflict-of-interest statement: Professor Rossana Berardi: Astra Zeneca, Advisory Board, Personal; Bayer, Advisory Board, Personal; Boehringer Ingelheim, Advisory Board, Personal; EISAI, Advisory Board, Personal; Incyte, Advisory Board, Personal; Lilly, Advisory Board, Personal; Menarini, Advisory Board, Personal; Merck, Advisory Board, Personal; MSD, Advisory Board, Personal; Gilead, Invited Speaker, Personal; Astra Zeneca, Funding, Institutional; Pfizer, Funding, Institutional; Roche, Funding, Institutional. The other authors indicated no financial relationships.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Rossana Berardi, MD, PhD, Professor, Department of Medical Oncology, Università Politecnica delle Marche, Azienda Ospedaliero-Universitaria delle Marche, Via Conca 71, Ancona 60126, Marche, Italy. r.berardi@univpm.it
Received: April 30, 2024
Revised: June 20, 2024
Accepted: July 15, 2024
Published online: December 15, 2024
Processing time: 195 Days and 20.4 Hours

Abstract

In this editorial we comment on the interesting article by Liu et al. The topic of discussion is the need for a cost-effective and easy-to-use scoring system for predicting the prognosis of colorectal cancer patients. In this context, nutritional assessment plays a crucial role in the multimodal evaluation of patients. In particular, the controlling nutritional status score was found to be an effective tool in the clinical decision-making process, in order to customize treatment strategies and to improve patient outcomes.

Key Words: Controlling nutritional status score; Colorectal cancer; Nutritional status; Clinical outcome; Nutritional biomarkers; Tailored-medicine; Personalized therapies

Core Tip: The controlling nutritional status (CONUT) score is significantly associated with the prognosis of colorectal cancer patients, as supported by a large body of literature. Compared with other nutritional scores, the CONUT score may be introduced in clinical practice as an optimal prognostic nutritional index to predict patient outcome.



INTRODUCTION

Colorectal cancer (CRC) represents a significant global health and financial burden, and is currently ranked the third most common cancer in the world and the second leading cause of cancer-related death[1] in both sexes. Over a million new cases of CRC have been diagnosed globally every year in the past decade[2].

Cancer patients usually experience malnutrition and weight loss, especially those with gastrointestinal tumors. Previous studies have shown that malnutrition and cachexia are responsible for 20% of cancer-related deaths, rather than cancer itself[3].

Malnutrition is linked to an increased risk of postoperative complications and to prolonged hospitalization, with a considerable burden in terms of health care costs[4]. Besides, a compromised nutritional status reduces patient's tolerance to radiation and chemotherapy, resulting in a poor response to treatment and worse prognosis[5]. Thus, nutritional assessment of CRC patients should become a part of routine clinical practice to determine its impact on treatment efficacy and survival[6,7].

Patients with good nutritional status at diagnosis and during treatments are expected to have a better quality of life and longer survival[8], but it has also been postulated that nutritional status may impact the activity of immune cells against cancer in patients receiving treatments with chemotherapy, targeted therapy or immune checkpoint inhibitors (ICIs)[4]. The matter of discussion is how systemic inflammation and body composition (BC) influence prognosis, and the identification of nutritional and immunological signatures able to predict clinical outcome and response to therapies, with the aim of better stratification of patients and personalized treatments.

Systemic inflammation status

Tumor growth has been essentially linked to cancer-associated systemic inflammatory response. A consistent body of literature has identified several circulating inflammatory indicators as potentially helpful for prognosis prediction. Serum markers associated with inflammation can be divided into two categories: Upregulated in disease progression (neutrophils, platelets, monocytes, and C-reactive protein), and downregulated in disease progression (lymphocytes and albumin). Their combination can be used as inflammation-related markers.

In this regard, Yamamoto et al[9] reviewed the prognostic impact of inflammation-related markers in CRC and their use in clinical practice.

