A simpler screening tool for sarcopenia in surgical patients

Onuma Chaiwat; Mingkwan Wongyingsinn; Weerasak Muangpaisan; Chalobol Chalermsri; Arunotai Siriussawakul; Pornpoj Pramyothin; Poungkaew Thitisakulchai; Panita Limpawattana; Chayanan Thanakiattiwibun

doi:10.1371/journal.pone.0257672

. 2021 Sep 23;16(9):e0257672. doi: 10.1371/journal.pone.0257672

A simpler screening tool for sarcopenia in surgical patients

Onuma Chaiwat ^1,^2,^*, Mingkwan Wongyingsinn ¹, Weerasak Muangpaisan ^2,³, Chalobol Chalermsri ³, Arunotai Siriussawakul ^1,², Pornpoj Pramyothin ⁴, Poungkaew Thitisakulchai ⁵, Panita Limpawattana ⁶, Chayanan Thanakiattiwibun ²

Editor: Joao Felipe Mota⁷

PMCID: PMC8460047 PMID: 34555077

Abstract

Background

Sarcopenia is defined as decreased skeletal muscle mass and muscle functions (strength and physical performance). Muscle mass is measured by specific methods, such as bioelectrical impedance analysis and dual-energy X-ray absorptiometry. However, the devices used for these methods are costly and are usually not portable. A simple tool to screen for sarcopenia without measuring muscle mass might be practical, especially in developing countries. The aim of this study was to design a simple screening tool and to validate its performance in screening for sarcopenia in older adult cancer patients scheduled for elective surgery.

Methods

Cancer surgical patients aged >60 years were enrolled. Their nutritional statuses were evaluated using the Mini Nutrition Assessment-Short Form. Sarcopenia was assessed using Asian Working Group for Sarcopenia (AWGS) criteria. Appendicular skeletal muscle mass was measured by bioelectrical impedance analysis. Four screening formulas with differing combinations of factors (muscle strength, physical performance, and nutritional status) were assessed. The validities of the formulas, compared with the AWGS definition, are presented as sensitivity, specificity, accuracy, and area under a receiver operating characteristic curve.

Results

Of 251 enrolled surgical patients, 84 (34%) were diagnosed with sarcopenia. Malnutrition (odds ratio [OR]: 2.89, 95% CI: 1.40–5.93); underweight status (OR: 2.80, 95% CI: 1.06–7.43); and age increments of 5 years (OR: 1.78, 95% CI: 1.41–2.24) were independent predictors of preoperative sarcopenia. The combination of low muscle strength and/or abnormal physical performance, plus malnutrition/risk of malnutrition had the highest sensitivity, specificity, and accuracy (81.0%, 78.4%, and 79.3%, respectively). This screening formula estimated the probability of sarcopenia with a positive predictive value of 65.4% and a negative predictive value of 89.1%.

Conclusion

Sarcopenia screening can be performed using a simple tool. The combination of low muscle strength and/or abnormal physical performance, plus malnutrition/risk of malnutrition, has the highest screening performance.

Background

According to the United States Census Bureau, 20% of Americans are predicted to be aged greater than 65 years in 2030, and 50% of them will require an operation [1]. In the case of Thailand, it is projected that 26.6% of the population will be aged over 60 years in 2030 [2]. Aging is associated with an increasing prevalence of frailty, comorbidities, a decline in functional reserve, and sarcopenia. Sarcopenia has been repeatedly demonstrated to be one of the strongest predictors of both short- and long-term outcomes following complicated surgical procedures [3]. Even though surgery is the most effective cancer therapy, complication rates and mortality increase among older adult patients, and this can lessen the advantage of oncological therapy [4]. Different definitions of sarcopenia have been utilized by research groups around the world [5–11], such as the European Working Group on Sarcopenia in Older People (EWGSOP) in 2010, the Asian Working Group for Sarcopenia (AWGS) in 2014, and the Japan Society of Hepatology (JSH) in 2016. In essence, each definition proposed to date defines sarcopenia as a state of decreased skeletal muscle mass and muscle function. Muscle function can be divided into those that require both muscle strength and physical performance, or only one of those elements [12]. However, skeletal muscle mass is mainly used as the core element of all definitions. In early 2018, the EWGSOP met again (EWGSOP2) to revise the definition and diagnosis of sarcopenia. The updated EWGSOP2 consensus targeted low muscle strength as the first key component of sarcopenia, confirmed sarcopenia diagnoses by low muscle quantity and/or quality, and identified poor physical performance as indicative of severe sarcopenia [13]. The recently updated 2019 AWGS consensus contains revisions to the diagnostic algorithm, the protocols, and some criteria, including the cutoff values for low muscle strength and low physical performance. Nevertheless, skeletal muscle strength and mass remain foundational to a definitive clinical diagnosis of sarcopenia [14].

As regards the assessment of muscle mass for a diagnosis of sarcopenia, muscle mass is commonly assessed by bioelectrical impedance analysis (BIA) or dual-energy X-ray absorptiometry (DXA) [15]. BIA is a practical and portable method that does not expose a patient to any radiological harm [16]. Although the use of analyzers and absorptiometers were the main methods previously recommended for the assessment of body composition [17], both devices have some limitations in terms of their accessibility and cost [18]. A recent study demonstrated that the use of anthropometric data, such as body mass index (BMI), was an indirect means of measuring body composition that produced results comparable with those obtained with DXA [17]. Malnutrition in hospitalized patients, especially cancer patients, was documented with a prevalence up to 50% [19]. Malnourished surgical patients were reported to have a postoperative morbidity rate as high as 33%, with outcomes that included poor wound healing, increased postoperative infection, overgrowth of bacteria in the gastrointestinal tract, delayed return of recovery function, and prolonged hospital stay [20–24]. Since malnutrition and malignancy are factors contributing to the development of sarcopenia [13], a simple tool to screen for sarcopenia in patients who have cancer might be possible by including malnutrition and an underweight status as screening factors.

In addition, several screening tools for sarcopenia have been introduced. The EWGSOP2 recommends the use of the SARC-F questionnaire to elicit self-reported signs and symptoms that are characteristic of sarcopenia [13]. Calf circumference was incorporated in SARc-CalF as an additional parameter to enable indirect measuring of muscle mass [25, 26]. The Ishii model was also developed to estimate the probability of sarcopenia in older community-dwelling adults [27]. However, no study has reported the superiority of any tool over the others because no head-to-head comparison study has been performed.

The aims of this study were to design a simple screening tool and to validate its performance in screening for sarcopenia in older adult cancer patients prior to undergoing elective surgery.

Materials and methods

Design

This prospective longitudinal study was conducted at Siriraj Pre-anesthesia Assessment Center (SiPAC), Department of Anesthesiology, Faculty of Medicine Siriraj Hospital, Mahidol University between April 2017 and December 2017. Siriraj Hospital is a 2300-bed, university-based, national tertiary-referral hospital in Bangkok, Thailand. All patients or their legal guardians provided informed consent in writing. The Siriraj Institutional Review Board approved the study protocol (SIRB COA no. Si 101/2017). The study was registered with the Thai Clinical Trials Registry (TCTR20181223002).

Study population

The study population comprised cancer patients aged older than 60 years who presented at SiPAC prior to undergoing elective surgery. Individuals unable to walk or stand unaided were excluded because the BIA device could measure muscle mass only while patients were in the standing position. Patients were also excluded if they had one or more of the following: limitations revealed by BIA; a pacemaker; the use of a medication, herb, or hormones that affect muscle mass and strength (eg, estrogen, testosterone, eltroxin, and steroid); and alcohol consumption or strenuous exercise during the 12 hours preceding the scheduled BIA. Patients meeting the selection criteria were invited to participate. After providing written informed consent, the enrolled patients underwent preoperative nutritional screening and sarcopenia assessment.

Measurement instruments and data collection

Preoperative patient characteristic data were collected. Details of the following were recorded: gender, age, body weight, American Society of Anesthesiologists (ASA) physical status, underlying medical problems, current medications, smoking status, alcohol consumption status, surgical services, diagnosis, operation, and preoperative preparation.

Preoperative nutritional screening was performed using the Mini Nutritional Assessment–Short Form (MNA-SF). The items examined were reduction in dietary intake and weight loss during the preceding 3 months, BMI, mobility, psychological stress or acute disease during the preceding 3 months, and neuropsychological problems [28, 29]. The maximum score was 14 points. Nutritional status was reported as “normal” (12–14 points), “at risk of malnutrition” (8–11 points), and “malnutrition” (0–7 points).

Assessment of sarcopenia was performed by measuring (1) the appendicular skeletal muscle mass, with a BIA device (Tanita MC-780U Multi Frequency Segmental Body Composition Analyzer; Tanita Corporation, Tokyo, Japan); (2) muscle grip strength of the dominant hand at maximum strength, using a handgrip dynamometer (TKK 5401 Grip D; Takei Scientific Instruments Co., Ltd., Niigata, Japan); and (3) physical performance, using the 6-meter walk test [5, 30]. For the walk test, participants stood with their feet behind a starting line, and started walking while following the examiner’s instructions. Timing started with the first step and stopped when the patient’s first foot completely crossed the 6-meter line. The AWGS recommends the following cutoff values for sarcopenia diagnoses: low handgrip strength: <26 kg for men, and <18 kg for women; and low physical performance: gait speed <0.8 m/s [9]. For muscle mass measurement in the Thai population, the Thai National Guideline for the Management of Geriatric Syndromes, Frailty and Sarcopenia defines low muscle mass as <7.9 kg/m² in men and <6.0 kg/m² in women [31]. A flowchart of the malnutrition and sarcopenia screening is presented in Fig 1.

A diagnosis of sarcopenia was based on documented low muscle mass plus low muscle strength or low physical performance [30]. Patients with low muscle mass, low muscle strength, and low physical performance were classed as having severe sarcopenia [32].

Outcome measures were scores for the Barthel Index of Activities of Daily Living at 3 months and 1 year after sarcopenia screening; any infections in the hospital; length of hospital stay; hospital mortality; and mortality at 3 months and 1 year after sarcopenia screening.

Design of a simple tool for sarcopenia diagnosis

Four formulas for the diagnosis of sarcopenia were developed. They used differing combinations (C1, C2, C3, and C4) of factors deemed to be relevant to the diagnosis of sarcopenia related to cancer (Table 1). The factors were “muscle strength”, “physical performance”, “risk of malnutrition”, “malnutrition”, and “underweight BMI”. Muscle mass was not used as a factor. Formula 1 used the combination of low muscle strength and abnormal physical performance (C1). Formula 2 used low muscle strength; abnormal physical performance; and malnutrition/risk of malnutrition (C2). Formula 3 used low muscle strength and/or abnormal physical performance, plus malnutrition/risk of malnutrition (C3). Formula 4 used low muscle strength and/or abnormal physical performance, plus underweight BMI (C4). The 2014 AWGS criteria [9] and the updated 2019 AWGS [14] criteria were used as gold standards for the sarcopenia diagnoses. The EWGSOP2 criteria were then compared to both AWGS versions.

Table 1. Combinations used to diagnose sarcopenia.

