Assessment of body composition and sarcopenia in patients with esophageal cancer: a systematic review and meta-analysis

Assessment of body composition and sarcopenia in patients with esophageal cancer: a systematic... SUMMARY There has recently been increased interest in the assessment of body composition in patients with esophageal cancer for the purpose of nutritional evaluation and prognostication. This systematic review and meta-analysis intends to summarize and critically evaluate the current literature concerning the assessment of body composition in patients with esophageal cancer and to assess its potential implication upon early and late outcomes. A systematic literature search (up to August, 2017) was conducted for studies describing the assessment of body composition in patients with esophageal and gastroesophageal junctional cancer. Meta-analysis of postoperative outcomes including long-term survival was performed using random effects models. Twenty-nine studies reported the assessment of body composition in 3193 patients. Methods used to assess body composition in patients with esophageal cancer included computerized tomography (n = 18 studies), bioelectrical impedance analysis (n = 10), and dual-energy X-ray absorptiometry (n = 1). Significant variability was observed in regard to study design and the criteria used to define individual parameters of body composition. Sarcopenic patients had a higher incidence of postoperative pulmonary complications (7 studies, OR 2.03, 95% CI 1.32–3.11, P = 0.001) after esophagectomy. Meta-analysis of six studies presenting long-term outcomes after esophagectomy identified significantly worse survival in patients who were sarcopenic (HR 1.70, 95% CI 1.33– 2.17, P < 0.0001). The assessment of body composition has the potential to become a clinically useful tool that could support decision-making in patients with esophageal cancer. Current evidence is however weakened by inconsistencies in methods of assessing and reporting body composition in this patient group. BACKGROUND Esophageal cancer is among the diseases with the highest known association with cancer-related malnutrition.1 Solid tumors, including esophageal cancer, are typically associated with some degree of anorexia as well as underlying metabolic alterations including elevated energy expenditure, excess catabolism, and inflammation. In esophageal cancer, these effects are compounded by esophageal obstruction by the tumor mass and the individual and combined effects of radiation therapy, chemotherapy, and major surgery that may all potentially reduce nutritional intake. Recently, there has been an increase in the number of reports relating to body composition assessment in patients diagnosed with esophageal cancer for the purpose of nutritional evaluation and prognostication. This interest is borne out of an appreciation for inadequacies in current methods of assessing nutrition in this patient group. The measurement of skeletal muscle and/or adipose tissue have found success in a number of other areas of medicine for nutritional assessment,2–5 supporting an argument for such measures to become part of routine assessment. Variation in methods of assessing and defining parameters of body composition however constitutes a barrier to adoption of such techniques in routine clinical practice. Research into body composition assessment in esophageal cancer patients and the development guidelines for its application in clinical practice have been hampered by the lack of a standardized methodology and diagnostic criteria. Definitions of sarcopenia, a state of severe of depletion of skeletal muscle mass (and function), have been largely established using CT measures and defined based on the risk of mortality.6,7 The predominance of CT-based measures relates to their availability in routine clinical practice and the high precision and specificity for muscle and fat distribution (visceral, intermuscular, and subcutaneous). Other measures of body composition have, less frequently been used in cancer patients, including dual-energy X-ray absorptiometry (DEXA) and bioelectrical impedance (BIA). In the midst of growing endeavors to determine the clinical utility of body composition assessment in patients with esophageal cancer, it is considered timely that existing evidence be reviewed. The purpose of this review is therefore to summarize current literature concerning the assessment of body composition in patients with esophageal cancer and to assess its potential implication for survival and perioperative morbidity. METHODS Search strategy A systematic literature search (title and abstract of full papers and conference abstracts) of the Medline (1946–2017), Embase (1947–2017), Cochrane Library (1800–2017), and PsycINFO (1806–2017) databases was conducted on the 11th August 2017 (a copy of the full search strategy for the OVID platform is provided on-line as supplementary digital content: SDC 1). After excluding duplicates, two researchers (PRB, RH) independently reviewed the titles and abstracts of studies identified by the literature search. Where a study was considered to be potentially relevant to the research question a full copy of the publication was obtained for further review. Inclusion criteria were: studies reporting the assessment of body composition (by any method) in human subjects with cancer of either the esophagus or the gastroesophageal junction (receiving palliative or curative treatment) and published in the English language. Conference abstracts were excluded if not associated with a full publication at the time of literature search. Publications with mixed populations wherein the outcomes of patients with either benign disease or cancers at another site could not be separated from those of patients with cancer of the esophageal or gastroesophageal junction were also excluded. The reference lists of all included studies were hand-searched in order to identify other potentially relevant studies. In cases where there was any uncertainty in regard to the design or outcomes of the individual studies identified by the literature search, the corresponding author of that publication was contacted. Any areas of disagreement between the two primary researchers reviewing the result of the literature search were resolved by a third researcher (VEB). One researcher (PRB) extracted data, including author, year of publication, country of origin, study design, patient number, characteristics of patient population (age, sex, tumor histology, tumor stage and tumor grade, length of follow-up), method of body composition assessment, body mass index, details of body composition assessment, and reported clinical outcomes. Body composition measures were abstracted according to method of assessment (CT, DEXA, BIA), definition and cut points defining obesity and sarcopenia, mean and standard deviation and prevalence of sarcopenia. Date extraction was independently reviewed by a second researcher (VEB). Definitions Esophageal cancer: malignancy of the any portion of the esophagus and/or gastroesophageal junction (as defined by Siewert's classification). Body composition assessment: any method reporting either the volume or characteristics of muscle and/or adipose compartments within the body. Sarcopenia: severe depletion of skeletal muscle mass that has been defined by a range of criteria that are specific for the method of assessment. Cachexia: multifactorial syndrome characterized by ongoing loss of skeletal muscle mass (with or without loss of fat), that is not fully reversible using conventional nutritional support and that eventually leads to functional impairment.8 Assessment of methodological quality Methodological quality and standard of outcome reporting within included studies were assessed by two independent researchers (PRB, RH) using the STROBE checklist.9 Statistical analysis This systematic review and meta-analysis was conducted in accordance with the recommendations of the Cochrane Library and MOOSE guidelines.10 Statistical analysis was performed using the StatsDirect software (Version 3.3, StatsDirect Ltd, Altrincham, UK). The primary summary statistic used for survival analysis was the logarithm of the hazard ratio (HR) with 95% confidence intervals (CI). HR and its variance were extracted directly from the published manuscript. Where these data were not available it was determined through additional calculations that were dependent on the data presented by the study: annual mortality rates, survival curves, number of deaths, or percentage freedom from death.11 For categorical variables, analysis was performed by calculating the odds ratio (OR). The random effects, the DerSimonian–Laird method was used for the meta-analysis of outcomes. Funnel plots were used to visually assess publication bias of included studies. Heterogeneity between studies was assessed using the I2 value in order to determine the degree of variation not attributable to chance alone. I2 values were considered to represent low, moderate, and high degrees of heterogeneity where values were <25%, 25–75%, and >75%, respectively. Funnel plot asymmetry was assessed using the Egger test. Statistical significance was assigned to P values < 0.05. RESULTS Details of the literature search and study selection are reported in accordance with PRISMA guidelines (Fig. 1), with 29 studies meeting inclusion criteria.12–40 Four studies included in this review presented the outcomes of patients that had been previously reported within other publications. Inclusion of these studies was based on either the publication of data from a unique patient cohort not reported elsewhere 21,28 or additional relevant subgroup analysis.26,30 Fig. 1 View largeDownload slide PRISMA flow chart of literature search. Fig. 1 View largeDownload slide PRISMA flow chart of literature search. Methods of assessment used in each study, including criteria for key descriptors of body composition, are presented in Table 1. CT (n = 18 studies) and BIA (n = 10) were the most commonly reported methods of body composition assessment, while DEXA was utilized in a single study. Of the 17 studies published since January 1, 2016, CT was the chosen method of assessment in 12 (70%). A total of 3193 patients were evaluated (CT, n = 2550; BIA, n = 623; DEXA, n = 20) (Table 2). Assessment was predominantly performed in patients with resectable esophageal cancer prior to surgery either before and/or after neoadjuvant therapy. (Specific parameters of body composition, reported by individual studies are provided on-line as supplementary digital content). Table 1 Details of body composition assessment methodology Authors Year Region Method CT level of assessment CT muscle (Hounsfield unit threshold) CT adipose tissue (Hounsfield unit threshold) Normalization of measurements Definition(s) Ref Harada 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 44.5cm2/m2, ♀ < 36.5 cm2/m2 (12) Li 2017 Asia CT L3-4 disc space – – NR Visceral obesity: >130 cm2 (13) Liu 2016 Asia CT L3 mid-point – – Yes (H)†† – (14) Nakashima 2017 Asia CT L3 mid-point −29 to +150 - Yes (H,BSA) Sarcopenia: ♂ < 47.2 cm2/m2, ♀ < 36.9 cm2/m2 (15) Okamura 2016 Asia CT Level of umbilicus – All −200 to −50 NR – (16) Tanaka 2008 Asia CT Level of umbilicus – – NR Visceral obesity: >100 cm2 (17) Nishigori 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (18) Anandavadivelan 2016 Europe CT L3 mid-point −29 to +150 All −150 to −30, IM −29 to +30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (19) Elliott† 2017 Europe CT L3 mid-point −29 to +150 All −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (20) Gannon† 2017 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2 (21) Grotenhuis 2016 Europe CT L3 mid-point −30 to −150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (22) Reisinger 2015 Europe CT L3 mid-point −29 to +150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 Visceral obesity: ♂ > 163.8 cm2, ♀ > 80.1 cm2 (23) Tan 2015 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (24) Yip 2014 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (25) Paireder‡ 2017 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2,♀ < 39 cm2/m2 (26) Tamandl‡ 2016 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2, ♀ < 39 cm2/m2 (27) Beddy 2010 Europe CT L3-4 disc space – All −150 to −50 NR – (28) Donohoe§ 2012 Europe CT L3-4 disc space – – NR Visceral obesity: ♂ > 160 cm2, ♀ > 80 cm2 (29) Ida¶ 2014 Asia BIA – – – NR – (30) Ida¶ 2015 Asia BIA – – – Yes (H,G,A) Sarcopenia: SMM less than standard (<90%) (31) Miyata 2017 Asia BIA – – – Yes (H,A,G) Sarcopenia: SMM less than standard (<90%) (32) Makiura 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (33) Ishikawa 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (34) Wu 2013 Asia BIA – – – NR – (35) Wu 2016 Asia BIA – – – NR – (36) Guinan 2017 Europe BIA – – – NR – (37) Ryan 2009 Europe BIA – – – Yes (Hy) – (38) Becker Veronese 2013 S. America BIA – – – Yes‡‡ – (39) Yamamoto 2010 Asia DEXA – – – NR – (40) Authors Year Region Method CT level of assessment CT muscle (Hounsfield unit threshold) CT adipose tissue (Hounsfield unit threshold) Normalization of measurements Definition(s) Ref Harada 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 44.5cm2/m2, ♀ < 36.5 cm2/m2 (12) Li 2017 Asia CT L3-4 disc space – – NR Visceral obesity: >130 cm2 (13) Liu 2016 Asia CT L3 mid-point – – Yes (H)†† – (14) Nakashima 2017 Asia CT L3 mid-point −29 to +150 - Yes (H,BSA) Sarcopenia: ♂ < 47.2 cm2/m2, ♀ < 36.9 cm2/m2 (15) Okamura 2016 Asia CT Level of umbilicus – All −200 to −50 NR – (16) Tanaka 2008 Asia CT Level of umbilicus – – NR Visceral obesity: >100 cm2 (17) Nishigori 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (18) Anandavadivelan 2016 Europe CT L3 mid-point −29 to +150 All −150 to −30, IM −29 to +30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (19) Elliott† 2017 Europe CT L3 mid-point −29 to +150 All −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (20) Gannon† 2017 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2 (21) Grotenhuis 2016 Europe CT L3 mid-point −30 to −150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (22) Reisinger 2015 Europe CT L3 mid-point −29 to +150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 Visceral obesity: ♂ > 163.8 cm2, ♀ > 80.1 cm2 (23) Tan 2015 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (24) Yip 2014 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (25) Paireder‡ 2017 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2,♀ < 39 cm2/m2 (26) Tamandl‡ 2016 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2, ♀ < 39 cm2/m2 (27) Beddy 2010 Europe CT L3-4 disc space – All −150 to −50 NR – (28) Donohoe§ 2012 Europe CT L3-4 disc space – – NR Visceral obesity: ♂ > 160 cm2, ♀ > 80 cm2 (29) Ida¶ 2014 Asia BIA – – – NR – (30) Ida¶ 2015 Asia BIA – – – Yes (H,G,A) Sarcopenia: SMM less than standard (<90%) (31) Miyata 2017 Asia BIA – – – Yes (H,A,G) Sarcopenia: SMM less than standard (<90%) (32) Makiura 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (33) Ishikawa 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (34) Wu 2013 Asia BIA – – – NR – (35) Wu 2016 Asia BIA – – – NR – (36) Guinan 2017 Europe BIA – – – NR – (37) Ryan 2009 Europe BIA – – – Yes (Hy) – (38) Becker Veronese 2013 S. America BIA – – – Yes‡‡ – (39) Yamamoto 2010 Asia DEXA – – – NR – (40) A, age; Adipose tissue assessment: All, all adipose compartments; BIA, bioelectrical impedance analysis; BSA, body surface area; CT, computerized tomography; DEXA, dual-energy X-ray absorptiometry; G, sex; H, height squared; Hy, hydration; IM, intramuscular; L3/4, Third/fourth lumbar vertebra; NR, not reported; S. America, South America; SC, subcutaneous; ... V, visceral..... . †Elliott 2017 and Gannon 2017 are studies presenting outcomes from the same patient populations. Only data relating to patients who underwent primary surgery with no neoadjuvant chemotherapy (n = 8) presented by Gannon 2017, but not by Elliott 2017 are presented herein; ‡Paireder 