Literature DB >> 30276001

Sarcopenia and Post-Operative Morbidity and Mortality in Patients with Gastric Cancer.

Stephen O'Brien1, Maria Twomey2, Fiachra Moloney2, Richard G Kavanagh2, Brian W Carey2, Derek Power3, Michael M Maher2, Owen J O'Connor2, Criostoir Ó'Súilleabháin1.   

Abstract

PURPOSE: Surgical resection for gastric adenocarcinoma is associated with significant post-operative morbidity and mortality. The aim of this study was to assess the prognostic significance of sarcopenia in patients undergoing resection for gastric adenocarcinoma with respect to post-operative morbidity and survival.
MATERIALS AND METHODS: A retrospective analysis was conducted on a cohort of consecutive patients who underwent surgical resection for gastric adenocarcinoma between 2008 and 2014. Patient demographics, radiological parameters, and pathological data were collected. OsiriX software (Pixmeo) was used to measure skeletal muscle area, which was normalized for height to calculate skeletal muscle index.
RESULTS: A total of 56 patients (41 male, 15 female; mean age, 68.4 ± 11.9 years) met the inclusion criteria. Of these, 36% (20 of 56) of the patients were sarcopenic pre-operatively. Both sarcopenic and non-sarcopenic patient groups were equally matched with the exception of weight and body mass index (P=0.036 and 0.001, respectively). Sarcopenia was associated with a decreased overall survival (log-rank P=0.003) and was an adverse prognostic predictor of overall survival in multivariate analysis (hazard ratio, 10.915; P=0.001). Sarcopenia was a predictor of serious in-hospital complications in multivariate analysis (odds ratio, 3.508; P=0.042).
CONCLUSIONS: In patients undergoing curative resection for gastric cancer, there was a statistically significant association between sarcopenia and both decreased overall survival and serious post-operative complications. The measurement and reporting of skeletal muscle index on pre-operative computed tomography should be considered.

Entities:  

Keywords:  Morbidity; Prognosis; Sarcopenia; Stomach neoplasms; Tomography, X-ray computed

Year:  2018        PMID: 30276001      PMCID: PMC6160525          DOI: 10.5230/jgc.2018.18.e25

Source DB:  PubMed          Journal:  J Gastric Cancer        ISSN: 1598-1320            Impact factor:   3.720


INTRODUCTION

Gastric cancer is the fifth most common malignancy worldwide and comprises 6.8% of all cancers diagnosed. It is the third leading cause of cancer-related deaths worldwide [1]. There is a wide geographical variation in the incidence of cases, with countries in Eastern Asia, such as South Korea and Japan, having age-standardized incidence rates of 41.8 and 29.9 per 100,000, respectively [1], while in the United States, an approximate incidence of 7.3 per 100,000 is observed [2]. Gastric cancer has a poor 5-year overall survival (OS) rate of 30.6% [2], with surgical resection being the only curative intervention [3]. Post-operative complications have been reported to be as high as 39% in patients undergoing surgery with curative intent [4]. A recent study on patients undergoing potentially curative total gastrectomy for gastric adenocarcinoma indicated that 28% of patients required invasive post-operative intervention, based on the grading of the interventions performed (Clavien-Dindo classification) [5]. A number of recent studies have demonstrated an adverse association between sarcopenia and immediate and long-term patient outcomes following surgery, including post-operative complications, length of hospital stay, recurrence-free survival (RFS), and OS [678]. Sarcopenia is defined by the European Working Group on Sarcopenia in Older People as a low muscle mass and either decreased muscle strength or low physical performance [9]. The deleterious effect of sarcopenia on patient outcomes has been shown to be significant in a number of different cancers such as colorectal and liver cancers. The skeletal muscle index is used to diagnose sarcopenia and this index may be calculated using computed tomography (CT). CT constitutes an important aspect of patient assessment prior to surgical triage and all such patients will undergo pre-operative staging CT. The calculation of skeletal muscle index on CT prior to surgery may provide addition useful information pertaining to the patient's condition and could help guide patient preparation and counselling. The aim of this study was to investigate the association between sarcopenia in patients undergoing surgery for gastric cancer and their post-operative outcomes in terms of morbidity, RFS, and OS.

