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Figure 1.  Risk of 5-Year Colon Cancer Recurrence Based on Body Composition Profiles
Risk of 5-Year Colon Cancer Recurrence Based on Body Composition Profiles

SC:TFR indicates subcutaneous to total fat ratio; SMA, skeletal muscle area; and V:TFR, visceral to total fat ratio. Box and circle markers indicate a recurrence when associated with a change in direction of the linear line or a point of censorship (ie, the time at which follow-up ceased).

Figure 2.  Risk of 5-Year Disease-Specific Mortality in Colon Cancer Based on Body Composition Profiles
Risk of 5-Year Disease-Specific Mortality in Colon Cancer Based on Body Composition Profiles

SC:TFR indicates subcutaneous to total fat ratio; SMA, skeletal muscle area; and V:TFR, visceral to total fat ratio. Box and circle markers indicate a disease-specific mortality or a point of censorship (ie, the time at which follow-up ceased).

Figure 3.  Comparison of Mean Inflammatory Mediator Levels in Patients Who Developed Cancer Recurrence and Those Who Did Not
Comparison of Mean Inflammatory Mediator Levels in Patients Who Developed Cancer Recurrence and Those Who Did Not

CRP indicates C-reactive protein; IFN, interferon; IL, interleukin; SMA, skeletal muscle area; TNF, tumor necrosis factor; V:TFR, visceral to total fat ratio; VEGF, vascular endothelial growth factor; and WCC, white cell count.

SI conversion factors: To convert albumin to grams per liter, multiply by 10; CRP to milligrams per liter, multiply by 10; WCC to ×109 per liter, multiply by 0.001.

aP < .01.

bP < .05.

cP < .001.

