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Background:
Systematic Review

Pre-Therapeutic Sarcopenia among Cancer Patients: An Up-to-Date Meta-Analysis of Prevalence and Predictive Value during Cancer Treatment

by
Anne-Laure Couderc
1,2,†,‡,
Evelyne Liuu
3,4,†,‡,
Pascaline Boudou-Rouquette
5,6,‡,
Johanne Poisson
7,8,
Maxime Frelaut
9,‡,
Coline Montégut
1,10,‡,
Soraya Mebarki
7,‡,
Romain Geiss
11,‡,
Zoé ap Thomas
12,
Aurélien Noret
7,
Monica Pierro
7,
Capucine Baldini
13,‡,
Elena Paillaud
7,14,‡,§ and
Frédéric Pamoukdjian
15,16,*,‡,§
1
Internal Medicine Geriatrics and Therapeutic Unit, APHM, 13009 Marseille, France
2
CNRS, EFS, ADES, Aix-Marseille University, 13015 Marseille, France
3
Department of Geriatrics, CHU Poitiers, 86000 Poitiers, France
4
CIC1402 INSERM Unit, Poitiers University Hospital, 86000 Poitiers, France
5
Ariane Program, Department of Medical Oncology, Cochin Hospital, Paris Cancer Institute CARPEM, APHP, 75014 Paris, France
6
INSERM U1016-CNRS UMR8104, Cochin Institute, Paris Cancer Institute CARPEM, Paris Cité University, 75015 Paris, France
7
Department of Geriatrics, Georges Pompidou European Hospital, Paris Cancer Institute CARPEM, APHP, 75015 Paris, France
8
Faculty of Health, Paris Cité University, 75006 Paris, France
9
Department of Medical Oncology, Gustave Roussy Institute, 94805 Villejuif, France
10
Coordination Unit for Geriatric Oncology (UCOG), PACA West, 13009 Marseille, France
11
Department of Medical Oncology, Curie Institute, 92210 Saint-Cloud, France
12
Department of Cancer Medicine, Gustave Roussy Institute, 94805 Villejuif, France
13
Drug Development Department, Gustave Roussy Institute, 94805 Villejuif, France
14
INSERM, IMRB, Clinical, Epidemiology and Ageing, Université Paris-Est Creteil, 94010 Creteil, France
15
Department of Geriatrics, Avicenne Hospital, APHP, 93000 Bobigny, France
16
INSERM UMR_S942 Cardiovascular Markers in Stressed Conditions MASCOT, Sorbonne Paris Nord University, 93000 Bobigny, France
 
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*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
‡
Current address: French Society of Geriatric Oncology (SoFOG), F-63122 Ceyrat, France.
§
These authors contributed equally to this work.
Nutrients 2023, 15(5), 1193; https://doi.org/10.3390/nu15051193
Submission received: 3 February 2023 / Revised: 18 February 2023 / Accepted: 21 February 2023 / Published: 27 February 2023
(This article belongs to the Special Issue Dietary Intake and Health Status in Older Adults)
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Abstract

:
This study will address the prevalence of pre-therapeutic sarcopenia (PS) and its clinical impact during cancer treatment among adult cancer patients ≥ 18 years of age. A meta-analysis (MA) with random-effect models was performed via a MEDLINE systematic review, according to the PRISMA statement, focusing on articles published before February 2022 that reported observational studies and clinical trials on the prevalence of PS and the following outcomes: overall survival (OS), progression-free survival (PFS), post-operative complications (POC), toxicities (TOX), and nosocomial infections (NI). A total of 65,936 patients (mean age: 45.7–85 y) with various cancer sites and extensions and various treatment modes were included. Mainly defined by CT scan-based loss of muscle mass only, the pooled prevalence of PS was 38.0%. The pooled relative risks were 1.97, 1.76, 2.70, 1.47, and 1.76 for OS, PFS, POC, TOX, and NI, respectively (moderate-to-high heterogeneity, I2: 58–85%). Consensus-based algorithm definitions of sarcopenia, integrating low muscle mass and low levels of muscular strength and/or physical performance, lowered the prevalence (22%) and heterogeneity (I2 < 50%). They also increased the predictive values with RRs ranging from 2.31 (OS) to 3.52 (POC). PS among cancer patients is prevalent and strongly associated with poor outcomes during cancer treatment, especially when considering a consensus-based algorithm approach.

1. Introduction

Since its first definition, introduced in 1989 as an age-associated loss of muscle mass, the definition of sarcopenia has been gradually refined [1]. In 2010, 2011, and 2014, the European Working Group On Sarcopenia (namely EWGOS 1), the International Working Group on Sarcopenia (IWGS), and the Asian Working Group on Sarcopenia (AWGS 1) agreed to define sarcopenia as a syndrome characterized by an age-related loss of skeletal muscle mass (quantitatively assessed by the skeletal muscle index (SMI) or appendicular skeletal muscle mass (ASM) using CT scan, and bioelectrical impedance analysis (BIA) or dual-energy X-ray absorptiometry (DXA) methods), and by loss of function (loss of muscle strength and/or physical performance) using a screening-based approach targeting gait speed measurement [2,3,4]. In 2019, the AWGS updated the threshold values of the operational criteria (then termed AWGS 2). The EWGOS definition was also updated (EWGOS 2), now defining sarcopenia as a muscle disease characterized by the association of low levels of muscle strength (handgrip strength) and low muscle mass, with low physical performance (typically slow gait speed) becoming an indicator of severity [5,6]. In addition, the condition does not affect solely older adults ≥65 years and it has now been recognized that sarcopenia can begin earlier in life. In particular, sarcopenia is considered as primary or age-related, and as secondary when a specific cause (mainly driven by inflammatory processes) is evidenced (Table A1).
Cancer is frequently considered to be a major cause of secondary sarcopenia. In our previous systematic review including 35 observational studies or clinical trials and 6894 patients with cancer before 2016, sarcopenia concerned 38.6% of patients before cancer treatment [7]. We found that pre-therapeutic sarcopenia (PS) was associated with poor survival rates, post-operative complications and chemotherapy-related toxicities during cancer treatment, but with a strong between-study heterogeneity with respect to cancer site or extension and the definitions of sarcopenia. Since this review, with the arrival of immune-therapies and an update in the consensuses, there has been a considerable increase in the number of additional studies among cancer patients, but no comprehensive analysis has been conducted to date.
We therefore aimed to update our previous systematic review and to decipher heterogeneity in the prevalence of PS and its predictive values for overall survival, progression-free survival, post-operative complications, treatment-related toxicities, disability, and nosocomial infections among cancer patients using a meta-analysis including research published before 2022.

2. Materials and Methods

We followed the recommendations of the preferred reporting items for systematic reviews and meta-analyses (PRISMA) method for reporting this systematic review with meta-analysis [8]. The protocol was registered on 6 February 2023 and is available on the OSF platform: https://doi.org/10.17605/OSF.IO/H7PUZ, accessed on 13 February 2023.

2.1. Information Sources

This meta-analysis was based on a systematic, comprehensive search on MEDLINE via PubMed for articles published in English or French from 31 March 2016 to 31 December 2021. Due to a considerable increase in the number of studies addressing sarcopenia among cancer patients, we chose only to consult the PubMed database. The following research algorithm was used: sarcopenia AND (cancer OR tumors OR malignancies) AND (death OR overall survival OR progression-free survival OR relapse OR chemotherapy OR targeted therapy OR radiotherapy OR hormonal therapy OR surgery OR immunotherapy OR toxicity OR disability OR infection) AND human NOT review NOT letter. All articles retrieved from our previous systematic review were also included [7].

2.2. Search Strategy

For this meta-analysis, the following issues were addressed:
(a)
What is the most commonly encountered definition of PS among patients with cancer?
(b)
What is the pooled prevalence of PS among patients with cancer, and what is the prevalence according to the definition of sarcopenia?
(c)
What are the mean differences in muscle strength (i.e., grip-strength) and physical performance (i.e., gait speed) between sarcopenic and non-sarcopenic groups of patients with cancer?
(d)
What is the predictive value of PS for overall survival (OS) and progression-free survival (PFS) among patients with cancer?
(e)
What is the predictive value of PS for severe post-operative complications (POC) among patients with cancer?
(f)
What is the predictive value of PS for severe treatment-related toxicities and/or dose-limiting toxicities (TOX) among patients with cancer?
(g)
What is the predictive value of PS for disability and nosocomial infections (NI) among patients with cancer?
To answer these questions, we pre-defined eligibility criteria for the articles: patients (adults 18 y and over with cancer), intervention (pre-therapeutic sarcopenia assessed using a consensual measurement), comparator (sarcopenia vs. no sarcopenia), outcomes (prevalence of sarcopenia, OS and PFS, severe post-operative complications defined as a Clavien–Dindo scale score ≥ 3a, ≥grade 3 treatment-related toxicities (CTCAE) and/or dose-limiting toxicities, disability defined in terms of an activities of daily living score (ADL) of ≤5/6, and nosocomial infections defined as hospital-acquired infections), and study design (clinical trials, prospective or retrospective studies with consecutive inclusions) (PICOS) criteria.

2.3. Selection Process

Articles meeting the eligibility criteria were first selected on the basis of titles and abstracts (FP) then on the basis of perusal of the full text by 5 independent groups (PBR/MF, ALC/CM, SM/RG, FP/JP, EL/ZapT, and EP/AN/MP). The term sarcopenia was to be clearly defined in the articles. If several articles reported similar results, only the article with the most complete information was retained. Duplicates were screened for and removed. Disagreements were resolved by consensus in each reviewing group.

2.4. Data Collection

The data recorded included publication date, country, study design, follow-up time, number of patients, number of men and women, cancer site, cancer extension (classified as local, locally advanced, or metastatic), treatment modes, mean or median age at inclusion, the definition of sarcopenia used (low muscle mass quantity only or consensus-based algorithm), cut-off values for quantitative muscle mass indices (arm muscle area (AMA, cm2), ASM (kg/m2), psoas muscle index (PMI, cm2/m2), SMI (cm2/m2) or total psoas area (TPA, cm2)), muscle strength assessed by handgrip-strength (kg), physical performance assessed by gait speed (m/s), number of sarcopenic patients, number of sarcopenic men and women, number of sarcopenic patients with a body mass index ≥30 kg/m2 (i.e., sarcopenic obesity), and finally the outcomes associated with either the PS values (%) or the hazard ratios or the odds ratios.

2.5. Meta-Analysis Endpoints

The primary endpoint was the pooled prevalence of PS among cancer patients.
The secondary endpoints were: mean differences in handgrip strength (kg) and gait speed (m/s) between sarcopenic and non-sarcopenic patients; OS; PFS; grade ≥ 3a post-operative complications (Clavien-Dindo scale); grade ≥ 3 treatment-related toxicities (CTCAE) and/or dose-limiting toxicities; ADL-score ≤ 5/6; and hospital-acquired infections.

2.6. Quality Assessment

We used the Newcastle–Ottawa quality assessment scale (NOS) designed for cohort studies which was the case for all patients, even for those recruited from RCTs [9]. Based on a risk-of-bias assessment, this scale rates the quality of studies with scores ranging from 0 to 9. The quality of the studies was classified as good (≥7), fair (4–6), or poor (0–3).

2.7. Effect Measures

The prevalence of PS was summarized as a pooled prevalence with 95% confidence interval (95% CI) using logit transformation.
Handgrip strength and gait speed were summarized as a pooled mean difference (MD) with 95% CI with reference to non-sarcopenic patients using the inverse variance method.
OS and PFS were summarized as a pooled risk ratio (RR) with 95% CI with reference to non-sarcopenic patients using the inverse variance method.
The remaining outcomes were summarized as a pooled RR with 95% CI with reference to non-sarcopenic patients using the Mantel–Haenszel method.