MATERIALS AND METHODS

The local Institutional Review Board granted ethical approval (approval number ECM 4 (cc) 04/04/16). All consecutive patients who underwent surgery with curative intent for gastric adenocarcinoma between January 1, 2008 and December 31, 2014 in a single tertiary referral center by one surgeon were included in this study. Patients were identified through surgical logbooks and cross-verified using the histopathology database confirming the diagnosis of gastric adenocarcinoma according to the American Joint Committee on Cancer (AJCC) staging system [10]. Pathological data including tumor location and stage were collected from this database. Patient medical records were analyzed to obtain pre-operative clinical demographics, including age, sex, date of surgery, use of neoadjuvant therapy, and the identification of patients' comorbidities. The Charlson comorbidity index (CCI) was calculated from patient pre-operative information [11]. Peri-operative reports were used to obtain patients' height, weight, and the American Society of Anesthesiologists physical status (ASA-PS) [12]. Post-operative information was obtained from patient medical records to include the occurrence of complications, which were graded according to the Clavien-Dindo classification system [13]. The total number of intensive care unit (ICU) and hospital bed days were obtained from the hospital inpatient medical system. Follow-up information regarding tumor recurrence and mortality were obtained from medical and radiological records. OS was defined as the length of time from the date of first therapy to the date of death or loss to follow-up. RFS was defined as the length of time from the date of first therapy to the date of detection of tumor recurrence, death, or loss to follow-up.

Diagnostic work-up and imaging

All patients were discussed at a multi-disciplinary team meeting. As part of the routine pre-operative diagnostic procedure, all patients underwent an esophagogastroduodenoscopy and a staging CT scan of the thorax, abdomen, and pelvis [14]. In all, 80.4% (45 of 56) of the patients had an endoscopic ultrasound for loco-regional staging and 73.2% (41 of 56) of the patients had a staging laparoscopy with peritoneal washings. Survival analysis was performed on data from the pre-operative CT or from before commencement of chemotherapy where applicable. Morbidity analysis was performed on data from the staging CT performed before surgery irrespective of whether chemotherapy was administered as this reflected the patient's skeletal muscle index entering surgery, which could be affected by the administration of chemotherapy. CT scans were electronically stored on the hospital imaging system. Pre-operative CT scans for the identified study patients were anonymized by a third-party imaging technician.

Image analysis

CT scans were analyzed using the OsiriX version 5.6.1 open source software (32-bit, Pixmeo, Geneva, Switzerland; http://www.osirix-viewer.com). The cross-sectional skeletal muscle area (cm2) was measured using a standardized approach [815]. Two sequential scans at the level of the third lumbar vertebra, in which both transverse processes were visible, were used. The grow/regrow tool was used to measure the skeletal muscle area on these axial slices by a reviewer blinded to the patients' demographics. The threshold range for skeletal muscle was −30 to +150 Hounsfield units [1617]. The skeletal muscles included were the psoas, paraspinal, and abdominal wall muscles. The average muscle area of these 2 slices was used. The skeletal muscle area was normalized for height to calculate the skeletal muscle index [18]. The specific cut-off values used for sarcopenia were 52.4 cm2/m2 for men and 38.5 cm2/m2 for women, as published by Prado et al. [17]. An example of an analyzed CT scan is shown in Fig. 1.
Fig. 1

Axial CT scan of a 77-year-old sarcopenic male with a skeletal muscle index of 41.58 cm2/m2. The total skeletal muscle area (indicated in purple) was measured on a CT slice at the level of L3.

CT = computed tomography.

Axial CT scan of a 77-year-old sarcopenic male with a skeletal muscle index of 41.58 cm2/m2. The total skeletal muscle area (indicated in purple) was measured on a CT slice at the level of L3.

CT = computed tomography.

Statistical analysis

Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) v20.0 software (SPSS Inc., Chicago, IL, USA). The independent t-test and Mann-Whitney U test were used to compare continuous variables including age, number of positive lymph nodes (LNs), number of LNs resected, patient height, weight, and body mass index (BMI). The χ2 test and Fisher's exact test were used to compare categorical variables such as sex, tumor site, TNM stage, use of neoadjuvant therapy, ASA-PS grade, and CCI score. The impact of sarcopenia on morbidity was analyzed by univariate and multivariate regression analyses. Morbidity was assessed according to serious in-hospital complications (Clavien-Dindo ≥3a), the number of ICU bed days, and the total length of hospital stay. OS and RFS were evaluated by Kaplan-Meier survival analysis and the log-rank test. The association of sarcopenia with OS was analyzed using univariate and multivariate Cox regression analyses. Graphs were constructed on GraphPad Prism v6.07 (GraphPad Software Inc., La Jolla, CA, USA). A P-value of <0.05 was used as the level of significance for the study.