Table 1.  Summary of Patient Demographic, Clinicopathological, Inflammatory Mediator, and Body Composition Profile Data
Summary of Patient Demographic, Clinicopathological, Inflammatory Mediator, and Body Composition Profile Data
Table 2.  Associations of Body Composition Profiles With 30-Day Morbidity and Postoperative Infectious Complications After Surgery for Nonmetastatic Colon Cancer
Associations of Body Composition Profiles With 30-Day Morbidity and Postoperative Infectious Complications After Surgery for Nonmetastatic Colon Cancer
1.
Watanabe  J, Tatsumi  K, Ota  M,  et al.  The impact of visceral obesity on surgical outcomes of laparoscopic surgery for colon cancer.   Int J Colorectal Dis. 2014;29(3):343-351. doi:10.1007/s00384-013-1803-9 PubMedGoogle ScholarCrossref
2.
Black  D, Mackay  C, Ramsay  G,  et al.  Prognostic value of computed tomography: measured parameters of body composition in primary operable gastrointestinal cancers.   Ann Surg Oncol. 2017;24(8):2241-2251. doi:10.1245/s10434-017-5829-z PubMedGoogle ScholarCrossref
3.
Balkwill  F, Mantovani  A.  Inflammation and cancer: back to Virchow?   Lancet. 2001;357(9255):539-545. doi:10.1016/S0140-6736(00)04046-0 PubMedGoogle ScholarCrossref
4.
Mantovani  A, Garlanda  C, Allavena  P.  Molecular pathways and targets in cancer-related inflammation.   Ann Med. 2010;42(3):161-170. doi:10.3109/07853890903405753 PubMedGoogle ScholarCrossref
5.
Donohoe  CL, Doyle  SL, Reynolds  JV.  Visceral adiposity, insulin resistance and cancer risk.   Diabetol Metab Syndr. 2011;3(1):12. doi:10.1186/1758-5996-3-12 PubMedGoogle ScholarCrossref
6.
Martinez-Useros  J, Garcia-Foncillas  J.  Obesity and colorectal cancer: molecular features of adipose tissue.   J Transl Med. 2016;14(1):21. doi:10.1186/s12967-016-0772-5 PubMedGoogle ScholarCrossref
7.
Doyle  SL, Donohoe  CL, Lysaght  J, Reynolds  JV.  Visceral obesity, metabolic syndrome, insulin resistance and cancer.   Proc Nutr Soc. 2012;71(1):181-189. doi:10.1017/S002966511100320X PubMedGoogle ScholarCrossref
8.
Sonnenberg  GE, Krakower  GRKA, Kissebah  AH.  A novel pathway to the manifestations of metabolic syndrome.   Obes Res. 2004;12(2):180-186. doi:10.1038/oby.2004.24 PubMedGoogle ScholarCrossref
9.
Aggarwal  BB, Vijayalekshmi  RV, Sung  B.  Targeting inflammatory pathways for prevention and therapy of cancer: short-term friend, long-term foe.   Clin Cancer Res. 2009;15(2):425-430. doi:10.1158/1078-0432.CCR-08-0149 PubMedGoogle ScholarCrossref
10.
O’Leary  DP, Wang  JH, Cotter  TG, Redmond  HP.  Less stress, more success: oncological implications of surgery-induced oxidative stress.   Gut. 2013;62(3):461-470. doi:10.1136/gutjnl-2011-300948 PubMedGoogle ScholarCrossref
11.
O’Leary  DP, O’Leary  E, Foley  N, Cotter  TG, Wang  JH, Redmond  HP.  Effects of surgery on the cancer stem cell niche.   Eur J Surg Oncol. 2016;42(3):319-325. doi:10.1016/j.ejso.2015.12.008 PubMedGoogle ScholarCrossref
12.
Dignam  JJ, Polite  BN, Yothers  G,  et al.  Body mass index and outcomes in patients who receive adjuvant chemotherapy for colon cancer.   J Natl Cancer Inst. 2006;98(22):1647-1654. doi:10.1093/jnci/djj442 PubMedGoogle ScholarCrossref
13.
Meyerhardt  JA, Niedzwiecki  D, Hollis  D,  et al; Cancer and Leukemia Group B 89803.  Impact of body mass index and weight change after treatment on cancer recurrence and survival in patients with stage III colon cancer: findings from Cancer and Leukemia Group B 89803.   J Clin Oncol. 2008;26(25):4109-4115. doi:10.1200/JCO.2007.15.6687 PubMedGoogle ScholarCrossref
14.
Malietzis  G, Aziz  O, Bagnall  NM, Johns  N, Fearon  KC, Jenkins  JT.  The role of body composition evaluation by computerized tomography in determining colorectal cancer treatment outcomes: a systematic review.   Eur J Surg Oncol. 2015;41(2):186-196. doi:10.1016/j.ejso.2014.10.056 PubMedGoogle ScholarCrossref
15.
Lennon  H, Sperrin  M, Badrick  E, Renehan  AG.  The obesity paradox in cancer: a review.   Curr Oncol Rep. 2016;18(9):56. doi:10.1007/s11912-016-0539-4 PubMedGoogle ScholarCrossref
16.
Moore  SC, Playdon  MC, Sampson  JN,  et al.  A metabolomics analysis of body mass index and postmenopausal breast cancer risk.   J Natl Cancer Inst. 2018;110(6):588-597. doi:10.1093/jnci/djx244 PubMedGoogle Scholar
17.
Ryan  AM, Power  DG, Daly  L, Cushen  SJ, Ní Bhuachalla  Ē, Prado  CM.  Cancer-associated malnutrition, cachexia and sarcopenia: the skeleton in the hospital closet 40 years later.   Proc Nutr Soc. 2016;75(2):199-211. doi:10.1017/S002966511500419X PubMedGoogle ScholarCrossref
18.
Blum  D, Omlin  A, Baracos  VE,  et al; European Palliative Care Research Collaborative.  Cancer cachexia: a systematic literature review of items and domains associated with involuntary weight loss in cancer.   Crit Rev Oncol Hematol. 2011;80(1):114-144. doi:10.1016/j.critrevonc.2010.10.004 PubMedGoogle ScholarCrossref
19.
Bye  A, Jordhøy  MS, Skjegstad  G, Ledsaak  O, Iversen  PO, Hjermstad  MJ.  Symptoms in advanced pancreatic cancer are of importance for energy intake.   Support Care Cancer. 2013;21(1):219-227. doi:10.1007/s00520-012-1514-8 PubMedGoogle ScholarCrossref
20.
Fearon  K, Strasser  F, Anker  SD,  et al.  Definition and classification of cancer cachexia: an international consensus.   Lancet Oncol. 2011;12(5):489-495. doi:10.1016/S1470-2045(10)70218-7 PubMedGoogle ScholarCrossref
21.
Mourtzakis  M, Prado  CMLJ, Lieffers  JR, Reiman  T, McCargar  LJ, Baracos  VE.  A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care.   Appl Physiol Nutr Metab. 2008;33(5):997-1006. doi:10.1139/H08-075 PubMedGoogle ScholarCrossref
22.
Shen  W, Punyanitya  M, Wang  Z,  et al.  Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross-sectional image.   J Appl Physiol (1985). 2004;97(6):2333-2338. doi:10.1152/japplphysiol.00744.2004 PubMedGoogle ScholarCrossref
23.
Choi  MH, Oh  SN, Lee  IK, Oh  ST, Won  DD.  Sarcopenia is negatively associated with long-term outcomes in locally advanced rectal cancer.   J Cachexia Sarcopenia Muscle. 2018;9(1):53-59. doi:10.1002/jcsm.12234 PubMedGoogle ScholarCrossref
24.
Peng  P, Hyder  O, Firoozmand  A,  et al.  Impact of sarcopenia on outcomes following resection of pancreatic adenocarcinoma.   J Gastrointest Surg. 2012;16(8):1478-1486. doi:10.1007/s11605-012-1923-5 PubMedGoogle ScholarCrossref
25.
Antoun  S, Baracos  VE, Birdsell  L, Escudier  B, Sawyer  MB.  Low body mass index and sarcopenia associated with dose-limiting toxicity of sorafenib in patients with renal cell carcinoma.   Ann Oncol. 2010;21(8):1594-1598. doi:10.1093/annonc/mdp605 PubMedGoogle ScholarCrossref
26.
Sharma  P, Zargar-Shoshtari  K, Caracciolo  JT,  et al.  Sarcopenia as a predictor of overall survival after cytoreductive nephrectomy for metastatic renal cell carcinoma.   Urol Oncol. 2015;33(8):339.e17-339.e23. doi:10.1016/j.urolonc.2015.01.011 PubMedGoogle ScholarCrossref
27.
Cushen  SJ, Power  DG, Murphy  KP,  et al.  Impact of body composition parameters on clinical outcomes in patients with metastatic castrate-resistant prostate cancer treated with docetaxel.   Clin Nutr ESPEN. 2016;13:e39-e45. doi:10.1016/j.clnesp.2016.04.001 PubMedGoogle ScholarCrossref
28.
Elliott  JA, Doyle  SL, Murphy  CF,  et al.  Sarcopenia: prevalence, and impact on operative and oncologic outcomes in the multimodal management of locally advanced esophageal cancer.   Ann Surg. 2017;266(5):822-830. doi:10.1097/SLA.0000000000002398 PubMedGoogle ScholarCrossref
29.
