Literature DB >> 28324283

Prognostic Value of Computed Tomography: Measured Parameters of Body Composition in Primary Operable Gastrointestinal Cancers.

Douglas Black1, Craig Mackay2, George Ramsay2, Zaid Hamoodi2, Shayanthan Nanthakumaran2, Kenneth G M Park2, Malcolm A Loudon2, Colin H Richards2.   

Abstract

BACKGROUND: Previous reports suggest that body composition parameters can be used to predict outcomes for patients with gastrointestinal (GI) cancers. However, evidence for an association with long-term survival is conflicting, with much of the data derived from patients with advanced disease. This study examined the effect of body composition on survival in primary operable GI cancer.
METHODS: Patients with resectable adenocarcinoma of the GI tract (esophagus, stomach, colon, rectum) between 2006 and 2014 were identified from a prospective database. Computed tomography (CT) scans were analyzed using a transverse section at L3 to calculate sex-specific body composition indices for skeletal muscle, visceral fat, and subcutaneous fat. Kaplan-Meier and log-rank analysis were used to compare unadjusted survival. Multivariate survival analyses were performed using a proportional hazards model.
RESULTS: The study enrolled 447 patients (191 woman and 256 men) with esophagogastric (OG) (n = 108) and colorectal (CR) (n = 339) cancer. Body composition did not predict survival for the OG cancer patients. Among the CR cancer patients, survival was shorter for those with sarcopenia (p = 0.017) or low levels of subcutaneous fat (p = 0.005). Older age (p = 0.046) and neutrophilia (p = 0.013) were associated with sarcopenia in patients with CR. Tumor stage (p = 0.033), neutrophil count (p = 0.011), and hypoalbuminemia (p = 0.023) were associated with sarcopenia in OG cancer patients. In the multivariate analysis, no single measure of body composition was an independent predictor of reduced survival.
CONCLUSION: Sarcopenia and reduced subcutaneous adiposity are associated with reduced survival for patients with primary operable CR cancer. However, in this study, no parameter of body composition was an independent prognostic marker when considered with age, tumor stage, and systemic inflammation.

Entities:  

Mesh:

Year:  2017        PMID: 28324283      PMCID: PMC5491683          DOI: 10.1245/s10434-017-5829-z

Source DB:  PubMed          Journal:  Ann Surg Oncol        ISSN: 1068-9265            Impact factor:   5.344


An increasing number of reports have suggested that body composition parameters may be used to predict outcomes for patients with cancer.1–7 In particular, depletion of skeletal muscle mass, termed “sarcopenia,” is widely reported to confer a poor prognosis for patients with tumors of the gastrointestinal (GI) tract, associated with an increased rate of postoperative complications2 and impaired response to chemotherapy.1 A smaller number of studies also have reported relationships between subcutaneous or visceral adiposity and outcomes for several tumor types, including esophageal,8 pancreatic,9 and colorectal cancers.10,11 The majority of these studies have used image analysis of computed tomography (CT) scans to measure parameters of body composition, and the accuracy of this technique is now widely accepted.12 This approach has considerable practical appeal because most patients with GI cancers undergo CT scanning as part of routine staging. Despite consistent reports regarding short-term outcomes, the evidence that body composition parameters relate to long-term survival for patients with GI cancers has been conflicting. Studies to date have tended to focus exclusively on one parameter of body composition such as skeletal muscle mass,3,4,6 and much of the survival data has been derived from small cohorts of patients with locally advanced or metastatic disease.4,6,7 To investigate this topic further, the current study aimed to analyze CT-measured parameters of body composition in a large cohort of patients with primary operable GI cancers and to examine their relationships with long-term survival.

Methods

Patients with confirmed adenocarcinoma of the gastrointestinal tract (esophagus, stomach, colon, and rectum) who underwent surgical resection with curative intent between 1 January 2006 and 31 December 2014 at Aberdeen Royal Infirmary were identified from a prospectively maintained regional database. Of these patients, only those who had preoperative CT images stored in an electronic format suitable for image analysis were included in the study. All tumors were confirmed histologically and staged according to conventional American Joint Committee on Cancer (AJCC) Tumor, Node, and Metastases (TNM) Classification (6th edition). Additional pathologic data, including the presence or absence of lymphovascular invasion, were recorded from reports issued at the time of resection. Patient variables recorded retrospectively from medical records included age, sex, and preoperative blood results recorded within 30 days before surgery. Using local reference values, anemia was defined as hemoglobin concentrations lower than 130 g/L in males and lower than 115 g/L in females. The systemic inflammatory response was assessed by differential serum white cell count (total white cell count, neutrophil count, and lymphocyte count) in line with published thresholds.13,14 The standard oncologic treatment for potentially resectable esophagogastric (OG) cancers was three cycles of neoadjuvant combination chemotherapy with epirubicin, cisplatin and capecitabine (ECX), followed by surgical resection and adjuvant chemotherapy with the same agents. Colon cancer was generally managed by surgical resection followed by adjuvant combination (fluorouracil- and oxaliplatin-based) chemotherapy for patients with involved lymph nodes or other pathologic indicators of a poor prognosis such as extramural venous invasion (EMVI). Locally advanced or margin-threatened rectal cancer was treated with “long course” chemoradiotherapy followed by surgery 8–10 weeks later, with adjuvant chemotherapy offered selectively for those with a good or partial response to preoperative treatment. Individual regimens changed over time and were dependent on patient fitness, inclusion in contemporary clinical trials, and multidisciplinary team (MDT) preference. To perform the body composition analysis, staging computed tomography (CT) scans were first accessed through the hospital’s Picture Archiving and Communication System (PACS). Preoperative staging CTs before the start of neoadjuvant therapy were selected. A single slice at the level of the third lumbar vertebra (L3) was analyzed using medical imaging software (ImageJ; The National Institutes of Health, Washington, MD, USA; version 1.47), and the total fat area (cm2), subcutaneous fat area (cm2), visceral fat area (cm2), and skeletal muscle area (cm2) were measured using accepted Hounsfield unit (HU) thresholds (adipose tissue, −190 to −30; skeletal muscle, −29 to +150). Finally, each parameter was normalized for patient stature and designated as total fat index (cm2/m2), subcutaneous fat index (cm2/m2), visceral fat index (cm2/m2), and skeletal muscle index (cm2/m2) in line with accepted methodology.15,16 Sarcopenia was defined as a skeletal muscle index lower than 43 cm2/m2 for males and lower than 41 cm2/m2 for females using previously published cutoff values.6 The primary end point of the study was overall survival, which was measured in months from the date of surgery to the date of death from any cause. The date of death was obtained from patients’ electronic medical records. All survival analyses were performed after exclusion of 30-day postoperative deaths. Ethical guidance was sought from the regional Caldicott Guardian, who confirmed that the study fulfilled the criteria of a clinical audit, negating the requirement for further ethical committee approval.