	Muscle	Muscle		Physical		Malnutrition/		BMI
	mass	strength		performance		Risk of malnutrition		BMI
AWGS	↓	↓	and/or	↓		–		–
EWGSOP2	↓	↓		–		–		–
C1	–	↓	and	↓		–		–
C2	–	↓	and	↓	and	↓		–
C3	–	↓	and/or	↓	and	↓		–
C4	–	↓	and/or	↓		–	and	↓

Open in a new tab

Abbreviations: AWGS, Asian Working Group for Sarcopenia (low muscle mass, and low muscle strength and/or low physical performance); BMI, body mass index; C1, combination of muscle strength and physical performance; C2, combination of muscle strength, physical performance, and malnutrition/risk of malnutrition; C3, combination of muscle strength and/or physical performance, plus malnutrition/risk of malnutrition; C4, combination of muscle strength and/or physical performance, plus body mass index; EWGSOP2, European Working Group on Sarcopenia in Older People 2 (low muscle mass and low muscle strength).

Statistical analysis

The sample size estimate was based on a reported 30% prevalence of sarcopenia among community-dwelling, older adult Thais [33]. Using a 6% error, a minimum sample size of 225 cases was calculated. To compensate for a possible 10% dropout rate, the size was increased to 250.

Demographic and clinical variables are summarized using descriptive statistics. Continuous variables are described as mean and standard deviation (SD) or median and interquartile range (IQR), depending on the data distribution. Normality was checked using a histogram and the Kolmogorov–Smirnov test. Categorical variables are described as frequency and percentage. The prevalences of sarcopenia and malnutrition are presented as percentage. Comparisons between the sarcopenia and non-sarcopenia groups were performed using the independent t-test or Mann–Whitney U test for continuous variables, and the chi-squared test or Fisher’s exact test for categorical variables. Factors associated with sarcopenia were identified using logistic regression. The risk factors with a univariable P value less than 0.2 were entered into multiple logistic regression. They were gender, age, BMI, ASA status, diabetes mellitus (DM), hypertension, dyslipidemia (DLP), chronic kidney disease/end-stage renal disease (CKD/ESRD), current smoker, alcohol consumption, preoperative Barthel Index score <70, MNA-SF, waiting time for surgery, and infection. With those factors, a multivariate logistic regression analysis with enter elimination was utilized to appraise the independent variables associated with preoperative sarcopenia. The validities of the 4 formulas for diagnosis of sarcopenia were assessed relative to the AWGS definition. The diagnostic performances were evaluated in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), negative likelihood ratio (LR-), accuracy, and area under a receiver operating characteristic curve (AUROC). Statistical analyses were performed using PASW Statistics for Windows (version 18.0; SPSS Inc., Chicago, IL, USA) (S1 File).

Results

Diagnosis of sarcopenia

In all, 3816 patients presented at SiPAC between April 2017 and December 2017, with 840 (22.0%) being diagnosed with cancer. Of that cancer group, 529 patients (62.9%) were aged greater than 60 years. Two hundred and seventy-eight (278) patients were excluded because they declined to participate (56%) or were unable to walk (44%). The remaining 251 surgical patients were enrolled. Eighty-four (34%) were diagnosed with sarcopenia as per the AWGS criteria. Fig 1 presents a flowchart of the malnutrition and sarcopenia screening process. Eighty-four subjects (34%) had an abnormal walking speed, and another 63 (25%) had an abnormal grip strength. Those 147 patients were then subjected to BIA. Of those, only 84 demonstrated a muscle mass below the recommended cutoff. This gave a sarcopenia prevalence of 34%. Based on the EWGSOP conceptual stages of sarcopenia [5], 40% (34/84 patients) of our sarcopenic patients were categorized as having severe sarcopenia. The prevalence of sarcopenia increased with advancing age, reaching 70% in the patients aged over 80 years. Eleven patients (13%) with preoperative sarcopenia experienced a change in their treatment plan; 82% (9/11 patients) were receiving palliative care; and 18% (2/11 patients) were receiving radiation therapy. In the non-sarcopenia group, only 5 patients (3%) experienced a change in their treatment plan; 80% (4/5 patients) were undergoing chemotherapy; and 20% (1/5 patients) was receiving palliative care. The remaining 235 patients were included in the outcome measurement analysis.

Our analysis revealed that 123 patients (49%) were at risk for malnutrition, while 28 (11%) had malnutrition. Among the 84 sarcopenic patients, 60% were at risk for malnutrition, and 21% had malnutrition.

Factors associated with sarcopenia

The demographic, anthropometric, clinical, and surgical characteristics of the study patients are detailed in Table 2. Relative to the non-sarcopenic patients, the sarcopenic patients were significantly older, had a higher proportion who were underweight, and a lower proportion who were overweight or obese. There was no statistically significant difference in the Charlson Comorbidity Index of the groups; however, the sarcopenic group had significantly fewer patients with DM and DLP. A significantly higher percentage of patients with sarcopenia demonstrated a moderate to severe disability or malnutrition before surgery (Table 2). There was no significant difference between the groups in terms of choice of anesthesia, duration of anesthesia, or total blood loss. The multivariate analysis (Table 3) revealed that the independent predictors of preoperative sarcopenia were malnutrition (odds ratio [OR]: 2.89, 95% confidence interval [CI]: 1.40–5.93); an underweight status (OR: 2.80, 95% CI: 1.06–7.43); and age increments of 5 years (OR: 1.78, 95% CI: 1.41–2.24). Being overweight was found to be a protective factor against preoperative sarcopenia (OR: 0.19, 95% CI: 0.08–0.47).

Table 2. Demographic, clinical, and surgical characteristics and outcomes.

Characteristics	All patients	Non-sarcopenic	Sarcopenic	P value
Characteristics	(n = 251)	(n = 167)	(n = 84)	P value
Male gender	145 (57.8%)	90 (53.9%)	55 (65.5%)	0.104
Age (years)	71.6±7.6	69.6±6.3	75.5±8.3	<0.001
BMI (kg/m²)	23.4±4.4	24.8±4.3	20.6±2.9	<0.001
BMI category:				<0.001
Underweight (<18.5)	29 (11.6%)	9 (5.4%)	20 (23.8%)
Normal weight (18.5–24.9)	138 (54.9%)	82 (49.1%)	56 (66.7%)
Overweight (25.0–29.9)	69 (27.5%)	61 (36.5%)	8 (9.5%)
Obesity (≥30.0)	15 (5.9%)	15 (9.0%)	0 (0.0%)
ASA classification:				0.074
≤2	157 (62.5%)	111 (66.5%)	46 (54.8%)
>2	94 (37.5%)	56 (33.5%)	38 (45.2%)
Underlying medical problem:
DM	75 (29.9%)	59 (35.3%)	16 (19.0%)	0.008
HT	157 (62.5%)	112 (67.1%)	45 (53.6%)	0.039
DLP	129 (51.4%)	95 (56.9%)	34 (40.5%)	0.016
CVA	11 (4.4%)	6 (3.6%)	5 (6.0%)	0.518
CKD/ESRD	25 (9.9%)	14 (8.4%)	11 (13.1%)	0.170
Charlson Comorbidity Index	4.1±2.3	4.1±2.3	4.0±2.3	0.752
Chemotherapy	8 (3.2%)	7 (4.2%)	1 (1.2%)	0.274
Radiotherapy	2 (0.8%)	0	2 (2.4%)	0.111
Current smoker	120 (47.8%)	73 (43.7%)	47 (56.0%)	0.082
Alcohol consumption:				0.183
None	173 (68.9%)	118 (70.7)	55 (65.5)
Habitual	53 (21.1%)	30 (18.0%)	23 (27.4%)
Social	25 (9.9%)	19 (11.4%)	6 (7.1%)
Preoperative data
Surgical service:				0.643
GI	68 (27.1%)	44 (26.3%)	24 (28.6%)
URO	70 (27.9%)	45 (26.9%)	25 (29.8%)
GYN	25 (9.9%)	20 (12.0%)	5 (6.0%)
HNB	34 (13.5%)	24 (14.4%)	10 (11.9%)
ENT	40 (15.9%)	24 (14.4%)	16 (19.0%)
Other	14 (5.6%)	10 (6.0%)	4 (4.8%)
Barthel index score ≤70	6 (2.4%)	1 (0.6%)	5 (6.2%)	0.017
Malnutrition	150 (59.8%)	82 (49.1%)	68 (81.0%)	<0.001
Waiting time for surgery (days)	24 (13–39)	25 (15–40)	22 (10–38)	0.129
Severity of cancer:
Distant organ metastasis	50 (19.9)	30 (18.0)	20 (23.8)	0.316
Intraoperative data
Duration of anesthesia (min)	227.9±164.1	229.1±158.6	225.2±176.9	0.868
Blood loss (ml)	65 (15–300)	70 (20–300)	50 (10–300)	0.470
Electrolyte imbalance	23 (9.8%)	15 (9.3%)	8 (11.0%)	0.644
Infection:				0.193
None	206 (87.7%)	145 (89.5%)	61 (83.6%)
Sepsis	4 (1.7%)	2 (1.2%)	2 (2.7%)
Wound	3 (1.3%)	1 (0.6%)	2 (2.7%)
Respiratory tract	7 (3.0%)	3 (1.9%)	4 (5.5%)
Urinary tract	4 (1.7%)	2 (1.2%)	2 (2.7%)
Others	11 (4.7%)	9 (5.6%)	2 (2.7%)
Outcomes
Length of stay (days)	6 (4–9)	6 (4–9)	6 (4.5–9.5)	0.198
Hospital mortality rate	3 (1.3%)	2 (1.2%)	1 (1.3%)	1.000
Barthel Index score ≤70 at 3 months	30 (12.6%)	13 (8.0%)	17 (22.1%)	0.006
after hospital discharge (n = 239)	30 (12.6%)	13 (8.0%)	17 (22.1%)	0.006
Mortality rate at 3 months	12 (4.8%)	5 (3.0%)	7 (8.3%)	0.061
after screening (n = 251)	12 (4.8%)	5 (3.0%)	7 (8.3%)	0.061
Barthel Index score ≤70 at 1 year	9 (4.6%)	4 (2.9%)	5 (8.8%)	0.127
after screening (n = 194)	9 (4.6%)	4 (2.9%)	5 (8.8%)	0.127
Mortality rate at 1 year	56 (22.4%)	29 (17.5%)	27 (32.1%)	0.010
after screening (n = 250)	56 (22.4%)	29 (17.5%)	27 (32.1%)	0.010

Open in a new tab

Data are presented as number and percentage, mean ± standard deviation, or median and interquartile range.

A P value<0.05 indicates statistical significance.

Malnutrition was assessed by MNA-SF (Mini Nutritional Assessment–Short Form).

Abbreviations: ASA, American Society of Anesthesiologists; BMI, body mass index; CAD, coronary artery disease; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; CVA, cerebrovascular accident; DLP, dyslipidemia; DM, diabetes mellitus; ENT, ear, nose, and throat; ESRD, end-stage renal disease; GA, general anesthesia; GI, gastrointestinal; GYN, gynecology; HNB, head, neck, and breast; HT, hypertension; RA, regional anesthesia; URO, urology.

Table 3. Independent risk factors associated with preoperative sarcopenia.

Factors	Adjusted odds ratio (95% CI)	P value
Age (years, 5 units)	1.78 (1.41–2.24)	<0.001
Body mass index:
Normal	1
Underweight	2.80 (1.06–7.43)	0.038
Overweight	0.19 (0.08–0.47)	<0.001
Malnutrition	2.89 (1.40–5.93)	0.004
Pre-Barthel Index score ≤70	10.48 (0.84–122.08)	0.061

Open in a new tab

Adjusted for gender, American Society of Anesthesiologists (ASA) Classification, diabetes mellitus, hypertension, dyslipidemia, chronic kidney disease/end-stage renal disease, current smoker, alcohol consumption, waiting time for surgery, and infection.