2.8. Synthesis Method

The data were analyzed using R statistical software (version 4.1.0; R Foundation for Statistical Computing, Vienna, Austria; http://www.r-project.org, accessed on 1 September 2022). All tests were 2-sided and statistical significance was set at p < 0.05.
Regarding the study characteristics, categorical variables were summarized as the numbers (%), and continuous variables were summarized as the means ± standard deviation (SD) or medians [Q1–Q3] as appropriate. The studies were described in descending order according to their publication date.
To detect a non-linear relationship between sarcopenia prevalence and the muscle mass indices (using reported cut-off values), we used a non-parametric regression via smoothing splines when possible.
On the basis of the selected articles, and given that between-study heterogeneity was expected, we performed a meta-analysis with random-effect models (with the package “meta”) to assess the prevalence of PS, the mean difference in muscle strength and physical performance indices (grip strength and gait speed), and the predictive value of PS for OS, PFS, Clavien–Dindo scale ≥grade 3 for POC, ≥grade-3 for TOX, disability (ADL score ≤ 5/6), and NI among cancer patients. As there was a single study addressing disability, we did not conduct a meta-analysis on this outcome. With regard to the prevalence of PS (first endpoint), we first ran a funnel plot to detect graphical asymmetry. Statistically, the funnel plot asymmetry was assessed using the Peters’ test, which is appropriate for meta-analyses of single proportion. We addressed the heterogeneity of the study results using the I2 indicator and the Cochran’s Q test. I2 values of 0%, 25%, 50%, and 75% were considered to indicate none, low, moderate, and high heterogeneity, respectively. A p value ≤ 0.05 in the Q test indicated a significant heterogeneity. Due to the heterogeneous nature of sarcopenia and the variety of the contexts assessed, we anticipated the need for subgroup analyses according to a sensitivity analysis, excluding studies over the 95% confidence interval from the funnel plot, according to the following: study quality (good, fair or poor), the mean or median age at inclusion classified as < or ≥65 y, sex, BMI (< or ≥30 kg/m2), cancer site, cancer extension, treatment mode, definition of sarcopenia (low muscle mass quantity only or consensus-based algorithm), and the cut-off values for muscle mass indices. We also considered post hoc subgroup analyses according to the publication date (2008–2012, 2013–2017, and 2018–2022), the number of patients included (<100, 100–200, 200–400, and ≥400), and world regions (Asian vs. non-Asian).
To decipher the factors that could explain heterogeneity, we then ran a multivariate meta-regression with a mixed-effect model for the first endpoint (prevalence). Factors (study groups) yielding p values under 0.20 in the univariate analysis were considered for inclusion in the multivariate analysis. A backward selection process of the highest p values was performed to retain the final multivariate model.

3. Results

3.1. Study Selection and Quality Rating of the Studies Included

As of 31 December 2021, including the final publications in 2022, the comprehensive search yielded 1318 articles potentially eligible for this review (Figure A1). After excluding non-eligible articles, 226 remained for review and meta-analysis, dated from 2008 to 2022 as follows: 5 in 2022 [10,11,12,13,14], 60 in 2021 [15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74], 36 in 2020 [75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110], 31 in 2019 [111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141], 29 in 2018 [142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170], 18 in 2017 [171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187], 15 in 2016 [188,189,190,191,192,193,194,195,196,197,198,199,200,201,202], 15 in 2015 [203,204,205,206,207,208,209,210,211,212,213,214,215,216,217], 2 in 2014 [218,219], 5 in 2013 [220,221,222,223,224], 6 in 2012 [225,226,227,228,229,230], none in 2011, 1 in 2010 [231], 2 in 2009 [232,233], and 1 in 2008 [234] (Table 1).
According to the NOS score, 151/226 studies (67%) were rated as good quality (NOS ≥ 7) meaning there was a low risk of bias (Table 1).

3.2. Patient and Study Characteristics

In all, 65,936 patients were included in this meta-analysis with sample sizes ranging from 16 to 6447 patients (Table 1). Overall, 118 studies were retrospective, 95 were prospective, and 13 were clinical trials. The studies were mainly from Asia, Europe, and North-America, while only two studies were from Africa [75,101]. The follow-up time ranged from 0 to 200 months. The mean or median age at inclusion ranged from 45.7 to 85 y. Thirty-three per cent (17,295/65,936) of the patients had a mean or median age at inclusion ≥65 years. A total of 419/65,936 patients had a mean or median age at inclusion ≥75 years. Most of the studies also included patients younger than 65 years (64%, 30,691/47,986 patients), Asians (51%, 33,453/65,936), men (66%, 30,424/46,265), and with a body mass index < 30 kg/m2 (69.5%, 2628/8627). The studies mainly included cancers in various sites (22%, 14,600/65,936), gastric (20.5%, 13,513/65,936), or colorectal (17%, 11,419/65,936), and with various extensions (82%, 54,269/65,936). The treatment modes observed were mainly surgery (61%, 40,486/65,936), chemotherapy (6%, 4169/65,936), immune therapy (1%, 909/65,936), and targeted therapy (1%, 634/65,936).

3.3. Definition of Sarcopenia among Cancer Patients

Sarcopenia was mainly defined from muscle mass measurement only (190/226 studies, 84%), from CT scan (n = 178), BIA (n = 11), or DXA (n = 1) (Table 1). Sixteen studies did not specify the muscle mass index used [43,45,68,85,86,95,96,120,122,123,139,141,147,148,186,207]. Of the 210 remaining studies, regardless of the sarcopenia definition used, the SMI by CT scan at lumbar three was the main muscle mass quantity index used (171/210, 81.5%) followed by the ASM (21/210, 10%), the PMI (13/210, 6%), the TPA (4/210 studies, 2%), and the AMA (1/226 studies, 0.5%). The SMI cut-off values ranged from 29.0 to 48.4 cm2/m2 (37 thresholds in all) for women (median [Q1–Q3] = 38.5 [37.5–41.0]), and from 36.0 to 68.9 cm2/m2 (43 thresholds in all) for men (median [Q1–Q3] = 47.3 [43.0–52.4]).
From 2015 to the present, of the 36 studies applying a consensus-based algorithm definition of sarcopenia, 17, 9, 6, and 2 studies respectively used the AWGS1, the EWGOS2, the EWGOS1, and the AWGS2 guidelines. The IWGS was not used.

3.4. PS Is Prevalent among Cancer Patients

All the studies were used to assess the prevalence. The pooled prevalence of PS among cancer patients was 38.0% (95% CI: 36.0–41.0) with a high between-study heterogeneity (I2 = 97%) (Table 2). Figure A2 shows a significant funnel plot asymmetry (p < 0.0001).
Although the sensitivity analysis excluding studies over the 95% confidence interval from the funnel plot (n = 137 studies) led to less heterogeneity (I2 = 66%), the 40.5% prevalence was not significantly different (p = 0.11).
The prevalence was significantly lower (p < 0.01) for consensus-based algorithm definitions of sarcopenia (22.0%) than for definitions based on muscle mass measures only (42.0%).
Using the muscle mass measurement-based definition only, the prevalence differed significantly (p < 0.01), ranging from 12.0% (AMA) to 40.0% (SMI). Above the SMI medians of 38.5 cm2/m2 and 47.3 cm2/m2 for women and men, respectively, the prevalence was 47.0% and 52.0%. Figure 1 shows the smoothing splines for the relationship between the prevalence of sarcopenia and muscle mass index measures for women and men (SMI, ASM, and PMI). Regarding SMI, up to the third quartiles of 41.0 cm2/m2 and 52.4 cm2/m2 for women and men, respectively, the association was linear with a tight confidence interval. Regarding ASM, the association was paradoxical for both women and men. For PMI, the association was strictly linear for women and men, but it resulted in a large confidence interval.
Depending on the cancer site, the prevalence varied very significantly from 24.0% (gastric) to 79.0% (small cell lung). In relation to cancer extension, the prevalence varied significantly from 39.0% (local) to 46.0% (metastatic). According to the treatment mode, the pre-therapeutic prevalence of sarcopenia varied significantly from 33.0% (surgery) to 68% (intra-arterial infusion for hepatocellular carcinoma). In the 26 studies that reported prevalence according to BMI, the prevalence of sarcopenic obesity was significantly lower (p < 0.01) (19.0%) than for non-sarcopenic obesity (39.0%). The prevalence did not differ significantly with study quality, the year of publication, the world region, the age-threshold of 65 years at inclusion, or sex.
In multivariate meta-regression, consensus-based algorithm definitions of sarcopenia (as opposed to loss of muscle mass only), a sample size ≥ 400, and SMI based on CT scan cut-off values for women (not for men) as continuous variables were independently and significantly associated with the prevalence results (Table A2).

3.5. Muscle Strength and Physical Performance among Cancer Patients with Sarcopenia

Twelve studies including 3466 patients provided data on muscle strength and physical performance. Handgrip strength values among sarcopenic patients ranged from 17.7 to 22.6 kg and gait speed values among sarcopenic patients ranged from 0.72 to 1.00 m/s [26,51,58,111,138,145,169,177,179,187,206,216]. Figure 2 summarizes the mean differences in handgrip strength and gait speed between sarcopenic and non-sarcopenic patients.
For handgrip strength, the pooled mean difference was −8.62 kg with a high between-study heterogeneity (I2 = 91%). Regarding gait speed, the pooled mean difference was −0.19 m/s with a moderate between-study heterogeneity (I2 = 68%).

3.6. Pre-Therapeutic Sarcopenia Is Associated with OS and PFS among Cancer Patients

Based on 101 studies including 28,995 patients, we found a strong, significant association between pre-therapeutic sarcopenia and OS with a pooled RR of 1.97 [1.79–2.17] and with a high between-study heterogeneity (I2 = 85%, p < 0.01). Subgroup analyses are presented in Table 3 and Figure A3, showing a reduction in heterogeneity. The effect measure differed significantly (p < 0.01) according to sample size, world region, cancer site, and muscle mass index, while no significant differences were found for sensitivity analysis, study quality, year of publication, age threshold of 65 years at inclusion, cancer extension, treatment mode, and definition of sarcopenia. When low between-study heterogeneity was envisaged (i.e., I2 < 50%), the greatest effects were associated with the PMI-based muscle index (RR = 2.76 [2.21–3.43]), bile duct cancers (RR = 2.71 [1.87–3.92]), and the consensus-based algorithm definitions of sarcopenia (RR = 2.31 [1.97–2.72]).
For 29 studies including 6546 patients, we found a strong and significant association between pre-therapeutic sarcopenia and PFS with a pooled RR of 1.76 [1.44–2.16] and a high between-study heterogeneity (I2 = 85%, p < 0.01). Subgroup analyses are presented in Table 4 and Figure A4, showing a reduction in heterogeneity. The effect measure differed significantly (p < 0.01) according to the world region, cancer site, sarcopenia definition, and muscle mass index used, while no significant differences were found for sensitivity analysis, study quality, year of publication, sample size, age threshold of 65 years at inclusion, cancer extension, or treatment mode. When low between-study heterogeneity was envisaged (i.e., I2 < 50%), the most marked effects were associated with the consensus-based algorithm definitions of sarcopenia (RR = 3.59 [2.17–5.92]) and non-small cell lung cancer (RR = 2.43 [1.90–3.12]).

3.7. Pre-Therapeutic Sarcopenia Is Predictive of Severe Postoperative Complications among Cancer Patients

Based on 56 studies including 17,172 patients, we found a strong and significant association between pre-therapeutic sarcopenia and severe post-operative complications, with a pooled RR of 2.70 [2.33–3.12] involving a moderate heterogeneity (I2 = 72%). Subgroup analyses are presented in Table 5 and Figure A5, showing a reduction in heterogeneity. The effect measure differed significantly (p < 0.01) according to sensitivity analysis, year of publication, sample size, world region, cancer site, and sarcopenia definition, while no significant differences were found for study quality, the age threshold of 65 years at inclusion, cancer extension, or muscle mass index. When low between-study heterogeneity was envisaged (i.e., I2 < 50%), the most marked effects were associated with the consensus-based algorithm definitions of sarcopenia (RR = 3.62 [2.79–4.69]) and gastric cancer (RR = 3.09 [2.42–3.93]).

3.8. Pre-Therapeutic Sarcopenia Is Predictive of Severe Treatment-Related Toxicity and/or Dose-Limiting Toxicity among Cancer Patients

Based on 19 studies including 2980 patients, we found a significant association between pre-therapeutic sarcopenia and severe treatment-related toxicities and/or dose-limiting toxicities, with a pooled RR of 1.47 [1.17–1.84] involving a moderate heterogeneity (I2 = 71%). Subgroup analyses are presented in Table 6 and Figure A6, showing a reduction in heterogeneity. The effect measure differed significantly (p < 0.01) according to study quality, sample size, cancer site, cancer extension, and definition of sarcopenia, while no significant differences were found for sensitivity analysis, year of publication, world region, age threshold of 65 years at inclusion, or treatment mode. When low between-study heterogeneity was envisaged (i.e., I2 < 50%), the most marked effects were associated with breast cancer (RR = 2.93 [1.82–4.73]), head and neck cancer (RR = 2.47 [1.65–3.69]), chemotherapy (RR = 1.98 [1.55–2.54]), and targeted therapy (RR = 1.63 [1.05–2.54]).

3.9. Pre-Therapeutic Sarcopenia Is Associated with Disability among Cancer Patients

Only one study including 131 patients was found on the association between pre-therapeutic sarcopenia and disability (ADL ≤ 5/6) [160]. In this single-center prospective study including 40.5% of patients aged ≥ 75 years with cancers in various sites and with different extensions, baseline disability was noted for 30.5% of the patients. Compared to normal muscle mass and non-severe sarcopenia, severe sarcopenia is defined according to the EWGOS1 by low muscle mass (CT scan-based SMI), and both low handgrip strength and slow gait speed were significantly (p < 0.001) associated with disability (90% vs. 26% of patients) in univariate analysis.