RESULTS

A total of 56 patients (41 male, 15 female; mean age, 68.4 ± 11.9 years) were included in the study. Follow-up was completed for all included patients. There was a mean of 28 days (range, 0–74 days) from the date of CT scan to the date of surgery. The majority of the patients (87.5%, 49 of 56) had the CT scan within 6 weeks of the surgery. In all, 20 patients (35.7%) were sarcopenic pre-operatively, which included three of 29 patients who received neoadjuvant chemotherapy and subsequently became sarcopenic. Patient demographics, clinical indices, and pathological data are summarized in Table 1.
Table 1

Clinical indices and pathological data of patients stratified by the presence of pre-operative sarcopenia

CharacteristicsAll Patients (n=56)Sarcopenic (n=20)Non-sarcopenic (n=36)P-value
Age (yr)68.4±11.967.4±12.770.3±10.20.385*
Sex0.393
Male411625
Female15411
Height (cm)168.4±8.8169±7.5167±9.50.356*
Weight (kg)73.8±14.868.3±11.676.9±15.70.036*
BMI (kg/m2)25.9±4.323±2.927.2±4.40.001*
ASA-PS0.803
Grade 1523
Grade 221813
Grade 3291019
Grade 4101
CCI0.144
0505
1211
217710
31174
41129
5624
6312
7101
Neoadjuvant therapy0.610
Yes281018
No281018
Type of surgery0.087
Total gastrectomy341618
Distal gastrectomy12210
Proximal gastrectomy1028
Tumor site0.416
Cardia16511
Fundus422
Body1587
Antrum14311
Pylorus725
Stage0.282
0734
1A1138
1B725
2A615
2B725
3A303
3B963
3C633
Number of LNs resected (range)28.7 (4–75)28.3 (13–79)29 (4–58)0.308
Number of positive LNs (range)2.2 (0–23)2.05 (0–10)2.33 (0–23)0.827

Continuous data presented as mean±1 standard deviation unless otherwise stated. Statistically significant values in bold.

BMI = body mass index; ASA-PS = American Society of Anesthesiologists physical status; CCI = Charlson comorbidity index; Stage = overall TNM staging as per American Joint Committee on Cancer 7th edition; LN = lymph node.

*Independent t-test, †χ2 test ‡Mann-Whitney U test.

Continuous data presented as mean±1 standard deviation unless otherwise stated. Statistically significant values in bold. BMI = body mass index; ASA-PS = American Society of Anesthesiologists physical status; CCI = Charlson comorbidity index; Stage = overall TNM staging as per American Joint Committee on Cancer 7th edition; LN = lymph node. *Independent t-test, †χ2 test ‡Mann-Whitney U test. Stratification of patients based on the presence or absence of sarcopenia demonstrated that only patient weight and BMI were statistically different between the groups (P=0.036 and 0.001, respectively). There was no statistical difference in the patients' comorbidities, assessed by the ASA-PS and CCI scores (P=0.803 and 0.144, respectively). No statistically significant difference was observed in the tumor profile between the patient groups. This was assessed by tumor site, stage, and the number of LNs resected. In all, 50% (28 of 56) of patients received neoadjuvant chemotherapy and 64.3% (18 of 28) of these patients went on to have adjuvant chemotherapy. The seven patients with stage 0 gastric cancer were treated surgically and did not receive neoadjuvant chemotherapy. A mean of 28.7 LNs were resected in the whole patient cohort. In total, 52 patients (92.9%) of the whole patient cohort had a resection of ≥15 LNs. Of the remainder, three patients had stage 1A disease. The median follow-up time for the whole patient cohort was 39.88 months (interquartile range, 17.43–61.2 months). RFS and OS curves for patients with and without sarcopenia are shown in Figs. 2 and 3, respectively. No statistically significant difference was observed in RFS between patient groups (P=0.084, log-rank test). However, there was a statistically significant difference in OS between the 2 groups (P=0.003, log-rank test), with sarcopenic patients having reduced survival.
Fig. 2

Kaplan-Meier analysis for RFS indicated that there was no statistically significant difference in RFS between sarcopenic and non-sarcopenic patients (P=0.084, log-rank test).