Wagner  D, DeMarco  MM, Amini  N,  et al.  Role of frailty and sarcopenia in predicting outcomes among patients undergoing gastrointestinal surgery.   World J Gastrointest Surg. 2016;8(1):27-40. doi:10.4240/wjgs.v8.i1.27 PubMedGoogle ScholarCrossref
30.
O’Brien  S, Twomey  M, Moloney  F,  et al.  Sarcopenia and post-operative morbidity and mortality in patients with gastric cancer.   J Gastric Cancer. 2018;18(3):242-252. doi:10.5230/jgc.2018.18.e25 PubMedGoogle ScholarCrossref
31.
Redmond  HP, Neary  PM, Jinih  M,  et al.  Randomised Clinical Trial Assessing Use of an Anti-inflammatory Agent in Attenuating Peri-operative Inflammation in Non-metastatic Colon Cancer—the S.U.R.G.U.V.A.N.T. trial.   BMC Cancer. 2018;18(1):794. doi:10.1186/s12885-018-4641-x PubMedGoogle ScholarCrossref
32.
Leong  K, Hartley  J, Karandikar  S.  Association of coloproctology of Great Britain & Ireland (ACPGBI): guidelines for the management of cancer of the colon, rectum and anus (2017)—follow up, lifestyle and survivorship.   Colorectal Dis. 2017;19(suppl 1):67-70. doi:10.1111/codi.13706 PubMedGoogle ScholarCrossref
33.
Demerath  EW, Shen  W, Lee  M,  et al.  Approximation of total visceral adipose tissue with a single magnetic resonance image.   Am J Clin Nutr. 2007;85(2):362-368. doi:10.1093/ajcn/85.2.362 PubMedGoogle ScholarCrossref
34.
Dello  SA, Lodewick  TM, van Dam  RM,  et al.  Sarcopenia negatively affects preoperative total functional liver volume in patients undergoing liver resection.   HPB (Oxford). 2013;15(3):165-169. doi:10.1111/j.1477-2574.2012.00517.x PubMedGoogle ScholarCrossref
35.
Lieffers  JR, Bathe  OF, Fassbender  K, Winget  M, Baracos  VE.  Sarcopenia is associated with postoperative infection and delayed recovery from colorectal cancer resection surgery.   Br J Cancer. 2012;107(6):931-936. doi:10.1038/bjc.2012.350 PubMedGoogle ScholarCrossref
36.
van der Werf  A, Langius  JAE, de van der Schueren  MAE,  et al.  Percentiles for skeletal muscle index, area and radiation attenuation based on computed tomography imaging in a healthy Caucasian population.   Eur J Clin Nutr. 2018;72(2):288-296. doi:10.1038/s41430-017-0034-5 PubMedGoogle ScholarCrossref
37.
Cruz-Jentoft  AJ, Baeyens  JP, Bauer  JM,  et al; European Working Group on Sarcopenia in Older People.  Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older People.   Age Ageing. 2010;39(4):412-423. doi:10.1093/ageing/afq034 PubMedGoogle ScholarCrossref
38.
Doyle  SL, Bennett  AM, Donohoe  CL,  et al.  Establishing computed tomography-defined visceral fat area thresholds for use in obesity-related cancer research.   Nutr Res. 2013;33(3):171-179. doi:10.1016/j.nutres.2012.12.007 PubMedGoogle ScholarCrossref
39.
Tsujinaka  S, Konishi  F, Kawamura  YJ,  et al.  Visceral obesity predicts surgical outcomes after laparoscopic colectomy for sigmoid colon cancer.   Dis Colon Rectum. 2008;51(12):1757-1765. doi:10.1007/s10350-008-9395-0 PubMedGoogle ScholarCrossref
40.
Ishii  Y, Hasegawa  H, Nishibori  H, Watanabe  M, Kitajima  M.  Impact of visceral obesity on surgical outcome after laparoscopic surgery for rectal cancer.   Br J Surg. 2005;92(10):1261-1262. doi:10.1002/bjs.5069 PubMedGoogle ScholarCrossref
41.
Rickles  AS, Iannuzzi  JC, Mironov  O,  et al.  Visceral obesity and colorectal cancer: are we missing the boat with BMI?   J Gastrointest Surg. 2013;17(1):133-143. doi:10.1007/s11605-012-2045-9 PubMedGoogle ScholarCrossref
42.
Ballian  N, Lubner  MG, Munoz  A,  et al.  Visceral obesity is associated with outcomes of total mesorectal excision for rectal adenocarcinoma.   J Surg Oncol. 2012;105(4):365-370. doi:10.1002/jso.22031 PubMedGoogle ScholarCrossref
43.
Guiu  S, Mouret Reynier  MA, Toure  M, Coudert  B.  Predictive factors of response in HER2-positive breast cancer treated by neoadjuvant therapy.   J Oncol. 2013;2013:854121. doi:10.1155/2013/854121 PubMedGoogle Scholar
44.
Clark  W, Siegel  EM, Chen  YA,  et al.  Quantitative measures of visceral adiposity and body mass index in predicting rectal cancer outcomes after neoadjuvant chemoradiation.   J Am Coll Surg. 2013;216(6):1070-1081. doi:10.1016/j.jamcollsurg.2013.01.007 PubMedGoogle ScholarCrossref
45.
Xiao  J, Mazurak  VC, Olobatuyi  TA, Caan  BJ, Prado  CM.  Visceral adiposity and cancer survival: a review of imaging studies.   Eur J Cancer Care (Engl). 2018;27(2):e12611. doi:10.1111/ecc.12611PubMedGoogle Scholar
46.
Lee  CS, Murphy  DJ, McMahon  C,  et al.  Visceral adiposity is a risk factor for poor prognosis in colorectal cancer patients receiving adjuvant chemotherapy.   J Gastrointest Cancer. 2015;46(3):243-250. doi:10.1007/s12029-015-9709-0 PubMedGoogle ScholarCrossref
47.
Guiu  B, Petit  JM, Bonnetain  F,  et al.  Visceral fat area is an independent predictive biomarker of outcome after first-line bevacizumab-based treatment in metastatic colorectal cancer.   Gut. 2010;59(3):341-347. doi:10.1136/gut.2009.188946 PubMedGoogle ScholarCrossref
48.
Moon  H-G, Ju  Y-T, Jeong  C-Y,  et al.  Visceral obesity may affect oncologic outcome in patients with colorectal cancer.   Ann Surg Oncol. 2008;15(7):1918-1922. doi:10.1245/s10434-008-9891-4 PubMedGoogle ScholarCrossref
49.
Cheah  MT, Chen  JY, Sahoo  D,  et al.  CD14-expressing cancer cells establish the inflammatory and proliferative tumor microenvironment in bladder cancer.   Proc Natl Acad Sci U S A. 2015;112(15):4725-4730. doi:10.1073/pnas.1424795112 PubMedGoogle ScholarCrossref
50.
Hmama  Z, Mey  A, Normier  G, Binz  H, Revillard  JP.  CD14 and CD11b mediate serum-independent binding to human monocytes of an acylpolygalactoside isolated from Klebsiella pneumoniae.   Infect Immun. 1994;62(5):1520-1527. doi:10.1128/IAI.62.5.1520-1527.1994 PubMedGoogle ScholarCrossref
51.
Thomas  G, Tahir  MR, Bongers  BC, Kallen  VL, Slooter  GD, van Meeteren  NL.  Prehabilitation before major intra-abdominal cancer surgery: a systematic review of randomised controlled trials.   Eur J Anaesthesiol. 2019;36(12):933-945. doi:10.1097/EJA.0000000000001030 PubMedGoogle ScholarCrossref
52.
Baldwin  C, Spiro  A, Ahern  R, Emery  PW.  Oral nutritional interventions in malnourished patients with cancer: a systematic review and meta-analysis.   J Natl Cancer Inst. 2012;104(5):371-385. doi:10.1093/jnci/djr556 PubMedGoogle ScholarCrossref
53.
Shaashua  L, Shabat-Simon  M, Haldar  R,  et al.  Perioperative COX-2 and β-adrenergic blockade improves metastatic biomarkers in breast cancer patients in a phase-II randomized trial.   Clin Cancer Res. 2017;23(16):4651-4661. doi:10.1158/1078-0432.CCR-17-0152 PubMedGoogle ScholarCrossref
54.
Sooriakumaran  P, Coley  HM, Fox  SB,  et al.  A randomized controlled trial investigating the effects of celecoxib in patients with localized prostate cancer.   Anticancer Res. 2009;29(5):1483-1488.PubMedGoogle Scholar
55.
Dhawan  D, Craig  BA, Cheng  L,  et al.  Effects of short-term celecoxib treatment in patients with invasive transitional cell carcinoma of the urinary bladder.   Mol Cancer Ther. 2010;9(5):1371-1377. doi:10.1158/1535-7163.MCT-10-0049 PubMedGoogle ScholarCrossref
56.
Clancy  C, O’Leary  DP, Burke  JP,  et al.  A meta-analysis to determine the oncological implications of conversion in laparoscopic colorectal cancer surgery.   Colorectal Dis. 2015;17(6):482-490. doi:10.1111/codi.12875PubMedGoogle ScholarCrossref
57.
Beecher  SM, OʼLeary  DP, McLaughlin  R, Kerin  MJ.  The impact of surgical complications on cancer recurrence rates: a literature review.   Oncol Res Treat. 2018;41(7-8):478-482. doi:10.1159/000487510 PubMedGoogle ScholarCrossref
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    Original Investigation
    Oncology
    August 30, 2021