3.10. Pre-Therapeutic Sarcopenia Is Predictive of Nosocomial Infections among Cancer Patients

Based on 22 studies including 6246 patients, we found a strong, significant association between pre-therapeutic sarcopenia and nosocomial infections with a pooled RR of 1.76 [1.41–2.22] and moderate heterogeneity (I2 = 58%). Subgroup analyses are presented in Table 7 and Figure A7, showing a reduction in heterogeneity. The effect measure differed significantly (p < 0.01) according to sensitivity analysis, sample size, age threshold of 65 years at inclusion, cancer site, and definition of sarcopenia, while no significant differences were found for study quality, year of publication, world region, cancer extension, treatment mode, or muscle mass index. When low between-study heterogeneity was envisaged (i.e., I2 < 50%), the most marked effects were associated with gastric cancer (RR = 2.55 [1.88–3.46]) and a sample size ≥ 400 (RR = 2.26 [1.66–3.07]).

4. Discussion

In this meta-analysis including 226 articles and 65,936 patients with various cancers, various extensions, and various treatment modes, PS was mainly defined as a loss of muscle mass using the SMI on CT scan-based assessment. PS was highly prevalent and was strongly associated with OS, PFS, POC, TOX, and NI during cancer treatment, with pooled relative risks ranging from 1.50 (toxicities) to 2.70 (post-operative complications).
To date, and despite successive sarcopenia consensus-based definitions of sarcopenia provided since 2010, the definition of sarcopenia mainly relies only on loss of muscle mass quantity among cancer patients. The standardized use of CT scans in pre-therapeutic oncological settings probably explains this. Unlike the ASM and the PMI indices, the SMI muscle mass index was linearly associated with the prevalence of sarcopenia for both women and men and had the tightest confidence interval, suggesting that it is probably the most suitable index for the quantification of muscle mass. However, homogeneous optimal cut-off thresholds remain to be clarified in the oncological setting.
As expected, we found great heterogeneity for all endpoints addressed here. Consistent with our previous review, the pooled prevalence of pre-therapeutic sarcopenia concerned 38% of cancer patients [7]. Using a multivariate meta-regression, we were able to identify sources of between-study heterogeneity as follows: consensus-based algorithm definitions of sarcopenia (as opposed to loss of muscle mass only), a powerful sample size (≥400), and the cut-off values of CT scan-based SMI for women (not for men) as continuous variables were independently and significantly associated with the prevalence results for pre-therapeutic sarcopenia. With respect to the prevalence results according to cancer localisation, our results require caution given the impact of the definition used. Strikingly, compared with definitions based on loss of muscle mass only (SMI), consensus-based algorithm definitions of sarcopenia reduced the prevalence significantly (42% vs. 22%), decreasing heterogeneity and increasing the predictive value for OS (RR = 1.85 vs. 2.31), PFS (RR = 1.61 vs. 3.59), post-operative complications (RR = 1.48 vs. 3.62), and nosocomial infections (RR = 1.85 vs. 2.49). This discrepancy could be explained by the additional criteria used for consensus algorithms, which consider both loss of muscle strength and/or physical performance and muscle mass. Indeed, it is known that grip strength and gait speed are independent factors associated with survival among cancer patients [236].
Surprisingly, except for nosocomial infections, we did not identify any significant difference for prevalence of sarcopenia, OS, PFS, post-operative complications, or severe treatment-related toxicities according to the age threshold of 65. This result highlights the leading role played by cancer (mainly due to cancer-related inflammatory processes) rather than age alone in promoting sarcopenia (namely secondary sarcopenia) and its clinical impact on adverse outcomes [6].
To our knowledge, although it was not performed on individual data, this is the largest and most powerful meta-analysis on this topic. It contains a stringent methodology, bringing together oncologists, geriatricians, and methodologists using data from many countries in numerous cancer settings, enabling us to provide a comprehensive up-to-date review of sarcopenia prevalence and its clinical impact in the course of cancer treatment. In particular, in a cancer setting we were able to highlight an association between pre-therapeutic sarcopenia and PFS on the one hand, and between pre-therapeutic sarcopenia and nosocomial infections on the other, subjects that have been studied infrequently to date. However, there are still insufficient data to provide a synthesis regarding the association between pre-therapeutic sarcopenia and disability.
On the basis of the findings of our meta-analysis, there clearly is an urgent need to agree on an operational definition of sarcopenia in oncological settings to improve study comparability. Given both the high prevalence and the strong clinical impact of pre-therapeutic sarcopenia during cancer treatment, we suggest that its detection should occur as early as possible. In agreement with the EWGOS 2 consensus, we support the use of the simple SARC-F (strength, assistance with walking, rise from a chair, climb stairs, and falls) screening tool, which has been previously validated in older cancer patients [237]. The early detection of sarcopenia can help to initiate early muscle rehabilitation combining protein supplementation and resistance exercise training in order to improve the healthcare trajectories during cancer treatment [238]. Finally, we encourage the use of sarcopenia as a stratification variable in the development of future clinical trial designs in oncology.

5. Conclusions

Using the findings of the largest and the most powerful meta-analysis on this topic to date, we conclude that pre-therapeutic sarcopenia among cancer patients, mainly defined as a loss of muscle mass quantity, is prevalent and strongly associated with OS, PFS, severe post-operative complications, severe treatment-related toxicities and/or dose-limiting toxicities, and nosocomial infections. We stress the need to agree on a consensual definition of sarcopenia in oncological settings.

Author Contributions

Conceptualization, E.P. and F.P.; methodology, F.P.; software, F.P.; validation, A.-L.C., E.L., P.B.-R., J.P., M.F., C.M., S.M., R.G., Z.a.T., A.N., M.P., C.B., E.P. and F.P.; formal analysis, F.P.; investigation, A.-L.C., E.L., P.B.-R., J.P., M.F., C.M., S.M., R.G., Z.a.T., A.N., M.P., E.P. and F.P.; resources, A.-L.C., E.L., P.B.-R., J.P., M.F., C.M., S.M., R.G., Z.a.T., A.N., M.P., E.P. and F.P.; data curation, A.-L.C., E.L., P.B.-R., J.P., M.F., C.M., S.M., R.G., Z.a.T., A.N., M.P., E.P. and F.P.; writing—original draft preparation, A.-L.C., E.L., P.B.-R., E.P. and F.P.; writing—review and editing, A.-L.C., E.L., P.B.-R., J.P., M.F., C.M., S.M., R.G., Z.a.T., A.N., M.P., C.B., E.P. and F.P.; visualization, A.-L.C., E.L., P.B.-R., J.P., M.F., C.M., S.M., R.G., Z.a.T., A.N., M.P., C.B., E.P. and F.P.; supervision, A.-L.C., E.L., P.B.-R., E.P. and F.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author.

Acknowledgments

We thank the French Society of Geriatric Oncology (SoFOG) which supported this work. We thank Angela Swaine and Sarah Leyshon for revising the English language in the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Consensus-based algorithm definition of sarcopenia.
Table A1. Consensus-based algorithm definition of sarcopenia.
ConsensusYearScreeningDefinition
Muscle Mass Muscular Strength Muscular Performance
EWGOS 12010No↓
DXA, BIA, CT or MRI		AND↓
Hand-grip strength (kg)
[M < 30, F < 20]		OR↓
GS < 0.8 m/s or SPPB < 9/12 or TGUG ≥ 20 s
IWGS2011No↓
DXA		ANDNo-↓
GS < 1 m/s
AWGS 12014No↓
DXA or BIA		AND↓
Hand-grip strength (kg)
[M < 26, F < 18]		AND↓
GS < 0.8 m/s
EWGOS 22019Yes
(SARCF)		↓
DXA, BIA, CT or MRI		AND↓
Hand-grip strength (kg)
[M < 27, F < 16]
Or
5 Rising from a chair > 15 s		AND
(severity)		↓
GS < 0.8 m/s or SPPB < 9/12 or TGUG ≥ 20 s
AWGS 22019Yes
(SARCF)		↓
DXA or BIA		AND↓
Hand-grip strength (kg)
[M < 28, F < 18]
5 Rising from a chair > 12 s		AND
(severity)		↓
GS < 1 m/s or SPPB < 9/12
EWGOS: European Working Group On Sarcopenia; IWGS: International Working Group on Sarcopenia; AWGS: Asian Working Group on Sarcopenia; DXA: dual-energy X-ray absorptiometry; BIA: bioelectrical impedance analysis; CT: computed tomography; MRI: magnetic resonance imagery. M: male; F: female. GS: gait speed; SPPB: short physical performance battery; TGUG: timed get up and go test. SARCF: strength, assistance with walking, rise from a chair, climb stairs, and falls. ↓: reduced muscle mass; Bold = consensus names, and syndromic combination.
Table
Table A2. Multivariate meta-regression of factors significantly influencing the prevalence of pre-therapeutic sarcopenia among cancer patients.
Table A2. Multivariate meta-regression of factors significantly influencing the prevalence of pre-therapeutic sarcopenia among cancer patients.
Study GroupsEstimatesStandard Errorp
N° of patients included (n = 65,936)
<1001 (reference)--
100–1990.020.150.89
200–300−0.250.160.10
≥4000.510.19<0.01
Definition of sarcopenia
Muscle mass only (n = 54,923)1 (reference)--
Consensus algorithm-based (n = 11,013)−0.850.18<0.0001
Cut-off values of CT scan-based SMI for women (per 6.0 cm2/m2 of more) (n = 14,216) 0.050.02<0.01
Bold = grouping data, and significant p value at the threshold of 5%.