RFS = recurrence-free survival.

Fig. 3

Kaplan-Meier analysis for OS indicated a statistically significant difference in OS between non-sarcopenic and sarcopenic patients (P=0.003, log-rank test).

OS = overall survival.

Kaplan-Meier analysis for RFS indicated that there was no statistically significant difference in RFS between sarcopenic and non-sarcopenic patients (P=0.084, log-rank test).

RFS = recurrence-free survival.

Kaplan-Meier analysis for OS indicated a statistically significant difference in OS between non-sarcopenic and sarcopenic patients (P=0.003, log-rank test).

OS = overall survival. Overall, 20 patients experienced severe post-operative complications (Clavien-Dindo >3A). The sarcopenic group had a higher rate of severe complications than the non-sarcopenic group (11 patients vs. 9 patients, respectively). Radiologically guided pleural drainage or chest tube insertion was required by 8 patients: 3 from the sarcopenic group and 5 from the non-sarcopenic group. Surgical intervention under general anesthetic was required by 5 patients for wound debridement (n=1), perforation (n=1), tracheostomy insertion (n=1), and small bowel obstruction (n=2): 3 from the sarcopenic group and 2 from the non-sarcopenic group. ICU admission was required by 7 patients: 5 from the sarcopenic group and 2 from the non-sarcopenic group. A summary of univariate and multivariate cox regression analyses for OS is presented in Table 2. In the univariate regression analysis, sarcopenia, BMI, and AJCC tumor stages 2A–2B and 3A–3C were statistically significant prognosticators of OS. Due to the small study group, only the variables that were statistically significant in the univariate analysis were included in the multivariate regression analysis. Only sarcopenia and AJCC tumor stages 2A–2B and 3A–3C were statistically significant predictors of poor OS in the multivariate analysis (hazard ratio [HR], 10.915; P=0.001; HR, 50.177, P≤0.001; and HR, 56.377; P≤0.001, respectively).
Table 2

Univariate and multivariate Cox regression analysis of clinicopathological factors and OS

CharacteristicsUnivariate analysisMultivariate analysis
HR95% CIP-valueHR95% CIP-value
Age1.0300.991–1.0700.135
Sex0.6050.227–1.6130.315
Height1.0130.972–1.0560.542
Weight0.9810.955–1.0070.144
BMI0.8960.809–0.9930.0370.8940.791–1.0110.074
Sarcopenia3.8851.754–8.6070.00110.9153.195–37.2880.001
ASA-PS group ≥20.6800.310–1.4940.337
CCI ≥31.4160.625–3.2090.404
Neoadjuvant therapy1.2550.569–2.7680.573
Type of surgery
Total gastrectomy1
Distal gastrectomy1.3300.467–3.7910.594
Proximal gastrectomy1.5960.609–4.1820.341
Tumor site
Cardia1
Fundus1.2250.259–5.7860.798
Body1.3700.514–3.6870.525
Antrum0.6830.223–2.0930.505
Pylorus0.7370.156–3.4810.700
Stage
0–1B11
2A–2B10.7492.320–49.8040.00250.1777.682–327.752<0.001
3A–3C19.6104.366–88.079<0.00156.3779.175–346.407<0.001
Number of LNs resected1.0120.979–1.0470.485

Statistically significant values in bold.

OS = overall survival; HR = hazard ratio; CI = confidence interval; BMI = body mass index; ASA-PS = American Society of Anesthesiologists physical status; CCI = Charlson comorbidity index; Stage = overall TNM staging as per American Joint Committee on Cancer 7th edition.