Statistical Analysis

All variables were grouped according to clinically relevant or previously published thresholds. All statistical tests were two-sided, and a p value lower than 0.05 was considered to indicate statistical significance. χ 2 and Mann–Whitney U tests were used to compare clinical characteristics between groups. Kaplan–Meier analysis and the log-rank test were used to compare unadjusted survival differences. Uni- and multivariate survival analyses were performed using a Cox proportional hazards model. Statistical analysis was performed using SPSS, version 22 (SPSS, Chicago, IL, USA).

Results

During the study period, 608 patients with primary operable gastrointestinal cancers who had undergone surgical resection with curative intent were identified. Of these patients, 161 were excluded from the study (108 patients did not have a documented height and weight; 34 patients did not have CT images suitable for analysis; and 19 patients underwent a palliative procedure after more extensive disease had been diagnosed intraoperatively), leaving 447 patients (191 women and 256 men) included in the final analysis. A flow diagram of the study selection process is shown in Fig. 1.
Fig. 1

Flow diagram showing patient selection and reasons for exclusion of patients from the study

Flow diagram showing patient selection and reasons for exclusion of patients from the study The baseline clinicopathologic characteristics and body composition parameters of the cohort are shown in Table 1. Of the 447 patients included in the study, 108 had eophagogastric (OG) cancers (43 esophageal; 65 gastric), and 339 had colorectal (CR) cancers (253 colonic; 86 rectal). More than 40% of the patients were anemic preoperatively, and 18% exhibited a systemic inflammatory response, as evidenced by an elevated neutrophil count. There were significant differences between upper GI and colorectal cancer in terms of age (p < 0.001), sex (p = 0.003), and lymphovascular invasion (p < 0.001).
Table 1

Clinical, pathologic, and body composition parameters of the included patients

VariableAll patients (n = 447) n (%)OG cancer n (%)CR cancer n (%) p valuea
Age (years)
 ≤65133 (30)46 (43)87 (26)<0.001
 65–74148 (33)40 (37)108 (32)
 ≥75166 (37)22 (20)144 (42)
Sex
 Female191 (43)33 (31)158 (47)0.003
 Male256 (57)74 (69)181 (53)
Neoadjuvant therapy
 No316 (71)43 (40)273 (81)<0.001
 Yes131 (29)65 (60)66 (19)
Adjuvant therapy
 No343 (77)66 (61)277 (82)<0.001
 Yes104 (23)42 (39)62 (18)
TNM stage
 188 (20)30 (28)58 (17)0.052
 2196 (44)43 (40)153 (45)
 3163 (36)35 (32)128 (38)
Lymphovascular invasion
 Yes111 (25)51 (47)60 (18)<0.001
 No336 (75)57 (53)279 (82)
Anemiab,c
 Yes186 (42)44 (42)142 (42)0.873
 No255 (58)62 (58)193 (58)
White cell count (× 109/L)c
 <8.5280 (63)70 (66)210 (63)0.711
 8.5–11109 (25)23 (22)86 (26)
 >1152 (12)13 (12)39 (12)
Neutrophil count (× 109/L)c
 <7.5362 (82)87 (82)275 (82)0.997
 ≥7.579 (18)19 (18)60 (18)
Lymphocyte count (× 109/L)c
 <1.094 (21)18 (17)76 (23)0.211
 ≥1.0347 (79)88 (83)259 (77)
Albumin (g/L)c
 ≥35387 (88)89 (84)298 (89)0.172
 <3554 (12)17 (16)37 (11)
Subcutaneous fat index (cm2/m2)
 Median66.264.970.00.114
 Range200.5193.4191.9
 Low d 152 (34)38 (35)114 (34)
 Mediumd 148 (33)33 (31)115 (34)
 Highd 147 (33)37 (34)110 (32)
Visceral fat index (cm2/m2)
 Median61.363.461.00.886
 Range198.4155.0198.4
 Lowe 152 (34)38 (35)114 (34)
 Mediume 146 (33)38 (35)108 (32)
 Highd 149 (33)32 (30)117 (35)
Skeletal muscle index (cm2/m2)
 Median47.447.747.30.888
 Range80.144.280.1
 Sarcopeniaf 104 (23)23 (21)81 (24)
 Normal343 (77)85 (79)258 (76)