    Body Composition, Inflammation, and 5-Year Outcomes in Colon Cancer

    Author Affiliations
    • 1Surguvant Research Centre, Cork University Hospital, Cork, Ireland
    • 2Department of Colorectal Surgery, Cork University Hospital, Cork, Ireland
    • 3Department of Radiology, Cork University Hospital, Cork, Ireland
    JAMA Netw Open. 2021;4(8):e2115274. doi:10.1001/jamanetworkopen.2021.15274
    Key Points

    Question  Are underlying inflammatory pathways and body composition profiles associated with less favorable 5-year colon cancer outcomes?

    Findings  In this cohort study including 28 patients with nonmetastatic colon cancer, high visceral fat and low muscle mass were associated with increased inflammatory activity and poor 5-year cancer outcomes, including recurrence and disease-specific mortality. Low skeletal muscle area and high visceral to total fat ratio were associated with increased expression of proinflammatory cytokines and vascular endothelial growth factor and inhibition of protective inhibitory cytokines in patients with less favorable 5-year cancer outcomes.

    Meaning  These findings suggest that less favorable colon cancer outcomes associated with low skeletal muscle area and high visceral to total fat ratio were also associated with increased expression of proinflammatory cytokines and vascular endothelial growth factor and lower levels of protective inhibitory cytokines.

    Abstract

    Importance  Obesity, particularly visceral obesity and sarcopenia, are poor prognostic indicators in colon cancer.

    Objectives  To explore the association between body composition profiles and 5-year colon cancer outcomes and delineate the associated underlying inflammatory processes.

    Design, Setting, and Participants  This multicenter translational cohort study included patients with nonmetastatic colon cancer who did not have underlying chronic inflammatory disorders and were not receiving anti-inflammatory drugs referred to tertiary cancer centers from 2009 to 2015. Preoperative acute phase proteins (white cell count, C-reactive protein, and albumin), cytokines (interleukin [IL]-1b, IL-2, IL-6, IL-10, interferon γ, and tumor necrosis factor α), vascular endothelial growth factor (VEGF), and cell surface receptor expression levels (CD11b and CD14) were measured. All patients underwent follow-up for at least 5 years. Data were analyzed in December 2020.

    Exposure  Nonmetastatic colon cancer.

    Main Outcomes and Measures  The associations of body composition profiles with 5-year cancer recurrence and disease-specific mortality were analyzed using Mantel Cox log-rank test and Kaplan-Meier curves.

    Results  A total of 28 patients were included (median [interquartile range] age, 67 [58-72] years; 22 [78.6%] men). Low skeletal muscle area (SMA) and high visceral to total fat ratio were associated with poor clinical and oncological outcomes, including increased 5-year recurrence (low SMA: hazard ratio [HR], 2.30 [95% CI, 1.41-2.89]; P = .04; high visceral to total fat ratio: HR, 5.78 [95% CI, 3.66-7.95]; P = .02). High visceral to total fat ratio was associated with increased 5-year disease-specific mortality (HR, 5.92 [95% CI, 4.04-8.00]; P = .02). Patients with low SMA who developed a cancer recurrence, compared with those who did not, had higher C-reactive protein (mean [SD], 31.24 [6.95] mg/dL vs 8.11 [0.58] mg/dL; P = .003), IL-6 (mean [SD], 1.93 [1.16] ng/mL vs 0.88 [0.14] ng/mL; P = .004), VEGF (mean [SD], 310.03 [122.66] ng/mL vs 176.12 [22.94] ng/mL; P = .007), and CD14 (mean [SD], 521.23 [302.02] ng/mL vs 322.07 [98.35] ng/mL; P = .03) expression and lower albumin (mean [SD], 3.8 [0.6] g/dL vs 43.50 [3.69] g/dL; P = .01), IL-2 (mean [SD], 0.45 [0.25] ng/mL vs 0.94 [0.43] ng/mL; P < .001), IL-10 (mean [SD], 8.15 [1.09] ng/mL vs 16.32 [4.43] ng/mL; P = .004), and interferon γ (mean [SD], 2.61 [1.36] ng/mL vs 14.87 [3.43] ng/mL; P = .02) levels. Patients with high visceral to total fat ratio who developed recurrence had higher levels of IL-6 (mean [SD], 5.26 [7.05] ng/mL vs 2.76 [3.11] ng/mL; P = .03) and tumor necrosis factor α (mean [SD], 5.74 [4.53] ng/mL vs 4.50 [1.99] ng/mL; P = .03).