Statistically significant values in bold. OS = overall survival; HR = hazard ratio; CI = confidence interval; BMI = body mass index; ASA-PS = American Society of Anesthesiologists physical status; CCI = Charlson comorbidity index; Stage = overall TNM staging as per American Joint Committee on Cancer 7th edition. The association between sarcopenia and post-operative morbidity is shown in Table 3. There was a statistically significant difference between the 2 groups with respect to serious post-operative complications (Clavien-Dindo ≥3a) (P=0.025), in-hospital mortality (P=0.041), and number of ICU bed days (P=0.007). There was no statistically significant difference in the total length of hospital stay between the 2 groups (P=0.373). Univariate and multivariate regression analyses were used to identify factors associated with hospital complications (Table 4). In the univariate analysis, being male and having sarcopenia were found to be statistically significant factors associated with in-hospital complications (odds ratio [OR], 5.087; P=0.048 and OR, 3.667; P=0.028). However, in the multivariate analysis, only sarcopenia was found to be a significant prognosticator of serious in-hospital complications (OR, 3.508; P=0.042).
Table 3

Analysis of hospital outcomes by pre-operative sarcopenia

OutcomesAll patients (n=56)Sarcopenic (n=20)Non-sarcopenic (n=36)P-value
Serious complications (%)20 (35.7)11 (55.0)9 (25.0)0.025*
Length of hospital stay21.46 (7–71)25.1 (7–57)19.44 (8–71)0.373
Total number of ICU/HDU bed days6.68 (0–62)9.45 (0–43)5.08 (0–62)0.007
In-hospital mortality (%)3 (5.4)3 (15.0)0 (0)0.041

Results of length of hospital stay and number of ICU bed days are presented as mean number of days (range). Serious complications (Clavien-Dindo ≥3a) and in-hospital mortality are recorded as number (%).

ICU = intensive care unit; HDU = high-dependency unit.

*χ2 test, †Mann-Whitney U test, ‡Fisher's exact test.

Table 4

Univariate and multivariate regression analyses for risk factors of serious complications (Clavien-Dindo ≥3A)

CharacteristicsUnivariate analysisMultivariate analysis
OR95% CIP-valueOR95% CIP-value
Age1.0080.962–1.0570.743
Sex (male)5.0871.015–25.4850.0484.8360.922–25.3610.062
Height1.0530.985–1.1250.129
Weight1.0100.973–1.0480.591
BMI0.9790.859–1.1160.752
Sarcopenic3.6671.150–11.6940.0283.5081.048–11.7390.042
ASA-PS ≥30.5840.194–1.7600.340
CCI ≥30.6360.211–1.9180.422
Neoadjuvant therapy0.4310.139–1.3330.144
Type of surgery
Total gastrectomy1
Distal gastrectomy0.0000.00–Infinity0.999
Proximal gastrectomy2.1430.509–9.0240.299
Location of tumor
Cardia1
Fundus3.8570.326–45.5700.284
Body1.1250.273–4.6350.870
Antrum0.2140.036–1.2880.092
Pylorus0.2140.021–2.2160.196
Stage
0–1B1
2A–2B2.2040.545–8.9100.267
3A–3C1.6360.451–5.9360.454
Number of LNs resected0.9670.918–1.0190.211

Statistically significant values in bold.

OR = odds ratio; CI = confidence interval; BMI = body mass index; ASA-PS = American Society of Anesthesiologists physical status; CCI = Charlson comorbidity index; Stage = overall TNM staging as per American Joint Committee on Cancer 7th edition; LN = lymph node.

Results of length of hospital stay and number of ICU bed days are presented as mean number of days (range). Serious complications (Clavien-Dindo ≥3a) and in-hospital mortality are recorded as number (%). ICU = intensive care unit; HDU = high-dependency unit. *χ2 test, †Mann-Whitney U test, ‡Fisher's exact test. Statistically significant values in bold. OR = odds ratio; CI = confidence interval; BMI = body mass index; ASA-PS = American Society of Anesthesiologists physical status; CCI = Charlson comorbidity index; Stage = overall TNM staging as per American Joint Committee on Cancer 7th edition; LN = lymph node.