OG esophagogastric, CR colorectal, TNM tumor-node-metastasis

a p Values represent X 2 tests for a linear trend in categorical variables and Mann–Whitney U tests for continuous variables

bAnemia is defined as <13 g/dL in males, <11.5 g/dL in females

cData are missing in six cases

dSex-specific tertiles for subcutaneous fat index

eSex-specific tertiles for visceral fat index

fSarcopenia is defined as <43 cm2/m2 in males and <41 cm2/m2 in females

Clinical, pathologic, and body composition parameters of the included patients OG esophagogastric, CR colorectal, TNM tumor-node-metastasis a p Values represent X 2 tests for a linear trend in categorical variables and Mann–Whitney U tests for continuous variables bAnemia is defined as <13 g/dL in males, <11.5 g/dL in females cData are missing in six cases dSex-specific tertiles for subcutaneous fat index eSex-specific tertiles for visceral fat index fSarcopenia is defined as <43 cm2/m2 in males and <41 cm2/m2 in females To account for the differences in body composition distribution between the men and women, the subcutaneous fat index and the visceral fat index were classified into sex-specific tertiles, whereas previously published sex-specific cutoff values for skeletal muscle index were used to define sarcopenia in the men (<43 cm2/m2) and the women (<41 cm2/m2). According to these definitions, 23 patients (21%) with esophagogastric cancer and 81 patients (24%) with colorectal cancer showed evidence of sarcopenia on their staging CT scan (Table 1). Figure 2 shows the relationships between body composition parameters and long-term survival. Levels of subcutaneous fat, visceral fat, and skeletal muscle did not influence overall survival for the patients with esophagogastric cancer. Among the patients with colorectal cancer, survival was significantly shorter for those with low levels of subcutaneous fat (p = 0.005, log-rank test) or evidence of sarcopenia (p = 0.017, log-rank test).
Fig. 2

The relationships between body composition parameters and overall survival for patients with primary operable gastrointestinal cancers. Top panel (left to right): subcutaneous fat index (SFA) (p = 0.793, log-rank test), visceral fat index (VFA) (p = 0.278, log-rank test), and skeletal muscle index (SMI; sarcopenia) (p = 0.607, log-rank test) in esophagogastric cancer. Bottom panel (left to right): subcutaneous fat index (SFA) (p = 0.005, log-rank test), visceral fat index (VFA) (p = 0.375, log-rank test), and skeletal muscle index (SMI; sarcopenia) (p = 0.017, log-rank test) in colorectal cancer

The relationships between body composition parameters and overall survival for patients with primary operable gastrointestinal cancers. Top panel (left to right): subcutaneous fat index (SFA) (p = 0.793, log-rank test), visceral fat index (VFA) (p = 0.278, log-rank test), and skeletal muscle index (SMI; sarcopenia) (p = 0.607, log-rank test) in esophagogastric cancer. Bottom panel (left to right): subcutaneous fat index (SFA) (p = 0.005, log-rank test), visceral fat index (VFA) (p = 0.375, log-rank test), and skeletal muscle index (SMI; sarcopenia) (p = 0.017, log-rank test) in colorectal cancer To investigate these relationships further, the associations between body composition and clinicopathologic variables were examined. An association between sarcopenia and advanced T stage (p = 0.033), elevated neutrophil count (p = 0.011), and hypoalbuminemia (p = 0.023) was observed in the patients with esophagogastric cancer (Table 2). In the patients with colorectal cancer, associations between sarcopenia and older age (p = 0.046) and elevated neutrophil count (p = 0.026) were demonstrated. Similar relationships were seen between low levels of subcutaneous fat and older age (p < 0.001) and elevated neutrophil count (p = 0.013) (Table 3).
Table 2

Associations between body composition parameters and clinicopathologic variables for patients with esophagogastric cancer