A P value <0.05 indicates statistical significance.

Malnutrition was assessed by MNA^-SF (Mini Nutritional Assessment–Short Form).

Abbreviation: CI, confidence interval.

Screening performance of the tool

Formula-combination C3 (low muscle strength and/or abnormal physical performance, plus malnutrition/risk of malnutrition) demonstrated the highest sensitivity and accuracy when using the 2014 AWGS or the updated 2019 AWGS criteria as the gold standards. The sensitivity, specificity, accuracy, and AUROC of formula-combination C3 were 81.0%, 78.4%, 79.3%, and 0.8, respectively when using the 2014 AWGS criteria as the gold standard. The C3 formula presented the ability to estimate the probability of sarcopenia, with a PPV of 65.4% and an NPV of 89.1%. EWGSOP2 demonstrated the highest specificity (100%) for diagnosis of sarcopenia (Table 4A). The prevalence of sarcopenia by EWGSOP2 definition was 28%. In addition, EWGSOP2 proposed the term “probable sarcopenia”, for which the diagnosis requires only lower muscle strength. The prevalence of probable sarcopenia was 49.8%; however, muscle mass measurement was needed to confirm a diagnosis of sarcopenia. Regarding the screening performance of formula-combination C3 in males, that formula showed a high sensitivity, specificity, PPV, and NPV (72.7%, 91.1%, 83.3%, and 86.5%, respectively). As to its screening performance in females, while it demonstrated a high sensitivity (96.6%) and high NPV (98%), formula-combination C3 had a low specificity (63.3%) and low PPV (50.0%). The sensitivity, specificity, accuracy, and AUROC of formula C3 was 80%, 68.5%, 73.3%, and 0.74, respectively, when using the updated 2019 AWGS criteria as the gold standard (Table 4B).

Table 4. Validity of combinations used to diagnose sarcopenia.

a. Validity based on 2014 AWGS criteria as gold standard
Tools	Sensitivity	Specificity	PPV	NPV	LR+	LR-	Accuracy	AUROC
Tools	(95% CI)	(95% CI)	(95% CI)	(95% CI)	(95% CI)	(95% CI)	(95% CI)	(95% CI)
EWGSOP2	84.5%	100.0%	–	92.8%	–	0.15	94.8%	0.70
EWGSOP2	(74.9–91.5)	(97.8–100)	–	(88.6–95.5)	–	(0.09–0.26)	(91.3–97.2)	(0.63–0.78)
C 1	40.5%	83.2%	54.8%	73.5%	2.4	0.7	68.9%	0.62
C 1	(29.9–51.8)	(76.7–88.6)	(44.2–65.0)	(69.7–77.1)	(1.6–3.7)	(0.6–0.9)	(62.8–74.6)	(0.54–0.70)
C 2	35.7%	90.4%	65.2%	73.7%	3.7	0.7	72.1%	0.63
C 2	(25.6–46.9)	(84.9–94.4)	(52.0–76.4)	(70.3–76.8)	(2.2–6.4)	(0.6–0.8)	(66.1–77.6)	(0.55–0.71)
C 3	81.0%	78.4%	65.4%	89.1%	3.8	0.2	79.3%	0.80
C 3	(70.9–88.7)	(71.4–84.4)	(58.1–72.0)	(84.0–92.8)	(2.8–5.1)	(0.2–0.4)	(73.7–84.1)	(0.74–0.86)
C 4	23.8%	98.8%	90.9%	72.1%	19.9	0.8	73.7%	0.61
C 4	(15.2–34.4)	(95.7–99.9)	(70.5–97.7)	(69.6–74.4)	(4.8–83.1)	(0.7–0.9)	(67.8–79.0)	(0.54–0.69)
b. Validity based on 2019 AWGS criteria as gold standard
Tools	Sensitivity	Specificity	PPV	NPV	LR+	LR-	Accuracy	AUROC
Tools	(95% CI)	(95% CI)	(95% CI)	(95% CI)	(95% CI)	(95% CI)	(95% CI)	(95% CI)
EWGSOP2	76.2%	100%	–	85.4%	–	0.24	90.0%	0.88
	(66.9–84.0)	100%		85.4%		0.24	90.0%	0.88
	(66.9–84.0)	(97.5–100.0)		(80.6–89.2)		(0.17–0.34)	(85.7–93.5)	(0.83–0.93)
C 1	59.1%	64.4%	54.4%	68.6%	1.66	0.6	62.2%	0.62
	(49.0–68.6)	64.4%	54.4%	68.6%	1.66	0.6	62.2%	0.62
	(49.0–68.6)	(56.0–72.1)	(47.7–61.0)	(62.8–73.9)	(1.3–2.2)	(0.5–0.8)	(55.8–68.2)	(0.55–0.69)
C 2	49.5%	79.5%	63.4%	68.6%	2.4	0.6	66.9%	0.65
	(39.6–59.5)	79.5%	63.4%	68.6%	2.4	0.6	66.9%	0.65
	(39.6–59.5)	(72.0–85.7)	(54.4–71.6)	(64.0–72.9)	(1.7–3.5)	(0.5–0.8)	(60.7–72.7)	(0.57–0.72)
C 3	80%	68.5%	64.6%	82.6%	2.5	0.3	73.3%	0.74
C 3	(71.1–87.2)	(60.3–75.9	(58.5–70.3)	(76.2–87.6)	(2.0–3.3)	(0.2–0.4)	(67.4–78.7)	(0.68–0.81)
C 4	23.8%	97.3%	86.2%	64.0%	8.7	0.8	66.5%	0.61
	(16.0–33.1)	97.3%	86.2%	64.0%	8.7	0.8	66.5%	0.61
	(16.0–33.1)	(93.1–99.3)	(69.2–94.6)	(61.4–66.5)	(3.1–24.2)	(0.7–0.9)	(60.3–72.3)	(0.53–0.68)

Open in a new tab

Abbreviations: C1, combination of muscle strength and physical performance; C2, combination of muscle strength, physical performance, and malnutrition/risk of malnutrition; C3, combination of muscle strength and/or physical performance, plus malnutrition/risk of malnutrition; C4, combination of muscle strength and/or physical performance, plus body mass index; CI, confidence interval; EWGSOP2, European Working Group on Sarcopenia in Older People 2 (low muscle strength and low muscle mass); LR+, positive likelihood ratio; LR-, negative likelihood ratio; NPV, negative predictive value; PPV, positive predictive value.

Sarcopenia and clinical outcomes

Three months after hospital discharge, the sarcopenic patients demonstrated a higher incidence of moderate to severe disability than the non-sarcopenic patients (22% vs. 8%, P = 0.006). However, there was no significant difference 1 year after the sarcopenia screening (sarcopenic and non-sarcopenic surgical patients: 8.8% vs. 2.9%, P = 0.127). As to the mortality rates, there was no significant difference in the rates 3 months after the sarcopenia screening. In contrast, the sarcopenic patients had a significantly higher mortality than the non-sarcopenic patients 1 year after the screening (32% vs. 17.5%, P = 0.01; Table 2).

Discussion

Although advances in perioperative management and surgical techniques for oncology patients have reduced postoperative complications, challenges remain for older adults. This is due to the declines in their functional reserves, worsening frailty, and increasing incidence of comorbidities [34]. It is therefore essential to identify high-risk older adult patients during the preoperative period. Since the patients in this study were all Thai, we applied the AWGS sarcopenia diagnosis criteria to identify sarcopenia in older-adult cancer patients presenting at SiPAC prior to undergoing elective surgery. The prevalence of sarcopenia in this population was 34%. A higher age, an underweight status, and malnutrition were found to be significantly associated with sarcopenia. Furthermore, this study demonstrated that a simple tool can be used to screen for sarcopenia in older-adult, surgical cancer patients without measuring muscle mass. The combination of low muscle strength and/or abnormal physical performance, plus malnutrition/risk of malnutrition (formula-combination C3), demonstrated high sensitivity, specificity, and predictive power when validated against a consensus of the AWGS.

Regarding the factors related to sarcopenia, we found older age, malnutrition, and an underweight status were significantly associated with sarcopenia. This was partially consistent with the findings of other studies. Khongsri et al. [33] reported that older age, low BMI, and low quadriceps strength were predictive factors for sarcopenia in community-dwelling, older adult Thais. However, older-adult cancer patients may be different from the general older-adult population because of their increased inflammatory response. This response leads to cachexia, which exacerbates sarcopenia. This may explain why an underweight status was associated with sarcopenia in this study. Our nutritional status assessment using the MNA-SF revealed that 80% of the sarcopenic patients had malnutrition. Moreover, and importantly, we found that malnutrition was a strong predictor of preoperative sarcopenia (OR: 2.89, 95% CI: 1.4–2.9). Our results strongly suggest that sarcopenia and malnutrition should be considered and assessed together in surgical oncology patients. In addition, we demonstrated that the sarcopenic group had a significantly lower number of patients with DM and DLP. Hypothetically, sarcopenia should be related to higher DM and dyslipidemia due to the loss of metabolically active muscle tissue. However, sarcopenia was reported to be associated with lower DM if muscle mass was adjusted by height², but it was associated with a higher DM if the muscle mass was adjusted by weight or BMI [35]. In the current work, the unit of measurement used to measure muscle mass was kg/m².

The precise definition of sarcopenia varies from one research group to another [5, 6, 8–12]. Nevertheless, all definitions recommend that sarcopenia should be defined by a low muscle mass. This is commonly assessed by DXA, BIA, magnetic resonance imaging, and computed tomography [15, 27]. However, these tools are expensive, difficult to access, and are usually not portable. BIA is not routinely available in clinics and hospitals in developing countries. Research has been conducted on sarcopenia screening tools that do not require muscle mass to be measured, such as the SARC-F questionnaire, Ishii model, Goodman model, and anthropometric predictive equation models [13]. The SARC-F questionnaire has 5 items that are based on the cardinal features or consequences of sarcopenia [36]. Woo J et al. validated that questionnaire against 3 consensus definitions of sarcopenia from Europe, Asia, and an international group in Hong Kong. The questionnaire had excellent specificity (94%–99%) and NPV, but poor sensitivity [37]. Although SARC-F can be readily used in community healthcare and other clinical settings, it might be of limited value in rural areas and community hospitals in developing countries. This is because many patients might not be capable of self-reporting due to their very low levels of formal education. Interestingly, the Ishii model can estimate the probability of sarcopenia using the parameters of age, handgrip strength, and calf circumference in community-dwelling older adults at high risk for sarcopenia. The Ishii model demonstrated high sensitivity, specificity, PPV, and NPV when compared with EWGSOP [38]. However, the model was specifically developed for community-based older-adult Japanese, and it has not undergone external validation. It might therefore not be applicable to our particular population. The Goodman model is based on age and BMI, and it is employed as a screening tool to identify individuals likely to have low muscle mass and to benefit from a DXA scan. However, this screening tool was not specifically developed to screen for sarcopenia, whose current definitions include muscle strength measurement. It also has limitations when used with obese patients [27, 39]. Anthropometric predictive equation models assign scores based on routine clinical parameters such as weight, height, and gender [40, 41]. Although they can be used as a screening tool for sarcopenia in primary care settings, they have not yet been validated for hospital inpatients and non-Caucasian populations [27].