They divided the markers into five groups: Neutrophil-related markers, albumin-related markers, monocyte-related markers, C-reactive protein-related markers[10] and platelet-related markers. The most relevant in CRC are reported in the Table 1.

Table 1 Most frequently reported inflammation-related biomarkers for the prediction of prognosis in colorectal cancer patients as shown in previous reports[9].
Inflammation-related biomarkers

Neutrophil-related markersNLR: Low NLR was related to better CSS and DFS, with different cut-off values depending on the study: The smallest was 2, while the largest was 5
Albumin-related markersGPS that includes serum CRP levels and serum albumin levels: High GPS indicated systemic inflammation (elevated CRP) and low nutritional state (hypoalbuminemia), that was associated with lower CSS and DFS
Monocyte-related markersMonocyte count: Elevated monocyte count was significantly associated with poor OS and DFS, with variable cut off values depending on the study. LMR: Low LMR was independently associated with worse OS and DFS. The cutoff value depended on the study
C-reactive protein-related markersCAR: Elevated CAR was significantly associated with worse OS and RFS in patients who underwent curative resection. The cutoff value varied between 0.025 and 0.22 according to the study. LCR: Low LCR (cut off between 12980 and 6000 depending on the study) was most significantly and independently correlated with worse OS and DFS. CLR: Was reported as an independent and significant indicator of poor long-term outcomes in patients with CRCm after hepatic resection, with a cutoff level of 62.8 × 10-6[10]
Platelet-related markersPLR: High PLT reflects both an increase in PLT count and a decrease in lymphocyte count and was negatively related to OS in previous reports on colorectal cancer. The cutoff value varied among studies from 150 to 246.36
Nutritional status and body composition

In the issue of the World Journal of Gastrointestinal Oncology Liu et al[6], published a valuable paper. This case control study highlights the role of preoperative nutritional status as an independent prognostic factor to predict the outcome of CRC patients who underwent potentially curative resection. In particular, the study addresses the role of the Controlling Nutritional Status (CONUT) score, an immune-nutritional screening tool based on serum albumin, total cholesterol, and lymphocyte count, in predicting CRC patients’ prognosis[11]. According to the study, a pre-operative CONUT score ≥ 5, characterizing patients with moderate or severe malnutrition, was independently associated with poorer overall survival (OS) and relapse-free survival (RFS) compared to those with a CONUT score ≤ 4, who showed significantly longer RFS and OS (Table 2).

Table 2 Definition of controlling nutritional status score.
Variable
Normal
Light
Moderate
Severe
Albumin (g/dL)3.5-4.53.0-3.492.5-2.9< 2.5
Albumin score0246
Total lymphocyte count (mm3)≥ 16001200-1599800-1199< 800
Total lymphocyte count score0123
Total cholesterol (mg/dL)< 180140-180100-139< 100
Total cholesterol score0123
CONUT score0-12-45-89-12
AssessmentNormalLightModerateSevere

Recent studies have confirmed that the CONUT score is an easy-to-use parameter to prognosticate cancer response during treatment[12-14]. A review published by Chen et al[7] including 62 studies involving a total of 25224 patients showed the value of the CONUT score, assessed before surgical or medical treatment. A high CONUT was correlated with shorter OS, cancer-specific survival, progression and recurrence-free survival, disease-free survival and a higher incidence of postoperative complications and mortality.

WHAT IS INNOVATIVE ABOUT CONUT COMPARED TO OTHER SCORES?

The CONUT score is a cost-effective immuno-metabolic tool evaluated from three peripheral blood parameters routinely assessed in clinical practice. Compared to the abovementioned biomarkers, derived from a maximum of two serum markers, the CONUT score provides a more comprehensive representation of both the nutritional and immunological status of patients[14].

Albumin, the main component of serum proteins, is highly correlated with body cell mass and inflammation. The presence of an ongoing inflammatory response contributes to sarcopenia, with repercussions on patients’ prognosis[15]. The albumin level reflects nutritional and metabolic status in cancer patients.