Appendix B

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Figure A1. Flaw chart of the meta-analysis.
Figure A1. Flaw chart of the meta-analysis.
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Figure A2. Funnel plot of the prevalence of pre-therapeutic sarcopenia among cancer patients (p value for asymmetry [Peters’ test] < 0.0001). Gold points = studies; blue dash lines = common effect with 95% CI; red dash lines = random effect.
Figure A2. Funnel plot of the prevalence of pre-therapeutic sarcopenia among cancer patients (p value for asymmetry [Peters’ test] < 0.0001). Gold points = studies; blue dash lines = common effect with 95% CI; red dash lines = random effect.
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Figure A3. Pooled relative risk (RR) of the predictive value of pre-therapeutic sarcopenia on overall survival among cancer patients [14,15,16,17,18,23,24,25,26,28,30,33,34,36,37,39,42,43,47,48,49,50,51,52,55,56,58,61,65,67,70,72,75,77,79,80,81,83,89,91,93,94,96,98,100,101,102,103,104,107,108,112,113,114,115,116,117,119,125,130,132,133,135,136,144,146,147,148,149,150,153,155,159,161,162,163,165,167,168,169,170,171,174,181,184,189,191,193,194,195,196,197,198,200,209,210,211,214,224,229,230,232,234].
Figure A3. Pooled relative risk (RR) of the predictive value of pre-therapeutic sarcopenia on overall survival among cancer patients [14,15,16,17,18,23,24,25,26,28,30,33,34,36,37,39,42,43,47,48,49,50,51,52,55,56,58,61,65,67,70,72,75,77,79,80,81,83,89,91,93,94,96,98,100,101,102,103,104,107,108,112,113,114,115,116,117,119,125,130,132,133,135,136,144,146,147,148,149,150,153,155,159,161,162,163,165,167,168,169,170,171,174,181,184,189,191,193,194,195,196,197,198,200,209,210,211,214,224,229,230,232,234].
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Figure A4. Pooled relative risk (RR) of the predictive value of pre-therapeutic sarcopenia on progression-free survival among cancer patients [15,17,19,23,25,31,35,36,42,46,50,62,63,72,77,81,98,102,112,116,122,130,153,159,184,191,197,214,229,233].
Figure A4. Pooled relative risk (RR) of the predictive value of pre-therapeutic sarcopenia on progression-free survival among cancer patients [15,17,19,23,25,31,35,36,42,46,50,62,63,72,77,81,98,102,112,116,122,130,153,159,184,191,197,214,229,233].
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Nutrients 15 01193 g0a5 550
Figure A5. Pooled relative risk (RR) of the predictive value of pre-therapeutic sarcopenia on severe post-operative complications among cancer patients [18,26,49,51,54,55,56,57,58,59,70,71,72,76,77,84,85,86,103,104,111,119,123,125,126,127,129,131,138,143,150,155,157,158,162,164,169,170,175,177,179,184,187,188,190,191,192,199,202,203,205,206,207,209,212,213,214,216,217,220].
Figure A5. Pooled relative risk (RR) of the predictive value of pre-therapeutic sarcopenia on severe post-operative complications among cancer patients [18,26,49,51,54,55,56,57,58,59,70,71,72,76,77,84,85,86,103,104,111,119,123,125,126,127,129,131,138,143,150,155,157,158,162,164,169,170,175,177,179,184,187,188,190,191,192,199,202,203,205,206,207,209,212,213,214,216,217,220].
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Figure A6. Pooled relative risk (RR) of the predictive value of pre-therapeutic sarcopenia on severe treatment-related toxicity and/or dose limiting toxicity among cancer patients [22,36,40,47,70,79,82,89,96,118,129,130,136,156,161,176,183,186,215,221,233].
Figure A6. Pooled relative risk (RR) of the predictive value of pre-therapeutic sarcopenia on severe treatment-related toxicity and/or dose limiting toxicity among cancer patients [22,36,40,47,70,79,82,89,96,118,129,130,136,156,161,176,183,186,215,221,233].
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Figure A7. Pooled relative risk (RR) of the predictive value of pre-therapeutic sarcopenia on nosocomial infections among cancer patients [57,64,76,84,95,111,123,146,151,152,168,177,179,182,190,192,199,206,207,210,225,235].
Figure A7. Pooled relative risk (RR) of the predictive value of pre-therapeutic sarcopenia on nosocomial infections among cancer patients [57,64,76,84,95,111,123,146,151,152,168,177,179,182,190,192,199,206,207,210,225,235].
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Figure 1. Non-parametric regression via smoothing splines for assessing the relationship between prevalence of pre-therapeutic sarcopenia and cut-off values of SMI (A,B), ASM (C,D), or PMI (E,F) in women and men with cancer, respectively.
Figure 1. Non-parametric regression via smoothing splines for assessing the relationship between prevalence of pre-therapeutic sarcopenia and cut-off values of SMI (A,B), ASM (C,D), or PMI (E,F) in women and men with cancer, respectively.
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Figure 2. Pooled mean differences (MD) of handgrip strength (A, kg) and gait speed (B, m/s) between sarcopenic and non-sarcopenic groups among cancer patients [26,51,58,111,138,145,169,177,179,187,206,216].
Figure 2. Pooled mean differences (MD) of handgrip strength (A, kg) and gait speed (B, m/s) between sarcopenic and non-sarcopenic groups among cancer patients [26,51,58,111,138,145,169,177,179,187,206,216].
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Table
Table 1. Study characteristics.
Table 1. Study characteristics.
ReferenceAsia (Y/N)Recruitment
RCT/P/RP		Follow-Up (m)PatientsSiteExtensionTreatmentMean or Median Age (y)Definition of Sarcopenia/Muscle Mass IndexSarcopeniaOver the 95% CI (Y/N)NOS
G/F/P
TotalMFTotalMF
Takagi A et al., 2022 [10]YP1.01147440VariousVariousVarious68.4CT scan/SMI57NANANG
Lu JL et al., 2022 [11]YP0.026019664GastricLocally advancedSurgery62.4EWGOS 2/ASM412219YG
Deluche E et al., 2022 [12]NP1.01392137BreastMetastaticVarious61.2EWGOS 1/SMI41140NF
Tagliafico AS et al., 2022 [13]NP200.0743737MyelomaMetastaticChemotherapy60.8CT scan/SMI18612YG
Orzell S et al., 2022 [14]NP72.025119158Head and neckVariousSurgery67.4EWGOS 2/SMI392118YG
Bajric T et al., 2021 [15]NRP63.6355135220ColorectalMetastaticSurgery68.0CT scan/SMI786513YF
Cárcamo L. et al., 2021 [16]NRP72.0359193166ColorectalVariousSurgery64.0CT scan/SMI85NANAYG
Catanese S et al., 2021 [17]NRP87.6785622GastricMetastaticVarious67.0CT scan/SMI342212NG
Chai VW et al., 2021 [18]NRP12.022813989ColorectalVariousSurgery69.0CT scan/SMI362412YG
Chang YR et al., 2021 [19]YRP141.61096346SarcomaMetastaticTargeted therapy61.0CT scan/PMI25NANAYF
Chen HW et al., 2021 [20]YRP86.4163NANAUrothelialVariousSurgery64.3CT scan/SMI132NANAYF
Daffrè E et al., 2021 [21]NRP60.023816969Lung NSCVariousSurgery63.0CT scan/SMI473611YG
Ferini G et al., 2021 [22]NRP70.028253UrothelialVariousRadiotherapy85.0CT scan/SMI880NF
Haik L et al., 2021 [23]NRP60.026119863VariousVariousImmunotherapy61.9CT scan/SMI1228735NF
Harry Hsu TM et al., 2021 [24]NP33.61366373PancreasVariousNot specified67.0CT scan/SMI21912YF
Hu WH et al.,2021 [25]YRP80.41146846ColorectalVariousSurgery63.2CT scan/SMI52NANANG
Huang DD et al.,2021 [26]YP67.2419282137GastricVariousSurgery72.0CT scan/SMI28520877YG
Kim J et al., 2021 [27]YRP41.0840526534GastricVariousVarious60.4CT scan/SMI1191109YG
Kim GH et al., 2021 [28]YRP70.528018298GastricLocalSurgery82.0CT scan/SMI173NANAYG
Kawaguchi Y et al., 2021 [29]YRP60.025617383Lung NSCVariousSurgery68.5CT scan/PMI1288939YF
Juris A et al., 2021 [30]NRP48.0894049VariousVariousVarious57.0CT scan/SMI221111YF
Jullien M et al., 2021 [31]NP36.6656367289LymphomaVariousVarious49.0CT scan/SMI22517946NG
Jalal M et al., 2021 [32]NRP0.020411490PancreasLocally advancedVarious69.0CT scan/SMI1114170YF
Kirsten J et al., 2021 [33]NP12.017810969LeukemiaMetastaticChemotherapy58.3EWGOS149427YG
Kim N et al., 2021 [34]YRP30.118512065GastricMetastaticImmunotherapy59.0CT scan/SMI93858YG
Leone R et al., 2021 [35]NRP40.0431528LymphomaVariousChemotherapy61.0CT scan/SMI13NANANF
Lee CH et al., 2021 [36]YRP57.1785919KidneyMetastaticTargeted therapy61.6CT scan/SMI412813NG
Liang H et al., 2021 [37]YRP17.7100937EsophagealVariousRadiotherapy59.0CT scan/SMI77743YF
Makal GB et al., 2021 [38]YRP1.022514184VariousVariousSurgery58.7CT scan/TPA1024260NP
Nilsson M et al., 2021 [39]NRP60.01062284AnalVariousRadiotherapy63.8CT scan/SMI411130NG
Takeda T et al., 2021 [40]YRP63.6803545PancreasMetastaticChemotherapy77.0CT scan/SMI612536YG
Takiguchi K et al., 2021 [41]YRP96.020911693ColorectalLocally advancedSurgeryNACT scan/PMI815031NF
Thureau S et al., 2021 [42]NP60.024318756Head and neckVariousVarious61.0CT scan/SMI88NANANG
Troschel FM et al., 2021 [43]NRP96,0367247120Lung NSCVariousSurgery62.2CT scan/NA1048618YG
Trussardi Fayh AP et al., 2021 [44]NP0.01085157VariousVariousVarious70.6EWGOS 2/SMI26NANAYF
van den Berg I et al., 2021 [45]NRP60.0754352306ColorectalVariousSurgeryNACT scan/NA266NANANF
Wu WY et al., 2021 [46]YP67.2648486162GastricVariousSurgery64.3AWGS2/ EWGOS2/SMI1339142YG
Xu YY et al., 2021 [47]YRP50.018414143EsophagealVariousVarious62.0CT scan/SMI947519YF
Yamashita S et al., 2021 [48]YRP72.012310320UrothelialVariousSurgery74.0CT scan/SMI48NANANF
Zhang FM et al., 2021 [49]YP80.0507367140GastricLocalSurgery63.0CT scan/SMI735320YF
Zilioli VR et al., 2021 [50]NRP144.01547876LymphomaVariousVarious71.0CT scan/SMI664224NG
Zou HB et al., 2021 [51]YP6.01359144GastricVariousSurgery64.0AWGS 2/SMI271413YF
Peng H et al., 2021 [52]YRP82.01219625EsophagealVariousSurgery70.3CT scan/SMI655213YF
Rinninella E et al., 2021 [53]NRP0.026188GastricLocally advancedVarious63.3CT scan/SMI19NANAYF
Runkel M et al., 2021 [54]NRP0.0945836ColorectalMetastaticSurgery61.4CT scan/SMI34NANANF
Sakurai K et al., 2021 [55]YRP127.01054691363GastricVariousSurgeryNACT scan/SMI19311776YG
Sehouli J et al., 2021 [56]NP59.02260226VariousVariousSurgery59.0BIA/ASM68068NG
Şengül Ayçiçek G et al., 2021 [57]NP0.0492524VariousVariousSurgery70.0BIA/ASM14113NF
Sun X et al., 2021 [58]YP50.026720265GastricVariousSurgery64.8AWGS 1/SMI493217YG
Pessia B et al., 2021 [59]NRP48.068NANAPancreasLocalSurgery63.0CT scan/SMI32NANANG
Choi H et al., 2021 [60]YRP60.0440243197Lung NSCLocalSurgery65.0CT scan/SMI246NANAYG
Jang HY et al., 2021 [61]YRP120.016012040LiverLocalSurgery55.2CT scan/SMI281711YG
Tenuta M et al., 2021 [62]NP62.5472720Lung NSCLocally advancedImmunotherapy67.0EWGOS 2/ASM19109NG
Lee JH et al., 2021 [63]YP36.070700ProstateMetastaticVarious66.5CT scan/SMI47470YG
Taniguchi Y et al., 2021 [64]YRP72.0567393174GastricVariousSurgeryNACT scan/PMI88817YG
Deng L et al., 2021 [65]YP80.01215269CholangiocarcinomaVariousSurgery65.0CT scan/PMI53NANANG
Uemura S et al., 2021 [66]YRP60.0693831PancreasVariousChemotherapy63.0CT scan/SMI331221NF
Jung AR et al., 2021 [67]YP96.019015634Head and neckVariousVarious71.9CT scan/SMI64568NG
Huang X et al., 2021 [68]YP3.0825527Head and neckVariousChemotherapy45.7AWGS 1//NA371720NG
Regnier R et al., 2021 [69]NRP3.0826220KidneyLocally advancedVarious65.0CT scan/SMI47398YG
Jin K et al., 2021 [70]YRP0.01195960PancreasLocally advancedVarious60.2CT scan/SMI57NANANG
Miura A et al., 2021 [71]YRP79.6259155104Lung NSCVariousSurgery73.0CT scan/PMI17912752YF
Takahashi Y et al., 2021 [72]YRP137.0315192123Lung NSCLocalSurgery70.0CT scan/PMI794633YG
Silva PB et al., 2021 [73]NP0.071710Head and neckVariousNot specified66.9EWGOS 1/ASM32320NF
Seror M et al., 2021 [74]NRP60.01109218LiverLocalSurgery67.7CT scan/SMI26251YG
Badran H et al., 2020 [75]NP12.02629653LiverLocally advancedVarious59.6CT scan/SMI1138627NF
Chen WS et al., 2020 [76]YP0.0360214146ColorectalVariousSurgery72.0AWGS 1/SMI1337657NG
Fraisse G et al., 2020 [77]NRP64.814612620UrothelialVariousVariousNACT scan/SMI67598NP
Hirsch L et al.,2020 [78]NP18.0925834VariousMetastaticImmunotherapy64.6CT scan/SMI45NANANG