DISCUSSION

The role of sarcopenia in the management of patients with cancer is an evolving area of research. Numerous studies encompassing different tumor biologies have demonstrated that a low skeletal muscle index has an adverse effect on the outcomes of oncology patients. Sarcopenia has been associated with increased length of hospital stay, serious in-hospital complications, increased inpatient mortality, and lower disease-free survival and OS [681920]. The present study investigated the effect of sarcopenia on patients undergoing potentially curative surgery for gastric adenocarcinoma with respect to post-operative morbidity, RFS, and OS. The study groups were very well-matched and the surgical approach was standardized, given that only 1 surgeon was involved. Sarcopenia was adversely associated with serious post-operative hospital complications (Clavien-Dindo ≥3a) and decreased OS. Interestingly, there was no statistically significant difference observed in the length of hospital stay between the patient groups, which was expected due to the association of sarcopenia with major in-hospital complications and increased length of stay in the ICU. This may be due in part to the small study group. However, the differences observed in the incidence of major complications and the number of ICU bed days indicate that sarcopenic patients are more resource intensive than non-sarcopenic patients. Sarcopenic thresholds reported by Prado et al. [17] are frequently referenced and used for patient stratification; these are derived from an obese cohort of cancer patients with a number of different tumor etiologies. Despite the potential for bias in these cut-off values, significant associations with many disease outcomes have been found. This may be due to the general population becoming increasingly obese and the study's restriction to obese patients may, in fact, be representative of modern society [21]. Hence, it was deemed appropriate to use these threshold values for the purposes of the present study. Almost 59% (33 of 56) of patients in the present study were overweight or obese and although there was a statistical difference in BMI between the 2 patient groups, BMI was not associated with a worse outcome in terms of morbidity or survival in the multivariate analysis. A similar finding was reported in a study of patients with hepatocellular carcinoma [19]. Cachexia associated with cancer is characterized by loss of a muscle mass, which may not be accompanied by a loss of fat mass and may be poorly reflected by changes in BMI [22]. With the rising prevalence of obesity in the community, sarcopenia may be a more suitable prognostic factor than BMI. The use of CT to identify patients who have sarcopenia despite having a normal BMI has not been widely exploited. The reporting of skeletal muscle index represents a potential added value that radiologists could provide to guide referring physicians. Some studies have failed to demonstrate these relationships; a recent study that investigated the effect of sarcopenia on patients with gastric cancer undergoing surgery did not show an association between sarcopenia and short-term post-operative morbidity and mortality [23]. There are fundamental differences in the profile of patients' in that study: 57.7% of patients in that study were sarcopenic compared with only 35.7% in the present study, and 30.6% of patients in that study underwent palliative surgery, with 37.1% having stage 4 disease, whereas the present study group was restricted to those undergoing curative surgery. These differences may explain the different study results. Another recent paper reported that sarcopenia is associated with decreased OS in esophago-gastric cancer patients [24]. The incidence of sarcopenia in that study was 49.4% and a larger variety of cancers were studied (esophageal, esophago-gastric junction, and gastric cancers) in comparison to the present, more focused study. The incorporation of skeletal muscle index calculation into pre-operative risk stratification and prognostic models may require tumor-specific cut-off values for a low skeletal muscle index. Tumor pathophysiology and prognosis can vary widely, as can the physiologic challenge of surgery. The concept of tumor-specific values has been investigated in several studies. An adverse association has been demonstrated between sarcopenia and RFS and OS in patients with colorectal cancer [25]. Similarly, an association between sarcopenia and OS in patients with pancreatic cancer has also been shown [26]. Both of these studies used the lowest sex-specific quartile to define a low skeletal muscle index. The identification of patients who are sarcopenic at the time of diagnosis may aid the selection of patients for early nutritional and physical intervention. This might be particularly suitable for patients with gastric cancer who require neoadjuvant chemotherapy. In a study which analyzed the change in body composition in patients after neoadjuvant chemotherapy for esophago-gastric cancer, there was a statistically significant increase in the number of patients with sarcopenia post-chemotherapy [27]. This was reflected in the present study with previously non-sarcopenic patients becoming sarcopenic post-chemotherapy. The present study included consecutive patients who underwent curative surgery for gastric cancer at a single tertiary referral center. The study was retrospective and although comparable with similar papers studying other cancers, the patient group was relatively small. A multicenter prospective study with a larger patient population may be necessary to better elucidate the association between sarcopenia and post-operative outcomes in specific subgroups of patients undergoing curative resection for gastric cancer. The relationship between the systemic inflammatory response and sarcopenia and its influence on this study's findings were not included due to lack of relevant data (C-reactive protein, etc.). Results from the recent C-SCANS study indicated that pre-diagnosis systemic inflammation and at-diagnosis sarcopenia were associated with an increased mortality risk in patients with non-metastatic colorectal cancer [28]. Further study of the influence of the systemic inflammatory response on skeletal muscle in gastric cancer may help guide interventions to prevent sarcopenia and potentially improve survival outcomes. In conclusion, the present study demonstrated that, in patients undergoing curative resection for gastric cancer, there was a statistically significant association between sarcopenia and both decreased OS and serious post-operative complications. The measurement and reporting of skeletal muscle index from pre-operative CT should be considered for patient preparation purposes.
  26 in total