Lymphopenia is independently associated with poorer survival outcomes in cancer patients, as the lymphocyte count suggests the grade of immunological and systemic inflammatory response in these patients[16,17].

The neutrophil-to-lymphocyte ratio (NLR) describes tumor inflammation. According to many studies, a high NLR is linked to poor survival in different solid tumors, including colon cancer[18,19].

Lymphocytes and the NLR play a crucial role in cancer immune evasion and surveillance, in addition to the tumor microenvironment, and this seems to be related to response to immunotherapy[20].

With regard to the CONUT score, high serum cholesterol levels have been shown to enhance the anticancer activity of natural killer cells in mice[21], and in solid cancers treated with ICIs, high cholesterol has been demonstrated to correlate with better clinical outcomes[22].

Another element worth mentioning is the relationship between the CONUT score and BC.

In the study of Liu et al[6], no significant association was observed between body mass index (BMI) and the CONUT score. BMI is a crude measure, does not adequately discriminate the percentage of fat-free mass and does not rule out sarcopenia in cancer patients.

By contrast, in their study an inverse correlation between the CONUT score and skeletal muscle mass index (SMI) was shown (Liu et al[6], Figure 4C). The incidence of sarcopenia was higher in the high CONUT group. Moreover, comparing the time-dependent curves of CONUT + tumor-node-metastasis (TNM) stage and SMI + TNM stage, they showed concordance in both 3-year OS (Liu et al[6], Figure 4A) and 3-year RFS (Liu et al[6], Figure 4B), suggesting that the CONUT score is as reliable as SMI in predicting the postoperative prognosis of CRC. This association likely relies on both the CONUT score and SMI reflecting the body protein reserves.

KEY POINTS

The SMI was obtained by dividing the skeletal muscle area (SMA) (cm2) by the square of height (m). The SMA was evaluated in a cross-section of the third lumbar vertebrae on CT, by measuring the areas of psoas major, paraspinal muscles, transverse abdominis, external oblique, internal oblique, and rectus abdominis muscles. Sarcopenia was defined as SMI < 40.8 (cm2/m2) in men and SMI < 34.9 (cm2/m2) in women.

Sarcopenia is a multifactorial condition that is frequently seen in cancer patients. It is characterized by a degenerative and systemic loss of skeletal muscle mass (SMM) and function[23].

Previous studies have demonstrated that a decreased SMM in cancer patients, as well as proven sarcopenia/cachexia, have negative effects on response to treatments, both in surgical and oncological treatments[24,25].

In addition, a SMM assessed by CT seems to be associated with increased chemotherapy and radiotherapy toxicity[26].

Several studies in advanced tumors treated with ICIs have confirmed the key prognostic role of SMM and the importance of patients’ assessment, at baseline and during treatment, to actively assess the efficacy and tolerance of immunotherapy[27].

One of the potential limitations of the paper written by Liu et al[6] is that the authors focused on the CONUT score, neglecting other nutritional markers, such as the NLR, Glasgow prognostic score (GPS/modified GPS, (mGPS)) and prognostic nutritional index, which have been largely validated in previous studies[9]. However, their choice to focus on the CONUT score could be justified considering that it represents a more comprehensive prognostic indicator, as it combines nutritional parameters (albumin, and cholesterol) with immunologic status (including lymphocyte count), whose interplay validated by a body of literature, is significant in prognosis[7].

Nutritional assessment has an essential role in gastrointestinal tumors, particularly in CRC, that has generally a low survival rate due to its high prevalence, delayed diagnosis and elevated rate of local recurrence or metastasis, despite continuous therapeutic progress.

A multidisciplinary team-based approach has improved clinical outcomes, but substantial disparities between patients are still often observed in terms of disease presentation, response to treatments and prognosis. Therefore, it is necessary to identify new biological indicators to improve the accuracy of prognostic prediction and patient outcome[25,28].