    Conclusions and Relevance  These findings suggest that low SMA and high visceral to total fat ratio were associated with worse colon cancer outcomes and with increased expression of proinflammatory cytokines and VEGF and inhibition of anti-inflammatory cytokines.

    Introduction

    Analysis of differential body composition profiles has been suggested as a useful prognostic indicator in colorectal cancer (CRC).1,2 Baseline inflammation is increased in obesity, and the current doctrine in obesity-related cancer research is that excess visceral adiposity produces adipocytokines that fuel a proinflammatory state with an associated pro-oncogenic and prometastatic environment.3-6 Visceral adipocytes secrete higher levels of tumor necrosis factor α (TNFα) and interleukin (IL)-6 compared with subcutaneous adipocytes, and higher macrophage and other inflammatory cell levels have also been observed.5,7 These inflammatory cytokines upregulate proinflammatory pathways NF-κB, STAT3, and inhibitor of NF-κB kinase subunit β, which lead to transcription of downstream genes that are associated with mediating cancer cell proliferation, invasion, angiogenesis, cell survival, and metastatic development.8-11

    In obesity-related cancer research, the use of body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) alone to estimate oncological outcomes is conflicting, since BMI does not provide a measure of body fat distribution, particularly the difference in metabolically active visceral fat and more inert subcutaneous fat levels.12,13 High visceral fat is significantly proinflammatory and has been demonstrated to be an indicator associated with poor prognosis in colorectal, esophageal, gastric, kidney, bladder, and breast cancers.5,14-16 Sarcopenia is a clinical manifestation of the cancer cachexia syndrome, a catabolic state that develops owing to the metabolic demand and proinflammatory systemic state created by the presence of cancer.17 Sarcopenia may be potentiated by poor dietary intake in particular cancers of the gastrointestinal tract that obstruct the ability to eat or as a result of treatment adverse effects.18,19 Cancer cachexia syndrome requires the presence of sarcopenia, which is best measured directly on imaging (dual-energy radiographic absorptiometry or computed tomography [CT]).20-22 Therefore, sarcopenia is synonymous with the inflammatory state of cancer cachexia. Sarcopenia is consistently associated with lower survival rates in multiple cancers.23-26 It is also associated with reduced tolerance to and increased toxic effects from chemotherapy.25,27 Sarcopenia is also associated with higher postoperative complications after cancer surgery.28-30

    Investigating clinically relevant associations between inflammatory pathways and body composition in a clinical setting is complex owing to the higher prevalence of underlying chronic inflammatory disorders in patients who develop cancer and the high prevalence of anti-inflammatory and immunomodulator therapy in the general population. In this study, we aimed to better understand the associations between differential body compositions, systemic inflammation, and 30-day morbidity and 5-year cancer outcomes in patients with nonmetastatic colon cancer.

    Methods

    Prospective ethical approval of this study was obtained from the Clinical Research Ethics Committee of the Cork Teaching Hospitals. All patients provided written informed consent. This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

    Patient Recruitment, Treatment, and Follow-up

    The placebo group enrolled in the Randomised Clinical Trial Assessing Use of an Anti-inflammatory Agent in Attenuating Peri-operative Inflammation in Non-metastatic Colon Cancer (S.U.R.G.U.V.A.N.T.) trial offered a unique opportunity to investigate the associations among differential body composition, inflammation, and colon cancer outcomes in a human model.31 Patients presenting for elective resection for colon cancer, with nonmetastatic disease, aged 18 to 85 years to 3 tertiary referral cancer centers were screened for inclusion. Extensive exclusion criteria were applied as follows: pregnant and lactating women, evidence of underlying liver disease (ie, liver function test results >2-fold reference ranges), international normalized ratio greater than 1.5, evidence of underlying kidney disease (ie, creatinine >2.36 mg/dL for women, >1.97 for men [to convert to micromoles per liter, multiply by 76.25], blood dyscrasia (neutrophils <1500 cells/μL [to convert to ×109 per liter, multiply by 0.001], thrombocytes <100 × 103/μL [to convert to ×109 per liter, multiply by 1]), evidence of intestinal obstruction; metastases (M1: distant spread or Dukes D), morbid obesity (ie, BMI >40), operative risk greater than American Society of Anesthesiologists class III, previous cancer or malignant disease other than nonmelanoma skin cancer, coexisting active inflammatory disorder (including active rheumatoid arthritis, inflammatory bowel disease, or systemic lupus erythematosus), corticosteroids use, immunosuppressive drugs, previous diagnosis of HIV, chronic active hepatitis B or C, and active infection at the time of surgical intervention.

    All patients with CRC were treated in keeping with recommendations from the Association of Coloproctologists of Great Britain and Ireland.32 After initial diagnosis with CRC, all patients were staged, and metastatic disease was ruled out using CT of the thorax, abdomen, and pelvis (TAP) and full endoscopy (in the absence of colonic obstruction) with tissue biopsy. All CRC operations were performed adhering to principles of oncological resection for CRC, including a no-touch technique with a high-tie of the vessels. Active surveillance continued for 5 years using a combination of clinical review, carcinoembryonic antigen testing, colonoscopy, and CT TAP, as recommended by the Association of Coloproctologists of Great Britain and Ireland.32

    Inflammatory Mediator Analysis

    Blood samples were phlebotomized from patients preoperatively. Full blood counts were analyzed using the Sysmex XN 200 analyzer using a particle counting method based on size and density, and white cell count (WCC) was extracted from these results. Albumin levels were analyzed in our institute using a Roche Biochemistry Platform that uses a colorimetric assay (pH based). In all clinical laboratories in Ireland, National External Quality Assessment Scheme testing is performed in conjunction with daily internal control assessments to allow for accuracy of data and standardization of results. Acute phase protein and cytokine levels were measured using a standard enzyme-linked immunosorbent assay technique using a custom-made panel for the following cytokines: human IL-1b, IL-2, IL-6, IL-10, interferon (IFN) γ, TNFα, vascular endothelial growth factor (VEGF), and C-reactive protein (CRP). Neutrophil and monocyte surface receptor expression CD11b and CD14 levels were detected using flow cytometry using a FACScan flow cytometer and analyzed using the software package Cell-Quest version 5.1 (BD). The assay method involved direct staining of cell surface antigen in whole blood.

    CT Anthropometric Measurements and Categorization

    CT anthropometric measurements were obtained from CT studies acquired preoperatively, usually within 4 to 6 weeks prior to surgery using a 64-slice multidetector CT (GE Healthcare). Total fat area and subcutaneous fat area were measured on a single axial CT slice 6 cm above the L4-5 intervertebral disc in centimeters-squared and visceral fat area was calculated by subtraction. Visceral fat area at this level correlates strongly with overall visceral adipose volume.33 Fat volume measurements were performed using the segmentation tool in the DICOM image viewer Horos (Horos Project). The full study protocol is available in eAppendix 1 in the Supplement. Visceral to total fat ratio and subcutaneous to total fat ratio were calculated. Skeletal muscle area (SMA) was measured on axial CT images at the L3 level in centimeters-squared, as this is accepted as an accurate surrogate for total skeletal muscle mass.34,35 Reduced SMA has been used as a surrogate for sarcopenia (an age-related or pathological state of low muscle mass and function).36,37 Muscle volume measurements were also performed using Horos (eAppendix 1 in the Supplement).

    Visceral fat levels were categorized based on previously validated sex-specific cutoffs that have been associated with metabolic syndrome and thus are clinically significant.38 SMA was categorized as low at less than the 10th percentile of that observed in age- and sex-specific levels in the general population.36 For all other body composition profiles relating to adiposity, sex-specific median and interquartile range (IQR) values were calculated, and the parameter was categorized as the reference range at less than the 60th percentile and high at greater than the 60th percentile (50th percentile was the median). Cutoffs for each category used in this study are summarized in eAppendix 2 in the Supplement.