Huang CH et al., 2020 [79]YRP84.01071016EsophagealVariousVarious54.1CT scan/SMI65632YP
Lanza E et al., 2020 [80]NRP60.014211032LiverVariousIntra-arterial infusion for hepatocellular carcinoma73.0CT scan/SMI1219724YG
Tsukagoshi M et al., 2020 [81]YRP36.030237Lung NSCVariousImmunotherapy67.0CT scan/PMI13103NG
Ueno A et al., 2020 [82]YRP0.082082BreastVariousChemotherapy54.0CT scan/SMI10NA10YF
Pielkenrood BJ et al., 2020 [83]NP19.2310194116VariousMetastaticRadiotherapy67.0CT scan/SMI119NANANG
Wang PY et al., 2020 [84]YP0.221214567EsophagealVariousSurgery64.9AWGS 1/ASM553718YG
Martini K et al., 2020 [85]NRP1.023469165Lung NSCVariousSurgeryNACT scan/NA782355NF
Berardi G et al., 2020 [86]NP3.023415876VariousVariousSurgery66.5EWGOS 2/NA683137YG
den Boer RB et al., 2020 [87]NP3.019915841GastricVariousVarious66.1CT scan/SMI846717NF
Xu LB et al., 2020 [88]YP48.0749499250GastricVariousSurgeryNAAWGS 2/SMI1349143YG
Yu J II et al., 2020 [89]YRCT192.0458282176GastricVariousVariousNACT scan/SMI75741YG
Mishra A et al., 2020 [90]NP0.0296161135LeukemiaMetastaticChemotherapy52.4CT scan/SMI1327557NG
Choi K et al., 2020 [91]YP72.023819345LiverVariousVarious59.0CT scan/PMI1351305YG
Benadon B et al., 2020 [92]NP60.01047232EsophagealLocally advancedVarious63.0CT scan/SMI84NANAYG
Mallet R et al., 2020 [93]NP120.0978116EsophagealVariousVarious63.6CT scan/SMI54495YG
Ryu Y et al., 2020 [94]YP60.0548326222PancreasVariousVarious62.5CT scan/SMI25218666YG
Giani A et al., 2020 [95]NP0.017311162ColorectalLocalSurgery70.0CT scan/NA43NANAYF
van Rijn-Dekker MI et al., 2020 [96]NP60.0750555195Head and neckVariousVariousNACT scan/NA18914346YG
Srpcic M et al., 2020 [97]NP120.013911722EsophagealVariousSurgery63.9CT scan/SMI23203YG
Roch B et al., 2020 [98]NRP30.01429349Lung NSCMetastaticImmunotherapy63.5CT scan/SMI92NANAYG
Agalar C et al., 2020 [99]NP36.0652342ColorectalMetastaticVarious56.0CT scan/SMI20614NF
Shinohara S et al., 2020 [100]YRP96.0391275116Lung NSCVariousSurgery69.3CT scan/PMI19816038YG
Salman MA et al., 2020 [101]NP12.0523814LiverLocalSurgery53.9CT scan/SMI27189NG
Stangl-Kremser J et al., 2020 [102]NRCT60.01861860ProstateMetastaticChemotherapy68.8CT scan/SMI154154NAYG
Zhuang CL et al., 2020 [103]YRP36.0883619264GastricVariousSurgery65.0EWGOS 1/EWGOS 2/SMI15010347YG
Hendrickson NR et al., 2020 [104]NRP12.01458362SarcomaVariousSurgeryNACT scan/PMI382117YG
Yumioka T et al., 2020 [105]YRP0.0805525VariousVariousChemotherapy71.6CT scan/TPA39NANANF
Oflazoglu U et al., 2020 [106]NP0.0461203258VariousVariousNot specified58.2EWGOS 1/ASM775918YG
Lee EC et al., 2020 [107]YP60.01587385UrothelialVariousSurgery64.0CT scan/SMI885830YF
Martin L et al., 2020 [108]NP19.61157744413VariousVariousVarious63.6CT scan/SMI173NANAYF
Couderc AL et al., 2020 [109]NP0.031310ProstateVariousVarious80.4EWGOS 2/ASM88NANF
He WZ et al., 2020 [110]YP144.017671382385Head and neckVariousVariousNACT scan/SMI683573110NG
Chen XY et al., 2019 [111]YP0.031322984GastricVariousSurgery62.0AWGS 1/SMI372314YG
Dijksterhuis WPM et al., 2019 [112]NP0.0886622VariousMetastaticChemotherapy63.0CT scan/SMI432914NF
Dolan RD et al., 2019 [113]NP109.2650354296ColorectalVariousSurgeryNACT scan/SMI283150133NG
de Paula N et al., 2019 [114]NRP13.02320232UterusVariousVarious64.3CT scan/SMI60060YF
Griffin OM et al., 2019 [115]NP48.0783741PancreasVariousChemotherapy64.2CT scan/SMI39NANANF
Hopkins JJ et al., 2019 [116]NRP123.0968589379ColorectalVariousSurgery65.8CT scan/SMI488262226YG
Jung A et al., 2019 [117]YP70.525822335Head and neckVariousVarious64.0CT scan/SMI17NANAYG
Huillard O et al., 2019 [118]NRCT0.0180NANAThyroidMetastaticTargeted therapy63.0CT scan/SMI89NANAYG
Kitano Y et al., 2019 [119]YRP94.11107535CholangiocarcinomaLocally advancedSurgery71.0CT scan/SMI311714NG
Kurk S et al., 2019 [120]NRCT57.018211567ColorectalMetastaticChemotherapy64.0CT scan/NA996336YG
Lin J et al., 2019 [121]YP0.0594448146GastricLocally advancedSurgery64.3CT scan/SMI195NANANG
Matsunaga T et al., 2019 [122] YRP54.016312835EsophagealVariousVarious64.7BIA/NA826418YG
Tamura T et al., 2019 [123]YRP1.015310152GastricVariousSurgeryNABIA/NA24177YG
Vashi PG et al., 2019 [124]NRP70.01126349ColorectalVariousVarious56.3CT scan/SMI462620NG
Yamamoto K et al., 2019 [125]YRP60.0906129GastricVariousSurgeryNAEWGOS 1/ASM19172YG
Yang J et al., 2019 [126]YRP1.0417251166ColorectalVariousSurgery57.9CT scan/SMI614219YG
Okabe H et al., 2019 [127]YRP0.0269167102ColorectalVariousSurgery74.0CT scan/SMI1598178YG
Otten L et al., 2019 [128]NP12.0439248191VariousVariousVarious69.6EWGOS 1/ASM1198237YG
Panje CM et al., 2019 [129]NRCT84.061574EsophagealLocally advancedVarious61.0CT scan/SMI31NANANG
Sasaki S et al., 2019 [130]YRCT6.021914376ColorectalVariousVarious64.0CT scan/SMI13510926YG
Shi B et al., 2019 [131]YRP0.027920574GastricVariousSurgery56.2CT scan/SMI12510619NG
da Silva JR et al., 2019 [132]NP13.0334151183VariousVariousPalliative63.0CT scan/ASM219NANAYG
Charette N et al., 2019 [133]NRCT30.021712394ColorectalLocally advancedChemotherapy63.0CT scan/SMI150NANAYG
Jang M et al., 2019 [134]YRP0.0284163121PancreasLocalSurgery62.6CT scan/SMI191NANAYG
Kiss N et al., 2019 [135]NP80.0412912Lung NSCVariousVarious65.6CT scan/SMI25NANAYG
Kurita Y et al., 2019 [136]YRP66.0826022PancreasMetastaticChemotherapy64.0CT scan/SMI423111NF
Nakamura N et al., 2019 [137]YRP146.5905139LymphomaMetastaticChemotherapy59.0CT scan/SMI392514NF
Ma BW et al., 2019 [138]YP1.0545418127GastricLocally advancedSurgery62.6EWGOS 1/SMI402515YG
Wang P et al., 2019 [139]YP12.0442618EsophagealVariousSurgery65.7BIA/NA18NANANG
Soma D et al., 2019 [140]YP0.01028913EsophagealVariousVarious67.3CT scan/SMI453411NG
Zhang S et al., 2019 [141]YRP43.2644743172130VariousVariousSurgeryNACT scan/NA16381109529YF
Ataseven B et al., 2018 [142]NRP0.03230323OvaryVariousSurgery60.0CT scan/SMI152NA152YG
Banaste N et al., 2018 [143]NRP81.6214105109ColorectalMetastaticVarious59.5CT scan/SMI90NANANG
Chambard LC et al., 2018 [144]NP50.0644816Lung NSCMetastaticVarious65.1DXA/ASM16NANANG
Chen WZ et al., 2018 [145]YP0.0376228148ColorectalVariousSurgery64.3AWGS 1/SMI924448YG
Kawamura T et al., 2018 [146]YRP66.5951660291GastricVariousSurgery74.2AWGS 1/AMA1116942YG
Ní Bhuachalla EB et al., 2018 [147]NP26.1725433292VariousVariousChemotherapy64.3CT scan/NA274144130NG
Kim YR et al., 2018 [148]YRP80.092920LiverMetastaticSurgery54.0CT scan/NA72720YG
Lee JS et al., 2018 [149]YRP31.914010634GastricVariousChemotherapy67.0CT scan/SMI67661NF
Mayr R et al., 2018 [150]NRP3.032726265UrothelialVariousSurgery70.0CT scan/SMI1088127NG
Mao CC et al., 2018 [151]YP1.2682513169GastricVariousSurgery64.5AWGS 1/SMI1329042YF
Motoori M et al., 2018 [152]YRP0.0836617EsophagealVariousVarious65.0BIA/ASM2855NANP
McSorley ST et al., 2018 [153]NP96.0322174148ColorectalVariousSurgeryNACT scan/SMI158NANAYF
van der Kroft G et al., 2018 [154]NP1.0633924ColorectalVariousSurgery69.0CT scan/SMI332013NF
van Vugt JLA et al., 2018 [155]NP1.0816440376ColorectalVariousSurgeryNACT scan/SMI411NANAYG
Williams GR et al., 2018 [156]NP0.1251213ColorectalVariousChemotherapy59.0CT scan/SMI12NANANF
Zhang WT et al., 2018 [157]YRP1.0636478158GastricVariousSurgeryNAAWGS 1/SMI866422YG
Zhang Y et al., 2018 [158]YRP0.215611541GastricVariousSurgery59.1CT scan/SMI24177YG
Okugawa Y et al., 2018 [159]YP60.01679968ColorectalVariousVarious67.0CT scan/PMI552035NF
Rier HN et al., 2018 [160]NP0.01317358VariousVariousVarious 72.0 EWGOS 1/SMI341816YF
Sato S et al., 2018 [161]YRP36.0483216EsophagealLocally advancedVarious65.5CT scan/SMI342311YF
Stretch C et al., 2018 [162]NRP120.01236152PancreasVariousSurgery68.5CT scan/SMI502921NF
Sugimoto M et al., 2018 [163]NRP60.0323176147PancreasVariousVarious 65.0 CT scan/SMI200NANAYG
Sui K et al., 2018 [164]YP60.0354203151PancreasVariousSurgery70.0CT scan/SMI875136YG
Limpawattana P et al., 2018 [165]YP30.0755817Bile ductsVariousVarious57.0AWGS 1/ASM40406YF
Caan BJ et al., 2018 [166]NRP120.0324103241BreastVariousVarious54.1CT scan/SMI108601086NG
Ha Y et al., 2018 [167]YRP96.017814137LiverVariousVariousNACT scan/SMI624319NG
Nakashima Y et al., 2018 [168]YRP60.034128952EsophagealVariousSurgeryNACT scan/SMI171NANAYG
Makiura D et al., 2018 [169]YP60.0988315EsophagealVariousSurgery67.0AWGS 1/ASM31247NF
Mason RJ et al., 2018 [170]NRP84.06986980ProstateVariousSurgery61.8CT scan/SMI3883880YG
Begini P et al., 2017 [171]NRP100.0926527LiverVariousVarious71.6CT scan/SMI372017NG
Black D et al., 2017 [172]NRP61.0447256191VariousVariousVariousNACT scan/SMI104NANAYG
Daly LE et al., 2017 [173]NRP0.0845232MelanomaMetastaticImmunotherapy54.0CT scan/SMI201010YG
Endo T et al., 2017 [174]YP0.01218140VariousVariousSurgery70.3BIA/ASM29NANAYF
Härter J et al., 2017 [175]NP5.0603426VariousVariousSurgeryNABIA/ASM11NANAYP
Heidelberger V et al., 2017 [176]NRP17.0683632MelanomaVariousImmunotherapy65.0CT scan/SMI34NANANF
Huang DD et al., 2017 [177]YP1.0470364106GastricVariousSurgery65.0AWGS 1/SMI795920YF
Imai K et al., 2017 [178]YRP0.0351242109LiverVariousVarious70.4CT scan/SMI33303YG
Paireder M et al., 2017 [235]NRP99.413010624EsophagealVariousVarious61.4CT scan/SMI806812YG
Lou N et al., 2017 [179]YP1.020616145GastricVariousSurgery64.0AWGS 1/SMI1495YG
Cushen SJ et al., 2017 [180]NRP0.0554312KidneyMetastaticTargeted therapy66.0CT scan/SMI18180NG
Cespedes Feliciano EMC et al., 2017 [181]NP120.0247012511219ColorectalVariousSurgery63.0CT scan/SMI1133NANAYG
Elliott JA et al., 2017 [182]NP60.020716542EsophagealVariousSurgery61.6CT scan/SMI49454YF
Wendrich AW et al., 2017 [183]NRP90.01127240Head and neckVariousChemotherapy54.5CT scan/SMI612338YG
Bronger H et al., 2017 [184]NRP60.01280128OvaryVariousVarious65.0CT scan/SMI16016YG
Ishihara H et al., 2017 [185]YRP58.01378948UrothelialLocally advancedSurgery72.8CT scan/SMI904842YF
Miyata H et al., 2017 [186] YP0.0947618EsophagealVariousVarious64.2BIA/NA44NANANG
Zhou CJ et al., 2017 [187]YP1.024019050GastricVariousSurgery73.0AWGS 1/SMI695217YF
Chemama S et al., 2016 [188]NRP0.0973760ColorectalMetastaticVarious53.0CT scan/SMI39633NG
Grotenhuis BA et al., 2016 [189]NRCT104.01208832EsophagealLocally advancedVarious62.0CT scan/SMI544212NG
Nishigori T et al., 2016 [190]YRP0.019916435EsophagealVariousSurgery65.0CT scan/SMI14913316YG
Okumura S et al., 2016 [191]YRP60.020711196Bile ductsVariousSurgery68.0CT scan/SMI713635NG
Pecorelli N et al., 2016 [192]NRP2.020210894PancreasVariousSurgery66.8CT scan/SMI1327953YF
Park I et al., 2016 [193]YP44.3885929VariousMetastaticChemotherapy65.0CT scan/ASM765719YF
Suzuki Y et al., 2016 [194]YRP100.0905238Lung NSCLocalSurgery68.7CT scan/SMI381622NF
Takeoka Y et a. 2016 [195]YRP60.0561937MyelomaMetastaticChemotherapy71.0CT scan/SMI37829YF
Fukushima H et al., 2016 [196]YRP96.0815328UrothelialVariousSurgery71.0CT scan/SMI472819YG
Go SI et al., 2016 [197]YRP132.018711275LymphomaMetastaticChemotherapyNACT scan/SMI462818YG
Kumar A et al., 2016 [198]NP60.02960296OvaryMetastaticChemotherapy64.6CT scan/SMI1320132NG
Pędziwiatr M et al., 2016 [199]NP1.01247351ColorectalVariousSurgery65.9CT scan/SMI341222YG
Rollins KE et al., 2016 [200]NRP66.0228124104PancreasVariousChemotherapyNACT scan/SMI138NANAYG
Yabusaki N et al., 2016 [201]YRP60.019515738LiverLocalSurgery66.0CT scan/SMI895732NF
Buettner S et al., 2016 [202]NP12.01326730596VariousVariousSurgery62.5CT scan/TPA398219179YG
Amini N et al., 2015 [203]NRP60.0763418345PancreasVariousSurgery67.0CT scan/TPA192NANAYG
Anandavadivelan P et al., 2015 [204]NRCT0.0726111EsophagealVariousChemotherapy67.0CT scan/SMI31NANANG
Fukuda Y et al., 2015 [205]YP0.0996633GastricVariousSurgeryNAAWGS 1/ASM21192YG
Huang DD et al., 2015 [206]YP1.01428854ColorectalVariousSurgery62.0AWGS 1/SMI17116YG