2017 and Tamandl 2016 are studies presenting outcomes from the same patient populations. Data relating to patient survival and postoperative morbidity, use for the purpose of meta-analysis, are taken from Tamandl 2016 and Paireder 2017 respectively; §Beddy 2010 and Donohoe 2012 are studies presenting outcomes from the same patient populations. Only data relating to patients with squamous cell carcinoma (n = 46/156) reported by Beddy 2010, but not by Donohoe 2012 are presented herein; ¶Ida 2014 and Ida 2015 are studies presenting outcomes from the same patient populations. Ida 2014 reported the effect of neoadjuvant therapy on body composition whilst Ida 2015 reported data for postoperative morbidity use for the purpose of meta-analysis; ††Psoas muscle index determined by normalizing the cross-sectional areas of both psoas muscles, determined at the midpoint of the L3 vertebra, to patients height (cm2/m2); ‡‡Bioelectrical impedance analysis performed after 8hr fast and avoidance of physical exertion from the day before analysis; §§Definition of sarcopenia is based on the Asian Working Group for Sarcopenia (AWGS) consensus guidelines. View Large Table 1 Details of body composition assessment methodology Authors Year Region Method CT level of assessment CT muscle (Hounsfield unit threshold) CT adipose tissue (Hounsfield unit threshold) Normalization of measurements Definition(s) Ref Harada 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 44.5cm2/m2, ♀ < 36.5 cm2/m2 (12) Li 2017 Asia CT L3-4 disc space – – NR Visceral obesity: >130 cm2 (13) Liu 2016 Asia CT L3 mid-point – – Yes (H)†† – (14) Nakashima 2017 Asia CT L3 mid-point −29 to +150 - Yes (H,BSA) Sarcopenia: ♂ < 47.2 cm2/m2, ♀ < 36.9 cm2/m2 (15) Okamura 2016 Asia CT Level of umbilicus – All −200 to −50 NR – (16) Tanaka 2008 Asia CT Level of umbilicus – – NR Visceral obesity: >100 cm2 (17) Nishigori 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (18) Anandavadivelan 2016 Europe CT L3 mid-point −29 to +150 All −150 to −30, IM −29 to +30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (19) Elliott† 2017 Europe CT L3 mid-point −29 to +150 All −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (20) Gannon† 2017 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2 (21) Grotenhuis 2016 Europe CT L3 mid-point −30 to −150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (22) Reisinger 2015 Europe CT L3 mid-point −29 to +150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 Visceral obesity: ♂ > 163.8 cm2, ♀ > 80.1 cm2 (23) Tan 2015 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (24) Yip 2014 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (25) Paireder‡ 2017 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2,♀ < 39 cm2/m2 (26) Tamandl‡ 2016 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2, ♀ < 39 cm2/m2 (27) Beddy 2010 Europe CT L3-4 disc space – All −150 to −50 NR – (28) Donohoe§ 2012 Europe CT L3-4 disc space – – NR Visceral obesity: ♂ > 160 cm2, ♀ > 80 cm2 (29) Ida¶ 2014 Asia BIA – – – NR – (30) Ida¶ 2015 Asia BIA – – – Yes (H,G,A) Sarcopenia: SMM less than standard (<90%) (31) Miyata 2017 Asia BIA – – – Yes (H,A,G) Sarcopenia: SMM less than standard (<90%) (32) Makiura 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (33) Ishikawa 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (34) Wu 2013 Asia BIA – – – NR – (35) Wu 2016 Asia BIA – – – NR – (36) Guinan 2017 Europe BIA – – – NR – (37) Ryan 2009 Europe BIA – – – Yes (Hy) – (38) Becker Veronese 2013 S. America BIA – – – Yes‡‡ – (39) Yamamoto 2010 Asia DEXA – – – NR – (40) Authors Year Region Method CT level of assessment CT muscle (Hounsfield unit threshold) CT adipose tissue (Hounsfield unit threshold) Normalization of measurements Definition(s) Ref Harada 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 44.5cm2/m2, ♀ < 36.5 cm2/m2 (12) Li 2017 Asia CT L3-4 disc space – – NR Visceral obesity: >130 cm2 (13) Liu 2016 Asia CT L3 mid-point – – Yes (H)†† – (14) Nakashima 2017 Asia CT L3 mid-point −29 to +150 - Yes (H,BSA) Sarcopenia: ♂ < 47.2 cm2/m2, ♀ < 36.9 cm2/m2 (15) Okamura 2016 Asia CT Level of umbilicus – All −200 to −50 NR – (16) Tanaka 2008 Asia CT Level of umbilicus – – NR Visceral obesity: >100 cm2 (17) Nishigori 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (18) Anandavadivelan 2016 Europe CT L3 mid-point −29 to +150 All −150 to −30, IM −29 to +30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (19) Elliott† 2017 Europe CT L3 mid-point −29 to +150 All −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (20) Gannon† 2017 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2 (21) Grotenhuis 2016 Europe CT L3 mid-point −30 to −150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (22) Reisinger 2015 Europe CT L3 mid-point −29 to +150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 Visceral obesity: ♂ > 163.8 cm2, ♀ > 80.1 cm2 (23) Tan 2015 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (24) Yip 2014 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (25) Paireder‡ 2017 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2,♀ < 39 cm2/m2 (26) Tamandl‡ 2016 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2, ♀ < 39 cm2/m2 (27) Beddy 2010 Europe CT L3-4 disc space – All −150 to −50 NR – (28) Donohoe§ 2012 Europe CT L3-4 disc space – – NR Visceral obesity: ♂ > 160 cm2, ♀ > 80 cm2 (29) Ida¶ 2014 Asia BIA – – – NR – (30) Ida¶ 2015 Asia BIA – – – Yes (H,G,A) Sarcopenia: SMM less than standard (<90%) (31) Miyata 2017 Asia BIA – – – Yes (H,A,G) Sarcopenia: SMM less than standard (<90%) (32) Makiura 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (33) Ishikawa 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (34) Wu 2013 Asia BIA – – – NR – (35) Wu 2016 Asia BIA – – – NR – (36) Guinan 2017 Europe BIA – – – NR – (37) Ryan 2009 Europe BIA – – – Yes (Hy) – (38) Becker Veronese 2013 S. America BIA – – – Yes‡‡ – (39) Yamamoto 2010 Asia DEXA – – – NR – (40) A, age; Adipose tissue assessment: All, all adipose compartments; BIA, bioelectrical impedance analysis; BSA, body surface area; CT, computerized tomography; DEXA, dual-energy X-ray absorptiometry; G, sex; H, height squared; Hy, hydration; IM, intramuscular; L3/4, Third/fourth lumbar vertebra; NR, not reported; S. America, South America; SC, subcutaneous; ... V, visceral..... . †Elliott 2017 and Gannon 2017 are studies presenting outcomes from the same patient populations. Only data relating to patients who underwent primary surgery with no neoadjuvant chemotherapy (n = 8) presented by Gannon 2017, but not by Elliott 2017 are presented herein; ‡Paireder 2017 and Tamandl 2016 are studies presenting outcomes from the same patient populations. Data relating to patient survival and postoperative morbidity, use for the purpose of meta-analysis, are taken from Tamandl 2016 and Paireder 2017 respectively; §Beddy 2010 and Donohoe 2012 are studies presenting outcomes from the same patient populations. Only data relating to patients with squamous cell carcinoma (n = 46/156) reported by Beddy 2010, but not by Donohoe 2012 are presented herein; ¶Ida 2014 and Ida 2015 are studies presenting outcomes from the same patient populations. Ida 2014 reported the effect of neoadjuvant therapy on body composition whilst Ida 2015 reported data for postoperative morbidity use for the purpose of meta-analysis; ††Psoas muscle index determined by normalizing the cross-sectional areas of both psoas muscles, determined at the midpoint of the L3 vertebra, to patients height (cm2/m2); ‡‡Bioelectrical impedance analysis performed after 8hr fast and avoidance of physical exertion from the day before analysis; §§Definition of sarcopenia is based on the Asian Working Group for Sarcopenia (AWGS) consensus guidelines. View Large Table 2. Details of included studies Authors Method Cancer site No. Design Time of assessment Age Sex (% male) Histology T stage 3/4 Stage III/IV STARD score Refs. Harada CT E 325c P,CS Pre-Tx 53% ≥ 66 year 93% SCC = 100% 46% 46% 15 (12) Li CT GOJ 116 R,CS Pre-opg 61 [31–73]j 60% Ad-100% – – 11 (13) Liu CT E 84 R,CS B/A-NAT, PO 63 [40–74]j 86% SCC = 100% 44% – 11 (14) Nakashima CT E 341 R,CS Pre-opg – 85% Ad = 2%/SCC = 95%o – 40% 11 (15) Okamura CT E 150 R,CS Pre-opg 66 ± 8k 82% SCC = 100% 27% 32% 13 (16) Tanaka CT E 64 R,CS Pre-opg – 100% – 51% 45% 11 (17) Nishigori CT E 199 R,CS Pre-opg 56% ≥ 65 years 82% – 49% 35% 14 (18) Anandavadivelan CT E,GOJ 72 R,CS Pre-Tx 67 ± 7k 61% Ad 67%/SCC 33% 50% – 16 (19) Elliott CT E,GOJ 252d R,CS B/A-NAT, PO 62 ± 9k 80% Ad 81%/SCC 19% 56% – 16 (20) Gannon CTa E,GOJ 8 P,CC Pre-Tx – 100% – – – 13 (21) Grotenhuis CT E,GOJb 120 R,CS Pre-Tx 62 [19–78]j 73% Ad = 74%/SCC = 26% 36% – 12 (22) Reisinger CT E 123e R,CS B/A-NAT 63 ± 10k 82% Ad = 81%/SCC = 19% – 50% 16 (23) Tan CT E,GOJ 65 R,CS Pre-Tx – – – – – 12 (24) Yip CT E 35 R,CS B/A-NAT 63 [34–78]l 86% Ad = 86%/SCC = 14% – – 12 (25) Paireder CT E,GOJ 130 R,CS B/A-NAT 61 [31–81]j 82% Ad = 67%/SCC = 33% 31% – 15 (26) Tamandl CT E,GOJ 200 R,CS Pre-opg 64 [57–70]j 76% Ad = 69%/SCC = 30%p 50% – 15 (27) Beddy CT E,GOJ 46 R,CC Pre-Tx 65 ± 10k 46% SCC = 100% – – 12 (28) Donohoe CT E,GOJb 220 P,CS Pre-Tx 65 ± 11k 81% Ad = 100% 62% – 10 (29) Ida BIA E 30 P,CS B/A-NAT 64 [53–75]l 83% SCC = 100% 73% 83% 12 (30) Ida BIA E 138 P,CS Pre-opg 65 [42–85]l 88% SCC = 100% 41% 41% 12 (31) Miyata BIA E 94 P,CS B/A-NAT 64 ± 9k 81% SCC = 100% 76% 69% 12 (32) Makiura BIA E 104f R,CS Pre-opg, PO [61–76]m 85% Ad = 5%/SCC = 94%p 44% – 16 (33) Ishikawa BIA E 33 P,RCT B/A-NAT [44–79]m 82% SCC = 100% 73% – 11 (34) Wu BIA E 56 P,CC Pre-Tx 61 ± 9k 100% SCC = 100% – – 9 (35) Wu BIA E 73 P,RCT Pre-oph, PO – 69% Ad = 1%/SCC = 99% – 45% 16 (36) Guinan BIA E 12 P,CS PO 61 ± 7k 67% Ad = 67%/SCC = 33% – – 11 (37) Ryan BIA E,GOJ 53 P,RCT Pre-opi, PO – 72% – 36% – 15 (38) Becker Veronese BIA E,GOJ 30 P,CS Pre-Tx 61 ± 9k 70% SCC = 100% – 63% 12 (39) Yamamoto DEXA E 20 P,RCT PO 65 ± 6k,n 90% SCC = 100% – 70% 13 (40) Authors Method Cancer site No. Design Time of assessment Age Sex (% male) Histology T stage 3/4 Stage III/IV STARD score Refs. Harada CT E 325c P,CS Pre-Tx 53% ≥ 66 year 93% SCC = 100% 46% 46% 15 (12) Li CT GOJ 116 R,CS Pre-opg 61 [31–73]j 60% Ad-100% – – 11 (13) Liu CT E 84 R,CS B/A-NAT, PO 63 [40–74]j 86% SCC = 100% 44% – 11 (14) Nakashima CT E 341 R,CS Pre-opg – 85% Ad = 2%/SCC = 95%o – 40% 11 (15) Okamura CT E 150 R,CS Pre-opg 66 ± 8k 82% SCC = 100% 27% 32% 13 (16) Tanaka CT E 64 R,CS Pre-opg – 100% – 51% 45% 11 (17) Nishigori CT E 199 R,CS Pre-opg 56% ≥ 65 years 82% – 49% 35% 14 (18) Anandavadivelan CT E,GOJ 72 R,CS Pre-Tx 67 ± 7k 61% Ad 67%/SCC 33% 50% – 16 (19) Elliott CT E,GOJ 252d R,CS B/A-NAT, PO 62 ± 9k 80% Ad 81%/SCC 19% 56% – 16 (20) Gannon CTa E,GOJ 8 P,CC Pre-Tx – 100% – – – 13 (21) Grotenhuis CT E,GOJb 120 R,CS Pre-Tx 62 [19–78]j 73% Ad = 74%/SCC = 26% 36% – 12 (22) Reisinger CT E 123e R,CS B/A-NAT 63 ± 10k 82% Ad = 81%/SCC = 19% – 50% 16 (23) Tan CT E,GOJ 65 R,CS Pre-Tx – – – – – 12 (24) Yip CT E 35 R,CS B/A-NAT 63 [34–78]l 86% Ad = 86%/SCC = 14% – – 12 (25) Paireder CT E,GOJ 130 R,CS B/A-NAT 61 [31–81]j 82% Ad = 67%/SCC = 33% 31% – 15 (26) Tamandl CT E,GOJ 200 R,CS Pre-opg 64 [57–70]j 76% Ad = 69%/SCC = 30%p 50% – 15 (27) Beddy CT E,GOJ 46 R,CC Pre-Tx 65 ± 10k 46% SCC = 100% – – 12 (28) Donohoe CT E,GOJb 220 P,CS Pre-Tx 65 ± 11k 81% Ad = 100% 62% – 10 (29) Ida BIA E 30 P,CS B/A-NAT 64 [53–75]l 83% SCC = 100% 73% 83% 12 (30) Ida BIA E 138 P,CS Pre-opg 65 [42–85]l 88% SCC = 100% 41% 41% 12 (31) Miyata BIA E 94 P,CS B/A-NAT 64 ± 9k 81% SCC = 100% 76% 69% 12 (32) Makiura BIA E 104f R,CS Pre-opg, PO [61–76]m 85% Ad = 5%/SCC = 94%p 44% – 16 (33) Ishikawa BIA E 33 P,RCT B/A-NAT [44–79]m 82% SCC = 100% 73% – 11 (34) Wu BIA E 56 P,CC Pre-Tx 61 ± 9k 100% SCC = 100% – – 9 (35) Wu BIA E 73 P,RCT Pre-oph, PO – 69% Ad = 1%/SCC = 99% – 45% 16 (36) Guinan BIA E 12 P,CS PO 61 ± 7k 67% Ad = 67%/SCC = 33% – – 11 (37) Ryan BIA E,GOJ 53 P,RCT Pre-opi, PO – 72% – 36% – 15 (38) Becker Veronese BIA E,GOJ 30 P,CS Pre-Tx 61 ± 9k 70% SCC = 100% – 63% 12 (39) Yamamoto DEXA E 20 P,RCT PO 65 ± 6k,n 90% SCC = 100% – 70% 13 (40) E, esophageal. GOJ, gastroesophageal junction. R, retrospective. P, prospective. CS, case series. CC, case control. RCT, randomized controlled trial. Pre-Tx, pre-treatment (including neo-adjuvant therapy). B/A-NAT, before and after neo-adjuvant therapy. Pre-op, pre-operative. PO, post-operative. CT, computerized tomography. BIA, bioelectrical impedance analysis. DEXA, Dual-energy X-ray absorptiometry. SD, standard deviation. Ad, adenocarcinoma. SCC, squamous cell carcinoma. aData for body composition assessment by BIA is not considered herein; bSiewert type III tumors were excluded by authors; cIncludes 256 patients who underwent esophagectomy and 69 patients who received definitive chemoradiotherapy; d207 patients underwent surgery for which outcomes are reported for 192; eCT scans performed both before and after neoadjuvant chemoradiotherapy were available for 96 patients; fPostoperative body composition assessment was available for 74 patients; gSpecific timing of body composition assessment relative to neoadjuvant therapy is not reported by study; hAssessment of 11 preoperative patients was performed after neoadjuvant therapy; iAssessment of 27 preoperative patients was performed after neoadjuvant therapy; jMedian [range]; kMean ± standard deviation; lMean [range]; m[range]; nValue is for placebo group (n = 10); o3% other; p1% other. View Large Table 2. Details of included studies Authors Method Cancer site No. Design Time of assessment Age Sex (% male) Histology T stage 3/4 Stage III/IV STARD score Refs. Harada CT E 325c P,CS Pre-Tx 53% ≥ 66 year 93% SCC = 100% 46% 46% 15 (12) Li CT GOJ 116 R,CS Pre-opg 61 [31–73]j 60% Ad-100% – – 11 (13) Liu CT E 84 R,CS B/A-NAT, PO 63 [40–74]j 86% SCC = 100% 44% – 11 (14) Nakashima CT E 341 R,CS Pre-opg – 85% Ad = 2%/SCC = 95%o – 40% 11 (15) Okamura CT E 150 R,CS Pre-opg 66 ± 8k 82% SCC = 100% 27% 32% 13 (16) Tanaka CT E 64 R,CS Pre-opg – 100% – 51% 45% 11 (17) Nishigori CT E 199 R,CS Pre-opg 56% ≥ 65 years 82% – 49% 35% 14 (18) Anandavadivelan CT E,GOJ 72 R,CS Pre-Tx 67 ± 7k 61% Ad 67%/SCC 33% 50% – 16 (19) Elliott CT E,GOJ 252d R,CS B/A-NAT, PO 62 ± 9k 80% Ad 81%/SCC 19% 56% – 16 (20) Gannon CTa E,GOJ 8 P,CC Pre-Tx – 100% – – – 13 (21) Grotenhuis CT E,GOJb 120 R,CS Pre-Tx 62 [19–78]j 73% Ad = 74%/SCC = 26% 36% – 12 (22) Reisinger CT E 123e R,CS B/A-NAT 63 ± 10k 82% Ad = 81%/SCC = 19% – 50% 16 (23) Tan CT E,GOJ 65 R,CS Pre-Tx – – – – – 12 (24) Yip CT E 35 R,CS B/A-NAT 63 [34–78]l 86% Ad = 86%/SCC = 14% – – 12 (25) Paireder CT E,GOJ 130 R,CS B/A-NAT 61 [31–81]j 82% Ad = 67%/SCC = 33% 31% – 15 (26) Tamandl CT E,GOJ 200 R,CS Pre-opg 64 [57–70]j 76% Ad = 69%/SCC = 30%p 50% – 15 (27) Beddy CT E,GOJ 46 R,CC Pre-Tx 65 ± 10k 46% SCC = 100% – – 12 (28) Donohoe CT E,GOJb 220 P,CS Pre-Tx 65 ± 11k 81% Ad = 100% 62% – 10 (29) Ida BIA E 30 P,CS B/A-NAT 64 [53–75]l 83% SCC = 100% 73% 83% 12 (30) Ida BIA E 138 P,CS Pre-opg 65 [42–85]l 88% SCC = 100% 41% 41% 12 (31) Miyata BIA E 94 P,CS B/A-NAT 64 ± 9k 81% SCC = 100% 76% 69% 12 (32) Makiura BIA E 104f R,CS Pre-opg, PO [61–76]m 85% Ad = 5%/SCC = 94%p 44% – 16 (33) Ishikawa BIA E 33 P,RCT B/A-NAT [44–79]m 82% SCC = 100% 73% – 11 (34) Wu BIA E 56 P,CC Pre-Tx 61 ± 9k 100% SCC = 100% – – 9 (35) Wu BIA E 73 P,RCT Pre-oph, PO – 69% Ad = 1%/SCC = 99% – 45% 16 (36) Guinan BIA E 12 P,CS PO 61 ± 7k 67% Ad = 67%/SCC = 33% – – 11 (37) Ryan BIA E,GOJ 53 P,RCT Pre-opi, PO – 72% – 36% – 15 (38) Becker Veronese BIA E,GOJ 30 P,CS Pre-Tx 61 ± 9k 70% SCC = 100% – 63% 12 (39) Yamamoto DEXA E 20 P,RCT PO 65 ± 6k,n 90% SCC = 100% – 70% 13 (40) Authors Method Cancer site No. Design Time of assessment Age Sex (% male) Histology T stage 3/4 Stage III/IV STARD score Refs. Harada CT E 325c P,CS Pre-Tx 53% ≥ 66 year 93% SCC = 100% 46% 46% 15 (12) Li CT GOJ 116 R,CS Pre-opg 61 [31–73]j 60% Ad-100% – – 11 (13) Liu CT E 84 R,CS B/A-NAT, PO 63 [40–74]j 86% SCC = 100% 44% – 11 (14) Nakashima CT E 341 R,CS Pre-opg – 85% Ad = 2%/SCC = 95%o – 40% 11 (15) Okamura CT E 150 R,CS Pre-opg 66 ± 