    Statistical Analysis

    Statistical analysis was performed using SPSS version 26 (IBM), and graphs were generated using Prism version 8.4.2 (GraphPad). The association between body composition profiles and 30-day postoperative morbidity and more specifically postoperative infective complications was reported using odds ratios (ORs), 95% CIs, and P values generated with χ2 testing. Infectious complications included anastomotic leak, surgical site infection, and lower respiratory tract infection. The associations of body composition profiles with 5-year cancer recurrence and disease-specific mortality were analyzed using Mantel Cox log-rank test and Kaplan-Meier curves were produced. Hazard ratios (HRs) were generated to compare survival distributions by reference range and pathological body composition profile subgroups. Finally, when particular body composition profiles were significantly associated with poor clinical and cancer outcomes, comparison of mean inflammatory mediator expression levels was performed using Mann-Whitney U test, and statistical significance was set at 2-sided P < .05.

    Results
    Demographic and Clinicopathological Data

    A total of 28 patients who underwent elective resection for colon cancer with curative intent were analyzed. Table 1 summarizes patient demographic and clinicopathological data. The median (IQR) age was 67 (58-72) years, and 22 patients (78.6%) were men. A total of 14 tumors (50.0%) were left sided, 13 tumors (46.4%) were right sided, and 1 transverse colon tumor (3.6%) was included. There were 15 T3 tumors (53.6%), 6 T4 tumors (21.4%), 5 T2 tumors (17.9%), and 2 T1 tumors (7.1%). Furthermore, 16 tumors (57.2%) were node negative, and 12 tumors (42.8%) were node positive. The median (range) nodal harvest was 15.5 (11-32) nodes. Most procedures (23 procedures [82.1%]) were completed laparoscopically, 2 procedures (7.1%) were open, and 3 procedures (10.7%) were converted from laparoscopic to open. Patients were surveyed clinically, radiologically, and endoscopically for a median (IQR) of 64 (51-95) months. Table 1 summarizes median levels of mediators of systemic inflammation and CT-derived body composition profiles with age and sex-specific categories. A total of 4 patients (14.3%) had a low SMA, and 11 patients (39.3%) had high total fat area. Differential fat measurements identified 22 patients (78.6%) with high visceral fat area and 10 patients (35.7%) with high subcutaneous fat levels. Correlation between body composition profiles and mediators of systemic inflammation and comparison of mean inflammatory level expressions based on body composition profile are summarized in the eTable in the Supplement.

    Clinical and Oncological Outcomes

    Nine patients (32.1%) developed a postoperative complication within the first 30 days postoperatively (Table 1), including 5 patients (17.9%) who developed a surgical site infection, 2 patients (7.1%) who developed an anastomotic leak, both requiring a return to surgery, 1 patient (3.6%) who developed a lower respiratory tract infection, and 1 patient (3.6%) who developed prolonged postoperative ileus (ie, persistent ileus >48 hours postoperatively). A total of 4 patients experienced cancer recurrence at a median (range) interval of 22 (5-31) months. All were distant recurrence, including 3 hepatic tumors and 1 pulmonary tumor. A total of 3 patients (10.7%) experienced disease-specific mortality. The median (range) interval from surgery to mortality was 27 (51-95) months.

    Associations of Body Composition Profiles With Colon Cancer Outcomes

    Low SMA and high visceral to total fat ratio were associated with less favorable clinical and oncological outcomes. There was no significant association between differential body composition profiles and overall 30-day morbidity. Low SMA (OR, 2.13 [95% CI, 1.85-5.36]; P = .004) and high visceral to total fat ratio (OR, 3.20 [95% CI, 1.85-10.84]; P = .01] were significantly associated with developing a 30-day infective complication (Table 2). A log-rank Mantel test was performed to analyze the association of differential body composition profiles with 5-year colon cancer recurrence (Figure 1). Low SMA (HR, 2.30 [95% CI, 1.41-2.89]; P = .04) and high visceral to total fat ratio (HR, 5.78 [95% CI, 3.66-7.95]; P = .02) were significantly associated with developing a cancer recurrence within the first 5 years after surgery. A log-rank Mantel test was performed to analyze the association of differential body composition profiles with 5-year disease-specific mortality (Figure 2). High visceral to total fat ratio (HR, 5.92 [95% CI, 4.04-8.00]; P = .02) was the only body composition profile significantly associated with cancer-related mortality within the first 5 years after surgery. There was no significant association between low SMA and 5-year disease-specific mortality (HR, 3.22 [95% CI, 0.13-8.37]; P = .48).

    Systemic Inflammation, Body Composition Profiles, and Outcome Analysis

    Patients with low SMA who developed an infectious complication, compared with those who did not, had significantly higher WCC (mean [SD], 7100 [1870] cells/μL vs 5600 [1580] cells/μL [to convert to ×109/L, multiply by 0.001]; P = .04) and CRP (mean [SD], 3.29 [2.52] mg/dL vs 0.70 [0.10] mg/dL [to convert to milligrams per liter, multiply by 10]; P = .01) levels, higher expression of IL-10 (mean [SD], 8.75 [5.79] ng/mL vs 0.42 [0.24] ng/mL; P = .004), VEGF (mean [SD], 298.42 [134.90] ng/mL vs 183.86 [23.67] ng/mL; P = .004), and CD14 (mean [SD], 521.23 [302.02] ng/mL vs 322.07 [98.35] ng/mL; P = .03), and lower levels of IFN-γ (mean [SD], 1.38 [1.62] ng/mL vs 3.22 [1.15] ng/mL; P = .046) (eFigure 1 in the Supplement). Patients with high visceral to total fat ratio who developed infectious complications, compared with those who did not, had significantly higher CRP (mean [SD], 5.30 [0.88] mg/dL vs 1.09 [1.40] mg/dL; P = .001) and IFN-γ (mean [SD], 7.76 [1.41] ng/mL vs 2.89 [1.84] ng/mL; P = .01) and lower expression of IL-2 (mean [SD], 0.12 [0.09] ng/mL vs 0.41 [0.31] ng/mL; P = .03). Figure 3 shows that patients with low SMA who developed cancer recurrence, compared with those who did not, had significantly higher levels of CRP (mean [SD], 31.24 [6.95] mg/dL vs 8.11 [0.58] mg/dL; P = .003), IL-6 (mean [SD], 1.93 [1.16] ng/mL vs 0.88 [0.14] ng/mL; P = .004), VEGF (mean [SD], 310.03 [122.66] ng/mL vs 176.12 [22.94] ng/mL; P = .007), and CD14 (mean [SD], 521.23 [302.02] ng/mL vs 322.07 [98.35] ng/mL; P = .03) expression. Significantly lower levels of albumin (mean [SD], 3.8 [0.6] g/dL vs 4.4 [3.7] g/dL [to convert to grams per liter, multiply by 10]; P = .01), IL-2 (mean [SD], 0.45 [0.25] ng/mL vs 0.94 [0.43] ng/mL; P < .001), IL-10 (mean [SD], 8.15 [1.09] ng/mL vs 16.32 [4.43] ng/mL; P = .004), and IFN-γ (mean [SD], 2.61 [1.36] ng/mL vs 14.87 [3.43] ng/mL; P = .02) were also observed. Patients with high visceral to total fat ratio who developed recurrence, compared with those who did not, had higher levels of IL-6 (mean [SD], 5.26 [7.05] ng/mL vs 2.76 [3.11] ng/mL; P = .03) and TNFα (mean [SD], 5.74 [4.53] ng/mL vs 4.50 [1.99] ng/mL; P = .03). There was no significant difference in systemic inflammatory mediator expression levels in patients who had high visceral to total fat ratio among those who experienced disease-specific mortality vs those who were disease-free at 5 years (eFigure 2 in the Supplement).

    Discussion

    This cohort study found that low SMA and high visceral to total fat ratio were associated with increased postoperative infections and higher 5-year cancer recurrence and disease-specific mortality rates in patients with CRC. High visceral to total fat ratio was significantly associated with poor outcomes compared with high total body fat or visceral fat levels alone. Interestingly, subcutaneous fat levels correlated with IL-2 and IL-10 levels, ie, cytokines proposed to possess predominantly anti-inflammatory as opposed to proinflammatory properties. Thus higher subcutaneous fat area may have a protective association with the deleterious inflammatory outcomes associated with visceral fat. This phenomenon may be why BMI is not a reliable prognostic marker in cancer and cancer surgery, as it does not reflect differential fat distribution or muscle mass distribution.20

    In obesity-related cancer research, BMI alone is not associated with predicting oncological outcomes, as BMI does not reflect body fat distribution, particularly the difference between metabolically active visceral fat and more inert subcutaneous fat levels.12,13 This is sometimes referred to as the obesity paradox in cancer, in which high sex-specific BMI levels are not always associated with poor prognosis in cancer.15 In CRC, increased visceral adiposity is associated with worse operative outcomes, including increased postoperative complications after resection,1,39,40 surgical site infection,1,39,41 and anastomotic leakage rates.1 In rectal cancer, high visceral fat levels are associated with lower lymph node harvests,42 less favorable tumor response to neoadjuvant therapy,43,44 and a reduction in disease-free and overall survival rates across all stages of CRC.41,42,44-48 In this study, we found that subcutaneous fat was associated with higher levels of cytokines with protective associations, including IL-2 and IL-10. This may explain why high visceral to total fat ratio was more prognostic of poor clinical outcomes (ie, postoperative infectious complications) and oncological outcomes (ie, 5-year cancer recurrence and disease-specific mortality) than visceral fat levels alone, as higher levels of protective cytokines abundant in subcutaneous fat may counteract the inflammasomes of visceral fat and neutralize their systemic effect.