VariableSubcutaneous fat index p valuea Visceral fat index p valuea Skeletal muscle index p valuea
Low n (%)Medium n (%)High n (%)Low n (%)Medium n (%)High n (%)Normal n (%)Sarcopenia n (%)
Age (years)
 ≤6413 (34)15 (45)18 (49)0.56020 (53)14 (37)12 (38)0.53337 (44)9 (39)0.744
 65–7416 (42)10 (30)14 (38)11 (29)17 (45)12 (38)32 (38)8 (35)
 ≥759 (24)8 (24)5 (14)7 (18)7 (18)8 (25)16 (19)6 (26)
Tumour (T) stage
 0/18 (21)5 (15)9 (24)0.7426 (16)7 (18)9 (28)0.53421 (25)1 (4)0.033
 24 (11)9 (27)5 (14)5 (13)9 (24)4 (13)13 (15)5 (22)
 322 (58)17 (52)20 (54)23 (61)18 (47)18 (56)47 (55)12 (52)
 44 (11)2 (6)3 (8)4 (11)4 (11)1 (3)4 (5)5 (22)
Nodal (N) stage
 017 (45)13 (39)20 (54)0.77613 (34)15 (39)22 (69)0.10341 (48)9 (39)0.362
 112 (32)13 (39)10 (27)14 (37)15 (39)6 (19)29 (34)6 (26)
 29 (24)7 (21)7 (19)11 (29)8 (21)4 (13)15 (18)8 (35)
TNM stage
 I9 (24)10 (30)11 (30)0.8466 (16)11 (29)13 (41)0.13627 (32)3 (13)0.175
 II16 (42)11 (33)16 (43)15 (39)16 (42)12 (38)33 (39)10 (43)
 III13 (34)12 (36)10 (27)17 (45)11 (29)7 (22)25 (29)10 (43)
Neoadjuvant therapy
 Yes18 (47)8 (24)17 (46)0.0909 (24)20 (53)14 (44)0.03134 (40)9 (39)0.940
 No20 (53)25 (76)20 (54)29 (76)18 (47)18 (56)51 (60)14 (61)
Adjuvant therapy
 Yes17 (45)10 (30)15 (41)0.44618 (47)13 (34)11 (34)0.41230 (35)12 (52)0.141
 No21 (55)23 (70)22 (59)20 (53)25 (66)21 (66)55 (65)11 (48)
Lymphovascular invasion
 Yes17 (45)13 (39)21 (57)0.32421 (55)16 (42)14 (44)0.46338 (45)13 (57)0.314
 No21 (55)20 (61)16 (43)17 (45)22 (58)18 (56)47 (55)10 (43)
Anemiab
 Yes17 (45)14 (45)13 (35)0.62119 (50)11 (30)14 (45)0.18133 (39)11 (50)0.364
 No21 (55)17 (55)24 (65)19 (50)26 (70)17 (55)51 (61)11 (50)
White cell count (×109/L)
 <8.523 (61)21 (68)26 (70)0.84024 (63)23 (62)23 (74)0.73661 (73)9 (41)0.011
 8.5–1110 (26)7 (23)6 (16)8 (21)10 (27)5 (16)16 (19)7 (32)
 >115 (13)3 (10)5 (14)6 (16)4 (11)3 (10)7 (8)6 (27)
Neutrophil count (×109/L)
 <7.529 (76)26 (84)32 (86)0.49330 (79)31 (84)26 (84)0.82173 (87)14 (64)0.011
 ≥7.59 (24)5 (16)5 (14)8 (21)6 (16)5 (16)11 (13)8 (36)
Lymphocyte count (× 109/L)
 <1.07 (18)6 (19)5 (14)0.7817 (18)6 (16)5 (16)0.95714 (17)4 (18)0.866
 ≥1.031 (82)25 (81)32 (86)31 (82)31 (84)26 (84)70 (83)18 (82)
Albumin (g/L)
 ≥3531 (82)24 (77)34 (92)0.23831 (82)30 (81)28 (90)0.51774 (88)15 (68)0.023
 <357 (18)7 (23)3 (8)7 (18)7 (19)3 (10)10 (12)7 (32)

TNM tumor-node-metastasis

a p Values represent X 2 tests for a linear trend in categorical variables and Mann–Whitney U tests for continuous variables

bAnemia is defined as <13 g/dL in males, <11.5 g/dL in females

Table 3

The associations between body composition parameters and clinicopathologic variables in patients with colorectal cancer