8k 82% SCC = 100% 27% 32% 13 (16) Tanaka CT E 64 R,CS Pre-opg – 100% – 51% 45% 11 (17) Nishigori CT E 199 R,CS Pre-opg 56% ≥ 65 years 82% – 49% 35% 14 (18) Anandavadivelan CT E,GOJ 72 R,CS Pre-Tx 67 ± 7k 61% Ad 67%/SCC 33% 50% – 16 (19) Elliott CT E,GOJ 252d R,CS B/A-NAT, PO 62 ± 9k 80% Ad 81%/SCC 19% 56% – 16 (20) Gannon CTa E,GOJ 8 P,CC Pre-Tx – 100% – – – 13 (21) Grotenhuis CT E,GOJb 120 R,CS Pre-Tx 62 [19–78]j 73% Ad = 74%/SCC = 26% 36% – 12 (22) Reisinger CT E 123e R,CS B/A-NAT 63 ± 10k 82% Ad = 81%/SCC = 19% – 50% 16 (23) Tan CT E,GOJ 65 R,CS Pre-Tx – – – – – 12 (24) Yip CT E 35 R,CS B/A-NAT 63 [34–78]l 86% Ad = 86%/SCC = 14% – – 12 (25) Paireder CT E,GOJ 130 R,CS B/A-NAT 61 [31–81]j 82% Ad = 67%/SCC = 33% 31% – 15 (26) Tamandl CT E,GOJ 200 R,CS Pre-opg 64 [57–70]j 76% Ad = 69%/SCC = 30%p 50% – 15 (27) Beddy CT E,GOJ 46 R,CC Pre-Tx 65 ± 10k 46% SCC = 100% – – 12 (28) Donohoe CT E,GOJb 220 P,CS Pre-Tx 65 ± 11k 81% Ad = 100% 62% – 10 (29) Ida BIA E 30 P,CS B/A-NAT 64 [53–75]l 83% SCC = 100% 73% 83% 12 (30) Ida BIA E 138 P,CS Pre-opg 65 [42–85]l 88% SCC = 100% 41% 41% 12 (31) Miyata BIA E 94 P,CS B/A-NAT 64 ± 9k 81% SCC = 100% 76% 69% 12 (32) Makiura BIA E 104f R,CS Pre-opg, PO [61–76]m 85% Ad = 5%/SCC = 94%p 44% – 16 (33) Ishikawa BIA E 33 P,RCT B/A-NAT [44–79]m 82% SCC = 100% 73% – 11 (34) Wu BIA E 56 P,CC Pre-Tx 61 ± 9k 100% SCC = 100% – – 9 (35) Wu BIA E 73 P,RCT Pre-oph, PO – 69% Ad = 1%/SCC = 99% – 45% 16 (36) Guinan BIA E 12 P,CS PO 61 ± 7k 67% Ad = 67%/SCC = 33% – – 11 (37) Ryan BIA E,GOJ 53 P,RCT Pre-opi, PO – 72% – 36% – 15 (38) Becker Veronese BIA E,GOJ 30 P,CS Pre-Tx 61 ± 9k 70% SCC = 100% – 63% 12 (39) Yamamoto DEXA E 20 P,RCT PO 65 ± 6k,n 90% SCC = 100% – 70% 13 (40) E, esophageal. GOJ, gastroesophageal junction. R, retrospective. P, prospective. CS, case series. CC, case control. RCT, randomized controlled trial. Pre-Tx, pre-treatment (including neo-adjuvant therapy). B/A-NAT, before and after neo-adjuvant therapy. Pre-op, pre-operative. PO, post-operative. CT, computerized tomography. BIA, bioelectrical impedance analysis. DEXA, Dual-energy X-ray absorptiometry. SD, standard deviation. Ad, adenocarcinoma. SCC, squamous cell carcinoma. aData for body composition assessment by BIA is not considered herein; bSiewert type III tumors were excluded by authors; cIncludes 256 patients who underwent esophagectomy and 69 patients who received definitive chemoradiotherapy; d207 patients underwent surgery for which outcomes are reported for 192; eCT scans performed both before and after neoadjuvant chemoradiotherapy were available for 96 patients; fPostoperative body composition assessment was available for 74 patients; gSpecific timing of body composition assessment relative to neoadjuvant therapy is not reported by study; hAssessment of 11 preoperative patients was performed after neoadjuvant therapy; iAssessment of 27 preoperative patients was performed after neoadjuvant therapy; jMedian [range]; kMean ± standard deviation; lMean [range]; m[range]; nValue is for placebo group (n = 10); o3% other; p1% other. View Large Reporting standards and methodological quality Assessment of reporting standards against the 22 criteria listed within the STROBE checklist demonstrated a mean score of 13 ± 2 (range: 9–16) (Table 2, full details of STROBE assessment for individual studies is provided on-line as supplementary digital content). Criteria for defining parameters of body composition varied considerably (Table 1). CT cut-points defining sarcopenia were reported in 12 studies. In 8 of these 12 reports the authors adopted sex specific cut-points previously described for mortality risk in a population of obese (BMI ≥ 30 kg/m2) Canadians with lung and GI cancers,6 regardless of whether the intended sample was obese. The somewhat higher cut-points used by Paireder et al.26,27 reflect a typographical error in the publication from which they were derived8 in which criteria published by Prado et al.6 are cited as the source. The values derived by Prado et al.6 have been used multiple times, permitting comparison between studies that used them. However different, lower sarcopenia cut-points have been shown in patients of BMI < 25 kg/m212 and these may be more relevant for esophageal cancer populations. The ‘true’ prevalence of sarcopenia in these populations may therefore be overestimated. Two Asian studies, determined cut-points based on the unique characteristics of their study population.12,15 Studies were also heterogeneous with respect to several factors known to influence body composition: race, sex, BMI, and tumor characteristics (Table 2). Variation in these factors was broadly reflective of known differences that exist between Asian and Western populations. For example the mean overall BMI in publications in Asian populations (22.1 kg/m2) was lower than that in Caucasian samples (25.6 kg/m2; P < 0.0001). Body composition assessment in esophageal cancer The reported prevalence of sarcopenia in preoperative esophageal cancer patients varied between 16% and 75% (full details of body composition parameters determined in esophageal cancer patients is provided on-line as supplementary digital content). Prevalence values can only be compared between studies that used identical criteria for sarcopenia in populations with similar characteristics; other comparisons are unreliable owing to differences in methodologies, patient populations, and criteria for defining this parameter (Tables 1 and 2). Based on 7 studies that used Prado's criteria for CT-defined sarcopenia in Caucasian populations, the overall prevalence of sarcopenia was 38% (range: 16–56%). Visceral adiposity of patients with squamous cell carcinoma was presented by two studies16,28 and tended to be lower than in patient cohorts where adenocarcinoma was the predominant tumor subtype.23,25,27,29 Meta-analysis of the studies reporting the influence of body composition on early postoperative outcomes and long-term survival Early postoperative mortality Meta-analysis of four studies determined that preoperative sarcopenia, assessed by CT, was not associated with early mortality (30-day and/or in-hospital) following esophagectomy (OR 1.18, 95% CI 0.47–2.96, P = 0.718).15,18,20,22 Studies exhibited low heterogeneity (I2 0%) and no significant bias (Egger −0.32, P = 0.821). Postoperative morbidity Preoperative sarcopenia, assessed by CT, was not associated with significantly higher rates of overall postoperative complications when defined as Clavien-Dindo ≥ II (OR 1.19, 95% CI 0.78 to 1.81, P = 0.431, I2 12.9%).18,20,22 The association of preoperative sarcopenia and post-esophagectomy pulmonary complications was reported in 7 studies (five CT, two BIA).12,15,18,20,26,31,33 Meta-analysis confirmed higher rates of postoperative pneumonia in sarcopenic patients (OR 2.03, 95% CI 1.32–3.11, P = 0.001) (Fig. 2). Moderate heterogeneity between studies was observed (I2 45.4%) without evidence of significant bias (Egger 2.91, P = 0.344). This finding was conserved when studies that assessed sarcopenia by CT methods were considered independently (OR 1.68, 95% CI 1.04 to 2.70, P = 0.033; I2 41.8%). Fig. 2 View largeDownload slide Summary meta-analysis of studies reporting the effect of sarcopenia on the occurrence of postoperative respiratory complications in patients undergoing esophagectomy for oesophageal cancer (OR 2.03, 95% CI 1.32–3.11, P = 0.001). Fig. 2 View largeDownload slide Summary meta-analysis of studies reporting the effect of sarcopenia on the occurrence of postoperative respiratory complications in patients undergoing esophagectomy for oesophageal cancer (OR 2.03, 95% CI 1.32–3.11, P = 0.001). There was no increased risk of nonpulmonary postoperative complications in patients with sarcopenia, including: anastomotic leak (six studies: OR 1.33, 95% CI 0.85–2.09, P = 0.213; I2 32.1%);12,15,18,20,26,31 cardiac complications (five studies: OR 1.32, 95% CI 0.82–2.14, P = 0.256; I2 0.0%);12,18,20,31,33 surgical site infection (three studies: OR 1.26, 95% CI 0.81 to 1.96, P = 0.315; I2 0.0%).12,18,31 These relationships remained nonsignificant following reanalysis of only those studies utilizing CT for the assessment of sarcopenia. Postoperative morbidity was not associated with measures of body composition including visceral adiposity and sarcopenia in a number of additional studies,14,16,17,22,23,25,32 however outcomes presented by these studies were not suitable for meta-analysis on account of variation in methodology and reporting of data. Long-term survival The influence of preoperative sarcopenia, as determined by CT, on the survival of patients following treatment for esophageal cancer was reported in six studies.12,15,20,22,25,27 Meta-analysis of outcomes presented within these studies identified that sarcopenia was associated with lower overall survival (HR 1.70, 95% CI 1.33–2.17, P < 0.0001) (Fig. 3). Heterogeneity between studies was moderate (I2 48.1%) and was without evidence of significant bias (Egger −0.22, P = 0.915). Meta-analysis of studies including patients from European centers that underwent esophagectomy, using CT criteria for sarcopenia largely based on those published by Prado et al.,6 confirmed the association between this variable and overall survival (HR 1.67, 95% CI 1.18 to 2.38, P = 0.004). This analysis was subject to moderate heterogeneity between studies (I2 61.7%) and was without significant bias (Egger −1.67, P = 0.724). Fig. 3 View largeDownload slide Summary meta-analysis of studies reporting the effect of sarcopenia on the survival of patients undergoing esophagectomy for oesophageal cancer (HR 1.70, 95% CI 1.33 to 2.17, P < 0.0001). Median reported follow-up: Elliott, 26 months; Grotenhuis, 20 months; Harada, 50 months; Tamandl, 35 months; Yip 24 months, and; Nakashima, no-reported. Fig. 3 View largeDownload slide Summary meta-analysis of studies reporting the effect of sarcopenia on the survival of patients undergoing esophagectomy for oesophageal cancer (HR 1.70, 95% CI 1.33 to 2.17, P < 0.0001). Median reported follow-up: Elliott, 26 months; Grotenhuis, 20 months; Harada, 50 months; Tamandl, 35 months; Yip 24 months, and; Nakashima, no-reported. Several studies reported the influence of a number of additional body composition parameters on survival, although these data were not suitable for meta-analysis. (Further details of associations between body composition parameters and treatment outcomes are provided on-line as supplementary digital content). DISCUSSION This systematic review and meta-analysis summarizes the existing evidence regarding body composition assessment in esophageal cancer and its potential implications for patient management and prognosis. The principal findings were: (i) heterogeneity of approaches to body composition assessment in patients with esophageal cancer; (ii) significant variance in the reported prevalence of sarcopenia; (iii) higher rates of pulmonary complications following esophagectomy in patients found to be sarcopenic prior to surgery, and; (iv) an association between sarcopenia and reduced overall survival in patients undergoing esophagectomy. Findings were similar to what has been shown for other solid organ tumors.41,42 Weight loss and malnutrition remain a central concern for patients at all stages of treatment for esophageal cancer. At the time of diagnosis more than half of patients with esophageal cancer report some degree of weight loss.43 The inability of patients to maintain body weight is recognized to be a poor prognostic indicator in terms of therapeutic response and overall survival.44,45 Historically, a wide range of approaches have been utilized to assess nutrition in patients with esophageal cancer. These can broadly be divided in anthropometric measures, blood markers, measures of energy expenditure, validate nutritional risk scores, and patient reported dietary history. The current review focuses on the assessment of body composition due to the promise this approach has demonstrated in other areas of medicine and surgery as well as the relative ease with which it might form part of future routine clinical practice.46 Although three techniques for body composition assessment in patients with esophageal cancer have been described, CT and BIA were most commonly utilized within studies identified in the review. Unlike BIA, CT forms a regular part of the standard management of esophageal cancer patients and hence offers an opportune method for the assessment of body composition at specific and relevant time-points in the patient treatment pathway. In comparison BIA, while relatively inexpensive and safe, is not routinely available outside the research setting and are generally considered less accurate than radiological assessment methods. A DEXA-based method was described by a single study and is an example of one of the earliest published experiences of body composition assessment in patients with esophageal cancer. While DEXA may have found some specific application in research at that time, it cannot be conceived for adoption in current standard practice. No study included in this review evaluates the cost of prospective assessment of body composition in patients with esophageal cancer. It is anticipated that with the development of both open-access and commercially available software that is able to perform semi-automated analysis of CT images the eventual cost of routine assessment of body composition in this patient group will be minimal. Variation in the way in which techniques were both applied in the measurement of body composition and interpretation of findings emphasize the need for more robust guidelines in this area. Convention dictates that CT assessment should account for total lumbar muscle cross-sectional area at the level of the midpoint of third lumbar vertebrae.6 Conveniently at this level, adipose tissue compartments may also be assessed simultaneously. As this review highlights, many authors fail to account for variation introduced by factors such as sex, race, tumor stage, and histological subtype when interpreting and reporting parameters of body composition. Where such controls do not exist it becomes impossible to compare individual studies and to draw meaning that is generalizable. Although one study included in this review sought to determine as psoas muscle index, based on the radiological feature of this muscle,14 there is no evidence to support the premise that the properties of a single muscle can be extrapolated to provide appraisal of global skeletal muscle mass or quality. Guidance for the use of BIA is less clear due to the nature of this technique. It is noteworthy that the current methods of defining pertinent characteristics of body composition, including sarcopenia and visceral adiposity, offer a binary interpretation of what are in reality complex parameters of body habitus.1 While such an approach is often desired within medical practice as it confers simplicity to management algorithms, it ignores patient specific factors that also predict an individual's risk. Furthermore, criteria that are adopted in the majority of studies to define sarcopenia are derived from a population of obese Canadian patients and as such may hold no relevance to other disease-specific patient cohorts.6 It is indeed remarkable that no other study identified herein originated from North America. Several studies from Asia included in this review did appear to adopt criteria that were ethnologically appropriate. Although results are derived from only two studies, the finding of lower visceral adipose tissue in patients with squamous cell carcinoma also serves to emphasize this point. The overall strength of conclusions that can be drawn from this review is diminished by the small number of heterogeneous studies that were identified. In regard to the finding of lower over-all survival in esophageal cancer patient with sarcopenia due to variability in reporting of cancer stage it was not possible to performed further subgroup analysis on the effects of this potentially