1.  7th edition of the AJCC cancer staging manual: stomach.

Authors:  Kay Washington
Journal:  Ann Surg Oncol       Date:  2010-12       Impact factor: 5.344

2.  Sarcopenia Impacts on Short- and Long-term Results of Hepatectomy for Hepatocellular Carcinoma.

Authors:  Thibault Voron; Lambros Tselikas; Daniel Pietrasz; Frederic Pigneur; Alexis Laurent; Philippe Compagnon; Chady Salloum; Alain Luciani; Daniel Azoulay
Journal:  Ann Surg       Date:  2015-06       Impact factor: 12.969

3.  Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography.

Authors:  N Mitsiopoulos; R N Baumgartner; S B Heymsfield; W Lyons; D Gallagher; R Ross
Journal:  J Appl Physiol (1985)       Date:  1998-07

4.  ASA classification and perioperative variables as predictors of postoperative outcome.

Authors:  U Wolters; T Wolf; H Stützer; T Schröder
Journal:  Br J Anaesth       Date:  1996-08       Impact factor: 9.166

5.  Validation of the Consensus-Definition for Cancer Cachexia and evaluation of a classification model--a study based on data from an international multicentre project (EPCRC-CSA).

Authors:  D Blum; G B Stene; T S Solheim; P Fayers; M J Hjermstad; V E Baracos; K Fearon; F Strasser; S Kaasa
Journal:  Ann Oncol       Date:  2014-02-20       Impact factor: 32.976

6.  Sarcopenia is a Negative Prognostic Factor After Curative Resection of Colorectal Cancer.

Authors:  Yuji Miyamoto; Yoshifumi Baba; Yasuo Sakamoto; Mayuko Ohuchi; Ryuma Tokunaga; Junji Kurashige; Yukiharu Hiyoshi; Shiro Iwagami; Naoya Yoshida; Megumi Yoshida; Masayuki Watanabe; Hideo Baba
Journal:  Ann Surg Oncol       Date:  2015-01-07       Impact factor: 5.344

7.  A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.

Authors:  M E Charlson; P Pompei; K L Ales; C R MacKenzie
Journal:  J Chronic Dis       Date:  1987

8.  Association of Systemic Inflammation and Sarcopenia With Survival in Nonmetastatic Colorectal Cancer: Results From the C SCANS Study.

Authors:  Elizabeth M Cespedes Feliciano; Candyce H Kroenke; Jeffrey A Meyerhardt; Carla M Prado; Patrick T Bradshaw; Marilyn L Kwan; Jingjie Xiao; Stacey Alexeeff; Douglas Corley; Erin Weltzien; Adrienne L Castillo; Bette J Caan
Journal:  JAMA Oncol       Date:  2017-12-01       Impact factor: 31.777

9.  Gastric cancer: which patients benefit from systematic lymphadenectomy?

Authors:  N M Bösing; P E Goretzki; H D Röher
Journal:  Eur J Surg Oncol       Date:  2000-08       Impact factor: 4.424

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

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

View more
  9 in total

1.  Prevalence and associated factors of sarcopenia among patients underwent abdominal CT scan in Tertiary Care Hospital of South India.

Authors:  Pankajakshan Rema Sreepriya; Shikha Sivasankara Pillai; Anjana Nalina Kumari Kesavan Nair; Arya Rahul; Sandeep Pillai; Anish Thekkumkara Surendran Nair
Journal:  J Frailty Sarcopenia Falls       Date:  2020-09-01

2.  Strong impact of sarcopenia as a risk factor of survival in resected gastric cancer patients: first Italian report of a Bicentric study.