VariableSubcutaneous fat index p valuea Visceral fat index p valuea Skeletal muscle index p Valuea
Low n (%)Medium n (%)High n (%)Low n (%)Medium n (%)High n (%)Normal n (%)Sarcopenia n (%)
Age (years)
 ≤6425 (22)23 (20)39 (35)<0.00143 (38)21 (19)23 (20)<0.00170 (27)17 (21)0.046
 65–7427 (23)39 (34)42 (38)18 (16)39 (36)51 (44)88 (34)20 (25)
 ≥7562 (54)53 (46)29 (26)53 (46)48 (44)43 (37)100 (39)44 (54)
Tumour (T) stage
 0/19 (8)5 (4)8 (7)0.4327 (6)10 (9)5 (4)0.21917 (7)5 (6)0.118
 212 (11)13 (11)20 (18)13 (11)13 (12)19 (16)40 (16)5 (6)
 372 (63)76 (66)69 (63)73 (64)74 (69)70 (60)164 (64)53 (65)
 421 (18)21 (18)13 (12)21 (18)11 (10)23 (20)37 (14)18 (22)
Nodal (N) stage
 069 (61)65 (57)77 (70)0.09969 (61)62 (57)80 (68)0.482168 (65)43 (53)0.099
 124 (21)35 (30)19 (17)29 (25)27 (25)22 (19)57 (22)21 (26)
 221 (18)15 (13)14 (13)16 (14)19 (18)15 (13)33 (13)17 (21)
TNM stage
 119 (17)13 (11)26 (24)0.09416 (14)18 (17)24 (21)0.39850 (19)8 (10)0.058
 250 (44)52 (45)51 (46)53 (46)44 (41)56 (48)118 (46)35 (43)
 345 (39)50 (43)33 (30)45 (39)46 (43)37 (32)90 (35)38 (47)
Neoadjuvant therapy
 Yes89 (78)92 (80)92 (84)0.56688 (77)88 (81)97 (83)0.524204 (79)69 (85)0.225
 No25 (22)23 (20)18 (16)26 (23)20 (19)20 (17)54 (21)12 (15)
Adjuvant therapy
 Yes15 (13)22 (19)25 (23)0.17326 (23)16 (15)20 (17)0.28149 (19)13 (16)0.550
 No99 (87)93 (81)85 (77)88 (77)92 (85)97 (83)209 (81)68 (84)
Lymphovascular invasion
 Yes23 (20)20 (17)17 (15)0.64820 (18)18 (17)22 (19)0.91445 (17)15 (19)0.825
 No91 (80)95 (83)93 (85)94 (82)90 (83)95 (81)213 (83)66 (81)
Anemiab
 Yes53 (47)53 (46)36 (33)0.06949 (44)44 (41)49 (42)0.925105 (41)37 (46)0.423
 No60 (53)61 (54)72 (67)63 (56)63 (59)67 (58)150 (59)43 (54)
White cell count (×109/L)
 <8.564 (57)73 (64)73 (68)0.24176 (68)64 (60)70 (60)0.110162 (64)48 (60)0.561
 8.5–1131 (27)32 (28)23 (21)24 (21)25 (23)37 (32)66 (26)20 (25)
 >1118 (16)9 (8)12 (11)12 (11)18 (17)9 (8)27 (11)12 (15)
Neutrophil count (×109/L)
 <7.583 (73)99 (87)93 (86)0.01394 (84)85 (79)96 (83)0.669216 (85)59 (74)0.026
 ≥7.530 (27)15 (13)15 (14)18 (16)22 (21)20 (17)39 (15)21 (26)
Lymphocyte count (×109/L)
 <1.031 (27)23 (20)22 (20)0.33428 (25)29 (27)19 (16)0.12557 (22)19 (24)0.795
 ≥1.082 (73)91 (80)86 (80)84 (75)78 (73)97 (84)198 (78)61 (76)
Albumin (g/L)
 ≥3597 (86)101 (89)100 (93)0.27598 (88)95 (89)105 (91)0.766229 (90)69 (86)0.376
 <3516 (14)13 (11)8 (7)14 (13)12 (11)11 (9)26 (10)11 (14)

TNM, tumor-node-metastasis

a p values represent X 2 tests for a linear trend in categorical variables and Mann–Whitney U tests for continuous variables

bAnemia is defined as <13 g/dL in males, <11.5 g/dL in females

Associations between body composition parameters and clinicopathologic variables for patients with esophagogastric cancer TNM tumor-node-metastasis a p Values represent X 2 tests for a linear trend in categorical variables and Mann–Whitney U tests for continuous variables bAnemia is defined as <13 g/dL in males, <11.5 g/dL in females The associations between body composition parameters and clinicopathologic variables in patients with colorectal cancer TNM, tumor-node-metastasis a p values represent X 2 tests for a linear trend in categorical variables and Mann–Whitney U tests for continuous variables bAnemia is defined as <13 g/dL in males, <11.5 g/dL in females Finally, logistic regression analyses were used to examine whether survival relationships were independent of established clinicopathologic risk factors. During the follow-up period, 213 patients died, leaving 234 were alive at the date of censor (31 March 2015). The median follow-up period for the survivors was 62 months (range 3–105 months). In the multivariate analysis, the only independent predictor of long-term survival for the patients with esophagogastric cancer was tumor stage [hazard ratio (HR) 2.78; p < 0.001] (Table 4). For the patients with colorectal cancer, advanced tumor stage (HR 1.67; p < 0.001), lymphovascular invasion (HR 2.61; p < 0.001), and elevated neutrophil count (HR 1.76; p = 0.005) were independently associated with reduced overall survival (Table 5). No single measure of body composition was an independent predictor of reduced survival for patients with primary operable GI cancer.
Table 4

Multivariate analysis of the relationships between body composition parameters and overall survival for patients with esophagogastric cancer

VariablesNo. of patientsNo. of deaths n (%)Univariate analysisMultivariate analysis
HR(95% CI) p valueHR(95% CI) p value
Age (years)
 ≤654623 (33)1.1480.832–1.5840.4021.5781.03–2.417NS
 65–744027 (40)
 ≥752212 (35)
Sex
 Female3318 (35)1.0260.593–1.7770.9261.1450.605–2.1670.667
 Male7544 (37)
TNM stage
 1305 (14)2.3901.681–3.398<0.0012.7821.766–4.382<0.001
 24330 (41)
 33527 (44)
Neoadjuvant therapy
 Yes4320 (32)1.5790.926–2.6910.0932.1111.015–4.388NS
 No6542 (39)
Adjuvant therapy
 Yes4223 (35)0.7190.429–1.2060.7190.4030.22–0.737NS
 No6639 (37)
Lymphovascular invasion
 Yes5134 (40)1.7221.037–2.8590.0360.8140.425–1.560NS
 No5728 (33)
Neutrophil count (×109/L)
 <7.58748 (36)1.0330.549–1.9460.9191.0480.517–2.124NS
 ≥7.51912 (39)
Subcutaneous fat index (cm2/m2)
 High3824 (39)0.9120.678–1.2280.5450.9340.627–1.39NS
 Medium3319 (37)
 Low3719 (34)
Visceral fat index (cm2/m2)
 High3826 (41)0.7860.571–1.0830.1410.7380.473–1.152NS
 Medium3821 (36)
 Low3215 (32)
Skeletal muscle index (cm2/m2)
 Normal8548 (36)1.1650.642–2.1140.6160.7610.351–1.649NS
 Sarcopenia2314 (38)