important confounding factor. Furthermore, the absence of studies assessing patients with advanced metastatic esophageal cancer who are receiving palliative therapy is also recognized. Another important limitation of this review was the inability to formally examine differences between esophageal adenocarcinoma and squamous cell carcinoma with respect to body composition. Such a comparison would be highly pertinent considering the recognized importance of nutrition in esophageal tumorigenesis, in particular the association between obesity and adenocarcinomas of the esophagus. It is anticipated that the incidence and implications of sarcopenia, in addition to other phenotypes of body composition, will vary significantly with respect to histological subtype. It is also noted that a number of other studies, that were not eligible for inclusion in this review as they reported body composition assessment in a mixed cohort including patients with esophageal cancer, may offer further valuable insight into this subject (a complete list of these additional studies is provided on-line as supplementary digital content). Notwithstanding findings are broadly consistent with what has been reported in other disciplines, and appear to support the potential prognostic value of body composition features in the management of patients with esophageal cancer. Collaborative international efforts should now seek to better establish patterns of variation in body composition in esophageal cancer patient from disparate racial and geographical backgrounds, with the aim of establish consensus guidelines. In particular, the adoption of either a continuous or graded scale for determining sarcopenia and features of adiposity should also be considered. At the same time, a deeper understanding of the effects of nutritional and other interventions aimed at optimizing patient physiological and functional status during treatment of esophageal cancer must be sought. It would seem sensible that these efforts should focus on CT as the primary method of body composition assessment owing to its routine use in this patient cohort as well as its superiority over other existing methods. We would propose that, after further validation of the existing methodology, assessment of body composition has the potential to become a feasible and clinically relevant adjunct in the management of esophageal cancer patients. CONCLUSIONS This review highlights how the standardized assessment of body composition has the potential to support future decision-making in patients with esophageal cancer. While the finding that sarcopenia negatively affects patients long-term survival is not unexpected, it offers fresh impetus for future studies that must seek to clarify mechanistic drivers linking malnutrition with poor outcomes in this patient population. The strength of the overall conclusions that can be drawn from this review is however limited by the lack of consensus in regard to optimal methodology and reporting standards. Priority should therefore be given to established consensus guidelines for body composition assessment in esophageal cancer. SUPPLEMENTARY DATA Supplementary data are available at DOTESO online. Additional Supporting Information may be found in the online version of this article at the publisher's website: Supplementary digital content: Search strategy Results of STROBE assessment Body composition parameters in esophageal cancer patients Further details of associations between body composition parameters and treatment outcomes Reference list of noneligible studies Acknowledgments This systematic review and meta-analysis did not receive specific funding. P. R. Boshier is the recipient of the 2017 Joint Royal College of Surgeons (England)/Ryan Hill Research Fellowship. S. R. Markar is supported by the National Institute for Health Research. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health. Notes Specific author contributions: Study design: Piers R. Boshier, Vickie E. Baracos, Donald E. Low; Construction of search strategy: Piers R. Boshier, Vickie E. Baracos, Donald E. Low; Literature search: Piers R. Boshier, Rachel Heneghan; Data extraction: Piers R. Boshier, Rachel Heneghan, Sheraz R. Markar; Data analysis: Piers R. Boshier, Rachel Heneghan, Sheraz R. Markar, Vickie E Baracos; Drafting manuscript: Piers R. Boshier; Approval of final manuscript: Rachel Heneghan, Sheraz R. Markar, Vickie E. Baracos, Donald E. Low. References 1 Anandavadivelan P , Lagergren P . Cachexia in patients with oesophageal cancer . Nat Rev Clin Oncol 2016 ; 13 : 185 – 98 . Google Scholar CrossRef Search ADS PubMed 2 Cespedes Feliciano E M , Kroenke C H , Meyerhardt J A et al. Association of systemic inflammation and sarcopenia with survival in nonmetastatic colorectal cancer: results from the C SCANS study . JAMA Oncol 2017 ; 3 : e172319 . Google Scholar CrossRef Search ADS PubMed 3 Ebadi M , Martin L , Ghosh S et al. Subcutaneous adiposity is an independent predictor of mortality in cancer patients . Br J Cancer 2017 ; 117 : 148 – 55 . Google Scholar CrossRef Search ADS PubMed 4 Palmela C , Velho S , Agostinho L et al. Body composition as a prognostic factor of neoadjuvant chemotherapy toxicity and outcome in patients with locally advanced gastric cancer . J Gastric Cancer 2017 ; 17 : 74 – 87 . Google Scholar CrossRef Search ADS PubMed 5 Rangel E L , Rios-Diaz A J , Uyeda J W et al. Sarcopenia increases risk of long-term mortality in elderly patients undergoing emergency abdominal surgery . J Trauma Acute Care Surg 2017 ; 83 : 1179 – 86 . Google Scholar CrossRef Search ADS PubMed 6 Prado C M , Lieffers J R , McCargar L J et al. Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study . Lancet Oncol 2008 ; 9 : 629 – 35 . Google Scholar CrossRef Search ADS PubMed 7 Martin L , Birdsell L , Macdonald N et al. Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index . J Clin Oncol 2013 ; 31 : 1539 – 47 . Google Scholar CrossRef Search ADS PubMed 8 Fearon K , Strasser F , Anker S D et al. Definition and classification of cancer cachexia: an international consensus . Lancet Oncol 2011 ; 12 : 489 – 95 . Google Scholar CrossRef Search ADS PubMed 9 Vandenbroucke J P , von Elm E , Altman D G et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration . PLoS Med 2007 ; 4 : e297 . Google Scholar CrossRef Search ADS PubMed 10 Stroup D F , Berlin J A , Morton S C et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group . JAMA 2000 ; 283 : 2008 – 12 . Google Scholar CrossRef Search ADS PubMed 11 Parmar M K , Torri V , Stewart L . Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints . Stat Med 1998 ; 17 : 2815 – 34 . Google Scholar CrossRef Search ADS PubMed 12 Harada K , Ida S , Baba Y et al. Prognostic and clinical impact of sarcopenia in esophageal squamous cell carcinoma . Dis Esophagus 2016 ; 29 : 627 – 33 . Google Scholar CrossRef Search ADS PubMed 13 Li H , Bai E , Zhang Y , Jia Z , He S , Fu J . Role of Nampt and visceral adiposity in esophagogastric junction adenocarcinoma . J. Immunol Res 2017 ; 2017 : 1 – 7 . 14 Liu J , Motoyama S , Sato Y et al. Decreased skeletal muscle mass after neoadjuvant therapy correlates with poor prognosis in patients with esophageal cancer . Anticancer Res 2016 ; 36 : 6677 – 86 . Google Scholar CrossRef Search ADS PubMed 15 Nakashima Y , Saeki H , Nakanishi R et al. Assessment of sarcopenia as a predictor of poor outcomes after esophagectomy in elderly patients with esophageal cancer . Ann Surg 2018 ; 267 : 1100 – 4 . Google Scholar CrossRef Search ADS PubMed 16 Okamura A , Watanabe M , Mine S et al. Clinical impact of abdominal fat distribution on prognosis after esophagectomy for esophageal squamous cell carcinoma . Ann Surg Oncol 2016 ; 23 : 1387 – 94 . Google Scholar CrossRef Search ADS PubMed 17 Tanaka K , Yano M , Motoori M et al. Excess visceral fat accumulation is a risk factor for postoperative systemic inflammatory response syndrome in patients with esophageal cancer . Esophagus 2008 ; 5 : 75 – 80 . Google Scholar CrossRef Search ADS 18 Nishigori T , Okabe H , Tanaka E , Tsunoda S , Hisamori S , Sakai Y . Sarcopenia as a predictor of pulmonary complications after esophagectomy for thoracic esophageal cancer . J Surg Oncol 2016 ; 113 : 678 – 84 . Google Scholar CrossRef Search ADS PubMed 19 Anandavadivelan P , Brismar T B , Nilsson M , Johar A M , Martin L . Sarcopenic obesity: a probable risk factor for dose limiting toxicity during neoadjuvant chemotherapy in oesophageal cancer patients . Clin Nutr 2016 ; 35 : 724 – 30 . Google Scholar CrossRef Search ADS PubMed 20 Elliott J A , Doyle S L , Murphy C F et al. Sarcopenia: prevalence, and impact on operative and oncologic outcomes in the multimodal management of locally advanced esophageal cancer . Ann Surg 2017 ; 266 : 822 – 30 . Google Scholar CrossRef Search ADS PubMed 21 Gannon J A , Guinan E M , Doyle S L , Beddy P , Reynolds J V , Hussey J . Reduced fitness and physical functioning are long-term sequelae after curative treatment for esophageal cancer: a matched control study . Dis Esophagus 2017 ; 30 : 1 – 7 . Google Scholar CrossRef Search ADS PubMed 22 Grotenhuis B A , Shapiro J , van Adrichem S et al. Sarcopenia/muscle mass is not a prognostic factor for short- and long-term outcome after esophagectomy for cancer . World J Surg 2016 ; 40 : 2698 – 704 . Google Scholar CrossRef Search ADS PubMed 23 Reisinger K W , Bosmans J W , Uittenbogaart M et al. Loss of skeletal muscle mass during neoadjuvant chemoradiotherapy predicts postoperative mortality in esophageal cancer surgery . Ann Surg Oncol 2015 ; 22 : 4445 – 52 . Google Scholar CrossRef Search ADS PubMed 24 Tan B H , Brammer K , Randhawa N et al. Sarcopenia is associated with toxicity in patients undergoing neo-adjuvant chemotherapy for oesophago-gastric cancer . Eur J Surg Oncol 2015 ; 41 : 333 – 8 . Google Scholar CrossRef Search ADS PubMed 25 Yip C , Goh V , Davies A et al. Assessment of sarcopenia and changes in body composition after neoadjuvant chemotherapy and associations with clinical outcomes in oesophageal cancer . Eur Radiol 2014 ; 24 : 998 – 1005 . Google Scholar CrossRef Search ADS PubMed 26 Paireder M , Asari R , Kristo I et al. Impact of sarcopenia on outcome in patients with esophageal resection following neoadjuvant chemotherapy for esophageal cancer . Eur J Surg Oncol 2017 ; 43 : 478 – 84 . Google Scholar CrossRef Search ADS PubMed 27 Tamandl D , Paireder M , Asari R , Baltzer P A , Schoppmann S F , Ba-Ssalamah A . Markers of sarcopenia quantified by computed tomography predict adverse long-term outcome in patients with resected oesophageal or gastro-oesophageal junction cancer . Eur Radiol 2016 ; 26 : 1359 – 67 . Google Scholar CrossRef Search ADS PubMed 28 Beddy P , Howard J , McMahon C et al. Association of visceral adiposity with oesophageal and junctional adenocarcinomas . Br J Surg 2010 ; 97 : 1028 – 34 . Google Scholar CrossRef Search ADS PubMed 29 Donohoe C L , Doyle S L , McGarrigle S et al. Role of the insulin-like growth factor 1 axis and visceral adiposity in oesophageal adenocarcinoma . Br J Surg 2012 ; 99 : 387 – 96 . Google Scholar CrossRef Search ADS PubMed 30 Ida S , Watanabe M , Karashima R et al. Changes in body composition secondary to neoadjuvant chemotherapy for advanced esophageal cancer are related to the occurrence of postoperative complications after esophagectomy . Ann Surg Oncol 2014 ; 21 : 3675 – 9 . Google Scholar CrossRef Search ADS PubMed 31 Ida S , Watanabe M , Yoshida N et al. Sarcopenia is a predictor of postoperative respiratory complications in patients with esophageal cancer . Ann Surg Oncol 2015 ; 22 : 4432 – 7 . Google Scholar CrossRef Search ADS PubMed 32 Miyata H , Sugimura K , Motoori M et al. Clinical assessment of sarcopenia and changes in body composition during neoadjuvant chemotherapy for esophageal cancer . Anticancer Res 2017 ; 37 : 3053 – 9 . Google Scholar PubMed 33 Makiura D , Ono R , Inoue J et al. Preoperative sarcopenia is a predictor of postoperative pulmonary complications in esophageal cancer following esophagectomy: a retrospective cohort study . J Geriatr Oncol 2016 ; 7 : 430 – 6 . Google Scholar CrossRef Search ADS PubMed 34 Ishikawa T , Yasuda T , Doi T et al. The amino acid-rich elemental diet Elental® preserves lean body mass during chemo- or chemoradiotherapy for esophageal cancer . Oncol Rep 2016 ; 36 : 1093 – 100 . Google Scholar CrossRef Search ADS PubMed 35 Wu J , Huang C , Xiao H , Tang Q , Cai W . Weight loss and resting energy expenditure in male patients with newly diagnosed esophageal cancer . Nutrition 2013 ; 29 : 1310 – 4 . Google Scholar CrossRef Search ADS PubMed 36 Wu W , Zhong M , Zhu D M et al. Effect of early full-calorie nutrition support following esophagectomy: a randomized controlled trial . JPEN J Parenter Enteral Nutr 2017; 41: 1146–54 . 37 Guinan E M , Doyle S L , O’Neill L et al. Effects of a multimodal rehabilitation programme on inflammation and oxidative stress in oesophageal cancer survivors: the ReStOre feasibility study . Support Care Cancer 2017 ; 25 : 749 – 56 . Google Scholar CrossRef Search ADS PubMed 38 Ryan A M , Reynolds J V , Healy L et al. Enteral nutrition enriched with eicosapentaenoic acid (EPA) preserves lean body mass following esophageal cancer surgery: results of a double-blinded randomized controlled trial . Ann Surg 2009 ; 249 : 355 – 63 . Google Scholar CrossRef Search ADS PubMed 39 Becker Veronese C B , Guerra L T , Souza Grigolleti S , et al . Basal energy expenditure measured by indirect calorimetry in patients with squamous cell carcinoma of the esophagus . Nutr Hosp 2013 ; 28 : 142 – 7 . Google Scholar PubMed 40 Yamamoto K , Takiguchi S , Miyata H et al. Randomized phase II study of clinical effects of ghrelin after esophagectomy with gastric tube reconstruction . Surgery 2010 ; 148 : 31 – 38 . Google Scholar CrossRef Search ADS PubMed 41 Levolger S , van Vugt J L , de Bruin R W , IJzermans J N . Systematic review of sarcopenia in patients operated on for gastrointestinal and hepatopancreatobiliary malignancies . Br J Surg 2015 ; 102 : 1448 – 58 . Google Scholar CrossRef Search ADS PubMed 42 Shachar S S , Williams G R , Muss H B , Nishijima T F . Prognostic value of sarcopenia in adults with solid tumours: a meta-analysis and systematic review . Eur J Cancer 2016 ; 57 : 58 – 67 . Google Scholar CrossRef Search ADS PubMed 43 Daly J M , Fry W A , Little A G et al. Esophageal cancer: results of an American College of Surgeons patient care evaluation study . J Am Coll Surg 2000 ; 190 : 562 – 72 ; discussion 72–3 . Google Scholar CrossRef Search ADS PubMed 44 Correia M I , Waitzberg D L . The impact of malnutrition on morbidity, mortality, length of hospital stay and costs evaluated through a multivariate model analysis . Clin Nutr 2003 ; 22 : 235 – 9 . Google Scholar CrossRef Search ADS PubMed 45 Hynes O , Anandavadivelan P , Gossage J , Johar A M , Lagergren J , Lagergren P . The impact of pre- and postoperative weight loss and body mass index on prognosis in patients with oesophageal cancer . Eur J Surg Oncol 2017 ; 43 : 1559 – 65 . Google Scholar CrossRef Search ADS PubMed 46 Popuri K , Cobzas D , Esfandiari N , Baracos V , Jagersand M . Body composition assessment in axial CT images using FEM-based automatic segmentation of skeletal muscle . IEEE Trans Med Imaging 2016 ; 35 : 512 – 20 . Google Scholar CrossRef Search ADS PubMed © The Authors 2018. Published by Oxford University Press on behalf of International Society for Diseases of the Esophagus. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Diseases of the Esophagus Oxford University Press

Assessment of body composition and sarcopenia in patients with esophageal cancer: a systematic review and meta-analysis

Loading next page...
 
/lp/ou_press/assessment-of-body-composition-and-sarcopenia-in-patients-with-B7nIQ0J0qS
Publisher
Oxford University Press
Copyright
© The Authors 2018. Published by Oxford University Press on behalf of International Society for Diseases of the Esophagus.
ISSN
1120-8694
eISSN
1442-2050
D.O.I.