Ida S et al., 2015 [207]YP0.013812117EsophagealVariousSurgeryNABIA/NA614714NG
Kim EY et al., 2015 [208]YRP38.014912722Lung SCVariousVarious68.6CT scan/SMI1181108YG
Levolger S et al., 2015 [209]NP36.0906327LiverVariousVarious62.0CT scan/SMI523913YG
Reisinger KW et al., 2015 [210]NRP1.0310155155EsophagealVariousSurgery69.0CT scan/SMI1489058YG
Tamandl D et al., 2015 [211]NRP60.020015149EsophagealVariousSurgery63.9CT scan/SMI13010723YG
Tegels JJ et al., 2015 [212]NRP6.0149NANAGastricVariousSurgery69.8EWGOS 1/SMI86NANAYG
Voron T et al., 2015 [213]NRP70.01099217LiverLocalSurgery61.7CT scan/SMI59536YG
Lodewic TM et al., 2015 [214]NP60.017110467ColorectalMetastaticSurgery64.0CT scan/SMI804535NG
Tan BH et al., 2015 [215]NRP83.3896722VariousVariousChemotherapy65.8CT scan/SMI443410NG
Wang SL et al., 2015 [216]YP1.025519065GastricVariousSurgery65.1AWGS 1/SMI32266YG
van Vugt JL et al., 2015 [217]NRP1.0206100106ColorectalMetastaticSurgeryNACT scan/SMI904644NG
Gonzalez MC et al., 2014 [218]NP36.017560115VariousVariousChemotherapy56.9BIA/ASM22NANAYG
Barret M et al., 2014 [219]NP2.0513813ColorectalMetastaticChemotherapy65.0CT scan/SMI36315YG
Harimoto N et al., 2013 [220]YRP60.018614541LiverVariousSurgeryNACT scan/SMI755025NG
Huillard O et al., 2013 [221]NRP52.0613859KidneyMetastaticTargeted therapy60.0CT scan/SMI32248NG
Veasey-Rodrigues H et al., 2013 [222]NP2.016511VariousMetastaticTargeted therapy60.0CT scan/SMI7NANAYF
Veasey-Rodrigues H et al., 2013 [223]NRCT3.0306159147VariousMetastaticVarious56.0CT scan/SMI1449351YG
Meza-Junco J et al., 2013 [224]NRP24.01169818LiverVariousVarious58.0CT scan/SMI35305NF
Lieffers JR et al., 2012 [225]NRP1.023413599ColorectalVariousSurgery63.0CT scan/SMI915734NG
Mir O et al., 2012 [226]NRP16.018153LiverMetastaticChemotherapy64.0CT scan/SMI9NANANF
Parsons HA et al., 2012 [227]NRCT26.61046539VariousMetastaticVariousNACT scan/SMI533617NG
Parsons HA et al., 2012 [228]NRP26.6481929VariousMetastaticIntra-arterial infusion for hepatocellular carcinoma56.0CT scan/SMI211011NF
van Vledder MG et al., 2012 [229]NRP97.019612076ColorectalMetastaticSurgery64.5CT scan/SMI381127YG
Dalal S et al., 2012 [230]NRCT90.0411823PancreasLocally advancedVarious58.9CT scan/SMI26NANAYF
Antoun S et al., 2010 [231]NRCT6.0806020KidneyMetastaticTargeted therapy59.8CT scan/SMI422013YG
Tan BH et al., 2009 [232]NP42.01115259PancreasVariousPalliative64.4CT scan/SMI623327YG
Prado CM et al., 2009 [233]NP19.255NA55BreastMetastaticTargeted therapy54.8CT scan/SMI14NA14NG
Prado CM et al., 2008 [234]NP39.6250136114VariousVariousNot specified63.9CT scan/SMI382810YF
Y = yes; N = no; RCT = randomized control trial; P = prospective observational study; RP = retrospective observational study with consecutive inclusion; M = male; F = female; NSC = non-small cell; SC = small cell; NA = not available; BIA = bioelectrical impedance analysis; DXA = dual energy X-ray absorptiometry; AMA = arm muscle area; ASM = appendicular skeletal muscle mass; SMI = skeletal muscle index; PMI = psoas muscle index; TPA = total psoas area; AWGS = Asian Working Group on Sarcopenia; EWGOS = European Working Group On Sarcopenia; NOS score: G = good; F = fair; P = poor.
Table
Table 2. Prevalence of sarcopenia among cancer patients.
Table 2. Prevalence of sarcopenia among cancer patients.
Study GroupsPatientsPrevalence
% [95% CI]		p Value for Subgroup DifferencesHeterogeneity
N(%)I2p
Overall 0.11
All studies65,936(100)38.0 [36.0–41.0] 97%<0.01
Excluding studies over the 95% CI (funnel plot)18,935(29)40.5 [39.0–42.0] 66%<0.01
Quality of study (NOS scale) 0.75
Good47,028(71)38.0 [34.0–41.0] 97%<0.01
Fair18,287(28)40.0 [35.0–44.0] 96%<0.01
Poor621(1)40.5 [28.5–54.0] 86.5%<0.01
Year of publication 0.80
2008–20121343(2)40.0 [30.0–50.0] 92%<0.01
2013–201713,411(20)40.0 [34.0–46.0] 96%<0.01
2018–202251,182(78)38.0 [35.0–41.0] 97%<0.01
N° of patients included <0.01
<1004364(7)45.0 [41.0–50.0] 84%<0.01
<100–1999606(14.5)41.0 [36.0–47.0] 95%<0.01
<200–39916,023(24)36.0 [31.0–42.0] 97%<0.01
≥40035,943(54.5)27.0 [22.0–32.0] 99%<0.01
World region 0.26
Asia33,453(51)37.0 [32.0–41.0] 97.5%<0.01
Not Asia32,483(49)40.0 [37.0–43.0] 95%<0.01
Mean or median age (y) at inclusion (n = 47,986) 0.21
<6530,691(64)38.0 [34.0–42.0] 96%<0.01
≥6517,295(36)42.0 [37.0–46.0] 96%<0.01
Sex (n = 46,265) 0.22
Women15,841(34)34.0 [30.0–38.0] 91%<0.01
Men30,424(66)37.0 [34.0–41.0] 96%<0.01
BMI (n = 8627) <0.01
≥30 kg/m22628(30.5)19.0 [13.0–27.0] 89.5%<0.01
<30 kg/m25999(69.5)39.0 [31.0–47.0] 96%<0.01
Cancer site <0.01
Gastric13,513(20.5)24.0 [19.0–29.5] 97.5%<0.01
Breast3517(5)25.0 [17.5–35.0] 82%<0.01
Sarcoma254(0.4)25.0 [20.0–30.5] 0%0.55
Uterus232(0.3)26.0 [21.0–32.0] --
Head and neck3724(6)31.0 [21.0–43.0] 95%<0.01
Ovarian747(1)33.0 [16.0–55.0] 95%<0.01
Lymphoma1130(2)35.0 [29.0–41.5] 75%<0.01
Various14,600(22)35.0 [29.0–41.0] 96%<0.01
Cholangiocarcinoma231(0.3)36.0 [26.0–47.0] 83%<0.01
Melanoma152(0.2)36.0 [20.0–56.0] 91%<0.01
Leukemia474(0.7)36.0 [25.0–49.0] 93%<0.01
Colorectal11,419(17)38.0 [33.0–44.0] 95%<0.01
Anal106(0.2)39.0 [30.0–48.0] --
Bile ducts282(0.4)42.5 [30.0–56.0] 88%<0.01
Non-small cell lung2914(4)43.0 [34.0–51.5] 95%<0.01
Liver2391(4)44.0 [33.0–55.5] 95%<0.01
Myeloma152(0.2)44.0 [18.0–74.0] 95%<0.01
Thyroids180(0.3)49.5 [42.0–57.0] --
Pancreatic3813(6)49.5 [41.5–57.5] 96%<0.01
Kidney356(0.5)50.0 [43.0–57.0] 53%0.07
Esophageal3474(5)50.0 [43.0–57.0] 92%<0.01
Urothelial1163(2)52.0 [39.5–64.0] 94%<0.01
Prostatic985(1.5)60.0 [38.0–79.0] 95%<0.01
Small cell lung149(0.2)79.0 [72.0–85.0] --
Cancer extension <0.01
Various54,269(82)35.0 [32.0–38.0] 97%<0.01
Local2783(4)39.0 [30.0–50.0] 97%<0.01
Locally advanced3186(5)48.0 [37.0–59.0] 96%<0.01
Metastatic5698(9)46.0 [40.0–51.0] 92%<0.01
Treatment modalities <0.01
Not specified918(1)21.0 [12.5–33.0] 91%<0.01
Surgery40,486(61)33.0 [30.0–37.0] 97%<0.01
Targeted therapy634(1)41.0 [32.0–50.0] 81%<0.01
Various17,641(27)41.0 [36.0–45.0] 96%<0.01
Immune therapy909(1)46.0 [38.0–54.5] 80%<0.01
Radiotherapy544(0.8)46.0 [28.0–66.0] 93%<0.01
Chemotherapy4169(6)48.0 [41.0–56.0] 93%<0.01
Exclusive supportive care445(0.7)62.0 [55.0–69.0] 70%<0.01
Intra-arterial infusion for hepatocellular carcinoma190(0.3)68.0 [35.0–90.0] 96.5%<0.01
Definition of sarcopenia <0.01
Consensus algorithm-based
Overall11,013(17)22.0 [19.0–26.0] 93%<0.01
AWGS6996 20.5 [16.0–25.0] 93%<0.01
EWGOS 22462 20.5 [15.5–27.0] 88%<0.01
EWGOS 13086 25.0 [17.0–35.0] 96%<0.01
Muscle mass quantity only
Overall54,923(83)42.0 [39.0–45.0] 96%<0.01
DXA64 25.0 [16.0–37.0] --
BIA1306 30.0 [23.0–38.0] 90%<0.01
CT scan53,553 43.0 [40.0–46.0] 96.5%<0.01
Muscle mass indices (n = 55,304) <0.01
AMA (cm2)951(2)12.0 [10.0–14.0] --
ASM (kg/m2)3261(6)31.0 [24.0–39.0] 95%<0.01
TPA (cm2/m2)2394(4)36.0 [27.0–46.0] 93%<0.01
PMI (cm2/m2)2967(5)36.5 [28.0–46.0] 96.5%<0.01
SMI (cm2/m2)45,731(83)40.0 [37.0–43.0] 97%<0.01
Median cut-off values of CT scan-based SMI for women (n = 14,216) <0.01
<38.5 (cm2/m2)4609(32)25.0 [21.0–29.0] 87%<0.01
≥38.5 (cm2/m2)9607(68)47.0 [40.0–54.0] 92%<0.01
Median cut-off values of CT scan-based SMI for men (n = 20,514) <0.01
<47.3 (cm2/m2)11,584(56)28.0 [24.0–32.0] 95%<0.01
≥47.3 (cm2/m2)8930(44)52.0 [46.0–58.0] 95%<0.01
Bold = grouping data, and significant p value at the threshold of 5%; BIA = bioelectrical impedance analysis; DXA = dual energy X-ray sbsorptiometry; AWGS = Asian Working Group on Sarcopenia; EWGOS = European Working Group On Sarcopenia; AMA = arm muscle area; ASM = appendicular skeletal muscle mass; SMI = skeletal muscle index; PMI = psoas muscle index; TPA = total psoas area.
Table
Table 3. Predictive value of pre-therapeutic sarcopenia on overall survival (OS) among cancer patients.
Table 3. Predictive value of pre-therapeutic sarcopenia on overall survival (OS) among cancer patients.
Study GroupsPatientsRelative Risk [95% CI] for OSp Value for Subgroup DifferencesHeterogeneity
N(%)I2p
Overall 0.37
All studies28,995(100)1.97 [1.79–2.17] 85%<0.01
Excluding studies over the 95% CI (funnel plot)7191(25)1.68 [1.55–1.80] 77%<0.01
Quality of study (NOS) 0.65
Good22,939(79)1.94 [1.73–2.16] 75%<0.01
Fair5803(20)2.10 [1.71–2.58] 90.5%<0.01
Poor253(1)1.40 [0.47–4.20] 77%0.04
Year of publication 0.93
2008–2012598(2)1.85 [1.29–2.65] 54%0.09
2013–20175977(21)1.97 [1.53–2.52] 93%<0.01
2018–202222,420(77)1.99 [1.78–2.22] 75%<0.01
N° of patients included 0.01
<1001718(6)2.24 [1.71–2.92] 87%<0.01
100–1995150(18)2.17 [1.86–2.53] 61%<0.01
200–3998417(29)1.90 [1.57–2.30] 81%<0.01
≥40013,710(47)1.57 [1.35–1.82] 71%<0.01
World region <0.01
Asia10,964(38)2.37 [2.07–2.71] 84%<0.01
Not Asia18,031(62)1.69 [1.48–1.91] 72%<0.01
Mean or median age (y) at inclusion (n = 23,630) 0.09
<6514,384(61)1.87 [1.62–2.16] 75%<0.01
≥659246(39)2.24 [1.93–2.61] 89%<0.01
Cancer site <0.01
Gastric5447(19)1.88 [1.46–2.44] 74%<0.01
Breast0(0)- --
Sarcoma145(0.5)3.42 [0.81–14.4] --
Uterus232(0.8)2.23 [1.18–3.92] --
Head and neck1692(6)2.75 [2.00–3.78] 62%0.03
Ovarian424(1.5)1.64 [0.53–5.06] 82.5%0.02
Lymphoma997(3)1.55 [0.89–2.70] 73%0.02
Various3649(13)1.72 [1.19–2.45] 96%<0.01
Cholangiocarcinoma231(0.8)2.66 [1.85–3.81] 0%0.69
Melanoma0(0)- --
Leukemia178(0.6)3.12 [1.53–6.35] --
Colorectal7252(25)1.58 [1.28–1.95] 67%<0.01
Anal106(0.4)4.50 [1.05–19.2] --
Bile ducts282(1)2.71 [1.87–3.92] 0%0.49
Non-small cell lung1440(5)2.92 [2.01–4.24] 53%0.04
Liver1422(5)2.56 [1.94–3.39] 43%0.07
Myeloma56(0.2)1.96 [0.78–5.00] --
Thyroids0(0)- --
Pancreatic1789(6)1.45 [1.13–1.86] 71%<0.01
Kidney78(0.3)2.63 [1.50–4.61] --
Esophageal1856(6)2.29 [1.77–2.95] 49%0.03
Urothelial835(3)1.87 [1.20–2.89] 51%0.08
Prostatic884(3)1.35 [0.89–2.03] 0%0.52
Small cell lung0(0)- --
Cancer extension 0.40
Various23,842(82)1.86 [1.68–2.07] 72%<0.01
Local1404(5)2.32 [1.71–3.15] 27%0.23
Locally advanced917(3)2.42 [1.50–3.92] 77%<0.01
Metastatic2832(10)2.09 [1.53–2.86] 94%<0.01
Treatment modalities 0.74
Not specified386(1)2.16 [1.49–3.13] 0%0.50
Surgery16,463(57)2.09 [1.84–2.37] 63%<0.01
Targeted therapy78(0.3)2.63 [1.50–4.61] --
Various7798(27)1.85 [1.55–2.20] 77%<0.01
Immune therapy618(2)2.37 [0.92–6.08] 92%<0.01
Radiotherapy516(2)2.91 [1.23–6.90] 77%0.01
Chemotherapy2549(9)1.70 [1.23–2.36] 95%<0.01
Exclusive supportive care445(1.5)1.62 [1.06–2.47] 64%0.10
Intra-arterial infusion for hepatocellular carcinoma142(0.5)2.22 [1.01–4.86] --
Definition of sarcopenia 0.24
Muscle mass quantity only
CT scan25,656(88)1.93 [1.74–2.15] 86%<0.01
BIA347(1)1.77 [1.00–2.13] 35%0.22
DXA64(0.2)2.96 [1.40–6.27] --
Consensus algorithm-based2928(10)2.31 [1.97–2.72] 22%0.25
Muscle mass indices (n = 27,061) <0.01
AMA (cm2)951(3)2.26 [1.69–3.03] --
ASM (kg/m2)1274(5)2.84 [2.01–4.00] 87%<0.01
TPA (cm2/m2)0(0)- --
PMI (cm2/m2)1567(6)2.76 [2.21–3.43] 0%0.63
SMI (cm2/m2)23,269(86)1.85 [1.66–2.07] 75%<0.01
Bold = grouping data, and significant p value at the threshold of 5%; BIA = bioelectrical impedance analysis; DXA = dual energy X-ray absorptiometry; AMA = arm muscle area; ASM = appendicular skeletal muscle mass; SMI = skeletal muscle index; PMI = psoas muscle index; TPA = total psoas area.
Table
Table 4. Predictive value of pre-therapeutic sarcopenia on progression-free survival (PFS) among cancer patients.
Table 4. Predictive value of pre-therapeutic sarcopenia on progression-free survival (PFS) among cancer patients.
Study GroupsPatientsRelative Risk [95% CI] for PFSp Value for Subgroup DifferencesHeterogeneity
N(%)I2p
Overall 0.23
All studies6546(100)1.76 [1.44–2.16] 85%<0.01
Excluding studies over the 95% CI (funnel plot)4008(61)1.35 [1.19–1.52] 80%<0.01
Quality of study (NOS) 0.15
Good5055(77)1.83 [1.51–2.21] 75%<0.01
Fair1345(20.5)1.68 [0.89–3.15] 94%<0.01
Poor146(2.5)0.92 [0.48–1.78] --
Year of publication 0.93
2008–2012251(4)1.89 [1.34–2.64] 0%0.98