HR hazard ratio, CI confidence interval, TNM tumor-node-metastasis

Table 5

Multivariate analysis of the relationships between body composition parameters and overall survival for patients with colorectal cancer

VariableNo. of patientsNo. of deaths n (%)Univariate analysisMultivariate analysis
HR(95% CI) p valueHR(95% CI) p Value
Age (years)
 ≤658736 (29)1.1970.976–1.4670.0841.0990.871–1.386NS
 65–7410841 (28)
 ≥7514474 (34)
Sex
 Female15874 (32)0.8560.622–1.1760.3390.9940.703–1.405NS
 Male18177 (30)
TNM stage
 15812 (17)1.9211.503–2.455<0.0011.6671.263–2.2<0.001
 215364 (29)
 312875 (37)
Neoadjuvant therapy
 Yes273120 (31)1.0950.738–1.6260.6511.4440.946–2.203NS
 No6631 (32)
Adjuvant therapy
 Yes6228 (31)0.9790.649–1.4760.9760.7640.479–1.218NS
 No277123 (31)
Lymphovascular invasion
 Yes6048 (44)3.6632.585–5.190<0.0012.6061.764–3.851<0.001
 No279103 (27)
Neutrophil count (× 109/L)
 <7.5275108 (28)2.5561.780–3.669<0.0011.7601.182–2.620.005
 ≥7.56041 (41)
Subcutaneous fat index (cm2/m2)
 High11462 (35)0.7200.589–0.8800.0010.8460.662–1.08NS
 Medium11552 (31)
 Low11037 (25)
Visceral fat index (cm2/m2)
 High11456 (33)0.8730.718–1/0610.1721.000.796–1.256NS
 Medium10848 (31)
 Low11747 (29)
Skeletal muscle index (cm2/m2)
 Normal258107 (29)1.5271.075–2.1700.0181.2110.818–1.795NS
 Sarcopenia8144 (35)

HR hazard ratio, CI confidence interval, TNM tumor-node-metastasis

Multivariate analysis of the relationships between body composition parameters and overall survival for patients with esophagogastric cancer HR hazard ratio, CI confidence interval, TNM tumor-node-metastasis Multivariate analysis of the relationships between body composition parameters and overall survival for patients with colorectal cancer HR hazard ratio, CI confidence interval, TNM tumor-node-metastasis

Discussion

The results of the current study show that CT measures of body composition, particularly sarcopenia and reduced levels of subcutaneous fat, are associated with shorter survival for patients with primary operable colorectal cancer, but not for patients with esophagogastric cancer. Furthermore, strong associations exist between these parameters and other indicators of poor outcome such as advanced age and elevated systemic inflammatory response. However, when body composition parameters were analyzed in a multivariate model, no single measure was found to have independent predictive value for patients with either esophagogastric or colorectal cancer. To our knowledge, this is one of the largest studies to investigate the impact of body composition on long-term survival of patients with operable GI cancers. Although associations between sarcopenia and colorectal cancer outcomes have been reported previously,3,4,6,7,17,18 the results have been inconsistent. Most previous studies have included a high proportion of patients with advanced disease, whereas the current study focused specifically on patients with operable disease. A systematic review by Malietzis et al.2 evaluated the role of body composition in predicting outcomes for patients with colorectal cancer and concluded that whereas evidence was consistent that sarcopenia is associated with poorer short-term outcomes, including excess chemotherapy toxicity17–19 and an increased risk of surgical complications,20,21 the evidence for a relationship with long-term survival was less robust. Indeed, the reviewers identified only one study of 196 patients, all of whom had metastatic disease,7 in which sarcopenia had a detrimental effect on survival. Not included in the aforementioned review but widely referenced as demonstrating the prognostic value of skeletal muscle depletion for cancer patients, a study by Martin et al.6 analyzed the body composition parameters of 1473 patients with respiratory and GI cancers. The authors reported that a predictive model composed entirely of body composition variables (weight loss, skeletal muscle depletion, and muscle attenuation) was superior to conventional prognostic markers, including cancer stage. However, more than 50% of the patients studied had metastatic disease, and our results suggest that their findings may not be applicable to patients with primary operable cancers. It is clear from our own appraisal of the literature and the conclusions of recent reviews3,4 that the question whether sarcopenia has prognostic value for patients with GI malignancies is being hampered by study heterogeneity. Despite the volume of published work, there still is no standard definition of CT-based assessments of skeletal muscle mass. Although a number of different cutoff values have been proposed,7,17,22 we chose to use a skeletal muscle index lower than 43 cm2/m2 for men and lower than 41 cm2/m2 for women to define sarcopenia. These values were proposed by the largest published dataset to document the body composition of patients with cancer6 and have been validated in at least one external cohort.7 It must be emphasised that discrepancies in the thresholds used to define sarcopenia have led to considerable variation in the proportion of patients reported to be “sarcopenic” in the aforementioned studies. For example, the study by van Vledder et al.,7 using one threshold, reported that 19% of patients with colorectal liver metastases have sarcopenia, whereas Martin et al.,6 using different definitions, reported that 53% of women and 31% of men are sarcopenic. Using the latter definitions, our levels of sarcopenia were considerably lower (23%), but all the patients in our cohort were undergoing curative surgery, whereas their study contained a large number of patients with metastatic disease. Similarly, the assessment of subcutaneous and visceral adiposity has been undertaken using a variety of methods including dichotomous cutoff values,23,24 continuous parameters,25 and visceral-to-subcutaneous ratios.26 Given this variability and with no single method yet validated, we chose to use sex-specific tertiles to assess adiposity. It may be that using an alternative technique would have yielded different results, but we believe our approach was a rational way of demonstrating any survival effect. One noteworthy finding from the current study was the association between depleted levels of skeletal muscle and subcutaneous fat and an elevation of the systemic inflammatory response in patients with colorectal cancer. The neutrophil count was used as a marker of systemic inflammation because findings previously showed it to be the most reliable prognostic component of the white cell count.27 In experimental models, pro-inflammatory cytokines such as interleukin-1 (IL-1), IL-6, and tumor necrosis factor-α (TNF) have been shown to play a key role in both anorexia and skeletal muscle proteolysis,28 but the relationships between systemic inflammation and changes in body composition in cancer patients are less well understood. Good evidence currently shows that systemic inflammation is universally associated with poor short- and long-term outcomes in a variety of solid organ tumor types,29–31 and an association with skeletal muscle wasting may offer one explanation for the unfavorable outcomes observed in sarcopenic patients.14,32,33 In the current study, despite no significant difference in the prevalence of sarcopenia between cancer types, a clear relationship was demonstrated between sarcopenia and survival in colorectal cancer but not in upper GI cancers. Further work is needed to clarify the relationships between tumor biology, inflammatory mediators, and parameters of body composition. The current study had a number of limitations. The retrospective nature of the data collection meant that contemporary records of patients’ height were missing in a number of cases. As a result, body composition indices could not be normalized for stature, thereby limiting the size of the cohort. Similarly, preoperative weight was poorly documented in the medical notes, so conventional parameters of body composition such as body mass index (BMI) could not be calculated. However, preoperative CT images were available for almost all the patients, and we believe that both the size and maturity of the cohort mean our results are likely to be reliable. In summary, the current study showed that sarcopenia and reduced subcutaneous adiposity are associated with shorter overall survival for patients with primary operable colorectal cancer. However, no parameter of body composition was an independent prognostic marker when considered with age, tumor stage, and systemic inflammatory response. No relationships between body composition and overall survival were observed in patients with esophagogastric cancers.
  33 in total