10.1093/dote/doy047
Publisher site
See Article on Publisher Site

Abstract

SUMMARY There has recently been increased interest in the assessment of body composition in patients with esophageal cancer for the purpose of nutritional evaluation and prognostication. This systematic review and meta-analysis intends to summarize and critically evaluate the current literature concerning the assessment of body composition in patients with esophageal cancer and to assess its potential implication upon early and late outcomes. A systematic literature search (up to August, 2017) was conducted for studies describing the assessment of body composition in patients with esophageal and gastroesophageal junctional cancer. Meta-analysis of postoperative outcomes including long-term survival was performed using random effects models. Twenty-nine studies reported the assessment of body composition in 3193 patients. Methods used to assess body composition in patients with esophageal cancer included computerized tomography (n = 18 studies), bioelectrical impedance analysis (n = 10), and dual-energy X-ray absorptiometry (n = 1). Significant variability was observed in regard to study design and the criteria used to define individual parameters of body composition. Sarcopenic patients had a higher incidence of postoperative pulmonary complications (7 studies, OR 2.03, 95% CI 1.32–3.11, P = 0.001) after esophagectomy. Meta-analysis of six studies presenting long-term outcomes after esophagectomy identified significantly worse survival in patients who were sarcopenic (HR 1.70, 95% CI 1.33– 2.17, P < 0.0001). The assessment of body composition has the potential to become a clinically useful tool that could support decision-making in patients with esophageal cancer. Current evidence is however weakened by inconsistencies in methods of assessing and reporting body composition in this patient group. BACKGROUND Esophageal cancer is among the diseases with the highest known association with cancer-related malnutrition.1 Solid tumors, including esophageal cancer, are typically associated with some degree of anorexia as well as underlying metabolic alterations including elevated energy expenditure, excess catabolism, and inflammation. In esophageal cancer, these effects are compounded by esophageal obstruction by the tumor mass and the individual and combined effects of radiation therapy, chemotherapy, and major surgery that may all potentially reduce nutritional intake. Recently, there has been an increase in the number of reports relating to body composition assessment in patients diagnosed with esophageal cancer for the purpose of nutritional evaluation and prognostication. This interest is borne out of an appreciation for inadequacies in current methods of assessing nutrition in this patient group. The measurement of skeletal muscle and/or adipose tissue have found success in a number of other areas of medicine for nutritional assessment,2–5 supporting an argument for such measures to become part of routine assessment. Variation in methods of assessing and defining parameters of body composition however constitutes a barrier to adoption of such techniques in routine clinical practice. Research into body composition assessment in esophageal cancer patients and the development guidelines for its application in clinical practice have been hampered by the lack of a standardized methodology and diagnostic criteria. Definitions of sarcopenia, a state of severe of depletion of skeletal muscle mass (and function), have been largely established using CT measures and defined based on the risk of mortality.6,7 The predominance of CT-based measures relates to their availability in routine clinical practice and the high precision and specificity for muscle and fat distribution (visceral, intermuscular, and subcutaneous). Other measures of body composition have, less frequently been used in cancer patients, including dual-energy X-ray absorptiometry (DEXA) and bioelectrical impedance (BIA). In the midst of growing endeavors to determine the clinical utility of body composition assessment in patients with esophageal cancer, it is considered timely that existing evidence be reviewed. The purpose of this review is therefore to summarize current literature concerning the assessment of body composition in patients with esophageal cancer and to assess its potential implication for survival and perioperative morbidity. METHODS Search strategy A systematic literature search (title and abstract of full papers and conference abstracts) of the Medline (1946–2017), Embase (1947–2017), Cochrane Library (1800–2017), and PsycINFO (1806–2017) databases was conducted on the 11th August 2017 (a copy of the full search strategy for the OVID platform is provided on-line as supplementary digital content: SDC 1). After excluding duplicates, two researchers (PRB, RH) independently reviewed the titles and abstracts of studies identified by the literature search. Where a study was considered to be potentially relevant to the research question a full copy of the publication was obtained for further review. Inclusion criteria were: studies reporting the assessment of body composition (by any method) in human subjects with cancer of either the esophagus or the gastroesophageal junction (receiving palliative or curative treatment) and published in the English language. Conference abstracts were excluded if not associated with a full publication at the time of literature search. Publications with mixed populations wherein the outcomes of patients with either benign disease or cancers at another site could not be separated from those of patients with cancer of the esophageal or gastroesophageal junction were also excluded. The reference lists of all included studies were hand-searched in order to identify other potentially relevant studies. In cases where there was any uncertainty in regard to the design or outcomes of the individual studies identified by the literature search, the corresponding author of that publication was contacted. Any areas of disagreement between the two primary researchers reviewing the result of the literature search were resolved by a third researcher (VEB). One researcher (PRB) extracted data, including author, year of publication, country of origin, study design, patient number, characteristics of patient population (age, sex, tumor histology, tumor stage and tumor grade, length of follow-up), method of body composition assessment, body mass index, details of body composition assessment, and reported clinical outcomes. Body composition measures were abstracted according to method of assessment (CT, DEXA, BIA), definition and cut points defining obesity and sarcopenia, mean and standard deviation and prevalence of sarcopenia. Date extraction was independently reviewed by a second researcher (VEB). Definitions Esophageal cancer: malignancy of the any portion of the esophagus and/or gastroesophageal junction (as defined by Siewert's classification). Body composition assessment: any method reporting either the volume or characteristics of muscle and/or adipose compartments within the body. Sarcopenia: severe depletion of skeletal muscle mass that has been defined by a range of criteria that are specific for the method of assessment. Cachexia: multifactorial syndrome characterized by ongoing loss of skeletal muscle mass (with or without loss of fat), that is not fully reversible using conventional nutritional support and that eventually leads to functional impairment.8 Assessment of methodological quality Methodological quality and standard of outcome reporting within included studies were assessed by two independent researchers (PRB, RH) using the STROBE checklist.9 Statistical analysis This systematic review and meta-analysis was conducted in accordance with the recommendations of the Cochrane Library and MOOSE guidelines.10 Statistical analysis was performed using the StatsDirect software (Version 3.3, StatsDirect Ltd, Altrincham, UK). The primary summary statistic used for survival analysis was the logarithm of the hazard ratio (HR) with 95% confidence intervals (CI). HR and its variance were extracted directly from the published manuscript. Where these data were not available it was determined through additional calculations that were dependent on the data presented by the study: annual mortality rates, survival curves, number of deaths, or percentage freedom from death.11 For categorical variables, analysis was performed by calculating the odds ratio (OR). The random effects, the DerSimonian–Laird method was used for the meta-analysis of outcomes. Funnel plots were used to visually assess publication bias of included studies. Heterogeneity between studies was assessed using the I2 value in order to determine the degree of variation not attributable to chance alone. I2 values were considered to represent low, moderate, and high degrees of heterogeneity where values were <25%, 25–75%, and >75%, respectively. Funnel plot asymmetry was assessed using the Egger test. Statistical significance was assigned to P values < 0.05. RESULTS Details of the literature search and study selection are reported in accordance with PRISMA guidelines (Fig. 1), with 29 studies meeting inclusion criteria.12–40 Four studies included in this review presented the outcomes of patients that had been previously reported within other publications. Inclusion of these studies was based on either the publication of data from a unique patient cohort not reported elsewhere 21,28 or additional relevant subgroup analysis.26,30 Fig. 1 View largeDownload slide PRISMA flow chart of literature search. Fig. 1 View largeDownload slide PRISMA flow chart of literature search. Methods of assessment used in each study, including criteria for key descriptors of body composition, are presented in Table 1. CT (n = 18 studies) and BIA (n = 10) were the most commonly reported methods of body composition assessment, while DEXA was utilized in a single study. Of the 17 studies published since January 1, 2016, CT was the chosen method of assessment in 12 (70%). A total of 3193 patients were evaluated (CT, n = 2550; BIA, n = 623; DEXA, n = 20) (Table 2). Assessment was predominantly performed in patients with resectable esophageal cancer prior to surgery either before and/or after neoadjuvant therapy. (Specific parameters of body composition, reported by individual studies are provided on-line as supplementary digital content). Table 1 Details of body composition assessment methodology Authors Year Region Method CT level of assessment CT muscle (Hounsfield unit threshold) CT adipose tissue (Hounsfield unit threshold) Normalization of measurements Definition(s) Ref Harada 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 44.5cm2/m2, ♀ < 36.5 cm2/m2 (12) Li 2017 Asia CT L3-4 disc space – – NR Visceral obesity: >130 cm2 (13) Liu 2016 Asia CT L3 mid-point – – Yes (H)†† – (14) Nakashima 2017 Asia CT L3 mid-point −29 to +150 - Yes (H,BSA) Sarcopenia: ♂ < 47.2 cm2/m2, ♀ < 36.9 cm2/m2 (15) Okamura 2016 Asia CT Level of umbilicus – All −200 to −50 NR – (16) Tanaka 2008 Asia CT Level of umbilicus – – NR Visceral obesity: >100 cm2 (17) Nishigori 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (18) Anandavadivelan 2016 Europe CT L3 mid-point −29 to +150 All −150 to −30, IM −29 to +30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (19) Elliott† 2017 Europe CT L3 mid-point −29 to +150 All −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (20) Gannon† 2017 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2 (21) Grotenhuis 2016 Europe CT L3 mid-point −30 to −150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (22) Reisinger 2015 Europe CT L3 mid-point −29 to +150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 Visceral obesity: ♂ > 163.8 cm2, ♀ > 80.1 cm2 (23) Tan 2015 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (24) Yip 2014 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (25) Paireder‡ 2017 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2,♀ < 39 cm2/m2 (26) Tamandl‡ 2016 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2, ♀ < 39 cm2/m2 (27) Beddy 2010 Europe CT L3-4 disc space – All −150 to −50 NR – (28) Donohoe§ 2012 Europe CT L3-4 disc space – – NR Visceral obesity: ♂ > 160 cm2, ♀ > 80 cm2 (29) Ida¶ 2014 Asia BIA – – – NR – (30) Ida¶ 2015 Asia BIA – – – Yes (H,G,A) Sarcopenia: SMM less than standard (<90%) (31) Miyata 2017 Asia BIA – – – Yes (H,A,G) Sarcopenia: SMM less than standard (<90%) (32) Makiura 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (33) Ishikawa 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (34) Wu 2013 Asia BIA – – – NR – (35) Wu 2016 Asia BIA – – – NR – (36) Guinan 2017 Europe BIA – – – NR – (37) Ryan 2009 Europe BIA – – – Yes (Hy) – (38) Becker Veronese 2013 S. America BIA – – – Yes‡‡ – (39) Yamamoto 2010 Asia DEXA – – – NR – (40) Authors Year Region Method CT level of assessment CT muscle (Hounsfield unit threshold) CT adipose tissue (Hounsfield unit threshold) Normalization of measurements Definition(s) Ref Harada 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 44.5cm2/m2, ♀ < 36.5 cm2/m2 (12) Li 2017 Asia CT L3-4 disc space – – NR Visceral obesity: >130 cm2 (13) Liu 2016 Asia CT L3 mid-point – – Yes (H)†† – (14) Nakashima 2017 Asia CT L3 mid-point −29 to +150 - Yes (H,BSA) Sarcopenia: ♂ < 47.2 cm2/m2, ♀ < 36.9 cm2/m2 (15) Okamura 2016 Asia CT Level of umbilicus – All −200 to −50 NR – (16) Tanaka 2008 Asia CT Level of umbilicus – – NR Visceral obesity: >100 cm2 (17) Nishigori 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (18) Anandavadivelan 2016 Europe CT L3 mid-point −29 to +150 All −150 to −30, IM −29 to +30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (19) Elliott† 2017 Europe CT L3 mid-point −29 to +150 All −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (20) Gannon† 2017 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2 (21) Grotenhuis 2016 Europe CT L3 mid-point −30 to −150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (22) Reisinger 2015 Europe CT L3 mid-point −29 to +150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 Visceral obesity: ♂ > 163.8 cm2, ♀ > 80.1 cm2 (23) Tan 2015 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (24) Yip 2014 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (25) Paireder‡ 2017 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2,♀ < 39 cm2/m2 (26) Tamandl‡ 2016 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2, ♀ < 39 cm2/m2 (27) Beddy 2010 Europe CT L3-4 disc space – All −150 to −50 NR – (28) Donohoe§ 2012 Europe CT L3-4 disc space – – NR Visceral obesity: ♂ > 160 cm2, ♀ > 80 cm2 (29) Ida¶ 2014 Asia BIA – – – NR – (30) Ida¶ 2015 Asia BIA – – – Yes (H,G,A) Sarcopenia: SMM less than standard (<90%) (31) Miyata 2017 Asia BIA – – – Yes (H,A,G) Sarcopenia: SMM less than standard (<90%) (32) Makiura 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (33) Ishikawa 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (34) Wu 2013 Asia BIA – – – NR – (35) Wu 2016 Asia BIA – – – NR – (36) Guinan 2017 Europe BIA – – – NR – (37) Ryan 2009 Europe BIA – – – Yes (Hy) – (38) Becker Veronese 2013 S. America BIA – – – Yes‡‡ – (39) Yamamoto 2010 Asia DEXA – – – NR – (40) A, age; Adipose tissue assessment: All, all adipose compartments; BIA, bioelectrical impedance analysis; BSA, body surface area; CT, computerized tomography; DEXA, dual-energy X-ray absorptiometry; G, sex; H, height squared; Hy, hydration; IM, intramuscular; L3/4, Third/fourth lumbar vertebra; NR, not reported; S. America, South America; SC, subcutaneous; ... V, visceral..... . †Elliott 2017 and Gannon 2017 are studies presenting outcomes from the same patient populations. Only data relating to patients who underwent primary surgery with no neoadjuvant chemotherapy (n = 8) presented by Gannon 2017, but not by Elliott 2017 are presented herein; ‡Paireder 2017 and Tamandl 2016 are studies presenting outcomes from the same patient