In this context, nutritional evaluation could have a key role, representing a cost-effective and modifiable chance of therapeutic intervention for clinicians. In fact, various effective nutritional assessment tools have already been described, especially in the pre-operative setting, but there is no gold standard and they have not been routinely implemented in clinical practice[29,30].

Shan et al[25] suggested a prognostic model based on multiple parameters such as psoas muscle index in stage II-III CRC patients, highlighting how the presence of sarcopenia before adjuvant chemotherapy affects RFS and OS[25].

A recent study by Wang et al[31] including 5014 CRC patients indicated white blood cells, neutrophils, monocytes, eosinophils, alkaline phosphatase, and lactate dehydrogenase levels as additional indicators to be included in the CONUT scoring system, to provide a more accurate assessment of the clinical prognosis for patients with CRC.

Considering the concordance between the CONUT score and SMI, both resonating with TNM staging in CRC patients undergoing surgery, the two indicators could be combined in an innovative prognostic index to better stratify patients before and during treatments. In this regard, in the pre- and post-operative setting it could help in selecting patients with an increased risk of relapse, who would benefit from a more intensive adjuvant and neo-adjuvant treatment, from those who do not require oncological therapy after curative resection. The role of the CONUT score together with TNM stage in predicting the risk of relapse in the study by Liu et al[6], suggests that the data recently observed on circulating tumor DNA in the adjuvant setting of CRC could be replicated with nutritional and metabolic tools in the future[32].

Therefore, in the era of immuno-oncology a new body of research is attempting to clarify the mechanism of resistance to immunotherapy in proficient mismatch repair CRC patients to enhance sensitivity to ICIs[8]. Ongoing clinical trials are focusing on this matter especially in the peri-operative setting[32]. Given its immune-metabolic dimension and the relationship to immunotherapy outcome[33], the CONUT score could also be considered in this setting as a stratification factor to evaluate patients.

CONCLUSION

The role of the CONUT score, as an independent prognostic factor in patients undergoing surgery for CRC and in advanced disease, is well established. Based on the abovementioned evidence and the valuable findings of Liu et al[6], use of the CONUT score should also be encouraged and considered in clinical practice due to its affordability[34]. Further studies are needed to validate the relevance of this promising score in the clinical decision-making process, and to suggest when early nutritional interventions are indicated; thus, implementing personalized oncology from a supportive care perspective[8].

Footnotes

Provenance and peer review: Invited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Oncology