2013–2017693(10)1.83 [1.07–3.13] 83%<0.01
2018–20225602(86)1.75 [1.37–2.24] 87%<0.01
N° of patients included 0.73
<100489(7.5)2.22 [1.24–3.97] <0.01
100–1991863(28.5)1.81 [1.35–2.42] <0.01
200–3991922(29)1.49 [0.98–2.24] <0.01
≥4002272(35)1.79 [0.97–3.29] <0.01
World region <0.01
Asia2307(35)2.38 [1.81–3.13] 80%<0.01
Not Asia4239(65)1.42 [1.12–1.81] 75.5%<0.01
Mean or median age (y) at inclusion (n = 5891) 0.78
<653186(54)1.75 [1.28–2.40] 91%<0.01
≥652705(46)1.85 [1.43–2.39] 60%0.01
Cancer site <0.01
Gastric726(11)1.68 [0.43–6.50] 96%<0.01
Breast55(0.8)1.90 [1.03–3.50] --
Sarcoma109(2)4.60 [3.53–6.00] --
Uterus0(0)- --
Head and neck243(3.5)2.45 [1.58–3.78] --
Ovarian128(2)2.64 [1.23–5.64] --
Lymphoma1040(16)1.95 [1.19–3.20] 73%0.01
Various349(5)0.70 [0.54–0.93] 0%0.92
Cholangiocarcinoma0(0)- --
Melanoma0(0)- --
Leukemia0(0)- --
Colorectal2512(38)1.35 [1.05–1.74] 55%0.03
Anal0(0)- --
Bile ducts207(3)2.14 [1.46–3.13] --
Non-small cell lung534(8)2.43 [1.90–3.12] 0%0.47
Liver0(0)- --
Myeloma0(0)- --
Thyroids0(0)- --
Pancreatic0(0)- --
Kidney78(1)3.18 [1.85–5.47] --
Esophageal163(2.5)1.24 [0.71–2.17] --
Urothelial146(2)0.92 [0.47–1.78] --
Prostatic256(4)2.23 [0.69–7.18] 71%0.06
Small cell lung0(0)- --
Cancer extension 0.13
Various4469(68)1.62 [1.26–2.08] 81%<0.01
Local315(5)2.32 [1.62–3.32] --
Locally advanced47(1)8.11 [1.61–41.0] --
Metastatic1715(26)1.84 [1.28–2.64] 89%<0.01
Treatment modalities 0.11
Not specified0(0)- --
Surgery3296(50)1.73 [1.28–2.35] 81%<0.01
Targeted therapy242(4)3.21 [1.94–5.33] 73%0.03
Various2024(31)1.45 [1.10–1.91] 62%<0.01
Immune therapy480(7)2.11 [0.84–5.29] 90%<0.01
Radiotherapy0(0)- --
Chemotherapy504(8)1.74 [0.83–3.64] 87%<0.01
Exclusive supportive care0(0)- --
Intra-arterial infusion for hepatocellular carcinoma0(0)- --
Definition of sarcopenia <0.01
Muscle mass quantity only
CT scan5688(87)1.70 [1.38–2.10] 84%<0.01
BIA163(2.5)1.24 [0.71–2.17] --
DXA0(0)- --
Consensus algorithm-based695(10.5)3.59 [2.17–5.92] 12%0.29
Muscle mass indices (n = 6383) <0.01
AMA (cm2)0(0)- --
ASM (kg/m2)47(1)8.11 [1.61–40.9] --
TPA (cm2/m2)0(0)- --
PMI (cm2/m2)621(9.5)3.05 [2.01–4.62] 72%0.01
SMI (cm2/m2)5715(87)1.61 [1.30–1.99] 81%<0.01
Bold = grouping data, and significant p value at the threshold of 5%; BIA = bioelectrical impedance analysis; DXA = dual energy X-ray absorptiometry; AMA = arm muscle area; ASM = appendicular skeletal muscle mass; SMI = skeletal muscle index; PMI = psoas muscle index; TPA = total psoas area.
Table
Table 5. Predictive value of pre-therapeutic sarcopenia on severe post-operative complications (POC) among cancer patients.
Table 5. Predictive value of pre-therapeutic sarcopenia on severe post-operative complications (POC) among cancer patients.
Study GroupsPatientsRelative Risk [95% CI] for POCp Value for Subgroup DifferencesHeterogeneity
N(%)I2p
Overall 0.02
All studies17,172(100)2.70 [2.33–3.12] 72%<0.01
Excluding studies over the 95% CI (funnel plot)3633(21)2.22 [1.84–2.68] 64%<0.01
Quality of study (NOS) 0.34
Good14,555(85)2.75 [2.34–3.24] 75%<0.01
Fair2411(14)2.67 [1.83–3.91] 60%<0.01
Poor206(1)1.87 [1.16–3.04] 0%0.51
Year of publication 0.02
2008–20120(0)-
2013–20176355(37)1.39 [1.18–1.63] 48.5%<0.01
2018–202210,817(63)1.91 [1.53–2.38] 81%<0.01
N° of patients included 0.04
<100806(5)1.78 [1.09–2.92] 72%<0.01
100–1992425(14)1.30 [1.08–1.56] 41%0.04
200–3995407(31)1.95 [1.42–2.68] 85%<0.01
≥4008534(50)1.87 [1.47–2.39] 58%<0.01
World region <0.01
Asia10,092(59)2.02 [1.60–2.55] 81%<0.01
Not Asia7080(41)1.38 [1.20–1.60] 57%<0.01
Mean or median age (y) at inclusion (n = 13,209) 0.39
<656572(50)1.91 [1.49–2.44] 64%<0.01
≥656637(50)1.64 [1.28–2.10] 78%<0.01
Cancer site <0.01
Gastric6856(40)3.09 [2.42–3.93] 43%0.02
Breast0(0)- --
Sarcoma145(1)1.78 [1.22–2.59] --
Uterus0(0)- --
Head and neck0(0)- --
Ovarian0(0)- --
Lymphoma0(0)- --
Various1895(11)3.95 [1.97–7.95] 71%<0.01
Cholangiocarcinoma110(1)2.44 [2.08–2.87] 0%0.46
Melanoma0(0)- --
Leukemia0(0)- --
Colorectal0(0)- --
Anal0(0)- --
Bile ducts0(0)- --
Non-small cell lung808(5)3.66 [1.12–11.9] 93%<0.01
Liver385(2)2.47 [0.90–6.77] 85%<0.01
Myeloma0(0)- --
Thyroids0(0)- --
Pancreatic1629(9)1.86 [1.26–2.75] 51%0.07
Kidney0(0)- --
Esophageal828(5)3.17 [1.82–5.52] 82%<0.01
Urothelial473(3)1.68 [1.33–2.11] 0%0.47
Prostatic698(4)4.50 [1.76–11.5] --
Small cell lung0(0)- --
Cancer extension 0.06
Various14,436(84)1.76 [1.46–2.11] 74%<0.01
Local999(6)2.35 [1.14–4.86] 80%<0.01
Locally advanced955(6)1.35 [0.85–2.14] 57%0.05
Metastatic782(4)1.30 [1.09–1.54] 0%0.80
Treatment modalities 0.04
Not specified0(0)- --
Surgery16,325(95)1.77 [1.50–2.09] 76%<0.01
Targeted therapy0(0)- --
Various847(5)1.26 [0.95–1.67] 43%0.10
Immune therapy0(0)- --
Radiotherapy0(0)- --
Chemotherapy0(0)- --
Exclusive supportive care0(0)- --
Intra-arterial infusion for hepatocellular carcinoma0(0)- --
Definition of sarcopenia 0.03
Muscle mass quantity only
CT scan11,212(65)2.39 [2.01–2.83] 75%<0.01
BIA626(4)3.16 [1.74–5.76] 65%0.02
DXA0(0)- --
Consensus algorithms5334(31)3.62 [2.79–4.69] 36%0.07
Muscle mass indices (n = 16,413) 0.06
AMA (cm2)0(0)- --
ASM (kg/m2)834(5)3.26 [1.80–5.90] 72%<0.01
TPA (cm2/m2)2089(13)1.60 [1.09–2.35] 72%0.06
PMI (cm2/m2)719(4)2.41 [0.99–5.91] 93%<0.01
SMI (cm2/m2)12,771(78)1.48 [1.27–1.71] 61%<0.01
Bold = grouping data, and significant p value at the threshold of 5%; BIA = bioelectrical impedance analysis; DXA = dual energy X-ray absorptiometry; AMA = arm muscle area; ASM = appendicular skeletal muscle mass; SMI = skeletal muscle index; PMI = psoas muscle index; TPA = total psoas area.
Table
Table 6. Predictive value of pre-therapeutic sarcopenia on severe treatment-related toxicities and/or dose-limiting toxicities (TOX) among cancer patients.
Table 6. Predictive value of pre-therapeutic sarcopenia on severe treatment-related toxicities and/or dose-limiting toxicities (TOX) among cancer patients.
Study GroupsPatientsRelative Risk [95% CI] for TOXp Value for Subgroup DifferencesHeterogeneity
N(%)I2p
Overall 0.49
All studies2980(100)1.47 [1.17–1.84] 71%<0.01
Excluding studies over the 95% CI (funnel plot)760(25.5)1.31 [1.11–1.57] 62%<0.01
Quality of study (NOS) 0.02
Good2356(79)1.34 [1.01–1.77] 67%<0.01
Fair517(17)1.78 [1.43–2.21] 24%0.25
Poor107(4)2.72 [1.76–4.21] --
Year of publication 0.38
2008–201255(2)2.56 [1.14–5.78] --
2013–2017424(14)1.56 [0.94–2.60] 70%<0.01
2018–20222501(84)1.40 [1.07–1.84] 73%<0.01
N° of patients included 0.03
<100851(28.5)1.39 [1.01–1.91] 67%<0.01
100–199702(23.5)1.92 [1.26–2.93] 68.5%<0.01
200–399219(7.5)0.98 [0.78–1.25] --
≥4001208(40.5)1.42 [0.63–3.21] 88%<0.01
World region 0.80
Asia1551(52)1.43 [1.04–1.98] 76.5%<0.01
Not Asia1429(48)1.52 [1.08–2.13] 65%<0.01
Mean or median age (y) at inclusion (n = 1772) 0.44
<651459(82)1.57 [1.18–2.11] 77%<0.01
≥65313(18)1.26 [0.79–2.02] 0%0.46
Cancer site <0.01
Gastric458(15)0.96 [0.72–1.29] --
Breast137(4.5)2.93 [1.82–4.73] 0%0.69
Sarcoma0(0)- --
Uterus0(0)- --
Head and neck862(29)2.47 [1.65–3.69] 0%0.40
Ovarian0(0)- --
Lymphoma0(0)- --
Various89(3)
Cholangiocarcinoma0(0)- --
Melanoma68(2)1.20 [0.40–3.56] --
Leukemia0(0)- --
Colorectal244(8)1.00 [0.80–1.26] 0%0.56
Anal0(0)- --
Bile ducts0(0)- --
Non-small cell lung0(0)- --
Liver0(0)- --
Myeloma0(0)- --
Thyroids180(6)1.20 [0.89–1.61] --
Pancreatic281(9)1.66 [1.13–2.42] 0%0.47
Kidney139(5)1.98 [0.99–3.98] 0%0.71
Esophageal494(16.5)1.17 [0.66–2.08] 86%<0.01
Urothelial28(1)0.83 [0.21–3.29] --
Prostatic0(0)- --
Small cell lung0(0)- --
Cancer extension <0.01
Various2216(74)1.57 [1.16–2.12] 77%<0.01
Local0(0)- --
Locally advanced228(8)0.69 [0.47–1.02] 0%0.62
Metastatic536(18)1.57 [1.18–2.09] 28%0.22
Treatment modalities 0.19
Not specified0(0)- --
Surgery0(0)- --
Targeted therapy374(12.5)1.63 [1.05–2.54] 30%0.23
Various2040(68.5)1.22 [0.85–1.74] 79%<0.01
Immune therapy68(2)1.20 [0.40–3.56] --
Radiotherapy28(1)0.83 [0.21–3.29] --
Chemotherapy470(16)1.98 [1.55–2.54] 32%0.20
Exclusive supportive care0(0)- --
Intra-arterial infusion for hepatocellular carcinoma0(0)- --
Definition of sarcopenia <0.01
Muscle mass quantity only
CT scan2886(97)1.53 [1.22–1.93] 70%<0.01
BIA94(3)0.82 [0.56–1.21] --
DXA0(0)- --
Consensus algorithm-based0(0)- --
Muscle mass indices (n = 2136) -
AMA (cm2)0(0)- --
ASM (kg/m2)0(0)- --
TPA (cm2/m2)0(0)- --
PMI (cm2/m2)0(0)- --
SMI (cm2/m2)2136(100)1.49 [1.18–1.90] 69%<0.01
Bold = grouping data, and significant p value at the threshold of 5%; BIA = bioelectrical impedance analysis; DXA = dual energy X-ray absorptiometry; AMA = arm muscle area; ASM = appendicular skeletal muscle mass; SMI = skeletal muscle index; PMI = psoas muscle index; TPA = total psoas area.
Table
Table 7. Predictive value of pre-therapeutic sarcopenia on severe treatment-related toxicities and/or dose-limiting toxicities (TOX) among cancer patients.
Table 7. Predictive value of pre-therapeutic sarcopenia on severe treatment-related toxicities and/or dose-limiting toxicities (TOX) among cancer patients.
Study GroupsPatientsRelative Risk [95% CI] for NIp Value for Subgroup DifferencesHeterogeneity
N(%)I2p
Overall <0.01
All studies6246(100)1.76 [1.41–2.22] 58%<0.01
Excluding studies over the 95% CI (funnel plot)864(14)1.15 [0.87–1.52]
Quality of study (NOS) 0.09
Good4380(70)1.90 [1.45–2.49] 52%0.01
Fair1783(28.5)1.64 [1.02–2.65] 69%<0.01
Poor83(1.5)0.83 [0.42–1.65] --
Year of publication 0.63
2008–2012234(4)1.83 [1.03–3.25] --
2013–20172128(34)1.50 [1.20–1.87] 30%0.17
2018–20223884(62)1.87 [1.56–2.23] 72%<0.01
N° of patients included <0.01
<100132(2)0.76 [0.44–1.32] 0%0.71
100–1991059(17)1.77 [1.22–2.56] 34%0.17
200–3992385(38)1.85 [1.23–2.80] 69%<0.01
≥4002670(43)2.26 [1.66–3.07] 6%0.36
World region 0.33
Asia4817(77)1.91 [1.42–2.57] 66%<0.01
Not Asia1429(33)1.53 [1.11–2.12] 36%0.14
Mean or median age (y) at inclusion (n = 5047) <0.01
<652126(42)2.60 [1.93–3.52] 41%0.10
≥652921(58)1.36 [1.01–1.83] 45%0.06
Cancer site <0.01
Gastric3342(53.5)2.55 [1.88–3.46] 29%0.21
Breast0(0)- --
Sarcoma0(0)- --
Uterus0(0)- --
Head and neck0(0)- --
Ovarian0(0)- --
Lymphoma0(0)- --
Various49(1)0.67 [0.27–1.66] --
Cholangiocarcinoma0(0)- --
Melanoma0(0)- --
Leukemia0(0)- --
Colorectal1033(16.5)1.80 [1.31–2.48] 14%0.33
Anal0(0)- --
Bile-ducts0(0)- --
Non-small cell lung0(0)- --
Liver0(0)- --
Myeloma0(0)- --
Thyroids0(0)- --
Pancreatic202(3)0.69 [0.32–1.49] --
Kidney0(0)0 --
Esophageal1620(26)1.49 [1.02–2.18] 61%0.01
Urothelial0(0)- --
Prostatic0(0)- --
Small cell lung0(0)- --
Cancer extension 0.57
Various6073(97)1.75 [1.38–2.22] 60%<0.01
Local173(3)2.13 [1.11–4.10] --
Locally-advanced0(0)- --
Metastatic0(0)- --
Treatment modalities 0.12
Not specified0(0)- --
Surgery6033(97)1.84 [1.45–2.32] 58%<0.01
Targeted therapy0(0)- --
Various213(3)1.05 [0.54–2.06] 19%0.27
Immune-therapy0(0)- --
Radiotherapy0(0)- --
Chemotherapy0(0)- --
Exclusive supportive care0(0)- --
Intra-arterial infusion for hepatocellular carcinoma0(0)- --
Definition of sarcopenia 0.03
-Muscle mass quantity only
CT-scan2487(40)1.59 [1.28–1.97] 0%0.45
BIA423(7)1.12 [0.62–2.02] 59%0.06
DXA0(0)- --
-Consensus algorithm-based3336(53)2.49 [1.75–3.54] 64%<0.01
Muscle mass indices (n = 5782) 0.92
AMA (cm2)951(16)1.86 [1.10–3.16] --
ASM (kg/m2)344(6)1.34 [0.44–4.06] 88%<0.01
TPA (cm2/m2)0(0)- --
PMI (cm2/m2)567(10)1.56 [0.73–3.30] --
SMI (cm2/m2)3920(68)1.85 [1.41–2.43] 53%0.01
Bold = grouping data, and significant p value at the threshold of 5%; BIA = bioelectrical impedance analysis; DXA = Dual Energy X-Ray Absorptiometry; AMA = arm muscle area; ASM = appendicular skeletal muscle mass; SMI = skeletal muscle index; PMI = psoas muscle index; TPA = total psoas area.
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MDPI and ACS Style