In view of the above constraints, our study developed a screening tool that did not involve the measurement of muscle mass. It was validated against the AWGS criteria, and its screening performance showed high sensitivity, specificity, PPV, and NPV. Its specificity and PPV values were slightly lower for females than males. Despite that, the tool represents a practical algorithm for the diagnosis of sarcopenia in older-adult, surgical cancer patients, and it does not need muscle mass to be measured (Fig 2). The algorithm starts with a case-finding phase. The C3 formula is applied, and surgical cancer patients with a high probability of having sarcopenia proceed to the next step. Step 2 involves screening. Muscle strength and physical performance (determined by walking speed) are measured, and nutritional status is evaluated with the MNA-SF. With male patients, sarcopenia is probable if they demonstrate a low muscle strength and/or low physical performance, and they are also assessed as being at risk of malnutrition or as having malnutrition. However, in the case of females meeting those conditions, sarcopenia should be considered as being only possible, given that the PPV for females is low (50%). As to the males and females who have negative findings in Step 2, they are deemed to not have sarcopenia. Step 3 is the confirmation phase. A BIA measurement is made of the muscle mass of the males and females who have positive findings in Step 2. If the mass is abnormal, sarcopenia is diagnosed. Conversely, if it is normal, sarcopenia is not diagnosed. The latter group of patients should be rescreened later.

With regard to the outcomes, Fukuda, et al. [34] found the incidence of severe postoperative complications (Clavien–Dindo grade >IIIa) to be significantly higher in a sarcopenic group than in a non-sarcopenic group (28.6% vs. 9.0%, P = 0.03) among gastrectomy patients [34]. In contrast, our study did not observe a significant difference in either the postoperative complications or the in-hospital mortality of the groups. Most patients in our cohort were not critically ill before undergoing surgery. Specifically, >60% of patients had an ASA score of <2, the average Charlson Comorbidity Index was only 4, and <3% received chemotherapy before surgery. We also found a greater decline in the activities of daily living in the sarcopenic patients 3 months after hospital discharge. It was suggested that an increased risk of physical limitation and disability in sarcopenic patients may adversely affect functional recovery, quality of life, and the independent performance of the activities of daily living [42].

This study has several limitations. Firstly, this was a single-center study that recruited patients from a preoperative assessment clinic. This suggests that our results may not be representative of, or generalizable to, all surgical patients at our center or in Thailand. Moreover, we used BIA to measure muscle mass, and only patients who could stand unaided were included. As a result, 21% of the patient candidates were excluded, which raises concerns about potential selection bias. Thirdly, the fat-free mass and body cell mass measured by BIA were calculated from the total body weight, using the assumption that 73% of the fat-free mass was water. Therefore, changes in the hydration state, such as edema, were the main limitation of this method [43]. In addition, we commenced this study before the publication of the updated AWGS recommendations on sarcopenia diagnoses. However, we used the revised diagnostic recommendations as another gold standard to validate our screening tool. The C3-combination of factors still demonstrated the highest sensitivity and accuracy. Furthermore, the cross-sectional design of our study meant that we were able to report that certain factors were found to be statistically significantly related to sarcopenia; however, we were not able to prove causation. Lastly, the proposed screening tool should be carefully interpreted with female patients because of its low specificity and PPV. In addition, as no external validation of the proposed screening tool was performed, its use with other populations is problematic. The strengths of this study are the prospective design, and the nutritional and sarcopenia assessments were performed by trained and experienced clinicians.

Conclusions

A simple tool can be used to screen for sarcopenia in older-adult, surgical cancer patients without measuring muscle mass. The combination of low muscle strength and/or abnormal physical performance, plus malnutrition/risk of malnutrition demonstrated high sensitivity, specificity, PPV, and NPV. Preoperative screening of sarcopenia and malnutrition should be performed on all older-adult, surgical oncology patients to identify at-risk patients. This will enable prehabilitation and rehabilitation protocols covering nutritional and physical therapy to be implemented, thereby improving short- and long-term patient outcomes.

Supporting information

S1 File. Raw data of screening tool for sarcopenia.

(XLSX)

Click here for additional data file.^{(24KB, xlsx)}

Acknowledgments

The authors gratefully acknowledge the patients who generously agreed to participate in this study; Asst. Prof. Dr. Chulaluk Komoltri for assistance with the statistical analyses; and Mrs. Dujprathana Pisalsarakij and Miss Tashita Pinsantia for assistance with the data collection. We also thank Mr. David Park for his careful proofreading and professional English editing of this manuscript.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This research project was supported by Faculty of Medicine Siriraj Hospital, Mahidol University, Grant Number (IO) R016034004. The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.

References

1.Blackwell DL, Lucas JW, Clarke TC. Summary health statistics for U.S. adults: national health interview survey, 2012. Vital Health Stat 10. 2014:1–161. [PubMed] [Google Scholar]
2.Office of the National Econimic and Social Development Board. Population projections for Thailand 2010–2040. Bangkok, Thailand; 2013.
3.Wagner D, DeMarco MM, Amini N, Buttner S, Segev D, Gani F, et al. Role of frailty and sarcopenia in predicting outcomes among patients undergoing gastrointestinal surgery. World J Gastrointest Surg. 2016;8:27–40. doi: 10.4240/wjgs.v8.i1.27 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Zbar AP, Gravitz A, Audisio RA. Principles of surgical oncology in the elderly. Clin Geriatr Med. 2012;28:51–71. doi: 10.1016/j.cger.2011.09.002 [DOI] [PubMed] [Google Scholar]
5.Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010;39:412–23. doi: 10.1093/ageing/afq034 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Muscaritoli M, Anker SD, Argilés J, Aversa Z, Bauer JM, Biolo G, et al. Consensus definition of sarcopenia, cachexia and pre-cachexia: joint document elaborated by Special Interest Groups (SIG) "cachexia-anorexia in chronic wasting diseases" and "nutrition in geriatrics". Clin Nutr. 2010;29:154–9. doi: 10.1016/j.clnu.2009.12.004 [DOI] [PubMed] [Google Scholar]
7.Fielding RA, Vellas B, Evans WJ, Bhasin S, Morley JE, Newman AB, et al. Sarcopenia: an undiagnosed condition in older adults. Current consensus definition: prevalence, etiology, and consequences. International working group on sarcopenia. J Am Med Dir Assoc. 2011;12:249–56. doi: 10.1016/j.jamda.2011.01.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Morley JE, Abbatecola AM, Argiles JM, Baracos V, Bauer J, Bhasin S, et al. Sarcopenia with limited mobility: an international consensus. J Am Med Dir Assoc. 2011;12:403–9. doi: 10.1016/j.jamda.2011.04.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al. Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc. 2014;15:95–101. doi: 10.1016/j.jamda.2013.11.025 [DOI] [PubMed] [Google Scholar]
10.McLean RR, Shardell MD, Alley DE, Cawthon PM, Fragala MS, Harris TB, et al. Criteria for clinically relevant weakness and low lean mass and their longitudinal association with incident mobility impairment and mortality: the foundation for the National Institutes of Health (FNIH) sarcopenia project. J Gerontol A Biol Sci Med Sci. 2014;69:576–83. doi: 10.1093/gerona/glu012 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Nishikawa H, Shiraki M, Hiramatsu A, Moriya K, Hino K, Nishiguchi S. Japan Society of Hepatology guidelines for sarcopenia in liver disease (1st edition): Recommendation from the working group for creation of sarcopenia assessment criteria. Hepatol Res. 2016;46:951–63. doi: 10.1111/hepr.12774 [DOI] [PubMed] [Google Scholar]
12.Akishita M, Kozaki K, Iijima K, Tanaka T, Shibasaki K, Ogawa S, et al. Chapter 1 Definitions and diagnosis of sarcopenia. Geriatr Gerontol Int. 2018;18Suppl 1:7–12. doi: 10.1111/ggi.13311 [DOI] [PubMed] [Google Scholar]
13.Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48:16–31. doi: 10.1093/ageing/afy169 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J Am Med Dir Assoc. 2020;21:300–7.e2. doi: 10.1016/j.jamda.2019.12.012 [DOI] [PubMed] [Google Scholar]
15.Mijnarends DM, Meijers JM, Halfens RJ, ter Borg S, Luiking YC, Verlaan S, et al. Validity and reliability of tools to measure muscle mass, strength, and physical performance in community-dwelling older people: a systematic review. J Am Med Dir Assoc. 2013;14:170–8. doi: 10.1016/j.jamda.2012.10.009 [DOI] [PubMed] [Google Scholar]
16.Yilmaz O, Bahat G. Suggestions for assessment of muscle mass in primary care setting. Aging Male. 2017;20:168–9. doi: 10.1080/13685538.2017.1311856 [DOI] [PubMed] [Google Scholar]
17.Shaw KA, Srikanth VK, Fryer JL, Blizzard L, Dwyer T, Venn AJ. Dual energy X-ray absorptiometry body composition and aging in a population-based older cohort. Int J Obes (Lond). 2007;31:279–84. [DOI] [PubMed] [Google Scholar]
18.Rubbieri G, Mossello E, Di Bari M. Techniques for the diagnosis of sarcopenia. Clin Cases Miner Bone Metab. 2014;11:181–4. [PMC free article] [PubMed] [Google Scholar]
19.Bruun LI, Bosaeus I, Bergstad L, Nygaard K. Prevalence of malnutrition in surgical patients: evaluation of nutritional support and documentation. Clin Nutr. 1999;18:141–7. doi: 10.1016/s0261-5614(99)80003-x [DOI] [PubMed] [Google Scholar]
20.MacKay D, Miller AL. Nutritional support for wound healing. Altern Med Rev. 2003;8:359–77. [PubMed] [Google Scholar]
21.Pacelli F, Bossola M, Rosa F, Tortorelli AP, Papa V, Doglietto GB. Is malnutrition still a risk factor of postoperative complications in gastric cancer surgery? Clin Nutr. 2008;27:398–407. doi: 10.1016/j.clnu.2008.03.002 [DOI] [PubMed] [Google Scholar]
22.Sungurtekin H, Sungurtekin U, Balci C, Zencir M, Erdem E. The influence of nutritional status on complications after major intraabdominal surgery. J Am Coll Nutr. 2004;23:227–32. doi: 10.1080/07315724.2004.10719365 [DOI] [PubMed] [Google Scholar]
23.Edington J, Boorman J, Durrant ER, Perkins A, Giffin CV, James R, et al. Prevalence of malnutrition on admission to four hospitals in England. The Malnutrition Prevalence Group. Clin Nutr. 2000;19:191–5. doi: 10.1054/clnu.1999.0121 [DOI] [PubMed] [Google Scholar]
24.Correia MI, Waitzberg DL. The impact of malnutrition on morbidity, mortality, length of hospital stay and costs evaluated through a multivariate model analysis. Clin Nutr. 2003;22:235–9. doi: 10.1016/s0261-5614(02)00215-7 [DOI] [PubMed] [Google Scholar]
25.Bahat G, Oren MM, Yilmaz O, Kılıç C, Aydin K, Karan MA. Comparing SARC-F with SARC-CalF to Screen Sarcopenia in Community Living Older Adults. J Nutr Health Aging. 2018;22:1034–8. doi: 10.1007/s12603-018-1072-y [DOI] [PubMed] [Google Scholar]
26.Barbosa-Silva TG, Menezes AM, Bielemann RM, Malmstrom TK, Gonzalez MC. Enhancing SARC-F: Improving Sarcopenia Screening in the Clinical Practice. J Am Med Dir Assoc. 2016;17:1136–41. doi: 10.1016/j.jamda.2016.08.004 [DOI] [PubMed] [Google Scholar]
27.Yu SC, Khow KS, Jadczak AD, Visvanathan R. Clinical Screening Tools for Sarcopenia and Its Management. Curr Gerontol Geriatr Res. 2016;2016:5978523. doi: 10.1155/2016/5978523 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Kaiser MJ, Bauer JM, Ramsch C, Uter W, Guigoz Y, Cederholm T, et al. Validation of the Mini Nutritional Assessment short-form (MNA-SF): a practical tool for identification of nutritional status. J Nutr Health Aging. 2009;13:782–8. doi: 10.1007/s12603-009-0214-7 [DOI] [PubMed] [Google Scholar]
29.Rubenstein LZ, Harker JO, Salva A, Guigoz Y, Vellas B. Screening for undernutrition in geriatric practice: developing the short-form mini-nutritional assessment (MNA-SF). J Gerontol A Biol Sci Med Sci. 2001;56:M366–72. doi: 10.1093/gerona/56.6.m366 [DOI] [PubMed] [Google Scholar]
30.Limpawattana P, Kotruchin P, Pongchaiyakul C. Sarcopenia in Asia. Osteoporosis Sarcopenia. 2015;1:92–7. [Google Scholar]
31.Limpawattana P. Frailty and Sarcopenia. In: Assantachai P, Niamhom S, Thongnuam N, editors. Guidelines for management of Geriatric syndromes: Institute of Geriatric Medicine, Department of Medical Service, Ministry of Public health. August Publishing Ltd; Nonthaburi, Thailand, 2015. pp. 39–51. [in Thai] [Google Scholar]
32.Cruz-Jentoft AJ, Landi F, Schneider SM, Zúñiga C, Arai H, Boirie Y, et al. Prevalence of and interventions for sarcopenia in ageing adults: a systematic review. Report of the International Sarcopenia Initiative (EWGSOP and IWGS). Age Ageing. 2014;43:748–59. doi: 10.1093/ageing/afu115 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Khongsri N, Tongsuntud S, Limampai P, Kuptniratsaikul V. The prevalence of sarcopenia and related factors in a community-dwelling elders Thai population. Osteoporosis Sarcopenia. 2016;2:110–5. doi: 10.1016/j.afos.2016.05.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Fukuda Y, Yamamoto K, Hirao M, Nishikawa K, Nagatsuma Y, Nakayama T, et al. Sarcopenia is associated with severe postoperative complications in elderly gastric cancer patients undergoing gastrectomy. Gastric Cancer. 2016;19:986–93. doi: 10.1007/s10120-015-0546-4 [DOI] [PubMed] [Google Scholar]
35.Bahat G, İlhan B. Sarcopenia and the cardiometabolic syndrome: A narrative review. Eur Geriatr Med. 2016;7:220–3. [Google Scholar]
36.Malmstrom TK, Morley JE. SARC-F: a simple questionnaire to rapidly diagnose sarcopenia. J Am Med Dir Assoc. 2013;14:531–2. doi: 10.1016/j.jamda.2013.05.018 [DOI] [PubMed] [Google Scholar]
37.Woo J, Leung J, Morley JE. Validating the SARC-F: a suitable community screening tool for sarcopenia? J Am Med Dir Assoc. 2014;15:630–4. doi: 10.1016/j.jamda.2014.04.021 [DOI] [PubMed] [Google Scholar]
38.Ishii S, Tanaka T, Shibasaki K, Ouchi Y, Kikutani T, Higashiguchi T, et al. Development of a simple screening test for sarcopenia in older adults. Geriatr Gerontol Int. 2014;14Suppl 1:93–101. doi: 10.1111/ggi.12197 [DOI] [PubMed] [Google Scholar]
39.Goodman MJ, Ghate SR, Mavros P, Sen S, Marcus RL, Joy E, et al. Development of a practical screening tool to predict low muscle mass using NHANES 1999–2004. J Cachexia Sarcopenia Muscle. 2013;4:187–97. doi: 10.1007/s13539-013-0107-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Visvanathan R, Yu S, Field J, Chapman I, Adams R, Wittert G, et al. Appendicular Skeletal Muscle Mass: Development and Validation of Anthropometric Prediction Equations. J Frailty Aging. 2012;1:147–51. doi: 10.14283/jfa.2012.23 [DOI] [PubMed] [Google Scholar]
41.Yu S, Appleton S, Chapman I, Adams R, Wittert G, Visvanathan T, et al. An anthropometric prediction equation for appendicular skeletal muscle mass in combination with a measure of muscle function to screen for sarcopenia in primary and aged care. J Am Med Dir Assoc. 2015;16:25–30. doi: 10.1016/j.jamda.2014.06.018 [DOI] [PubMed] [Google Scholar]
42.Santilli V, Bernetti A, Mangone M, Paoloni M. Clinical definition of sarcopenia. Clin Cases Miner Bone Metab. 2014;11:177–80. [PMC free article] [PubMed] [Google Scholar]
43.Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gómez JM, et al. Bioelectrical impedance analysis—part I: review of principles and methods. Clin Nutr. 2004;23:1226–43. doi: 10.1016/j.clnu.2004.06.004 [DOI] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0257672.r001