Country of origin: Italy

Peer-review report’s classification

Scientific Quality: Grade C

Novelty: Grade B

Creativity or Innovation: Grade B

Scientific Significance: Grade B

P-Reviewer: Yan B S-Editor: Li L L-Editor: Webster JR P-Editor: Zhao YQ

References
1.  Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74:229-263.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 72]  [Cited by in F6Publishing: 1262]  [Article Influence: 1262.0]  [Reference Citation Analysis (0)]
2.  Siegel RL, Miller KD, Goding Sauer A, Fedewa SA, Butterly LF, Anderson JC, Cercek A, Smith RA, Jemal A. Colorectal cancer statistics, 2020. CA Cancer J Clin. 2020;70:145-164.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2268]  [Cited by in F6Publishing: 3001]  [Article Influence: 750.3]  [Reference Citation Analysis (2)]
3.  Wu BW, Yin T, Cao WX, Gu ZD, Wang XJ, Yan M, Liu BY. Clinical application of subjective global assessment in Chinese patients with gastrointestinal cancer. World J Gastroenterol. 2009;15:3542-3549.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 37]  [Cited by in F6Publishing: 40]  [Article Influence: 2.7]  [Reference Citation Analysis (0)]
4.  Vidhya K, Gupta S, R L, Rs N, Velumani Y, Raina D, Kumari K, Gupta A. Assessment of Nutritional Status and Correlation of Factors With Body Mass Index of Cancer Patients: A Cross-Sectional Study. Cureus. 2024;16:e54146.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
5.  Hill A, Kiss N, Hodgson B, Crowe TC, Walsh AD. Associations between nutritional status, weight loss, radiotherapy treatment toxicity and treatment outcomes in gastrointestinal cancer patients. Clin Nutr. 2011;30:92-98.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 65]  [Cited by in F6Publishing: 73]  [Article Influence: 5.6]  [Reference Citation Analysis (0)]
6.  Liu LX, Wang H, Gao B, Xu TT, Yuan QG, Zhou SZ, Ding C, Miao J, Guan WX. Preoperative controlling nutritional status as an optimal prognostic nutritional index to predict the outcome for colorectal cancer. World J Gastrointest Oncol. 2024;16:343-353.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (1)]
7.  Chen J, Song P, Peng Z, Liu Z, Yang L, Wang L, Zhou J, Dong Q. The Controlling Nutritional Status (CONUT) Score and Prognosis in Malignant Tumors: A Systematic Review and Meta-Analysis. Nutr Cancer. 2022;74:3146-3163.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2]  [Cited by in F6Publishing: 8]  [Article Influence: 4.0]  [Reference Citation Analysis (0)]
8.  Ziętarska M, Krawczyk-Lipiec J, Kraj L, Zaucha R, Małgorzewicz S. Nutritional status assessment in colorectal cancer patients qualified to systemic treatment. Contemp Oncol (Pozn). 2017;21:157-161.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 10]  [Article Influence: 1.4]  [Reference Citation Analysis (0)]
9.  Yamamoto T, Kawada K, Obama K. Inflammation-Related Biomarkers for the Prediction of Prognosis in Colorectal Cancer Patients. Int J Mol Sci. 2021;22.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 28]  [Cited by in F6Publishing: 177]  [Article Influence: 59.0]  [Reference Citation Analysis (0)]
10.  Taniai T, Haruki K, Hamura R, Fujiwara Y, Furukawa K, Gocho T, Shiba H, Yanaga K. The Prognostic Significance of C-reactive Protein-To-Lymphocyte Ratio in Colorectal Liver Metastases. J Surg Res. 2021;258:414-421.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6]  [Cited by in F6Publishing: 14]  [Article Influence: 3.5]  [Reference Citation Analysis (0)]
11.  Zhang Y, Kong FF, Zhu ZQ, Shan HX. Controlling Nutritional Status (CONUT) score is a prognostic marker in III-IV NSCLC patients receiving first-line chemotherapy. BMC Cancer. 2023;23:225.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 5]  [Reference Citation Analysis (0)]
12.  Kuroda D, Sawayama H, Kurashige J, Iwatsuki M, Eto T, Tokunaga R, Kitano Y, Yamamura K, Ouchi M, Nakamura K, Baba Y, Sakamoto Y, Yamashita Y, Yoshida N, Chikamoto A, Baba H. Controlling Nutritional Status (CONUT) score is a prognostic marker for gastric cancer patients after curative resection. Gastric Cancer. 2018;21:204-212.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 152]  [Cited by in F6Publishing: 199]  [Article Influence: 33.2]  [Reference Citation Analysis (0)]