    Sarcopenia is described as a clinical manifestation of the cancer cachexia syndrome.17 CT analysis is increasingly used to assess surrogates of sarcopenia, including SMA, skeletal muscle index, and muscle radiation attenuation.36 In this cohort study, we found that low SMA was significantly associated with postoperative infectious complications and 5-year cancer recurrence. In patients who developed cancer recurrence and had low SMA on staging CT TAP, significantly higher systemic levels of CRP, IL-6, VEGF, and expression of cell surface receptor CD14 were observed. These inflammatory mediators and cell receptors are known to promote cancer cell survival and metastatic transformation. Interestingly, in these patients, there were also significantly lower levels of IL-2 and IL-10.

    Expression levels of CD11b and CD14 displayed an inverse association with total fat area, visceral fat area, and visceral to total fat ratio and a direct association with SMA, subcutaneous fat area, and subcutaneous to total fat ratio in all patients, and significantly higher expression of CD14 was observed in patients with low SMA who developed postoperative infections and 5-year cancer recurrence. Both receptors are expressed mainly by mononuclear phagocytes (monocytes and macrophages) but also neutrophils and dendritic cells.49,50 Mononuclear phagocytes represent the principal target for lipopolysaccharides of gram-negative bacteria. Lipopolysaccharides trigger a wide range of cellular responses, including the synthesis and release of a variety of inflammatory mediators, such as TNFα, IL-1b, and IL-6, which, if unregulated, can promote oncogenesis and metastatic development.49 The triggering of cellular responses is initiated by binding lipopolysaccharides to the cell surface via cell surface receptors (eg, CD11b and CD14) and its subsequent internalisation.50 Higher expression of CD14 in the setting of low SMA promotes lipopolysaccharide binding and development of infection that may contribute to activation of dormant circulating tumor cells and cellular migration and invasion for metastatic development.

    The question remains on whether targeted therapies can modulate the inflammatory association of body composition with cancer outcomes. Recently, the concept of prehabiliation has gained significant interest in CRC surgery, and, considering that the body composition profiles and inflammatory markers reported in this study were performed preoperatively, it raises the question as to whether prehabilitation could reverse this association. Prehabilitation involves physical, nutritional, and psychosocial optimization preoperatively, with an aim to reduce operative morbidity and promote recovery.51 However, outcomes from prehabilitation programs have been conflicting to date, mostly owing to difficulty in identifying the optimum interventions and measures of success.51 To our knowledge, no specific nutritional intervention has been identified as effective in reversing the effects of sarcopenia.52 The reason for this has been suggested as the catabolic effect of the primary tumor remaining in situ and the inability of nutritional efforts to overcome this.17 Some targeted anti-inflammatory therapies, including anti–IL-6 therapy or combined β-blockade and cyclooxygenase 2 inhibition, have shown promising results at counteracting outcomes associated with perioperative inflammation; however, whether this can be extrapolated to modulate the effect of body composition preoperatively has not been reported, to our knowledge.31,53-55

    Limitations

    There are several limitations to this study. This was a retrospective analysis of the placebo group in a prospective randomized clinical trial, with the associated limitations of such a study design. It also included a small sample size of 28 patients, and we propose the findings of this work as exploratory and preliminary. Furthermore, it is important to recognize that the study cohort included more men (78.6%) than women (21.4%). However, although small in number, the extensive exclusion criteria supported a homogenous group of patients with CRC in whom to purely study the associations of inflammation. The incidences of 30-day morbidity and cancer outcomes were also small owing to the limited sample size. Infectious complications were grouped for outcome analysis to overcome some of this limitation, since it is known that any infectious complication can affect cancer outcomes.56,57

    Conclusions

    This cohort study found that low SMA and high visceral to total fat ratio were associated with increased risk of postoperative infections and 5-year cancer recurrence; high visceral to total fat ratio was further associated with 5-year disease-specific mortality. Furthermore, upregulation of proinflammatory cytokines, acute phase proteins, and VEGF and downregulation of protective anti-inflammatory mediators was pronounced in patients with low SMA and high visceral to total fat ratio who experienced poor clinical or cancer outcomes. Therefore, these findings suggest that the negative impact of sarcopenia and visceral fat on cancer outcomes may be driven by systemic inflammation.

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    Article Information

    Accepted for Publication: March 30, 2021.

    Published: August 30, 2021. doi:10.1001/jamanetworkopen.2021.15274

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Fleming CA et al. JAMA Network Open.

    Corresponding Author: Christina A. Fleming, MD, Department of Academic Surgery, Cork University Hospital, Wilton Road, Cork, Ireland (christina.fleming49@gmail.com).

    Author Contributions: Drs Fleming and O’Leary had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Fleming, O’Connell, O’Leary, Twomey, Corrigan, Wang, Redmond.

    Acquisition, analysis, or interpretation of data: Fleming, O’Connell, Kavanagh, O’Leary, Twomey, Maher, O’Connor.

    Drafting of the manuscript: Fleming, O’Leary, Corrigan, O’Connor.

    Critical revision of the manuscript for important intellectual content: Fleming, O’Connell, Kavanagh, O’Leary, Twomey,H Wang, Maher, Redmond.

    Statistical analysis: Fleming, O’Connell.

    Administrative, technical, or material support: Fleming, Kavanagh, Twomey.

    Supervision: O’Leary, Corrigan, Wang, Maher, O’Connor, Redmond.

    Conflict of Interest Disclosures: None reported.