Couderc, A.-L.; Liuu, E.; Boudou-Rouquette, P.; Poisson, J.; Frelaut, M.; Montégut, C.; Mebarki, S.; Geiss, R.; ap Thomas, Z.; Noret, A.; et al. Pre-Therapeutic Sarcopenia among Cancer Patients: An Up-to-Date Meta-Analysis of Prevalence and Predictive Value during Cancer Treatment. Nutrients 2023, 15, 1193. https://doi.org/10.3390/nu15051193

AMA Style

Couderc A-L, Liuu E, Boudou-Rouquette P, Poisson J, Frelaut M, Montégut C, Mebarki S, Geiss R, ap Thomas Z, Noret A, et al. Pre-Therapeutic Sarcopenia among Cancer Patients: An Up-to-Date Meta-Analysis of Prevalence and Predictive Value during Cancer Treatment. Nutrients. 2023; 15(5):1193. https://doi.org/10.3390/nu15051193

Chicago/Turabian Style

Couderc, Anne-Laure, Evelyne Liuu, Pascaline Boudou-Rouquette, Johanne Poisson, Maxime Frelaut, Coline Montégut, Soraya Mebarki, Romain Geiss, Zoé ap Thomas, Aurélien Noret, and et al. 2023. "Pre-Therapeutic Sarcopenia among Cancer Patients: An Up-to-Date Meta-Analysis of Prevalence and Predictive Value during Cancer Treatment" Nutrients 15, no. 5: 1193. https://doi.org/10.3390/nu15051193

APA Style

Couderc, A. -L., Liuu, E., Boudou-Rouquette, P., Poisson, J., Frelaut, M., Montégut, C., Mebarki, S., Geiss, R., ap Thomas, Z., Noret, A., Pierro, M., Baldini, C., Paillaud, E., & Pamoukdjian, F. (2023). Pre-Therapeutic Sarcopenia among Cancer Patients: An Up-to-Date Meta-Analysis of Prevalence and Predictive Value during Cancer Treatment. Nutrients, 15(5), 1193. https://doi.org/10.3390/nu15051193

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