Decision Letter 0

Jamie Males

15 Jun 2021

PONE-D-21-00876

The validity of a simple screening tool for sarcopenia in surgical patients

PLOS ONE

Dear Dr. Chaiwat,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Both reviewers have raised a number of questions regarding the study design and analysis. Please ensure that you respond thoroughly to all of the reviewers' points when preparing your revised manuscript.

Please submit your revised manuscript by Jul 23 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Jamie Males

Staff Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Some text appears to be missing in your Ethics Statement: 'All patients or, if applicable, provided informed consent in writing'. We believe you may have omitted text regarding the legal guardian of the participants. Please amend this statement as necessary

3. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: N/A

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: No

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: 1. abstract: line27: sentence is not understandable ; methods section should be re-written to be more accurate.

2. Key words : assessment tool should be precised

3. Main manuscript : the exclusion criteria "patients unable to walk or stand up" is a bias and the prevalence of sarcopenia is underestimated. Those patients are the most fragile and they were not included in the study.

4. "presence of pacemaker" : a pacemaker is not a contraindication for BIA, see the reference in pubmed https://pubmed.ncbi.nlm.nih.gov/29525512/

5. The exclusion criteria lead the author to not included a large number of patients, the most fragil especially : "taking medication, herb and/or hormone that affected muscle mass"

6. Patients with an alcohol consumption were not included but the variable was collected (line 112) without any explanations on the method

7. History of weigth loss was also collected but not displayed in tables

8. The research team chose to measure handgrip strength on the dominant arm, but what's happen in case of stroke for example. It's better to perform 3 measurements of each arm and then keep the higher one.

9. line 156 "four combination formulas" : not clear enougth and the explanation is in the result section instead of the method section.

10. The research team should explain why they began their algorithm with walk test instead of grip strength as the EWGSOP2 guidelines. Indeed, handgrip strength is an easy and well accepted test as the chair rise. The patients that have a positive screening for sarcopenia can be care safety as they are sarcopenic, in cancer context especially.

Reviewer #2: I read the text with great interest. Authors explored the operational definition of sarcopenia according to AWGS criteria in a vulnerable patient population. % 34 of elderly cancer patients had sarcopenia and the sarcopenia in these patient population was significantly related with poor outcomes. Authors introduced a simpler algorithm for predicting sarcopenia by excluding the muscle mass measurement and incorporating MNA-SF tool. Presence of cachexia and secondary sarcopenia in cancer patients emphasized the importance of nutritional screening.

It is a prospective, well organized study and authors may consider the following comments:

1. The authors named the simpler method of defining sarcopenia, as a validated tool. However I think it will be better to present this as a simle algorithm not a validated tool. Actually authors are defining a simpler form of algorithm by incorporating MNA-SF instead of muscle mass into the operational definition of sarcopenia. I recommend to change as a simple algorithm instead of a validated tool in the title and in the text.

2. AWGS has updated consensus in 2019 and changed the cut-off values for handgrip strength for men (<28kg) and also changed cut-off criteria for low physical performance for 6-m walk (<1.0 m/s). In the text, the old AWGS cut off points reported in 2014 were used. I wonder why authors did not use the cut-offs defined in updated AWGS.

3. In table 1 surgical oncologic patients with sarcopenia had poorer outcomes such as lower Barthel index score at 3 months of discharge, higher mortality rate at 3 months and 1 year after discharge again. These outcome findings are valuable and have scientific impact. But these outcomes are not mentioned in result section and not discussed in discussion section. I recommend to highlight these outcomes both in result and discussion sections.

4. I also wonder if sarcopenia, when defined according to your new algorithm, is related with poor outcome measures?

5. Authors defining a flowchart for screening of sarcopenia in Figure 1. Figure 1 represents the sarcopenia screening algorithm of EWGSOP in 2010 by starting with gait speed only. Unlike EWGSOP, AWGS recommends measuring both muscle strength (handgrip strength) and physical performance (usual gait speed) as the screening test. Actually the final result does not change, but still the authors can rearrange figure 1 according to the AWGS algorithm.

Minor points

Abstract

1. Line 26: muscle mass and muscle functions (strength and function). Please use physical performance term instead of function in parentheses.

2. Line 27: Please change the word immobilization with immobile

Result section

1 Line 171-173: Please rewrite the sentence, it is not clear ‘’ Of those, only 84 subjects demonstrated low muscle mass below the recommended cutoff value for a prevalence of sarcopenia in this cohort of 34% .’’

3. Line 175-176: Presarcopenia was found in another 34 patients (40% ); however, these patients were included in the non–sarcopenia group for all other analyses’’. Here the term presarcopenia refers to patients only with low muscle mass not accompanying low muscle strength and muscle performance. I couldn't catch the rate 40% . 34 out of 104 patients have low muscle mass ?? In addition the term presarcopenia was included in EWGSOP in 2010, not addressed in revised EWGSOP, AWGS in 2014 and updated AWGS in 2019. You may remove this information from method and result sections.

4. Line 190: Please write open form of the abbreviation CCI

Discussion

1. Line:246-248: ‘’Previous study from China in oncology surgical patients defined sarcopenia by the combination of low muscle mass and/ or low muscle strength and low physical performance’’. This information lacks the reference. You may add reference or may remove this information, the discussion is long anyway.

2. Dİscussion is too long, from lines 286 to 315 should be shortened

Reviewer #3: Dear Author,

I read the article entitled “The validity of a simple screening tool for sarcopenia in surgical patients” with great interest. Screening and diagnosis of sarcopenia is important in geriatric assessment. Sarcopenia, the age-associated loss of skeletal muscle mass, has been postulated to be a major factor in the strength decline with aging. Moreover, sarcopenia is related to functional impairment, disability, falls, and loss of independence in older adults. In clinical use there are some screening tools for sarcopenia. Therefore, new tools may be tried for screening and / or diagnostic purposes. Accordingly, this study provides important data. A lot of efforts have been put together for this study. I congratulate the authors for the study because this is a worthwhile study and can be considered for publication. However, there are some major points that should be revised substantially. Please find my comments below.

Abstract

1- In the background part its written that ‘’...muscle functions (strength and function)": this phrase is confusing? What do you indicate by function within the parenthesis?

2- ‘’ ….which is costly and immobilization’’ This phrase also makes no sense.

3- In line 27, We differentiate between "assessment" and "screening". Assessment is used for diagnosis whereas screening is for screening. That is to further select cases for assessment (diagnostic) protocols. Please express your intend in a correct way.