1.  Cancer cachexia and fat-muscle physiology.

Authors:  Kenneth C H Fearon
Journal:  N Engl J Med       Date:  2011-08-11       Impact factor: 91.245

2.  Visceral obesity is associated with outcomes of total mesorectal excision for rectal adenocarcinoma.

Authors:  Nikiforos Ballian; Meghan G Lubner; Alejandro Munoz; Bruce A Harms; Charles P Heise; Eugene F Foley; Gregory D Kennedy
Journal:  J Surg Oncol       Date:  2011-07-12       Impact factor: 3.454

Review 3.  Systematic review of sarcopenia in patients operated on for gastrointestinal and hepatopancreatobiliary malignancies.

Authors:  S Levolger; J L A van Vugt; R W F de Bruin; J N M IJzermans
Journal:  Br J Surg       Date:  2015-09-16       Impact factor: 6.939

4.  Visceral obesity and colorectal cancer: are we missing the boat with BMI?

Authors:  Aaron S Rickles; James C Iannuzzi; Oleg Mironov; Andrew-Paul Deeb; Abhiram Sharma; Fergal J Fleming; John R T Monson
Journal:  J Gastrointest Surg       Date:  2012-10-23       Impact factor: 3.452

5.  Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index.

Authors:  Lisa Martin; Laura Birdsell; Neil Macdonald; Tony Reiman; M Thomas Clandinin; Linda J McCargar; Rachel Murphy; Sunita Ghosh; Michael B Sawyer; Vickie E Baracos
Journal:  J Clin Oncol       Date:  2013-03-25       Impact factor: 44.544

6.  Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People.

Authors:  Alfonso J Cruz-Jentoft; Jean Pierre Baeyens; Jürgen M Bauer; Yves Boirie; Tommy Cederholm; Francesco Landi; Finbarr C Martin; Jean-Pierre Michel; Yves Rolland; Stéphane M Schneider; Eva Topinková; Maurits Vandewoude; Mauro Zamboni
Journal:  Age Ageing       Date:  2010-04-13       Impact factor: 10.668

7.  Visceral obesity may affect oncologic outcome in patients with colorectal cancer.

Authors:  Hyeong-Gon Moon; Young-Tae Ju; Chi-Young Jeong; Eun-Jung Jung; Young-Joon Lee; Soon-Chan Hong; Woo-Song Ha; Soon-Tae Park; Sang-Kyung Choi
Journal:  Ann Surg Oncol       Date:  2008-04-05       Impact factor: 5.344

8.  Sarcopenia predicts early dose-limiting toxicities and pharmacokinetics of sorafenib in patients with hepatocellular carcinoma.