13.  Zhang Y, Zhang X. Controlling nutritional status score, a promising prognostic marker in patients with gastrointestinal cancers after surgery: A systematic review and meta-analysis. Int J Surg. 2018;55:39-45.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 17]  [Cited by in F6Publishing: 12]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]
14.  Niu X, Zhu Z, Bao J. Prognostic significance of pretreatment controlling nutritional status score in urological cancers: a systematic review and meta-analysis. Cancer Cell Int. 2021;21:126.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 7]  [Cited by in F6Publishing: 17]  [Article Influence: 5.7]  [Reference Citation Analysis (0)]
15.  McMillan DC, Watson WS, O'Gorman P, Preston T, Scott HR, McArdle CS. Albumin concentrations are primarily determined by the body cell mass and the systemic inflammatory response in cancer patients with weight loss. Nutr Cancer. 2001;39:210-213.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 272]  [Cited by in F6Publishing: 330]  [Article Influence: 15.0]  [Reference Citation Analysis (1)]
16.  Mehrazin R, Uzzo RG, Kutikov A, Ruth K, Tomaszewski JJ, Dulaimi E, Ginzburg S, Abbosh PH, Ito T, Corcoran AT, Chen DY, Smaldone MC, Al-Saleem T. Lymphopenia is an independent predictor of inferior outcome in papillary renal cell carcinoma. Urol Oncol. 2015;33:388.e19-388.e25.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 24]  [Cited by in F6Publishing: 33]  [Article Influence: 3.3]  [Reference Citation Analysis (0)]
17.  Li S, Yao W, Liu R, Lu Y, Zhang H, Liang X. Severe lymphopenia as a prognostic factor in rectal cancer patients receiving adjuvant chemoradiotherapy: a retrospective study. Sci Rep. 2023;13:7566.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 4]  [Reference Citation Analysis (0)]
18.  Banna GL, Friedlaender A, Tagliamento M, Mollica V, Cortellini A, Rebuzzi SE, Prelaj A, Naqash AR, Auclin E, Garetto L, Mezquita L, Addeo A. Biological Rationale for Peripheral Blood Cell-Derived Inflammatory Indices and Related Prognostic Scores in Patients with Advanced Non-Small-Cell Lung Cancer. Curr Oncol Rep. 2022;24:1851-1862.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Cited by in F6Publishing: 7]  [Article Influence: 3.5]  [Reference Citation Analysis (0)]
19.  Templeton AJ, McNamara MG, Šeruga B, Vera-Badillo FE, Aneja P, Ocaña A, Leibowitz-Amit R, Sonpavde G, Knox JJ, Tran B, Tannock IF, Amir E. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and meta-analysis. J Natl Cancer Inst. 2014;106:dju124.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1645]  [Cited by in F6Publishing: 2055]  [Article Influence: 205.5]  [Reference Citation Analysis (0)]
20.  Alturki NA. Review of the Immune Checkpoint Inhibitors in the Context of Cancer Treatment. J Clin Med. 2023;12.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 24]  [Reference Citation Analysis (0)]
21.  Qin WH, Yang ZS, Li M, Chen Y, Zhao XF, Qin YY, Song JQ, Wang BB, Yuan B, Cui XL, Shen F, He J, Bi YF, Ning G, Fu J, Wang HY. High Serum Levels of Cholesterol Increase Antitumor Functions of Nature Killer Cells and Reduce Growth of Liver Tumors in Mice. Gastroenterology. 2020;158:1713-1727.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 48]  [Cited by in F6Publishing: 101]  [Article Influence: 25.3]  [Reference Citation Analysis (0)]
22.  Pecci F, Cantini L, Cognigni V, Perrone F, Mazzaschi G, Agostinelli V, Mentrasti G, Favari E, Maffezzoli M, Cortellini A, Rossi F, Chiariotti R, Venanzi FM, Lo Russo G, Galli G, Proto C, Ganzinelli M, Tronconi F, Morgese F, Campolucci C, Moretti M, Vignini A, Tiseo M, Minari R, Rocchi MLB, Buti S, Berardi R. Prognostic Impact of Blood Lipid Profile in Patients With Advanced Solid Tumors Treated With Immune Checkpoint Inhibitors: A Multicenter Cohort Study. Oncologist. 2024;29:e372-e381.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