4- In line 28, What kind of an assessment tool is this? Is it something you suggest or already has been suggested in previous studies? If this was your first-time suggestion, then you should give details on its components.

5- In line 29, ‘’ ...diagnosis performance..’’ It should be "diagnostic performance" In general there are flaws in use of English. English should be edited by a native speaker preferably

6- In line 29, Instead of elderly, please use "older adults".

7- In the results part line 36, malnutrition and underweight are very inter-related. I do not think that they can be included as independent variables within the same regression analysis. Please clarify.

8- In line 39, ‘’….risk of malnutrition & malnutrition and/ or abnormal physical performance.’’ As far as I understood, it is better to write as “...risk of malnutrition/malnutrition". Also what do you mean by writing “...and/or .."

9- In conclusion part, line 43: We do not screen sarcopenia by muscle mass measurement. The authors might have had a confusion in this regard.

10- In the keywords, assessment tool is not the right word here. Consider screening tool.

Background

1- Two right square brackets in some references, please correct them.

2- In line 58 ‘’ Recent guidelines from the American College of Surgeons emphasize the importance of assessing sarcopenia prior to oncologic surgery in elderly patients.’’ In the referenced guideline they were not suggest assessing sarcopenia prior the surgery. They recommended document functional status, history of falls and frailty.

3- In line 62-65 ‘’ In essence….’’ This sentence is difficult to understand. Please describe better.

4- In line 69 ‘’… muscle quantity and quality’’ instead of "and", you should use "and/or".

5- In line 71-75 ‘’ Concerning the assessment of muscle mass….’’ Here, BIA comes forward due to its practical and portable application without exposure to any radiological harms. The authors are recommended to emphasize this fact, they may consider PMID: 28414253 to refer for this information.

6- In line 80 its written ‘assessment tool’. not assessment. Please be careful in your statements, particularly if your aim is to suggest a "screening" tool. Please review and correct your manuscript in terms of incorrect use of "assessment" word instead of screening.

7- In line 83-86 ‘’ Malnourished surgical……’’ After this sentence, the authors should develop the underlying the logic why they intended to use malnutrition as a component of sarcopenia screening in these patients.

8- Its written that the aims of this study were to design and validate the diagnosis performance of a simple assessment tool for screening sarcopenia in elderly cancer patients. There are some simple screening tools, such as SARC-F (PMID: 27066316 ). The authors should denote particularly SARC-F, as it is a very simple and convenient tool that demonstrated ability to predict adverse outcomes and sarcopenia, esp. the probable sarcopenia (PMID: 27066316 , PMID: 30272090). It has also potential other applications besides sarcopenia, such as frailty (PMID: 33786561). Moreover, SARC-F has been reported to screen for sarcopenia by application of alternative/lower cut-off scores (https://doi.org/10.1007/s12603-021-1617-3). SARC-F is also suggested by EWGSOP2 for "formal screening" and a project to widen its use has been endorsed by EuGMS (https://doi.org/10.1007/s41999-017-0003-5). Also, consider use of SARC-F by AWGS recommendation. These information on SARC-F should be noted in few sentences in order to avoid from a biased presentation of the literature. Moreover, I would suggest including at least a sentence on Ishii screening tool (PMID: 24450566). Also, SARc-CAlF which incorporates calf circumference as an indirect measure of muscle mass should be noted with few sentences (PMID: 27650212 and PMID: 30379299).

Materials and Methods

1- Its written that it is longitudinal and cross–sectional study. How can a study be both "longitudinal" and cross-sectional? It is conflicting.

2- In line 102 ‘Patients unable to walk or stand up were excluded.’ This makes that the proposed screening tool cannot be applied to those that are unable to walk, etc. This should be signified in the limitations section of the Discussion. Also, the authors should describe why they excluded these subjects.

3- In line 106 about the BIA measurement, Edema/ major fluid electrolyte abnormalities also precludes BIA assessment. Have you excluded those as well?

4- In line 118, the scoring categorization of MNA-SF should be integrated.

5- In line 119-120 measuring muscle mass with BIA, Is this appendicular muscle mass or total? You should specify.

6- In line 133-137 about the definition of sarcopenia, these are somewhat older references to define/diagnose sarcopenia. As authors would know, there are more updates diagnostic recommendations on sarcopenia both in Europe and Asia. This should be noted and discussed in the discussion section as a limitation of the study. Also, I guess the reference 27 should be corrected as reference 6.

7- In statistical analysis, have you checked normality? And how?

Results

1- In line 177 and 179 ‘Eleven patients..., five patients...’ Give % to allow readers understanding the impact of sarcopenia in decision processes better.

2- In line 190 ‘ …the sarcopenic group had a significantly lower number of patients with DM and DLP.’ This should be discussed with few sentences. Hypothetically sarcopenia should be related with higher DM and dyslipidemia due to loss of metabolic active muscle tissue. However, authors should clarify that sarcopenia is reported associated with low DM if muscle mass is adjusted by height2 but with higher DM if muscle is adjusted by weight/BMI (may refer https://doi.org/10.1016/j.eurger.2015.12.012).

3- In multivariate analysis, the authors should specify the dependent variable and independent variables in the regression analysis. This should also be given in the Table with a footnote.

4- In line 196, Barthel index is non-significant. Needless to state here.

5- About the formula 1, The authors should acknowledge that there is "probable sarcopenia" diagnosis that can be already made by solely measuring hand grip strength. The authors should specify that they are indicating confirmed sarcopenia or sarcopenia definitions that incorporate muscle mass.

6- Authors are recommended to give AUC values for the formulas as well.

7- In line 216, its written that EWGSOP2 demonstrated the highest specificity. Do you indicate confirmed sarcopenia or probable sarcopenia definitions of EWGSOP2 here?

Discussion

1- Discussion is too long. The authors should first outline main findings of their study and then discuss the findings by comparing with the similar studies in the literature.

2- In line 236 ‘In addition to the prevalence of sarcopenia being 34% , the prevalence rate increased with age...’ : I do not think that such detailed discussion on prevalence of sarcopenia in this study and comparison with others is needed. The objective of this study is NOT to report prevalence of sarcopenia. Your objective is to evaluate screening ability of the formulas you suggested. Therefore, shorten the Discussion and be sure that you discuss your findings around your main objective.

3- In line 263 ‘Regarding the factors related to sarcopenia, we found older age, malnutrition, and underweight status to be significantly associated with sarcopenia.’ : Refer to my previous comment on sarcopenia prevalence of sarcopenia/discussion. Concentrate on your main findings, not the secondary outputs. Just few sentences instead of this huge paragraph would be enough.

4- In line 295 they mentioned about SARC-F. My recommendations to note on SARC-F and Ishii tool in the Introduction sections may be detailed and answered at this part of the Discussion section. Nevertheless, some introductory sentences on SARC-f and Ishii should be stated in the Introduction section as well.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Firuzan Fırat Özer

Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachment

Submitted filename: Review.docx

Click here for additional data file.^{(16.7KB, docx)}

Attachment

Submitted filename: Review Plus-One.docx

Click here for additional data file.^{(21.7KB, docx)}

PLoS One. 2021 Sep 23;16(9):e0257672. doi: 10.1371/journal.pone.0257672.r002

Author response to Decision Letter 0

9 Jul 2021

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response: We corrected as recommended.

Response: We added these phrases.

“All procedures performed in studies involving human participants were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This study was approved by the Institutional Review Board of the faculty of Medicine Siriraj Hospital (Si 101/2017). All patients or their legal guardians provided informed consent in writing. The analysis used anonymous clinical data that were obtained after each patient agreed to intervention by written consent.”

3. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

Response: We corrected as recommended.

“This research project was supported by Faculty of Medicine Siriraj Hospital, Mahidol University, Grant Number (IO) R016034004. The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.”

________________________________________

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

________________________________________

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: N/A

________________________________________

3. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

________________________________________

4. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: No

________________________________________

5. Review Comments to the Author

Reviewer #1:

1. abstract: line27: sentence is not understandable; methods section should be re-written to be more accurate.

Response: Abstract: We add some words to explain this sentence. (Page 2, Line 34-35)

Methods: We corrected the information in methods to be more accurate and clearer. We deleted this sentence “The validity of four combination formulas used for a diagnosis of sarcopenia compared to AWGS definition was presented” to make the method more understandable.

2. Key words: assessment tool should be precised.

Response: We removed the word “assessment tool” and added “screening tool” as recommended by the reviewer#3. (Page 2, Line 47)

3. Main manuscript: the exclusion criteria "patients unable to walk or stand up" is a bias and the prevalence of sarcopenia is underestimated. Those patients are the most fragile and they were not included in the study.

Response: We realized about this limitation and addressed this in the limitation. Due to the limitation of funding and resources, we used the BIA from this company (Tanita MC–780U Multi Frequency Segmental Body Composition Analyzer; Tanita Corporation, Tokyo, Japan), this BIA can measure muscle mass only in the standing posture. We excluded 278 patients, 156 patients refused to participate and 122 (44%) patients cannot walk or stand up.

4. "presence of pacemaker”: a pacemaker is not a contraindication for BIA, see the reference in pubmed https://pubmed.ncbi.nlm.nih.gov/29525512/

Response: Thank you for this recommendation, however, at that time that we commenced this study, pace makers were the contraindication according to the manufacturer’s manual (https://www.tanita.com, page 4). Moreover, no patients were excluded from the presence of pacemaker.

5. The exclusion criteria lead the author to not included a large number of patients, the most fragil especially: "taking medication, herb and/or hormone that affected muscle mass"

Response: Yes, we agreed to this comment.

Nevertheless, in this study no patients were excluded regarding "taking medication, herb and/or hormone that affected muscle mass”.

6. Patients with an alcohol consumption were not included but the variable was collected (line 112) without any explanations on the method

Response: We excluded only patients who had consumed alcohol and/or had exercised strenuously within 12 hours prior to BIA measurement. We did collect the data regarding the history of alcohol consumption.

7. History of weight loss was also collected but not displayed in tables

Response: We collected the history of weight loss to define malnutrition by Mini Nutritional Assessment–Short Form (MNA®–SF) and reported as “malnutrition” in Table 1.

Response: Thank you for the comment and we agreed but we could not change at this time, for the next project we will consider this point. There were 11 stroke patients, we measured the handgrip in the non-weakness arm.

9. line 156 "four combination formulas": not clear enough and the explanation is in the result section instead of the method section.

Response: We totally agreed. We moved the whole section from the results to the method section. (Page 7, Line 154-164)

Response: We initially designed the protocol to assess sarcopenia according to the EWGSOP recommendation (ref 5.) at that time before the publication of EWGSOP2 guideline and it was recommended to start with gait speed.

Reference:

5. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010; 39:412-23.

________________________________________

Reviewer #2:

I read the text with great interest. Authors explored the operational definition of sarcopenia according to AWGS criteria in a vulnerable patient population. % 34 of elderly cancer patients had sarcopenia and the sarcopenia in these patient population was significantly related with poor outcomes. Authors introduced a simpler algorithm for predicting sarcopenia by excluding the muscle mass measurement and incorporating MNA-SF tool. Presence of cachexia and secondary sarcopenia in cancer patients emphasized the importance of nutritional screening.

It is a prospective, well organized study and authors may consider the following comments:

1. The authors named the simpler method of defining sarcopenia, as a validated tool. However I think it will be better to present this as a simple algorithm not a validated tool. Actually authors are defining a simpler form of algorithm by incorporating MNA-SF instead of muscle mass into the operational definition of sarcopenia. I recommend to change as a simple algorithm instead of a validated tool in the title and in the text.