populations. Data relating to patient survival and postoperative morbidity, use for the purpose of meta-analysis, are taken from Tamandl 2016 and Paireder 2017 respectively; §Beddy 2010 and Donohoe 2012 are studies presenting outcomes from the same patient populations. Only data relating to patients with squamous cell carcinoma (n = 46/156) reported by Beddy 2010, but not by Donohoe 2012 are presented herein; ¶Ida 2014 and Ida 2015 are studies presenting outcomes from the same patient populations. Ida 2014 reported the effect of neoadjuvant therapy on body composition whilst Ida 2015 reported data for postoperative morbidity use for the purpose of meta-analysis; ††Psoas muscle index determined by normalizing the cross-sectional areas of both psoas muscles, determined at the midpoint of the L3 vertebra, to patients height (cm2/m2); ‡‡Bioelectrical impedance analysis performed after 8hr fast and avoidance of physical exertion from the day before analysis; §§Definition of sarcopenia is based on the Asian Working Group for Sarcopenia (AWGS) consensus guidelines. View Large Table 1 Details of body composition assessment methodology Authors Year Region Method CT level of assessment CT muscle (Hounsfield unit threshold) CT adipose tissue (Hounsfield unit threshold) Normalization of measurements Definition(s) Ref Harada 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 44.5cm2/m2, ♀ < 36.5 cm2/m2 (12) Li 2017 Asia CT L3-4 disc space – – NR Visceral obesity: >130 cm2 (13) Liu 2016 Asia CT L3 mid-point – – Yes (H)†† – (14) Nakashima 2017 Asia CT L3 mid-point −29 to +150 - Yes (H,BSA) Sarcopenia: ♂ < 47.2 cm2/m2, ♀ < 36.9 cm2/m2 (15) Okamura 2016 Asia CT Level of umbilicus – All −200 to −50 NR – (16) Tanaka 2008 Asia CT Level of umbilicus – – NR Visceral obesity: >100 cm2 (17) Nishigori 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (18) Anandavadivelan 2016 Europe CT L3 mid-point −29 to +150 All −150 to −30, IM −29 to +30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (19) Elliott† 2017 Europe CT L3 mid-point −29 to +150 All −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (20) Gannon† 2017 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2 (21) Grotenhuis 2016 Europe CT L3 mid-point −30 to −150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (22) Reisinger 2015 Europe CT L3 mid-point −29 to +150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 Visceral obesity: ♂ > 163.8 cm2, ♀ > 80.1 cm2 (23) Tan 2015 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (24) Yip 2014 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (25) Paireder‡ 2017 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2,♀ < 39 cm2/m2 (26) Tamandl‡ 2016 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2, ♀ < 39 cm2/m2 (27) Beddy 2010 Europe CT L3-4 disc space – All −150 to −50 NR – (28) Donohoe§ 2012 Europe CT L3-4 disc space – – NR Visceral obesity: ♂ > 160 cm2, ♀ > 80 cm2 (29) Ida¶ 2014 Asia BIA – – – NR – (30) Ida¶ 2015 Asia BIA – – – Yes (H,G,A) Sarcopenia: SMM less than standard (<90%) (31) Miyata 2017 Asia BIA – – – Yes (H,A,G) Sarcopenia: SMM less than standard (<90%) (32) Makiura 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (33) Ishikawa 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (34) Wu 2013 Asia BIA – – – NR – (35) Wu 2016 Asia BIA – – – NR – (36) Guinan 2017 Europe BIA – – – NR – (37) Ryan 2009 Europe BIA – – – Yes (Hy) – (38) Becker Veronese 2013 S. America BIA – – – Yes‡‡ – (39) Yamamoto 2010 Asia DEXA – – – NR – (40) Authors Year Region Method CT level of assessment CT muscle (Hounsfield unit threshold) CT adipose tissue (Hounsfield unit threshold) Normalization of measurements Definition(s) Ref Harada 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 44.5cm2/m2, ♀ < 36.5 cm2/m2 (12) Li 2017 Asia CT L3-4 disc space – – NR Visceral obesity: >130 cm2 (13) Liu 2016 Asia CT L3 mid-point – – Yes (H)†† – (14) Nakashima 2017 Asia CT L3 mid-point −29 to +150 - Yes (H,BSA) Sarcopenia: ♂ < 47.2 cm2/m2, ♀ < 36.9 cm2/m2 (15) Okamura 2016 Asia CT Level of umbilicus – All −200 to −50 NR – (16) Tanaka 2008 Asia CT Level of umbilicus – – NR Visceral obesity: >100 cm2 (17) Nishigori 2016 Asia CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (18) Anandavadivelan 2016 Europe CT L3 mid-point −29 to +150 All −150 to −30, IM −29 to +30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (19) Elliott† 2017 Europe CT L3 mid-point −29 to +150 All −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 (20) Gannon† 2017 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2 (21) Grotenhuis 2016 Europe CT L3 mid-point −30 to −150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (22) Reisinger 2015 Europe CT L3 mid-point −29 to +150 All −190 to −30 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2, ♀ < 38.5 cm2/m2 Visceral obesity: ♂ > 163.8 cm2, ♀ > 80.1 cm2 (23) Tan 2015 Europe CT L3 mid-point −29 to +150 – Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (24) Yip 2014 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 52.4 cm2/m2,♀ < 38.5 cm2/m2 (25) Paireder‡ 2017 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2,♀ < 39 cm2/m2 (26) Tamandl‡ 2016 Europe CT L3 mid-point −29 to +150 SC/IM −190 to −30, V −150 to −50 Yes (H) Sarcopenia: ♂ < 55 cm2/m2, ♀ < 39 cm2/m2 (27) Beddy 2010 Europe CT L3-4 disc space – All −150 to −50 NR – (28) Donohoe§ 2012 Europe CT L3-4 disc space – – NR Visceral obesity: ♂ > 160 cm2, ♀ > 80 cm2 (29) Ida¶ 2014 Asia BIA – – – NR – (30) Ida¶ 2015 Asia BIA – – – Yes (H,G,A) Sarcopenia: SMM less than standard (<90%) (31) Miyata 2017 Asia BIA – – – Yes (H,A,G) Sarcopenia: SMM less than standard (<90%) (32) Makiura 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (33) Ishikawa 2016 Asia BIA – – – Yes (H) Sarcopenia§§: ♂ < 7.0 kg/m2, ♀ < 5.7 kg/m2 (34) Wu 2013 Asia BIA – – – NR – (35) Wu 2016 Asia BIA – – – NR – (36) Guinan 2017 Europe BIA – – – NR – (37) Ryan 2009 Europe BIA – – – Yes (Hy) – (38) Becker Veronese 2013 S. America BIA – – – Yes‡‡ – (39) Yamamoto 2010 Asia DEXA – – – NR – (40) A, age; Adipose tissue assessment: All, all adipose compartments; BIA, bioelectrical impedance analysis; BSA, body surface area; CT, computerized tomography; DEXA, dual-energy X-ray absorptiometry; G, sex; H, height squared; Hy, hydration; IM, intramuscular; L3/4, Third/fourth lumbar vertebra; NR, not reported; S. America, South America; SC, subcutaneous; ... V, visceral..... . †Elliott 2017 and Gannon 2017 are studies presenting outcomes from the same patient populations. Only data relating to patients who underwent primary surgery with no neoadjuvant chemotherapy (n = 8) presented by Gannon 2017, but not by Elliott 2017 are presented herein; ‡Paireder 2017 and Tamandl 2016 are studies presenting outcomes from the same patient populations. Data relating to patient survival and postoperative morbidity, use for the purpose of meta-analysis, are taken from Tamandl 2016 and Paireder 2017 respectively; §Beddy 2010 and Donohoe 2012 are studies presenting outcomes from the same patient populations. Only data relating to patients with squamous cell carcinoma (n = 46/156) reported by Beddy 2010, but not by Donohoe 2012 are presented herein; ¶Ida 2014 and Ida 2015 are studies presenting outcomes from the same patient populations. Ida 2014 reported the effect of neoadjuvant therapy on body composition whilst Ida 2015 reported data for postoperative morbidity use for the purpose of meta-analysis; ††Psoas muscle index determined by normalizing the cross-sectional areas of both psoas muscles, determined at the midpoint of the L3 vertebra, to patients height (cm2/m2); ‡‡Bioelectrical impedance analysis performed after 8hr fast and avoidance of physical exertion from the day before analysis; §§Definition of sarcopenia is based on the Asian Working Group for Sarcopenia (AWGS) consensus guidelines. View Large Table 2. Details of included studies Authors Method Cancer site No. Design Time of assessment Age Sex (% male) Histology T stage 3/4 Stage III/IV STARD score Refs. Harada CT E 325c P,CS Pre-Tx 53% ≥ 66 year 93% SCC = 100% 46% 46% 15 (12) Li CT GOJ 116 R,CS Pre-opg 61 [31–73]j 60% Ad-100% – – 11 (13) Liu CT E 84 R,CS B/A-NAT, PO 63 [40–74]j 86% SCC = 100% 44% – 11 (14) Nakashima CT E 341 R,CS Pre-opg – 85% Ad = 2%/SCC = 95%o – 40% 11 (15) Okamura CT E 150 R,CS Pre-opg 66 ± 8k 82% SCC = 100% 27% 32% 13 (16) Tanaka CT E 64 R,CS Pre-opg – 100% – 51% 45% 11 (17) Nishigori CT E 199 R,CS Pre-opg 56% ≥ 65 years 82% – 49% 35% 14 (18) Anandavadivelan CT E,GOJ 72 R,CS Pre-Tx 67 ± 7k 61% Ad 67%/SCC 33% 50% – 16 (19) Elliott CT E,GOJ 252d R,CS B/A-NAT, PO 62 ± 9k 80% Ad 81%/SCC 19% 56% – 16 (20) Gannon CTa E,GOJ 8 P,CC Pre-Tx – 100% – – – 13 (21) Grotenhuis CT E,GOJb 120 R,CS Pre-Tx 62 [19–78]j 73% Ad = 74%/SCC = 26% 36% – 12 (22) Reisinger CT E 123e R,CS B/A-NAT 63 ± 10k 82% Ad = 81%/SCC = 19% – 50% 16 (23) Tan CT E,GOJ 65 R,CS Pre-Tx – – – – – 12 (24) Yip CT E 35 R,CS B/A-NAT 63 [34–78]l 86% Ad = 86%/SCC = 14% – – 12 (25) Paireder CT E,GOJ 130 R,CS B/A-NAT 61 [31–81]j 82% Ad = 67%/SCC = 33% 31% – 15 (26) Tamandl CT E,GOJ 200 R,CS Pre-opg 64 [57–70]j 76% Ad = 69%/SCC = 30%p 50% – 15 (27) Beddy CT E,GOJ 46 R,CC Pre-Tx 65 ± 10k 46% SCC = 100% – – 12 (28) Donohoe CT E,GOJb 220 P,CS Pre-Tx 65 ± 11k 81% Ad = 100% 62% – 10 (29) Ida BIA E 30 P,CS B/A-NAT 64 [53–75]l 83% SCC = 100% 73% 83% 12 (30) Ida BIA E 138 P,CS Pre-opg 65 [42–85]l 88% SCC = 100% 41% 41% 12 (31) Miyata BIA E 94 P,CS B/A-NAT 64 ± 9k 81% SCC = 100% 76% 69% 12 (32) Makiura BIA E 104f R,CS Pre-opg, PO [61–76]m 85% Ad = 5%/SCC = 94%p 44% – 16 (33) Ishikawa BIA E 33 P,RCT B/A-NAT [44–79]m 82% SCC = 100% 73% – 11 (34) Wu BIA E 56 P,CC Pre-Tx 61 ± 9k 100% SCC = 100% – – 9 (35) Wu BIA E 73 P,RCT Pre-oph, PO – 69% Ad = 1%/SCC = 99% – 45% 16 (36) Guinan BIA E 12 P,CS PO 61 ± 7k 67% Ad = 67%/SCC = 33% – – 11 (37) Ryan BIA E,GOJ 53 P,RCT Pre-opi, PO – 72% – 36% – 15 (38) Becker Veronese BIA E,GOJ 30 P,CS Pre-Tx 61 ± 9k 70% SCC = 100% – 63% 12 (39) Yamamoto DEXA E 20 P,RCT PO 65 ± 6k,n 90% SCC = 100% – 70% 13 (40) Authors Method Cancer site No. Design Time of assessment Age Sex (% male) Histology T stage 3/4 Stage III/IV STARD score Refs. Harada CT E 325c P,CS Pre-Tx 53% ≥ 66 year 93% SCC = 100% 46% 46% 15 (12) Li CT GOJ 116 R,CS Pre-opg 61 [31–73]j 60% Ad-100% – – 11 (13) Liu CT E 84 R,CS B/A-NAT, PO 63 [40–74]j 86% SCC = 100% 44% – 11 (14) Nakashima CT E 341 R,CS Pre-opg – 85% Ad = 2%/SCC = 95%o – 40% 11 (15) Okamura CT E 150 R,CS Pre-opg 66 ± 8k 82% SCC = 100% 27% 32% 13 (16) Tanaka CT E 64 R,CS Pre-opg – 100% – 51% 45% 11 (17) Nishigori CT E 199 R,CS Pre-opg 56% ≥ 65 years 82% – 49% 35% 14 (18) Anandavadivelan CT E,GOJ 72 R,CS Pre-Tx 67 ± 7k 61% Ad 67%/SCC 33% 50% – 16 (19) Elliott CT E,GOJ 252d R,CS B/A-NAT, PO 62 ± 9k 80% Ad 81%/SCC 19% 56% – 16 (20) Gannon CTa E,GOJ 8 P,CC Pre-Tx – 100% – – – 13 (21) Grotenhuis CT E,GOJb 120 R,CS Pre-Tx 62 [19–78]j 73% Ad = 74%/SCC = 26% 36% – 12 (22) Reisinger CT E 123e R,CS B/A-NAT 63 ± 10k 82% Ad = 81%/SCC = 19% – 50% 16 (23) Tan CT E,GOJ 65 R,CS Pre-Tx – – – – – 12 (24) Yip CT E 35 R,CS B/A-NAT 63 [34–78]l 86% Ad = 86%/SCC = 14% – – 12 (25) Paireder CT E,GOJ 130 R,CS B/A-NAT 61 [31–81]j 82% Ad = 67%/SCC = 33% 31% – 15 (26) Tamandl CT E,GOJ 200 R,CS Pre-opg 64 [57–70]j 76% Ad = 69%/SCC = 30%p 50% – 15 (27) Beddy CT E,GOJ 46 R,CC Pre-Tx 65 ± 10k 46% SCC = 100% – – 12 (28) Donohoe CT E,GOJb 220 P,CS Pre-Tx 65 ± 11k 81% Ad = 100% 62% – 10 (29) Ida BIA E 30 P,CS B/A-NAT 64 [53–75]l 83% SCC = 100% 73% 83% 12 (30) Ida BIA E 138 P,CS Pre-opg 65 [42–85]l 88% SCC = 100% 41% 41% 12 (31) Miyata BIA E 94 P,CS B/A-NAT 64 ± 9k 81% SCC = 100% 76% 69% 12 (32) Makiura BIA E 104f R,CS Pre-opg, PO [61–76]m 85% Ad = 5%/SCC = 94%p 44% – 16 (33) Ishikawa BIA E 33 P,RCT B/A-NAT [44–79]m 82% SCC = 100% 73% – 11 (34) Wu BIA E 56 P,CC Pre-Tx 61 ± 9k 100% SCC = 100% – – 9 (35) Wu BIA E 73 P,RCT Pre-oph, PO – 69% Ad = 1%/SCC = 99% – 45% 16 (36) Guinan BIA E 12 P,CS PO 61 ± 7k 67% Ad = 67%/SCC = 33% – – 11 (37) Ryan BIA E,GOJ 53 P,RCT Pre-opi, PO – 72% – 36% – 15 (38) Becker Veronese BIA E,GOJ 30 P,CS Pre-Tx 61 ± 9k 70% SCC = 100% – 63% 12 (39) Yamamoto DEXA E 20 P,RCT PO 65 ± 6k,n 90% SCC = 100% – 70% 13 (40) E, esophageal. GOJ, gastroesophageal junction. R, retrospective. P, prospective. CS, case series. CC, case control. RCT, randomized controlled trial. Pre-Tx, pre-treatment (including neo-adjuvant therapy). B/A-NAT, before and after neo-adjuvant therapy. Pre-op, pre-operative. PO, post-operative. CT, computerized tomography. BIA, bioelectrical impedance analysis. DEXA, Dual-energy X-ray absorptiometry. SD, standard deviation. Ad, adenocarcinoma. SCC, squamous cell carcinoma. aData for body composition assessment by BIA is not considered herein; bSiewert type III tumors were excluded by authors; cIncludes 256 patients who underwent esophagectomy and 69 patients who received definitive chemoradiotherapy; d207 patients underwent surgery for which outcomes are reported for 192; eCT scans performed both before and after neoadjuvant chemoradiotherapy were available for 96 patients; fPostoperative body composition assessment was available for 74 patients; gSpecific timing of body composition assessment relative to neoadjuvant therapy is not reported by study; hAssessment of 11 preoperative patients was performed after neoadjuvant therapy; iAssessment of 27 preoperative patients was performed after neoadjuvant therapy; jMedian [range]; kMean ± standard deviation; lMean [range]; m[range]; nValue is for placebo group (n = 10); o3% other; p1% other. View Large Table 2. Details of included studies Authors Method Cancer site No. Design Time of assessment Age Sex (% male) Histology T stage 3/4 Stage III/IV STARD score Refs. Harada CT E 325c P,CS Pre-Tx 53% ≥ 66 year 93% SCC = 100% 46% 46% 15 (12) Li CT GOJ 116 R,CS Pre-opg 61 [31–73]j 60% Ad-100% – – 11 (13) Liu CT E 84 R,CS B/A-NAT, PO 63 [40–74]j 86% SCC = 100% 44% – 11 (14) Nakashima CT E 341 R,CS Pre-opg – 85% Ad = 2%/SCC = 95%o – 40% 11 (15) Okamura CT E 150 R,CS Pre-opg 66 ± 8k 82% SCC = 100% 27% 32% 13 (16) Tanaka CT E 64 R,CS Pre-opg – 100% – 51% 45% 11 (17) Nishigori CT E 199 R,CS Pre-opg 56% ≥ 65 years 82% – 49% 35% 14 (18) Anandavadivelan CT E,GOJ 72 R,CS Pre-Tx 67 ± 7k 61% Ad 67%/SCC 33% 50% – 16 (19) Elliott CT E,GOJ 252d R,CS B/A-NAT, PO 62 ± 9k 80% Ad 81%/SCC 19% 56% – 16 (20) Gannon CTa E,GOJ 8 P,CC Pre-Tx – 100% – – – 13 (21) Grotenhuis CT E,GOJb 120 R,CS Pre-Tx 62 [19–78]j 73% Ad = 74%/SCC = 26% 36% – 12 (22) Reisinger CT E 123e R,CS B/A-NAT 63 ± 10k 82% Ad = 81%/SCC = 19% – 50% 16 (23) Tan CT E,GOJ 65 R,CS Pre-Tx – – – – – 12 (24) Yip CT E 35 R,CS B/A-NAT 63 [34–78]l 86% Ad = 86%/SCC = 14% – – 12 (25) Paireder CT E,GOJ 130 R,CS B/A-NAT 61 [31–81]j 82% Ad = 67%/SCC = 33% 31% – 15 (26) Tamandl CT E,GOJ 200 R,CS Pre-opg 64 [57–70]j 76% Ad = 69%/SCC = 30%p 50% – 15 (27) Beddy CT E,GOJ 46 R,CC Pre-Tx 65 ± 10k 46% SCC = 100% – – 12 (28) Donohoe CT E,GOJb 220 P,CS Pre-Tx 65 ± 11k 81% Ad = 100% 62% – 10 (29) Ida BIA E 30 P,CS B/A-NAT 64 [53–75]l 83% SCC = 100% 73% 83% 12 (30) Ida BIA E 138 P,CS Pre-opg 65 [42–85]l 88% SCC = 100% 41% 41% 12 (31) Miyata BIA E 94 P,CS B/A-NAT 64 ± 9k 81% SCC = 100% 76% 69% 12 (32) Makiura BIA E 104f R,CS Pre-opg, PO [61–76]m 85% Ad = 5%/SCC = 94%p 44% – 16 (33) Ishikawa BIA E 33 P,RCT B/A-NAT [44–79]m 82% SCC = 100% 73% – 11 (34) Wu BIA E 56 P,CC Pre-Tx 61 ± 9k 100% SCC = 100% – – 9 (35) Wu BIA E 73 P,RCT Pre-oph, PO – 69% Ad = 1%/SCC = 99% – 45% 16 (36) Guinan BIA E 12 P,CS PO 61 ± 7k 67% Ad = 67%/SCC = 33% – – 11 (37) Ryan BIA E,GOJ 53 P,RCT Pre-opi, PO – 72% – 36% – 15 (38) Becker Veronese BIA E,GOJ 30 P,CS Pre-Tx 61 ± 9k 70% SCC = 100% – 63% 12 (39) Yamamoto DEXA E 20 P,RCT PO 65 ± 6k,n 90% SCC = 100% – 70% 13 (40) Authors Method Cancer site No. Design Time of assessment Age Sex (% male) Histology T stage 3/4 Stage III/IV STARD score Refs. Harada CT E 325c P,CS Pre-Tx 53% ≥ 66 year 93% SCC = 100% 46% 46% 15 (12) Li CT GOJ 116 R,CS Pre-opg 61 [31–73]j 60% Ad-100% – – 11 (13) Liu CT E 84 R,CS