Authors:  A A Ricciardolo; N De Ruvo; F Serra; F Prampolini; L Solaini; S Battisti; G Missori; S Fenocchi; E G Rossi; L Sorrentino; M Salati; A Spallanzani; N Cautero; A Pecchi; G Ercolani; R Gelmini
Journal:  Updates Surg       Date:  2021-10-26

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

Authors:  Christina A Fleming; Emer P O'Connell; Richard G Kavanagh; Donal P O'Leary; Maria Twomey; Mark A Corrigan; Jiang H Wang; Michael M Maher; Owen J O'Connor; Henry P Redmond
Journal:  JAMA Netw Open       Date:  2021-08-02

4.  Body Composition Is a Predictor for Postoperative Complications After Gastrectomy for Gastric Cancer: a Prospective Side Study of the LOGICA Trial.

Authors:  Thaís T T Tweed; Arjen van der Veen; Stan Tummers; David P J van Dijk; Misha D P Luyer; Jelle P Ruurda; Richard van Hillegersberg; Jan H M B Stoot; Juul J W Tegels; Karel W E Hulsewe; Hylke J F Brenkman; Maarten F J Seesing; Grard A P Nieuwenhuijzen; Jeroen E H Ponten; Bas P L Wijnhoven; Sjoerd M Lagarde; Wobbe O de Steur; Henk H Hartgrink; Ewout A Kouwenhoven; Marc J van Det; Eelco B Wassenaar; Edwin S van der Zaag; Werner A Draaisma; Ivo A M J Broeders; Suzanne S Gisbertz; Mark I van Berge Henegouwen; Hanneke W M van Laarhoven
Journal:  J Gastrointest Surg       Date:  2022-04-29       Impact factor: 3.267

5.  AWGS2019 vs EWGSOP2 for diagnosing sarcopenia to predict long-term prognosis in Chinese patients with gastric cancer after radical gastrectomy.

Authors:  Wen-Yi Wu; Jiao-Jiao Dong; Xin-Ce Huang; Zhe-Jing Chen; Xiao-Lei Chen; Qian-Tong Dong; Yong-Yu Bai
Journal:  World J Clin Cases       Date:  2021-06-26       Impact factor: 1.337

6.  CT-assessed sarcopenia is a predictive factor for both long-term and short-term outcomes in gastrointestinal oncology patients: a systematic review and meta-analysis.

Authors:  Huaiying Su; Junxian Ruan; Tianfeng Chen; Enyi Lin; Lijing Shi
Journal:  Cancer Imaging       Date:  2019-12-03       Impact factor: 3.909

Review 7.  The Predictive Value of Low Muscle Mass as Measured on CT Scans for Postoperative Complications and Mortality in Gastric Cancer Patients: A Systematic Review and Meta-Analysis.

Authors:  Alicia S Borggreve; Robin B den Boer; Gijs I van Boxel; Pim A de Jong; Wouter B Veldhuis; Elles Steenhagen; Richard van Hillegersberg; Jelle P Ruurda
Journal:  J Clin Med       Date:  2020-01-11       Impact factor: 4.241

8.  Body Composition Changes in Gastric Cancer Patients during Preoperative FLOT Therapy: Preliminary Results of an Italian Cohort Study.

Authors:  Emanuele Rinninella; Antonia Strippoli; Marco Cintoni; Pauline Raoul; Raffaella Vivolo; Mariantonietta Di Salvatore; Enza Genco; Riccardo Manfredi; Emilio Bria; Giampaolo Tortora; Antonio Gasbarrini; Carmelo Pozzo; Maria Cristina Mele
Journal:  Nutrients       Date:  2021-03-16       Impact factor: 5.717

9.  Prognostic Impact of Sarcopenia and Radiotherapy in Patients With Advanced Gastric Cancer Treated With Anti-PD-1 Antibody.

Authors:  Nalee Kim; Jeong Il Yu; Do Hoon Lim; Jeeyun Lee; Seung Tae Kim; Jung Yong Hong; Won Ki Kang; Woo Kyoung Jeong; Kyoung-Mee Kim
Journal:  Front Immunol       Date:  2021-07-08       Impact factor: 7.561

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.