23.  Deer RR, Volpi E. Protein intake and muscle function in older adults. Curr Opin Clin Nutr Metab Care. 2015;18:248-253.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 133]  [Cited by in F6Publishing: 142]  [Article Influence: 15.8]  [Reference Citation Analysis (0)]
24.  Lobo DN, Gianotti L, Adiamah A, Barazzoni R, Deutz NEP, Dhatariya K, Greenhaff PL, Hiesmayr M, Hjort Jakobsen D, Klek S, Krznaric Z, Ljungqvist O, McMillan DC, Rollins KE, Panisic Sekeljic M, Skipworth RJE, Stanga Z, Stockley A, Stockley R, Weimann A. Perioperative nutrition: Recommendations from the ESPEN expert group. Clin Nutr. 2020;39:3211-3227.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 125]  [Cited by in F6Publishing: 116]  [Article Influence: 29.0]  [Reference Citation Analysis (0)]
25.  Shan L, Li T, Gu W, Gao Y, Zuo E, Qiu H, Li R, Cheng X. Application of Prognostic Models Based on Psoas Muscle Index, Stage, Pathological Grade, and Preoperative Carcinoembryonic Antigen Level in Stage II-III Colorectal Cancer Patients Undergoing Adjuvant Chemotherapy. J Oncol. 2022;2022:6851900.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2]  [Cited by in F6Publishing: 2]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
26.  Güner G, Özçakar L, Baytar Y, Onur MR, Demir M, Aktaş BY, Aktepe OH, Güven DC, Taban H, Yıldırım HÇ, Akın S, Aksoy S, Kara M, Dizdar Ö. Sonographic Measurements of Rectus Femoris Muscle Thickness Strongly Predict Neutropenia in Cancer Patients Receiving Chemotherapy. Cancers (Basel). 2024;16.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
27.  Li S, Wang T, Tong G, Li X, You D, Cong M. Prognostic Impact of Sarcopenia on Clinical Outcomes in Malignancies Treated With Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis. Front Oncol. 2021;11:726257.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4]  [Cited by in F6Publishing: 19]  [Article Influence: 6.3]  [Reference Citation Analysis (0)]
28.  Abbass T, Tsz Ho YT, Horgan PG, Dolan RD, McMillan DC. The relationship between computed tomography derived skeletal muscle index, psoas muscle index and clinical outcomes in patients with operable colorectal cancer. Clin Nutr ESPEN. 2020;39:104-113.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6]  [Cited by in F6Publishing: 6]  [Article Influence: 1.5]  [Reference Citation Analysis (0)]
29.  Silva TH, Sillos André JC, Orlando Correa Schilithz A, Borges Murad L, Arantes Ferreira Peres W. Prediction of survival of preoperative colorectal patients: A new tool to assess the interaction of nutritional status and inflammation. Clin Nutr ESPEN. 2023;56:230-236.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 1]  [Reference Citation Analysis (0)]
30.  Misiewicz A, Dymicka-Piekarska V. Fashionable, but What is Their Real Clinical Usefulness? NLR, LMR, and PLR as a Promising Indicator in Colorectal Cancer Prognosis: A Systematic Review. J Inflamm Res. 2023;16:69-81.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 20]  [Reference Citation Analysis (0)]
31.  Wang Z, Bian J, Yuan J, Zhao S, Huang S, Wu R, Fei F. Study on the correlation between controlling nutritional status score and clinical biochemical indicators in patients with colorectal cancer. Heliyon. 2024;10:e27202.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
32.  Nair KG, Kamath SD, Chowattukunnel N, Krishnamurthi SS. Preoperative Strategies for Locally Advanced Colon Cancer. Curr Treat Options Oncol. 2024;25:376-388.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Reference Citation Analysis (0)]
33.  Zhang J, Li M, Zhang L, Kuang T, Yu J, Wang W. Prognostic value of controlling nutritional status on clinical and survival outcomes in cancer patients treated with immunotherapy. Sci Rep. 2023;13:17715.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
34.  Ko K, Park YH, Lee JW, Ku JH, Kwak C, Kim HH. Influence of nutritional deficiency on prognosis of renal cell carcinoma (RCC). BJU Int. 2013;112:775-780.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 30]  [Cited by in F6Publishing: 36]  [Article Influence: 3.3]  [Reference Citation Analysis (0)]