B/A-NAT, PO 63 [40–74]j 86% SCC = 100% 44% – 11 (14) Nakashima CT E 341 R,CS Pre-opg – 85% Ad = 2%/SCC = 95%o – 40% 11 (15) Okamura CT E 150 R,CS Pre-opg 66 ± 8k 82% SCC = 100% 27% 32% 13 (16) Tanaka CT E 64 R,CS Pre-opg – 100% – 51% 45% 11 (17) Nishigori CT E 199 R,CS Pre-opg 56% ≥ 65 years 82% – 49% 35% 14 (18) Anandavadivelan CT E,GOJ 72 R,CS Pre-Tx 67 ± 7k 61% Ad 67%/SCC 33% 50% – 16 (19) Elliott CT E,GOJ 252d R,CS B/A-NAT, PO 62 ± 9k 80% Ad 81%/SCC 19% 56% – 16 (20) Gannon CTa E,GOJ 8 P,CC Pre-Tx – 100% – – – 13 (21) Grotenhuis CT E,GOJb 120 R,CS Pre-Tx 62 [19–78]j 73% Ad = 74%/SCC = 26% 36% – 12 (22) Reisinger CT E 123e R,CS B/A-NAT 63 ± 10k 82% Ad = 81%/SCC = 19% – 50% 16 (23) Tan CT E,GOJ 65 R,CS Pre-Tx – – – – – 12 (24) Yip CT E 35 R,CS B/A-NAT 63 [34–78]l 86% Ad = 86%/SCC = 14% – – 12 (25) Paireder CT E,GOJ 130 R,CS B/A-NAT 61 [31–81]j 82% Ad = 67%/SCC = 33% 31% – 15 (26) Tamandl CT E,GOJ 200 R,CS Pre-opg 64 [57–70]j 76% Ad = 69%/SCC = 30%p 50% – 15 (27) Beddy CT E,GOJ 46 R,CC Pre-Tx 65 ± 10k 46% SCC = 100% – – 12 (28) Donohoe CT E,GOJb 220 P,CS Pre-Tx 65 ± 11k 81% Ad = 100% 62% – 10 (29) Ida BIA E 30 P,CS B/A-NAT 64 [53–75]l 83% SCC = 100% 73% 83% 12 (30) Ida BIA E 138 P,CS Pre-opg 65 [42–85]l 88% SCC = 100% 41% 41% 12 (31) Miyata BIA E 94 P,CS B/A-NAT 64 ± 9k 81% SCC = 100% 76% 69% 12 (32) Makiura BIA E 104f R,CS Pre-opg, PO [61–76]m 85% Ad = 5%/SCC = 94%p 44% – 16 (33) Ishikawa BIA E 33 P,RCT B/A-NAT [44–79]m 82% SCC = 100% 73% – 11 (34) Wu BIA E 56 P,CC Pre-Tx 61 ± 9k 100% SCC = 100% – – 9 (35) Wu BIA E 73 P,RCT Pre-oph, PO – 69% Ad = 1%/SCC = 99% – 45% 16 (36) Guinan BIA E 12 P,CS PO 61 ± 7k 67% Ad = 67%/SCC = 33% – – 11 (37) Ryan BIA E,GOJ 53 P,RCT Pre-opi, PO – 72% – 36% – 15 (38) Becker Veronese BIA E,GOJ 30 P,CS Pre-Tx 61 ± 9k 70% SCC = 100% – 63% 12 (39) Yamamoto DEXA E 20 P,RCT PO 65 ± 6k,n 90% SCC = 100% – 70% 13 (40) E, esophageal. GOJ, gastroesophageal junction. R, retrospective. P, prospective. CS, case series. CC, case control. RCT, randomized controlled trial. Pre-Tx, pre-treatment (including neo-adjuvant therapy). B/A-NAT, before and after neo-adjuvant therapy. Pre-op, pre-operative. PO, post-operative. CT, computerized tomography. BIA, bioelectrical impedance analysis. DEXA, Dual-energy X-ray absorptiometry. SD, standard deviation. Ad, adenocarcinoma. SCC, squamous cell carcinoma. aData for body composition assessment by BIA is not considered herein; bSiewert type III tumors were excluded by authors; cIncludes 256 patients who underwent esophagectomy and 69 patients who received definitive chemoradiotherapy; d207 patients underwent surgery for which outcomes are reported for 192; eCT scans performed both before and after neoadjuvant chemoradiotherapy were available for 96 patients; fPostoperative body composition assessment was available for 74 patients; gSpecific timing of body composition assessment relative to neoadjuvant therapy is not reported by study; hAssessment of 11 preoperative patients was performed after neoadjuvant therapy; iAssessment of 27 preoperative patients was performed after neoadjuvant therapy; jMedian [range]; kMean ± standard deviation; lMean [range]; m[range]; nValue is for placebo group (n = 10); o3% other; p1% other. View Large Reporting standards and methodological quality Assessment of reporting standards against the 22 criteria listed within the STROBE checklist demonstrated a mean score of 13 ± 2 (range: 9–16) (Table 2, full details of STROBE assessment for individual studies is provided on-line as supplementary digital content). Criteria for defining parameters of body composition varied considerably (Table 1). CT cut-points defining sarcopenia were reported in 12 studies. In 8 of these 12 reports the authors adopted sex specific cut-points previously described for mortality risk in a population of obese (BMI ≥ 30 kg/m2) Canadians with lung and GI cancers,6 regardless of whether the intended sample was obese. The somewhat higher cut-points used by Paireder et al.26,27 reflect a typographical error in the publication from which they were derived8 in which criteria published by Prado et al.6 are cited as the source. The values derived by Prado et al.6 have been used multiple times, permitting comparison between studies that used them. However different, lower sarcopenia cut-points have been shown in patients of BMI < 25 kg/m212 and these may be more relevant for esophageal cancer populations. The ‘true’ prevalence of sarcopenia in these populations may therefore be overestimated. Two Asian studies, determined cut-points based on the unique characteristics of their study population.12,15 Studies were also heterogeneous with respect to several factors known to influence body composition: race, sex, BMI, and tumor characteristics (Table 2). Variation in these factors was broadly reflective of known differences that exist between Asian and Western populations. For example the mean overall BMI in publications in Asian populations (22.1 kg/m2) was lower than that in Caucasian samples (25.6 kg/m2; P < 0.0001). Body composition assessment in esophageal cancer The reported prevalence of sarcopenia in preoperative esophageal cancer patients varied between 16% and 75% (full details of body composition parameters determined in esophageal cancer patients is provided on-line as supplementary digital content). Prevalence values can only be compared between studies that used identical criteria for sarcopenia in populations with similar characteristics; other comparisons are unreliable owing to differences in methodologies, patient populations, and criteria for defining this parameter (Tables 1 and 2). Based on 7 studies that used Prado's criteria for CT-defined sarcopenia in Caucasian populations, the overall prevalence of sarcopenia was 38% (range: 16–56%). Visceral adiposity of patients with squamous cell carcinoma was presented by two studies16,28 and tended to be lower than in patient cohorts where adenocarcinoma was the predominant tumor subtype.23,25,27,29 Meta-analysis of the studies reporting the influence of body composition on early postoperative outcomes and long-term survival Early postoperative mortality Meta-analysis of four studies determined that preoperative sarcopenia, assessed by CT, was not associated with early mortality (30-day and/or in-hospital) following esophagectomy (OR 1.18, 95% CI 0.47–2.96, P = 0.718).15,18,20,22 Studies exhibited low heterogeneity (I2 0%) and no significant bias (Egger −0.32, P = 0.821). Postoperative morbidity Preoperative sarcopenia, assessed by CT, was not associated with significantly higher rates of overall postoperative complications when defined as Clavien-Dindo ≥ II (OR 1.19, 95% CI 0.78 to 1.81, P = 0.431, I2 12.9%).18,20,22 The association of preoperative sarcopenia and post-esophagectomy pulmonary complications was reported in 7 studies (five CT, two BIA).12,15,18,20,26,31,33 Meta-analysis confirmed higher rates of postoperative pneumonia in sarcopenic patients (OR 2.03, 95% CI 1.32–3.11, P = 0.001) (Fig. 2). Moderate heterogeneity between studies was observed (I2 45.4%) without evidence of significant bias (Egger 2.91, P = 0.344). This finding was conserved when studies that assessed sarcopenia by CT methods were considered independently (OR 1.68, 95% CI 1.04 to 2.70, P = 0.033; I2 41.8%). Fig. 2 View largeDownload slide Summary meta-analysis of studies reporting the effect of sarcopenia on the occurrence of postoperative respiratory complications in patients undergoing esophagectomy for oesophageal cancer (OR 2.03, 95% CI 1.32–3.11, P = 0.001). Fig. 2 View largeDownload slide Summary meta-analysis of studies reporting the effect of sarcopenia on the occurrence of postoperative respiratory complications in patients undergoing esophagectomy for oesophageal cancer (OR 2.03, 95% CI 1.32–3.11, P = 0.001). There was no increased risk of nonpulmonary postoperative complications in patients with sarcopenia, including: anastomotic leak (six studies: OR 1.33, 95% CI 0.85–2.09, P = 0.213; I2 32.1%);12,15,18,20,26,31 cardiac complications (five studies: OR 1.32, 95% CI 0.82–2.14, P = 0.256; I2 0.0%);12,18,20,31,33 surgical site infection (three studies: OR 1.26, 95% CI 0.81 to 1.96, P = 0.315; I2 0.0%).12,18,31 These relationships remained nonsignificant following reanalysis of only those studies utilizing CT for the assessment of sarcopenia. Postoperative morbidity was not associated with measures of body composition including visceral adiposity and sarcopenia in a number of additional studies,14,16,17,22,23,25,32 however outcomes presented by these studies were not suitable for meta-analysis on account of variation in methodology and reporting of data. Long-term survival The influence of preoperative sarcopenia, as determined by CT, on the survival of patients following treatment for esophageal cancer was reported in six studies.12,15,20,22,25,27 Meta-analysis of outcomes presented within these studies identified that sarcopenia was associated with lower overall survival (HR 1.70, 95% CI 1.33–2.17, P < 0.0001) (Fig. 3). Heterogeneity between studies was moderate (I2 48.1%) and was without evidence of significant bias (Egger −0.22, P = 0.915). Meta-analysis of studies including patients from European centers that underwent esophagectomy, using CT criteria for sarcopenia largely based on those published by Prado et al.,6 confirmed the association between this variable and overall survival (HR 1.67, 95% CI 1.18 to 2.38, P = 0.004). This analysis was subject to moderate heterogeneity between studies (I2 61.7%) and was without significant bias (Egger −1.67, P = 0.724). Fig. 3 View largeDownload slide Summary meta-analysis of studies reporting the effect of sarcopenia on the survival of patients undergoing esophagectomy for oesophageal cancer (HR 1.70, 95% CI 1.33 to 2.17, P < 0.0001). Median reported follow-up: Elliott, 26 months; Grotenhuis, 20 months; Harada, 50 months; Tamandl, 35 months; Yip 24 months, and; Nakashima, no-reported. Fig. 3 View largeDownload slide Summary meta-analysis of studies reporting the effect of sarcopenia on the survival of patients undergoing esophagectomy for oesophageal cancer (HR 1.70, 95% CI 1.33 to 2.17, P < 0.0001). Median reported follow-up: Elliott, 26 months; Grotenhuis, 20 months; Harada, 50 months; Tamandl, 35 months; Yip 24 months, and; Nakashima, no-reported. Several studies reported the influence of a number of additional body composition parameters on survival, although these data were not suitable for meta-analysis. (Further details of associations between body composition parameters and treatment outcomes are provided on-line as supplementary digital content). DISCUSSION This systematic review and meta-analysis summarizes the existing evidence regarding body composition assessment in esophageal cancer and its potential implications for patient management and prognosis. The principal findings were: (i) heterogeneity of approaches to body composition assessment in patients with esophageal cancer; (ii) significant variance in the reported prevalence of sarcopenia; (iii) higher rates of pulmonary complications following esophagectomy in patients found to be sarcopenic prior to surgery, and; (iv) an association between sarcopenia and reduced overall survival in patients undergoing esophagectomy. Findings were similar to what has been shown for other solid organ tumors.41,42 Weight loss and malnutrition remain a central concern for patients at all stages of treatment for esophageal cancer. At the time of diagnosis more than half of patients with esophageal cancer report some degree of weight loss.43 The inability of patients to maintain body weight is recognized to be a poor prognostic indicator in terms of therapeutic response and overall survival.44,45 Historically, a wide range of approaches have been utilized to assess nutrition in patients with esophageal cancer. These can broadly be divided in anthropometric measures, blood markers, measures of energy expenditure, validate nutritional risk scores, and patient reported dietary history. The current review focuses on the assessment of body composition due to the promise this approach has demonstrated in other areas of medicine and surgery as well as the relative ease with which it might form part of future routine clinical practice.46 Although three techniques for body composition assessment in patients with esophageal cancer have been described, CT and BIA were most commonly utilized within studies identified in the review. Unlike BIA, CT forms a regular part of the standard management of esophageal cancer patients and hence offers an opportune method for the assessment of body composition at specific and relevant time-points in the patient treatment pathway. In comparison BIA, while relatively inexpensive and safe, is not routinely available outside the research setting and are generally considered less accurate than radiological assessment methods. A DEXA-based method was described by a single study and is an example of one of the earliest published experiences of body composition assessment in patients with esophageal cancer. While DEXA may have found some specific application in research at that time, it cannot be conceived for adoption in current standard practice. No study included in this review evaluates the cost of prospective assessment of body composition in patients with esophageal cancer. It is anticipated that with the development of both open-access and commercially available software that is able to perform semi-automated analysis of CT images the eventual cost of routine assessment of body composition in this patient group will be minimal. Variation in the way in which techniques were both applied in the measurement of body composition and interpretation of findings emphasize the need for more robust guidelines in this area. Convention dictates that CT assessment should account for total lumbar muscle cross-sectional area at the level of the midpoint of third lumbar vertebrae.6 Conveniently at this level, adipose tissue compartments may also be assessed simultaneously. As this review highlights, many authors fail to account for variation introduced by factors such as sex, race, tumor stage, and histological subtype when interpreting and reporting parameters of body composition. Where such controls do not exist it becomes impossible to compare individual studies and to draw meaning that is generalizable. Although one study included in this review sought to determine as psoas muscle index, based on the radiological feature of this muscle,14 there is no evidence to support the premise that the properties of a single muscle can be extrapolated to provide appraisal of global skeletal muscle mass or quality. Guidance for the use of BIA is less clear due to the nature of this technique. It is noteworthy that the current methods of defining pertinent characteristics of body composition, including sarcopenia and visceral adiposity, offer a binary interpretation of what are in reality complex parameters of body habitus.1 While such an approach is often desired within medical practice as it confers simplicity to management algorithms, it ignores patient specific factors that also predict an individual's risk. Furthermore, criteria that are adopted in the majority of studies to define sarcopenia are derived from a population of obese Canadian patients and as such may hold no relevance to other disease-specific patient cohorts.6 It is indeed remarkable that no other study identified herein originated from North America. Several studies from Asia included in this review did appear to adopt criteria that were ethnologically appropriate. Although results are derived from only two studies, the finding of lower visceral adipose tissue in patients with squamous cell carcinoma also serves to emphasize this point. The overall strength of conclusions that can be drawn from this review is diminished by the small number of heterogeneous studies that were identified. In regard to the