Response: We changed the title to “The simpler screening tool for sarcopenia in surgical patients”. However, we designed the new screening tool and validated the diagnostic performance of this screening tool against the gold standard. So, we still used the verb “validate” in the text.

Response: We agreed. However, we commenced this study before the updated consensus in 2019. Moreover, we have been being in the submission process when AWGS 2019 was published. We will address this point in the limitation section. We did analysis for the new cut-off, the prevalence of sarcopenia was 41.8 % as compared to 33.5% with AWGS 2014. We also added the table 4b regarding the validity of combinations used to diagnose sarcopenia by using AWGS-2019 as a gold standard. The combination of low muscle strength and risk of malnutrition & malnutrition and/or abnormal physical performance (C3) still showed the highest sensitivity and accuracy (Table 4b).

Response: We have added information regarding the outcomes as recommended in methods (Page 7, Line 150-152), results (Page 14-15, Line 287-293) and discussion (Page 18-19, Line 366-376).

4. I also wonder if sarcopenia, when defined according to your new algorithm, is related with poor outcome measures?

Response: Thank you, it was interesting and might be an opportunity to explore for the new project.

Response: We rearranged figure 1 as recommended.

Minor points

Abstract

1. Line 26: muscle mass and muscle functions (strength and function). Please use physical performance term instead of function in parentheses.

Response: We changed as recommended. (Page 2, Line 25)

2. Line 27: Please change the word immobilization with immobile.

Response: We changed as recommended (Page 2, Line 27)

Result section

Response: We rewrote to “Of those, only 84 subjects demonstrated low muscle mass below the recommended cutoff value resulted in a prevalence of sarcopenia in this cohort of 34%”.

3. Line 175-176: Presarcopenia was found in another 34 patients (40%); however, these patients were included in the non–sarcopenia group for all other analyses’’. Here the term presarcopenia refers to patients only with low muscle mass not accompanying low muscle strength and muscle performance. I couldn't catch the rate 40%. 34 out of 104 patients have low muscle mass ?? In addition the term presarcopenia was included in EWGSOP in 2010, not addressed in revised EWGSOP, AWGS in 2014 and updated AWGS in 2019. You may remove this information from method and result sections.

Response: We removed this information regarding “presarcopenia” as recommended.

4. Line 190: Please write open form of the abbreviation CCI

Response: We added open form of CCI as recommended. (Page 11, Line 231)

Discussion

Response: We removed this information as recommended.

2. Discussion is too long, from lines 286 to 315 should be shortened

Response: We shortened this information as recommended.

________________________________________

Reviewer #3:

Dear Author,

However, there are some major points that should be revised substantially. Please find my comments below.

Abstract

1- In the background part its written that ‘’...muscle functions (strength and function)": this phrase is confusing? What do you indicate by function within the parenthesis?

Response: We changed to “physical performance”. (Page 2, Line 25)

2- ‘’ ….which is costly and immobilization’’ This phrase also makes no sense.

Response: We changed to “which is costly and immobile” as recommended by the 1st reviewer.

Response: Thank you for this correction. We changed the word “assessment” to “screening”. (Page 2, Line 27)

Response: Yes, it was the first time suggestion for the screening tool but it was the aim to create this screening tool for screening sarcopenia without muscle mass measurement. We addressed its components in the results part of the abstract.

5- In line 29, ‘’ ...diagnosis performance..’’ It should be "diagnostic performance" In general there are flaws in use of English. English should be edited by a native speaker preferably

Response: Thank you for the correction. The manuscript was edited by the native speaker from our institution, however, there might be something wrong left. We will pay more attention to the gramma next time.

6- In line 29, Instead of elderly, please use "older adults".

Response: We changed as recommended. (Page 2, Line 30)

Response: It might not be very inter-related. Underweight patients might not have malnutrition especially in Thai population. Malnutrition according to MNA-SF, in addition to weight loss, relied on the history of eating, mobilization, stress and neuropsychological problems.

Response: and/or means 3 alternative ways (shown in Table 3, C3).

1. Low muscle strength + Low physical performance + risk of malnutrition/malnutrition

2. Low muscle strength +risk of malnutrition/malnutrition

3. Low physical performance +risk of malnutrition/malnutrition

9- In conclusion part, line 43: We do not screen sarcopenia by muscle mass measurement. The authors might have had a confusion in this regard.

Response: We changed the sentence to “The screening of sarcopenia can be performed using a simpler screening tool”. (Page 2, Line 44)

10- In the keywords, assessment tool is not the right word here. Consider screening tool.

Response: We changed to “screening tool”. (Page 2, Line 47)

Background

1- Two right square brackets in some references, please correct them.

Response: We corrected as recommended.

Response: We removed this sentence.

3- In line 62-65 ‘’ In essence….’’ This sentence is difficult to understand. Please describe better.

Response: We rewrote to “In essence, each deﬁnition proposed to date deﬁnes sarcopenia as a state of decreased skeletal muscle mass and muscle function. Muscle function can be divided into those that require both muscle strength and physical functionality or only one of these elements”. (Page 3, Line 61-64)

4- In line 69 ‘’… muscle quantity and quality’’ instead of "and", you should use "and/or".

Response: We changed as recommended. (Page 3, Line 68)

Response: We added this sentence as recommended. (Page 4, Line 75-76)

Reference:

16. Yilmaz O, Bahat G. Suggestions for assessment of muscle mass in primary care setting. Aging Male. 2017;20:168-9.

Response: Thank you. We changed as recommended. (Page 4, Line 98)

Response: We moved this sentence “Since malnutrition and malignancy were factors that contribute to sarcopenia development, a simple screening tool for screening sarcopenia in patients who have cancer might be possible by incorporating malnutrition and underweight as screening factors.” (Page 4, Line 86-89)

Response: We added as recommended. (Page 4, Line 90-96)

Materials and Methods

1- Its written that it is longitudinal and cross–sectional study. How can a study be both "longitudinal" and cross-sectional? It is conflicting.

Response: We agreed with the prospective longitudinal study. (Page 5, Line 103)

Response: We have addressed this in the limitation section of the discussion and add the sentence “because the bioimpedance analysis (BIA) (Tanita MC–780U Multi Frequency Segmental Body Composition Analyzer; Tanita Corporation, Tokyo, Japan) can measure muscle mass only in the standing position”. (Page 5, Line 113-114)

3- In line 106 about the BIA measurement, Edema/ major fluid electrolyte abnormalities also precludes BIA assessment. Have you excluded those as well?

Response: We performed the BIA measurement in the outpatients who visited the preoperative clinic so we did not exclude the patients who had edema/ major fluid electrolyte abnormalities.

4- In line 118, the scoring categorization of MNA-SF should be integrated.

Response: We added as recommended. (Page 6, Line 131-132)

5- In line 119-120 measuring muscle mass with BIA, Is this appendicular muscle mass or total? You should specify.

Response: We added “appendicular skeletal muscle mass” at that sentence. (Page 6, Line 133)

Response: We corrected the reference and added the information in the limitation section

7- In statistical analysis, have you checked normality? And how?

Response: We added this information in the statistical analysis section.

“The normally distribution was tested by histogram and the Kolmogorov-Smirnov test at P > 0.05.”

Results

1- In line 177 and 179 ‘Eleven patients..., five patients...’ Give % to allow readers understanding the impact of sarcopenia in decision processes better.

Response: We added as recommended. (Page 9, Line 207-211)

Response: Thank you for the suggestion. We added some discussion as recommended. (Page 16-17, Line 320-325)

3- In multivariate analysis, the authors should specify the dependent variable and independent variables in the regression analysis. This should also be given in the Table with a footnote.

Response: We have added a table of multivariate regression and footnote regarding adjusted variables. (Table 2)

4- In line 196, Barthel index is non-significant. Needless to state here.

Response: We removed this sentence as recommended.

Response: We added texts regarding the "probable sarcopenia” in the results section. (Page 13, Line 256-260)

6- Authors are recommended to give AUC values for the formulas as well.

Response: We added AUROC in the table 4 and results section.

7- In line 216, its written that EWGSOP2 demonstrated the highest specificity. Do you indicate confirmed sarcopenia or probable sarcopenia definitions of EWGSOP2 here?

Response: We did the analyses and reported as texts in the results section. (Page 13, Line 256-260)

Discussion

1- Discussion is too long. The authors should first outline main findings of their study and then discuss the findings by comparing with the similar studies in the literature.

Response: We did remove some irrelevant parts of the discussion as recommended.

2- In line 236 ‘In addition to the prevalence of sarcopenia being 34%, the prevalence rate increased with age...’ : I do not think that such detailed discussion on prevalence of sarcopenia in this study and comparison with others is needed. The objective of this study is NOT to report prevalence of sarcopenia. Your objective is to evaluate screening ability of the formulas you suggested. Therefore, shorten the Discussion and be sure that you discuss your findings around your main objective.

Response: We agreed and cut detail about the discussion regarding the prevalence

Response: We agreed and removed some information of this part as well.

Response: We did as recommend.

Attachment

Submitted filename: Response to reviewer__09-07-2021.docx

Click here for additional data file.^{(4.6MB, docx)}

PLoS One. doi: 10.1371/journal.pone.0257672.r003

Decision Letter 1

Joao Felipe Mota

11 Aug 2021

PONE-D-21-00876R1

A simpler screening tool for sarcopenia in surgical patients

PLOS ONE

Dear Dr. Chaiwat,

==============================

Please consider the reviewers and editor comments.

==============================

Please submit your revised manuscript by Sep 25 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Joao Felipe Mota

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

The study has many limitations which are addressed in this new version. I also consider as an important concern the inclusion of patients with oedema, so the authors should mention it in the limitation section.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: No

**********

6. Review Comments to the Author

Reviewer #2: Most of my concerns are addressed, but the text still needs a minör revision:

1.Please prefer the term “older adults” instead of “elderly” throughout the text

2.The text still needs a rigorous editing,

3.My suggestions for some phrases that cause misunderstanding are as follows:

Introduction

Line 77-78: The sentence’’ the DXA and BIA have some limitation in terms of the accessibility, and costly equipment’’. Please add the plural suffix ‘’s’’ to the word limitation. Instead of ‘’costly equipman’’ please write ‘’cost’’ only.

Line 95: In the sentence …….any one tool……, please remove the word ‘’one’’, write as ….any tool…

Line 97: Instead of ‘’diagnosis performance’’, please write ‘’diagnostic performance’’

Material and methods

Line 128: Other collected data included……Here the term other refers to components of MNA-SF tool. But it is perceived as a different data apart from MNA-SF tool. I recommend combine with previous sentence and you may write as ‘’ Preoperative nutritional screening was performed using the Mini Nutritional Assessment - Short Form (MNA® 128 –SF), which included reduction in dietary intake within the past three months, body mass index (BMI), history of weight loss within the last three months, mobility, psychological stress and/ or acute disease within the past 3 months, and neuropsychological problems.’’