    References
    1.
    Watanabe  J, Tatsumi  K, Ota  M,  et al.  The impact of visceral obesity on surgical outcomes of laparoscopic surgery for colon cancer.   Int J Colorectal Dis. 2014;29(3):343-351. doi:10.1007/s00384-013-1803-9 PubMedGoogle ScholarCrossref
    2.
    Black  D, Mackay  C, Ramsay  G,  et al.  Prognostic value of computed tomography: measured parameters of body composition in primary operable gastrointestinal cancers.   Ann Surg Oncol. 2017;24(8):2241-2251. doi:10.1245/s10434-017-5829-z PubMedGoogle ScholarCrossref
    3.
    Balkwill  F, Mantovani  A.  Inflammation and cancer: back to Virchow?   Lancet. 2001;357(9255):539-545. doi:10.1016/S0140-6736(00)04046-0 PubMedGoogle ScholarCrossref
    4.
    Mantovani  A, Garlanda  C, Allavena  P.  Molecular pathways and targets in cancer-related inflammation.   Ann Med. 2010;42(3):161-170. doi:10.3109/07853890903405753 PubMedGoogle ScholarCrossref
    5.
    Donohoe  CL, Doyle  SL, Reynolds  JV.  Visceral adiposity, insulin resistance and cancer risk.   Diabetol Metab Syndr. 2011;3(1):12. doi:10.1186/1758-5996-3-12 PubMedGoogle ScholarCrossref
    6.
    Martinez-Useros  J, Garcia-Foncillas  J.  Obesity and colorectal cancer: molecular features of adipose tissue.   J Transl Med. 2016;14(1):21. doi:10.1186/s12967-016-0772-5 PubMedGoogle ScholarCrossref
    7.
    Doyle  SL, Donohoe  CL, Lysaght  J, Reynolds  JV.  Visceral obesity, metabolic syndrome, insulin resistance and cancer.   Proc Nutr Soc. 2012;71(1):181-189. doi:10.1017/S002966511100320X PubMedGoogle ScholarCrossref
    8.
    Sonnenberg  GE, Krakower  GRKA, Kissebah  AH.  A novel pathway to the manifestations of metabolic syndrome.   Obes Res. 2004;12(2):180-186. doi:10.1038/oby.2004.24 PubMedGoogle ScholarCrossref
    9.
    Aggarwal  BB, Vijayalekshmi  RV, Sung  B.  Targeting inflammatory pathways for prevention and therapy of cancer: short-term friend, long-term foe.   Clin Cancer Res. 2009;15(2):425-430. doi:10.1158/1078-0432.CCR-08-0149 PubMedGoogle ScholarCrossref
    10.
    O’Leary  DP, Wang  JH, Cotter  TG, Redmond  HP.  Less stress, more success: oncological implications of surgery-induced oxidative stress.   Gut. 2013;62(3):461-470. doi:10.1136/gutjnl-2011-300948 PubMedGoogle ScholarCrossref
    11.
    O’Leary  DP, O’Leary  E, Foley  N, Cotter  TG, Wang  JH, Redmond  HP.  Effects of surgery on the cancer stem cell niche.   Eur J Surg Oncol. 2016;42(3):319-325. doi:10.1016/j.ejso.2015.12.008 PubMedGoogle ScholarCrossref
    12.
    Dignam  JJ, Polite  BN, Yothers  G,  et al.  Body mass index and outcomes in patients who receive adjuvant chemotherapy for colon cancer.   J Natl Cancer Inst. 2006;98(22):1647-1654. doi:10.1093/jnci/djj442 PubMedGoogle ScholarCrossref
    13.
    Meyerhardt  JA, Niedzwiecki  D, Hollis  D,  et al; Cancer and Leukemia Group B 89803.  Impact of body mass index and weight change after treatment on cancer recurrence and survival in patients with stage III colon cancer: findings from Cancer and Leukemia Group B 89803.   J Clin Oncol. 2008;26(25):4109-4115. doi:10.1200/JCO.2007.15.6687 PubMedGoogle ScholarCrossref
    14.
    Malietzis  G, Aziz  O, Bagnall  NM, Johns  N, Fearon  KC, Jenkins  JT.  The role of body composition evaluation by computerized tomography in determining colorectal cancer treatment outcomes: a systematic review.   Eur J Surg Oncol. 2015;41(2):186-196. doi:10.1016/j.ejso.2014.10.056 PubMedGoogle ScholarCrossref
    15.
    Lennon  H, Sperrin  M, Badrick  E, Renehan  AG.  The obesity paradox in cancer: a review.   Curr Oncol Rep. 2016;18(9):56. doi:10.1007/s11912-016-0539-4 PubMedGoogle ScholarCrossref
    16.
    Moore  SC, Playdon  MC, Sampson  JN,  et al.  A metabolomics analysis of body mass index and postmenopausal breast cancer risk.   J Natl Cancer Inst. 2018;110(6):588-597. doi:10.1093/jnci/djx244 PubMedGoogle Scholar
    17.
    Ryan  AM, Power  DG, Daly  L, Cushen  SJ, Ní Bhuachalla  Ē, Prado  CM.  Cancer-associated malnutrition, cachexia and sarcopenia: the skeleton in the hospital closet 40 years later.   Proc Nutr Soc. 2016;75(2):199-211. doi:10.1017/S002966511500419X PubMedGoogle ScholarCrossref
    18.
    Blum  D, Omlin  A, Baracos  VE,  et al; European Palliative Care Research Collaborative.  Cancer cachexia: a systematic literature review of items and domains associated with involuntary weight loss in cancer.   Crit Rev Oncol Hematol. 2011;80(1):114-144. doi:10.1016/j.critrevonc.2010.10.004 PubMedGoogle ScholarCrossref
    19.
    Bye  A, Jordhøy  MS, Skjegstad  G, Ledsaak  O, Iversen  PO, Hjermstad  MJ.  Symptoms in advanced pancreatic cancer are of importance for energy intake.   Support Care Cancer. 2013;21(1):219-227. doi:10.1007/s00520-012-1514-8 PubMedGoogle ScholarCrossref
    20.
    Fearon  K, Strasser  F, Anker  SD,  et al.  Definition and classification of cancer cachexia: an international consensus.   Lancet Oncol. 2011;12(5):489-495. doi:10.1016/S1470-2045(10)70218-7 PubMedGoogle ScholarCrossref
    21.
    Mourtzakis  M, Prado  CMLJ, Lieffers  JR, Reiman  T, McCargar  LJ, Baracos  VE.  A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care.   Appl Physiol Nutr Metab. 2008;33(5):997-1006. doi:10.1139/H08-075 PubMedGoogle ScholarCrossref
    22.
    Shen  W, Punyanitya  M, Wang  Z,  et al.  Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross-sectional image.   J Appl Physiol (1985). 2004;97(6):2333-2338. doi:10.1152/japplphysiol.00744.2004 PubMedGoogle ScholarCrossref
    23.
    Choi  MH, Oh  SN, Lee  IK, Oh  ST, Won  DD.  Sarcopenia is negatively associated with long-term outcomes in locally advanced rectal cancer.   J Cachexia Sarcopenia Muscle. 2018;9(1):53-59. doi:10.1002/jcsm.12234 PubMedGoogle ScholarCrossref
    24.
    Peng  P, Hyder  O, Firoozmand  A,  et al.  Impact of sarcopenia on outcomes following resection of pancreatic adenocarcinoma.   J Gastrointest Surg. 2012;16(8):1478-1486. doi:10.1007/s11605-012-1923-5 PubMedGoogle ScholarCrossref
    25.
    Antoun  S, Baracos  VE, Birdsell  L, Escudier  B, Sawyer  MB.  Low body mass index and sarcopenia associated with dose-limiting toxicity of sorafenib in patients with renal cell carcinoma.   Ann Oncol. 2010;21(8):1594-1598. doi:10.1093/annonc/mdp605 PubMedGoogle ScholarCrossref
    26.
    Sharma  P, Zargar-Shoshtari  K, Caracciolo  JT,  et al.  Sarcopenia as a predictor of overall survival after cytoreductive nephrectomy for metastatic renal cell carcinoma.   Urol Oncol. 2015;33(8):339.e17-339.e23. doi:10.1016/j.urolonc.2015.01.011 PubMedGoogle ScholarCrossref
    27.
    Cushen  SJ, Power  DG, Murphy  KP,  et al.  Impact of body composition parameters on clinical outcomes in patients with metastatic castrate-resistant prostate cancer treated with docetaxel.   Clin Nutr ESPEN. 2016;13:e39-e45. doi:10.1016/j.clnesp.2016.04.001 PubMedGoogle ScholarCrossref
    28.
    Elliott  JA, Doyle  SL, Murphy  CF,  et al.  Sarcopenia: prevalence, and impact on operative and oncologic outcomes in the multimodal management of locally advanced esophageal cancer.   Ann Surg. 2017;266(5):822-830. doi:10.1097/SLA.0000000000002398 PubMedGoogle ScholarCrossref
    29.
    Wagner  D, DeMarco  MM, Amini  N,  et al.  Role of frailty and sarcopenia in predicting outcomes among patients undergoing gastrointestinal surgery.   World J Gastrointest Surg. 2016;8(1):27-40. doi:10.4240/wjgs.v8.i1.27 PubMedGoogle ScholarCrossref
    30.
    O’Brien  S, Twomey  M, Moloney  F,  et al.  Sarcopenia and post-operative morbidity and mortality in patients with gastric cancer.   J Gastric Cancer. 2018;18(3):242-252. doi:10.5230/jgc.2018.18.e25 PubMedGoogle ScholarCrossref
    31.
    Redmond  HP, Neary  PM, Jinih  M,  et al.  Randomised Clinical Trial Assessing Use of an Anti-inflammatory Agent in Attenuating Peri-operative Inflammation in Non-metastatic Colon Cancer—the S.U.R.G.U.V.A.N.T. trial.   BMC Cancer. 2018;18(1):794. doi:10.1186/s12885-018-4641-x PubMedGoogle ScholarCrossref
    32.
    Leong  K, Hartley  J, Karandikar  S.  Association of coloproctology of Great Britain & Ireland (ACPGBI): guidelines for the management of cancer of the colon, rectum and anus (2017)—follow up, lifestyle and survivorship.   Colorectal Dis. 2017;19(suppl 1):67-70. doi:10.1111/codi.13706 PubMedGoogle ScholarCrossref
    33.
    Demerath  EW, Shen  W, Lee  M,  et al.  Approximation of total visceral adipose tissue with a single magnetic resonance image.   Am J Clin Nutr. 2007;85(2):362-368. doi:10.1093/ajcn/85.2.362 PubMedGoogle ScholarCrossref
    34.
    Dello  SA, Lodewick  TM, van Dam  RM,  et al.  Sarcopenia negatively affects preoperative total functional liver volume in patients undergoing liver resection.   HPB (Oxford). 2013;15(3):165-169. doi:10.1111/j.1477-2574.2012.00517.x PubMedGoogle ScholarCrossref
    35.
    Lieffers  JR, Bathe  OF, Fassbender  K, Winget  M, Baracos  VE.  Sarcopenia is associated with postoperative infection and delayed recovery from colorectal cancer resection surgery.   Br J Cancer. 2012;107(6):931-936. doi:10.1038/bjc.2012.350 PubMedGoogle ScholarCrossref
    36.
    van der Werf  A, Langius  JAE, de van der Schueren  MAE,  et al.  Percentiles for skeletal muscle index, area and radiation attenuation based on computed tomography imaging in a healthy Caucasian population.   Eur J Clin Nutr. 2018;72(2):288-296. doi:10.1038/s41430-017-0034-5 PubMedGoogle ScholarCrossref
    37.
    Cruz-Jentoft  AJ, Baeyens  JP, Bauer  JM,  et al; European Working Group on Sarcopenia in Older People.  Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older People.   Age Ageing. 2010;39(4):412-423. doi:10.1093/ageing/afq034 PubMedGoogle ScholarCrossref
    38.
    Doyle  SL, Bennett  AM, Donohoe  CL,  et al.  Establishing computed tomography-defined visceral fat area thresholds for use in obesity-related cancer research.   Nutr Res. 2013;33(3):171-179. doi:10.1016/j.nutres.2012.12.007 PubMedGoogle ScholarCrossref
    39.
    Tsujinaka  S, Konishi  F, Kawamura  YJ,  et al.  Visceral obesity predicts surgical outcomes after laparoscopic colectomy for sigmoid colon cancer.   Dis Colon Rectum. 2008;51(12):1757-1765. doi:10.1007/s10350-008-9395-0 PubMedGoogle ScholarCrossref
    40.
    Ishii  Y, Hasegawa  H, Nishibori  H, Watanabe  M, Kitajima  M.  Impact of visceral obesity on surgical outcome after laparoscopic surgery for rectal cancer.   Br J Surg. 2005;92(10):1261-1262. doi:10.1002/bjs.5069 PubMedGoogle ScholarCrossref
    41.
    Rickles  AS, Iannuzzi  JC, Mironov  O,  et al.  Visceral obesity and colorectal cancer: are we missing the boat with BMI?   J Gastrointest Surg. 2013;17(1):133-143. doi:10.1007/s11605-012-2045-9 PubMedGoogle ScholarCrossref
    42.
    Ballian  N, Lubner  MG, Munoz  A,  et al.  Visceral obesity is associated with outcomes of total mesorectal excision for rectal adenocarcinoma.   J Surg Oncol. 2012;105(4):365-370. doi:10.1002/jso.22031 PubMedGoogle ScholarCrossref
    43.
    Guiu  S, Mouret Reynier  MA, Toure  M, Coudert  B.  Predictive factors of response in HER2-positive breast cancer treated by neoadjuvant therapy.   J Oncol. 2013;2013:854121. doi:10.1155/2013/854121 PubMedGoogle Scholar
    44.
    Clark  W, Siegel  EM, Chen  YA,  et al.  Quantitative measures of visceral adiposity and body mass index in predicting rectal cancer outcomes after neoadjuvant chemoradiation.   J Am Coll Surg. 2013;216(6):1070-1081. doi:10.1016/j.jamcollsurg.2013.01.007 PubMedGoogle ScholarCrossref
    45.
    Xiao  J, Mazurak  VC, Olobatuyi  TA, Caan  BJ, Prado  CM.  Visceral adiposity and cancer survival: a review of imaging studies.   Eur J Cancer Care (Engl). 2018;27(2):e12611. doi:10.1111/ecc.12611PubMedGoogle Scholar
    46.
    Lee  CS, Murphy  DJ, McMahon  C,  et al.  Visceral adiposity is a risk factor for poor prognosis in colorectal cancer patients receiving adjuvant chemotherapy.   J Gastrointest Cancer. 2015;46(3):243-250. doi:10.1007/s12029-015-9709-0 PubMedGoogle ScholarCrossref
    47.
    Guiu  B, Petit  JM, Bonnetain  F,  et al.  Visceral fat area is an independent predictive biomarker of outcome after first-line bevacizumab-based treatment in metastatic colorectal cancer.   Gut. 2010;59(3):341-347. doi:10.1136/gut.2009.188946 PubMedGoogle ScholarCrossref
    48.
    Moon  H-G, Ju  Y-T, Jeong  C-Y,  et al.  Visceral obesity may affect oncologic outcome in patients with colorectal cancer.   Ann Surg Oncol. 2008;15(7):1918-1922. doi:10.1245/s10434-008-9891-4 PubMedGoogle ScholarCrossref
    49.
    Cheah  MT, Chen  JY, Sahoo  D,  et al.  CD14-expressing cancer cells establish the inflammatory and proliferative tumor microenvironment in bladder cancer.   Proc Natl Acad Sci U S A. 2015;112(15):4725-4730. doi:10.1073/pnas.1424795112 PubMedGoogle ScholarCrossref
    50.
    Hmama  Z, Mey  A, Normier  G, Binz  H, Revillard  JP.  CD14 and CD11b mediate serum-independent binding to human monocytes of an acylpolygalactoside isolated from Klebsiella pneumoniae.   Infect Immun. 1994;62(5):1520-1527. doi:10.1128/IAI.62.5.1520-1527.1994 PubMedGoogle ScholarCrossref
    51.
    Thomas  G, Tahir  MR, Bongers  BC, Kallen  VL, Slooter  GD, van Meeteren  NL.  Prehabilitation before major intra-abdominal cancer surgery: a systematic review of randomised controlled trials.   Eur J Anaesthesiol. 2019;36(12):933-945. doi:10.1097/EJA.0000000000001030 PubMedGoogle ScholarCrossref
    52.
    Baldwin  C, Spiro  A, Ahern  R, Emery  PW.  Oral nutritional interventions in malnourished patients with cancer: a systematic review and meta-analysis.   J Natl Cancer Inst. 2012;104(5):371-385. doi:10.1093/jnci/djr556 PubMedGoogle ScholarCrossref
    53.
    Shaashua  L, Shabat-Simon  M, Haldar  R,  et al.  Perioperative COX-2 and β-adrenergic blockade improves metastatic biomarkers in breast cancer patients in a phase-II randomized trial.   Clin Cancer Res. 2017;23(16):4651-4661. doi:10.1158/1078-0432.CCR-17-0152 PubMedGoogle ScholarCrossref
    54.
    Sooriakumaran  P, Coley  HM, Fox  SB,  et al.  A randomized controlled trial investigating the effects of celecoxib in patients with localized prostate cancer.   Anticancer Res. 2009;29(5):1483-1488.PubMedGoogle Scholar
    55.
    Dhawan  D, Craig  BA, Cheng  L,  et al.  Effects of short-term celecoxib treatment in patients with invasive transitional cell carcinoma of the urinary bladder.   Mol Cancer Ther. 2010;9(5):1371-1377. doi:10.1158/1535-7163.MCT-10-0049 PubMedGoogle ScholarCrossref
    56.
    Clancy  C, O’Leary  DP, Burke  JP,  et al.  A meta-analysis to determine the oncological implications of conversion in laparoscopic colorectal cancer surgery.   Colorectal Dis. 2015;17(6):482-490. doi:10.1111/codi.12875PubMedGoogle ScholarCrossref
    57.
    Beecher  SM, OʼLeary  DP, McLaughlin  R, Kerin  MJ.  The impact of surgical complications on cancer recurrence rates: a literature review.   Oncol Res Treat. 2018;41(7-8):478-482. doi:10.1159/000487510 PubMedGoogle ScholarCrossref
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