finding of lower over-all survival in esophageal cancer patient with sarcopenia due to variability in reporting of cancer stage it was not possible to performed further subgroup analysis on the effects of this potentially important confounding factor. Furthermore, the absence of studies assessing patients with advanced metastatic esophageal cancer who are receiving palliative therapy is also recognized. Another important limitation of this review was the inability to formally examine differences between esophageal adenocarcinoma and squamous cell carcinoma with respect to body composition. Such a comparison would be highly pertinent considering the recognized importance of nutrition in esophageal tumorigenesis, in particular the association between obesity and adenocarcinomas of the esophagus. It is anticipated that the incidence and implications of sarcopenia, in addition to other phenotypes of body composition, will vary significantly with respect to histological subtype. It is also noted that a number of other studies, that were not eligible for inclusion in this review as they reported body composition assessment in a mixed cohort including patients with esophageal cancer, may offer further valuable insight into this subject (a complete list of these additional studies is provided on-line as supplementary digital content). Notwithstanding findings are broadly consistent with what has been reported in other disciplines, and appear to support the potential prognostic value of body composition features in the management of patients with esophageal cancer. Collaborative international efforts should now seek to better establish patterns of variation in body composition in esophageal cancer patient from disparate racial and geographical backgrounds, with the aim of establish consensus guidelines. In particular, the adoption of either a continuous or graded scale for determining sarcopenia and features of adiposity should also be considered. At the same time, a deeper understanding of the effects of nutritional and other interventions aimed at optimizing patient physiological and functional status during treatment of esophageal cancer must be sought. It would seem sensible that these efforts should focus on CT as the primary method of body composition assessment owing to its routine use in this patient cohort as well as its superiority over other existing methods. We would propose that, after further validation of the existing methodology, assessment of body composition has the potential to become a feasible and clinically relevant adjunct in the management of esophageal cancer patients. CONCLUSIONS This review highlights how the standardized assessment of body composition has the potential to support future decision-making in patients with esophageal cancer. While the finding that sarcopenia negatively affects patients long-term survival is not unexpected, it offers fresh impetus for future studies that must seek to clarify mechanistic drivers linking malnutrition with poor outcomes in this patient population. The strength of the overall conclusions that can be drawn from this review is however limited by the lack of consensus in regard to optimal methodology and reporting standards. Priority should therefore be given to established consensus guidelines for body composition assessment in esophageal cancer. SUPPLEMENTARY DATA Supplementary data are available at DOTESO online. Additional Supporting Information may be found in the online version of this article at the publisher's website: Supplementary digital content: Search strategy Results of STROBE assessment Body composition parameters in esophageal cancer patients Further details of associations between body composition parameters and treatment outcomes Reference list of noneligible studies Acknowledgments This systematic review and meta-analysis did not receive specific funding. P. R. Boshier is the recipient of the 2017 Joint Royal College of Surgeons (England)/Ryan Hill Research Fellowship. S. R. Markar is supported by the National Institute for Health Research. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health. Notes Specific author contributions: Study design: Piers R. Boshier, Vickie E. Baracos, Donald E. Low; Construction of search strategy: Piers R. Boshier, Vickie E. Baracos, Donald E. Low; Literature search: Piers R. Boshier, Rachel Heneghan; Data extraction: Piers R. Boshier, Rachel Heneghan, Sheraz R. Markar; Data analysis: Piers R. Boshier, Rachel Heneghan, Sheraz R. Markar, Vickie E Baracos; Drafting manuscript: Piers R. Boshier; Approval of final manuscript: Rachel Heneghan, Sheraz R. Markar, Vickie E. Baracos, Donald E. Low. References 1 Anandavadivelan P , Lagergren P . Cachexia in patients with oesophageal cancer . Nat Rev Clin Oncol 2016 ; 13 : 185 – 98 . Google Scholar CrossRef Search ADS PubMed 2 Cespedes Feliciano E M , Kroenke C H , Meyerhardt J A et al. Association of systemic inflammation and sarcopenia with survival in nonmetastatic colorectal cancer: results from the C SCANS study . JAMA Oncol 2017 ; 3 : e172319 . Google Scholar CrossRef Search ADS PubMed 3 Ebadi M , Martin L , Ghosh S et al. Subcutaneous adiposity is an independent predictor of mortality in cancer patients . Br J Cancer 2017 ; 117 : 148 – 55 . Google Scholar CrossRef Search ADS PubMed 4 Palmela C , Velho S , Agostinho L et al. Body composition as a prognostic factor of neoadjuvant chemotherapy toxicity and outcome in patients with locally advanced gastric cancer . J Gastric Cancer 2017 ; 17 : 74 – 87 . Google Scholar CrossRef Search ADS PubMed 5 Rangel E L , Rios-Diaz A J , Uyeda J W et al. Sarcopenia increases risk of long-term mortality in elderly patients undergoing emergency abdominal surgery . J Trauma Acute Care Surg 2017 ; 83 : 1179 – 86 . Google Scholar CrossRef Search ADS PubMed 6 Prado C M , Lieffers J R , McCargar L J et al. Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study . Lancet Oncol 2008 ; 9 : 629 – 35 . Google Scholar CrossRef Search ADS PubMed 7 Martin L , Birdsell L , Macdonald N et al. Cancer cachexia in the age of obesity: skeletal muscle depletion is a powerful prognostic factor, independent of body mass index . J Clin Oncol 2013 ; 31 : 1539 – 47 . Google Scholar CrossRef Search ADS PubMed 8 Fearon K , Strasser F , Anker S D et al. Definition and classification of cancer cachexia: an international consensus . Lancet Oncol 2011 ; 12 : 489 – 95 . Google Scholar CrossRef Search ADS PubMed 9 Vandenbroucke J P , von Elm E , Altman D G et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration . PLoS Med 2007 ; 4 : e297 . Google Scholar CrossRef Search ADS PubMed 10 Stroup D F , Berlin J A , Morton S C et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group . JAMA 2000 ; 283 : 2008 – 12 . Google Scholar CrossRef Search ADS PubMed 11 Parmar M K , Torri V , Stewart L . Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints . Stat Med 1998 ; 17 : 2815 – 34 . Google Scholar CrossRef Search ADS PubMed 12 Harada K , Ida S , Baba Y et al. Prognostic and clinical impact of sarcopenia in esophageal squamous cell carcinoma . Dis Esophagus 2016 ; 29 : 627 – 33 . Google Scholar CrossRef Search ADS PubMed 13 Li H , Bai E , Zhang Y , Jia Z , He S , Fu J . Role of Nampt and visceral adiposity in esophagogastric junction adenocarcinoma . J. Immunol Res 2017 ; 2017 : 1 – 7 . 14 Liu J , Motoyama S , Sato Y et al. Decreased skeletal muscle mass after neoadjuvant therapy correlates with poor prognosis in patients with esophageal cancer . Anticancer Res 2016 ; 36 : 6677 – 86 . Google Scholar CrossRef Search ADS PubMed 15 Nakashima Y , Saeki H , Nakanishi R et al. Assessment of sarcopenia as a predictor of poor outcomes after esophagectomy in elderly patients with esophageal cancer . Ann Surg 2018 ; 267 : 1100 – 4 . Google Scholar CrossRef Search ADS PubMed 16 Okamura A , Watanabe M , Mine S et al. Clinical impact of abdominal fat distribution on prognosis after esophagectomy for esophageal squamous cell carcinoma . Ann Surg Oncol 2016 ; 23 : 1387 – 94 . Google Scholar CrossRef Search ADS PubMed 17 Tanaka K , Yano M , Motoori M et al. Excess visceral fat accumulation is a risk factor for postoperative systemic inflammatory response syndrome in patients with esophageal cancer . Esophagus 2008 ; 5 : 75 – 80 . Google Scholar CrossRef Search ADS 18 Nishigori T , Okabe H , Tanaka E , Tsunoda S , Hisamori S , Sakai Y . Sarcopenia as a predictor of pulmonary complications after esophagectomy for thoracic esophageal cancer . J Surg Oncol 2016 ; 113 : 678 – 84 . Google Scholar CrossRef Search ADS PubMed 19 Anandavadivelan P , Brismar T B , Nilsson M , Johar A M , Martin L . Sarcopenic obesity: a probable risk factor for dose limiting toxicity during neoadjuvant chemotherapy in oesophageal cancer patients . Clin Nutr 2016 ; 35 : 724 – 30 . Google Scholar CrossRef Search ADS PubMed 20 Elliott J A , Doyle S L , Murphy C F et al. Sarcopenia: prevalence, and impact on operative and oncologic outcomes in the multimodal management of locally advanced esophageal cancer . Ann Surg 2017 ; 266 : 822 – 30 . Google Scholar CrossRef Search ADS PubMed 21 Gannon J A , Guinan E M , Doyle S L , Beddy P , Reynolds J V , Hussey J . Reduced fitness and physical functioning are long-term sequelae after curative treatment for esophageal cancer: a matched control study . Dis Esophagus 2017 ; 30 : 1 – 7 . Google Scholar CrossRef Search ADS PubMed 22 Grotenhuis B A , Shapiro J , van Adrichem S et al. Sarcopenia/muscle mass is not a prognostic factor for short- and long-term outcome after esophagectomy for cancer . World J Surg 2016 ; 40 : 2698 – 704 . Google Scholar CrossRef Search ADS PubMed 23 Reisinger K W , Bosmans J W , Uittenbogaart M et al. Loss of skeletal muscle mass during neoadjuvant chemoradiotherapy predicts postoperative mortality in esophageal cancer surgery . Ann Surg Oncol 2015 ; 22 : 4445 – 52 . Google Scholar CrossRef Search ADS PubMed 24 Tan B H , Brammer K , Randhawa N et al. Sarcopenia is associated with toxicity in patients undergoing neo-adjuvant chemotherapy for oesophago-gastric cancer . Eur J Surg Oncol 2015 ; 41 : 333 – 8 . Google Scholar CrossRef Search ADS PubMed 25 Yip C , Goh V , Davies A et al. Assessment of sarcopenia and changes in body composition after neoadjuvant chemotherapy and associations with clinical outcomes in oesophageal cancer . Eur Radiol 2014 ; 24 : 998 – 1005 . Google Scholar CrossRef Search ADS PubMed 26 Paireder M , Asari R , Kristo I et al. Impact of sarcopenia on outcome in patients with esophageal resection following neoadjuvant chemotherapy for esophageal cancer . Eur J Surg Oncol 2017 ; 43 : 478 – 84 . Google Scholar CrossRef Search ADS PubMed 27 Tamandl D , Paireder M , Asari R , Baltzer P A , Schoppmann S F , Ba-Ssalamah A . Markers of sarcopenia quantified by computed tomography predict adverse long-term outcome in patients with resected oesophageal or gastro-oesophageal junction cancer . Eur Radiol 2016 ; 26 : 1359 – 67 . Google Scholar CrossRef Search ADS PubMed 28 Beddy P , Howard J , McMahon C et al. Association of visceral adiposity with oesophageal and junctional adenocarcinomas . Br J Surg 2010 ; 97 : 1028 – 34 . Google Scholar CrossRef Search ADS PubMed 29 Donohoe C L , Doyle S L , McGarrigle S et al. Role of the insulin-like growth factor 1 axis and visceral adiposity in oesophageal adenocarcinoma . Br J Surg 2012 ; 99 : 387 – 96 . Google Scholar CrossRef Search ADS PubMed 30 Ida S , Watanabe M , Karashima R et al. Changes in body composition secondary to neoadjuvant chemotherapy for advanced esophageal cancer are related to the occurrence of postoperative complications after esophagectomy . Ann Surg Oncol 2014 ; 21 : 3675 – 9 . Google Scholar CrossRef Search ADS PubMed 31 Ida S , Watanabe M , Yoshida N et al. Sarcopenia is a predictor of postoperative respiratory complications in patients with esophageal cancer . Ann Surg Oncol 2015 ; 22 : 4432 – 7 . Google Scholar CrossRef Search ADS PubMed 32 Miyata H , Sugimura K , Motoori M et al. Clinical assessment of sarcopenia and changes in body composition during neoadjuvant chemotherapy for esophageal cancer . Anticancer Res 2017 ; 37 : 3053 – 9 . Google Scholar PubMed 33 Makiura D , Ono R , Inoue J et al. Preoperative sarcopenia is a predictor of postoperative pulmonary complications in esophageal cancer following esophagectomy: a retrospective cohort study . J Geriatr Oncol 2016 ; 7 : 430 – 6 . Google Scholar CrossRef Search ADS PubMed 34 Ishikawa T , Yasuda T , Doi T et al. The amino acid-rich elemental diet Elental® preserves lean body mass during chemo- or chemoradiotherapy for esophageal cancer . Oncol Rep 2016 ; 36 : 1093 – 100 . Google Scholar CrossRef Search ADS PubMed 35 Wu J , Huang C , Xiao H , Tang Q , Cai W . Weight loss and resting energy expenditure in male patients with newly diagnosed esophageal cancer . Nutrition 2013 ; 29 : 1310 – 4 . Google Scholar CrossRef Search ADS PubMed 36 Wu W , Zhong M , Zhu D M et al. Effect of early full-calorie nutrition support following esophagectomy: a randomized controlled trial . JPEN J Parenter Enteral Nutr 2017; 41: 1146–54 . 37 Guinan E M , Doyle S L , O’Neill L et al. Effects of a multimodal rehabilitation programme on inflammation and oxidative stress in oesophageal cancer survivors: the ReStOre feasibility study . Support Care Cancer 2017 ; 25 : 749 – 56 . Google Scholar CrossRef Search ADS PubMed 38 Ryan A M , Reynolds J V , Healy L et al. Enteral nutrition enriched with eicosapentaenoic acid (EPA) preserves lean body mass following esophageal cancer surgery: results of a double-blinded randomized controlled trial . Ann Surg 2009 ; 249 : 355 – 63 . Google Scholar CrossRef Search ADS PubMed 39 Becker Veronese C B , Guerra L T , Souza Grigolleti S , et al . Basal energy expenditure measured by indirect calorimetry in patients with squamous cell carcinoma of the esophagus . Nutr Hosp 2013 ; 28 : 142 – 7 . Google Scholar PubMed 40 Yamamoto K , Takiguchi S , Miyata H et al. Randomized phase II study of clinical effects of ghrelin after esophagectomy with gastric tube reconstruction . Surgery 2010 ; 148 : 31 – 38 . Google Scholar CrossRef Search ADS PubMed 41 Levolger S , van Vugt J L , de Bruin R W , IJzermans J N . Systematic review of sarcopenia in patients operated on for gastrointestinal and hepatopancreatobiliary malignancies . Br J Surg 2015 ; 102 : 1448 – 58 . Google Scholar CrossRef Search ADS PubMed 42 Shachar S S , Williams G R , Muss H B , Nishijima T F . Prognostic value of sarcopenia in adults with solid tumours: a meta-analysis and systematic review . Eur J Cancer 2016 ; 57 : 58 – 67 . Google Scholar CrossRef Search ADS PubMed 43 Daly J M , Fry W A , Little A G et al. Esophageal cancer: results of an American College of Surgeons patient care evaluation study . J Am Coll Surg 2000 ; 190 : 562 – 72 ; discussion 72–3 . Google Scholar CrossRef Search ADS PubMed 44 Correia M I , Waitzberg D L . The impact of malnutrition on morbidity, mortality, length of hospital stay and costs evaluated through a multivariate model analysis . Clin Nutr 2003 ; 22 : 235 – 9 . Google Scholar CrossRef Search ADS PubMed 45 Hynes O , Anandavadivelan P , Gossage J , Johar A M , Lagergren J , Lagergren P . The impact of pre- and postoperative weight loss and body mass index on prognosis in patients with oesophageal cancer . Eur J Surg Oncol 2017 ; 43 : 1559 – 65 . Google Scholar CrossRef Search ADS PubMed 46 Popuri K , Cobzas D , Esfandiari N , Baracos V , Jagersand M . Body composition assessment in axial CT images using FEM-based automatic segmentation of skeletal muscle . IEEE Trans Med Imaging 2016 ; 35 : 512 – 20 . Google Scholar CrossRef Search ADS PubMed © The Authors 2018. Published by Oxford University Press on behalf of International Society for Diseases of the Esophagus. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

Journal

Diseases of the EsophagusOxford University Press

Published: Aug 1, 2018

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off