Authors:  Olivier Mir; Romain Coriat; Benoit Blanchet; Jean-Philippe Durand; Pascaline Boudou-Rouquette; Judith Michels; Stanislas Ropert; Michel Vidal; Stanislas Pol; Stanislas Chaussade; François Goldwasser
Journal:  PLoS One       Date:  2012-05-30       Impact factor: 3.240

9.  The relationships between body composition and the systemic inflammatory response in patients with primary operable colorectal cancer.

Authors:  Colin H Richards; Campbell S D Roxburgh; Mark T MacMillan; Sanad Isswiasi; Ewen G Robertson; Graeme K Guthrie; Paul G Horgan; Donald C McMillan
Journal:  PLoS One       Date:  2012-08-03       Impact factor: 3.240

10.  An inflammation-based prognostic score (mGPS) predicts cancer survival independent of tumour site: a Glasgow Inflammation Outcome Study.

Authors:  M J Proctor; D S Morrison; D Talwar; S M Balmer; D S J O'Reilly; A K Foulis; P G Horgan; D C McMillan
Journal:  Br J Cancer       Date:  2011-01-25       Impact factor: 7.640

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  23 in total

1.  The Association of Abdominal Adiposity With Mortality in Patients With Stage I-III Colorectal Cancer.

Authors:  Justin C Brown; Bette J Caan; Carla M Prado; Elizabeth M Cespedes Feliciano; Jingjie Xiao; Candyce H Kroenke; Jeffrey A Meyerhardt
Journal:  J Natl Cancer Inst       Date:  2020-04-01       Impact factor: 13.506

2.  Predictive Value of Preoperative Sarcopenia in Patients with Gastric Cancer: a Meta-analysis and Systematic Review.

Authors:  Zhengdao Yang; Xin Zhou; Bin Ma; Yanan Xing; Xue Jiang; Zhenning Wang
Journal:  J Gastrointest Surg       Date:  2018-07-09       Impact factor: 3.452

3.  Population-Scale CT-based Body Composition Analysis of a Large Outpatient Population Using Deep Learning to Derive Age-, Sex-, and Race-specific Reference Curves.

Authors:  Kirti Magudia; Christopher P Bridge; Camden P Bay; Ana Babic; Florian J Fintelmann; Fabian M Troschel; Nityanand Miskin; William C Wrobel; Lauren K Brais; Katherine P Andriole; Brian M Wolpin; Michael H Rosenthal
Journal:  Radiology       Date:  2020-11-24       Impact factor: 11.105

4.  Loss of skeletal muscle during systemic chemotherapy is prognostic of poor survival in patients with foregut cancer.

Authors:  Louise E Daly; Éadaoin B Ní Bhuachalla; Derek G Power; Samantha J Cushen; Karl James; Aoife M Ryan
Journal:  J Cachexia Sarcopenia Muscle       Date:  2018-01-09       Impact factor: 12.910

5.  Comparison of visceral fat area measured by CT and bioelectrical impedance analysis in Chinese patients with gastric cancer: a cross-sectional study.

Authors:  Xiaotian Chen; Xiaojie Bian; Bo Gao; Yu Liu; Chao Ding; Shunli Liu
Journal:  BMJ Open       Date:  2020-07-23       Impact factor: 2.692

6.  Skeletal muscle index is an independent predictor of early recurrence in non-obese colon cancer patients.

Authors:  Dagmar Schaffler-Schaden; Christof Mittermair; Theresa Birsak; Michael Weiss; Tobias Hell; Gottfried Schaffler; Helmut Weiss
Journal:  Langenbecks Arch Surg       Date:  2020-06-05       Impact factor: 3.445

7.  Computed Tomography-Determined Sarcopenia Is a Useful Imaging Biomarker for Predicting Postoperative Outcomes in Elderly Colorectal Cancer Patients.

Authors:  Hailun Xie; Yizhen Gong; Jiaan Kuang; Ling Yan; Guotian Ruan; Shuangyi Tang; Feng Gao; Jialiang Gan
Journal:  Cancer Res Treat       Date:  2020-04-17       Impact factor: 4.679

8.  Preoperative skeletal muscle index vs the controlling nutritional status score: Which is a better objective predictor of long-term survival for gastric cancer patients after radical gastrectomy?

Authors:  Zhi-Fang Zheng; Jun Lu; Jian-Wei Xie; Jia-Bin Wang; Jian-Xian Lin; Qi-Yue Chen; Long-Long Cao; Mi Lin; Ru-Hong Tu; Chao-Hui Zheng; Chang-Ming Huang; Ping Li
Journal:  Cancer Med       Date:  2018-06-28       Impact factor: 4.452

9.  Prognostic Value of Pretreatment Overweight/Obesity and Adipose Tissue Distribution in Resectable Gastric Cancer: A Retrospective Cohort Study.

Authors:  Lihu Gu; Yangfan Zhang; Jiaze Hong; Binbin Xu; Liuqiong Yang; Kun Yan; Jingfeng Zhang; Ping Chen; Jianjun Zheng; Jie Lin
Journal:  Front Oncol       Date:  2021-06-24       Impact factor: 6.244

Review 10.  Lifestyle after Colorectal Cancer Diagnosis in Relation to Survival and Recurrence: A Review of the Literature.

Authors:  Moniek van Zutphen; Ellen Kampman; Edward L Giovannucci; Fränzel J B van Duijnhoven
Journal:  Curr Colorectal Cancer Rep       Date:  2017-09-14
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