Results

Line 249: Please rewrite subheading, you may write as ‘’ Diagnostic performance of a simple tool for screening sarcopenia’’

Line 250-252: Please rewrite the sentence ‘’The combination of low muscle strength and risk of malnutrition & malnutrition and/ or abnormal physical performance (C3) showed the highest sensitivity and accuracy either the AWGS or the updated AWGS as the gold standards’’you may write as ‘’ The combination of low muscle strength and risk of malnutrition & malnutrition and/ or abnormal physical performance (C3) showed the highest sensitivity and accuracy when using the AWGS or the updated AWGS as the gold standards’’

Line 252-254:Please rewrite the sentence ‘’ The sensitivity, specificity, accuracy and AUROC were 81.0%, 78.4%, 79.3% and 0.8, respectively as compared to C1, C2 and C4 when using AWGS as a gold standard’’. In this sentence percent results are belong to C3, but C3 is not mentioned in the sentence, in addition sentence gives the statistical information only related to C3, there is not a comparision between the statistical results of the formulas. You may rewrite the sentence as ‘’ The sensitivity, specificity, accuracy and AUROC of C3 were 81.0%, 78.4%, 79.3% and 0.8, respectively when using AWGS as gold standard.’’

Line 264-266: with similar reasons as above mentioned you may rewrite the sentence as ‘’ The sensitivity, specificity, accuracy, and AUROC of C3 were 80% , 68. 5% , 73. 3% and 0.74 respectively when using the updated AWGS criteria as gold standard (Table 4b).’’

Discussion

Line 306-308: Please rewrite the sentence, you may rewrite as ‘’ The combination of low muscle strength and risk of malnutrition & malnutrition and/or abnormal physical performance (C3), demonstrated high sensitivity, specificity, and predictive power when validated against a consensus of the Asian Working Group for Sarcopenia (AWGS).

Line 329: Please write immobile instead of immobilization

Reviewer #3: *English should be improved in the whole writing.

Abstract

*Page 2, Line 27: ‘Non-portable’ should be used instead of immobile device.

*Page 2, Line 28: The aim of this study was to design and validate the diagnostic performance of a simple screening tool for screening sarcopenia

These formula are not suggested for diagnosis of sarcopenia. Therefore, ‘diagnostic’ term should not be used.

*Page 2, Line 32: The details about this screening tool should be explained in methods part. Which parameters were considered for analyses, the details about formula should be briefly mentioned.

*Page 2, Line 37: Malnutrition and underweight status are surely expected to be strongly related. Therefore, before putting into the same regression analysis, multicollinearity should be checked.

Background

*Page 3, Line 57: In whole writing, elderly term should be changed to older adults.

*Page 3, Line 62: Muscle function can be divided into those that require both muscle strength and physical functionality or only one of these elements.

Functionality should be revised as ‘performance’.

*Introduction should be shortened.

Materials and methods

*Page 5, Study population exclusion criteria: Edema can also affect the BIA results, therefore, measurements without regarding edema status should also be stated as a limitation of the study.

*Page 7, Line 155: At risk and malnutrition and underweight BMI were considered to be factors for diagnosing sarcopenia.

Underweight BMI should be changed as ‘Being underweight by BMI’. Again, language revision should be done seriously.

Results

*Page 12, Line 249: Diagnosis performance a simple tool for screening sarcopenia

Diagnostic performance term should not be used. These formula were suggested for sarcopenia screening, so 'screening' and 'diagnosis' terms should not be used interchangeably.

*Page 13, Line 256: EWGSOP2 demonstrated the highest specificity (100%).

Whether the high specificity proposed by EWGSOP2 is for probable sarcopenia or confirmed sarcopenia should be stated.

Discussion

*Page 18, Line 355: Although, there was a slightly low specificity and PPV in female, we introduced a practical algorithm for a diagnosis of sarcopenia in elderly cancerous surgical patients without using muscle mass measurement (Fig 2).

The algorhythm the authors proposed for sarcopenia diagnosis seems problematic. The authors should decide whether they propose this formula for screening (finding cases) or assessment of sarcopenia. In addition, muscle mass measurement was included for diagnosis in the algorhythm. But they claimed that the algorhythm enables to diagnose sarcopenia without muscle mass measurement. There seems a paradox.

Conclusion

*Conclusion should be shortened. The first two sentences are the findings previously mentioned, unnecessary to repeat at the end.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: Yes: Firuzan Fırat Özer

Reviewer #3: Yes: Gulistan Bahat

Attachment

Submitted filename: Review PLOSOne-The validity of a simple screening tool.docx

Click here for additional data file.^{(14.7KB, docx)}

Attachment

Submitted filename: second review.docx

Click here for additional data file.^{(16.6KB, docx)}

PLoS One. 2021 Sep 23;16(9):e0257672. doi: 10.1371/journal.pone.0257672.r004

Author response to Decision Letter 1

5 Sep 2021

Dear editors,

We attached file the responses to the reviewers to this resubmission.

Please find our point-by-point responses.

Regards,

Onuma Chaiwat

Attachment

Submitted filename: Response to reviewer__5092021.pdf

Click here for additional data file.^{(1.4MB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0257672.r005

Decision Letter 2

Joao Felipe Mota

8 Sep 2021

A simpler screening tool for sarcopenia in surgical patients

PONE-D-21-00876R2

Dear Dr. Chaiwat,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Joao Felipe Mota

Academic Editor

PLOS ONE

PLoS One. doi: 10.1371/journal.pone.0257672.r006

Acceptance letter

Joao Felipe Mota

14 Sep 2021

PONE-D-21-00876R2

A simpler screening tool for sarcopenia in surgical patients

Dear Dr. Chaiwat:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Joao Felipe Mota

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 File. Raw data of screening tool for sarcopenia.

(XLSX)

Click here for additional data file.^{(24KB, xlsx)}

Attachment

Submitted filename: Review.docx

Click here for additional data file.^{(16.7KB, docx)}

Attachment

Submitted filename: Review Plus-One.docx

Click here for additional data file.^{(21.7KB, docx)}

Attachment

Submitted filename: Response to reviewer__09-07-2021.docx

Click here for additional data file.^{(4.6MB, docx)}

Attachment

Submitted filename: Review PLOSOne-The validity of a simple screening tool.docx

Click here for additional data file.^{(14.7KB, docx)}

Attachment

Submitted filename: second review.docx

Click here for additional data file.^{(16.6KB, docx)}

Attachment

Submitted filename: Response to reviewer__5092021.pdf

Click here for additional data file.^{(1.4MB, pdf)}

Data Availability Statement

All relevant data are within the paper and its Supporting Information files.

[pone.0257672.ref001] 1.Blackwell DL, Lucas JW, Clarke TC. Summary health statistics for U.S. adults: national health interview survey, 2012. Vital Health Stat 10. 2014:1–161. [PubMed] [Google Scholar]

[pone.0257672.ref002] 2.Office of the National Econimic and Social Development Board. Population projections for Thailand 2010–2040. Bangkok, Thailand; 2013.

[pone.0257672.ref003] 3.Wagner D, DeMarco MM, Amini N, Buttner S, Segev D, Gani F, et al. Role of frailty and sarcopenia in predicting outcomes among patients undergoing gastrointestinal surgery. World J Gastrointest Surg. 2016;8:27–40. doi: 10.4240/wjgs.v8.i1.27 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref004] 4.Zbar AP, Gravitz A, Audisio RA. Principles of surgical oncology in the elderly. Clin Geriatr Med. 2012;28:51–71. doi: 10.1016/j.cger.2011.09.002 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref005] 5.Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010;39:412–23. doi: 10.1093/ageing/afq034 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref006] 6.Muscaritoli M, Anker SD, Argilés J, Aversa Z, Bauer JM, Biolo G, et al. Consensus definition of sarcopenia, cachexia and pre-cachexia: joint document elaborated by Special Interest Groups (SIG) "cachexia-anorexia in chronic wasting diseases" and "nutrition in geriatrics". Clin Nutr. 2010;29:154–9. doi: 10.1016/j.clnu.2009.12.004 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref007] 7.Fielding RA, Vellas B, Evans WJ, Bhasin S, Morley JE, Newman AB, et al. Sarcopenia: an undiagnosed condition in older adults. Current consensus definition: prevalence, etiology, and consequences. International working group on sarcopenia. J Am Med Dir Assoc. 2011;12:249–56. doi: 10.1016/j.jamda.2011.01.003 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref008] 8.Morley JE, Abbatecola AM, Argiles JM, Baracos V, Bauer J, Bhasin S, et al. Sarcopenia with limited mobility: an international consensus. J Am Med Dir Assoc. 2011;12:403–9. doi: 10.1016/j.jamda.2011.04.014 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref009] 9.Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al. Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc. 2014;15:95–101. doi: 10.1016/j.jamda.2013.11.025 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref010] 10.McLean RR, Shardell MD, Alley DE, Cawthon PM, Fragala MS, Harris TB, et al. Criteria for clinically relevant weakness and low lean mass and their longitudinal association with incident mobility impairment and mortality: the foundation for the National Institutes of Health (FNIH) sarcopenia project. J Gerontol A Biol Sci Med Sci. 2014;69:576–83. doi: 10.1093/gerona/glu012 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref011] 11.Nishikawa H, Shiraki M, Hiramatsu A, Moriya K, Hino K, Nishiguchi S. Japan Society of Hepatology guidelines for sarcopenia in liver disease (1st edition): Recommendation from the working group for creation of sarcopenia assessment criteria. Hepatol Res. 2016;46:951–63. doi: 10.1111/hepr.12774 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref012] 12.Akishita M, Kozaki K, Iijima K, Tanaka T, Shibasaki K, Ogawa S, et al. Chapter 1 Definitions and diagnosis of sarcopenia. Geriatr Gerontol Int. 2018;18Suppl 1:7–12. doi: 10.1111/ggi.13311 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref013] 13.Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48:16–31. doi: 10.1093/ageing/afy169 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref014] 14.Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J Am Med Dir Assoc. 2020;21:300–7.e2. doi: 10.1016/j.jamda.2019.12.012 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref015] 15.Mijnarends DM, Meijers JM, Halfens RJ, ter Borg S, Luiking YC, Verlaan S, et al. Validity and reliability of tools to measure muscle mass, strength, and physical performance in community-dwelling older people: a systematic review. J Am Med Dir Assoc. 2013;14:170–8. doi: 10.1016/j.jamda.2012.10.009 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref016] 16.Yilmaz O, Bahat G. Suggestions for assessment of muscle mass in primary care setting. Aging Male. 2017;20:168–9. doi: 10.1080/13685538.2017.1311856 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref017] 17.Shaw KA, Srikanth VK, Fryer JL, Blizzard L, Dwyer T, Venn AJ. Dual energy X-ray absorptiometry body composition and aging in a population-based older cohort. Int J Obes (Lond). 2007;31:279–84. [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref018] 18.Rubbieri G, Mossello E, Di Bari M. Techniques for the diagnosis of sarcopenia. Clin Cases Miner Bone Metab. 2014;11:181–4. [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref019] 19.Bruun LI, Bosaeus I, Bergstad L, Nygaard K. Prevalence of malnutrition in surgical patients: evaluation of nutritional support and documentation. Clin Nutr. 1999;18:141–7. doi: 10.1016/s0261-5614(99)80003-x [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref020] 20.MacKay D, Miller AL. Nutritional support for wound healing. Altern Med Rev. 2003;8:359–77. [PubMed] [Google Scholar]

[pone.0257672.ref021] 21.Pacelli F, Bossola M, Rosa F, Tortorelli AP, Papa V, Doglietto GB. Is malnutrition still a risk factor of postoperative complications in gastric cancer surgery? Clin Nutr. 2008;27:398–407. doi: 10.1016/j.clnu.2008.03.002 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref022] 22.Sungurtekin H, Sungurtekin U, Balci C, Zencir M, Erdem E. The influence of nutritional status on complications after major intraabdominal surgery. J Am Coll Nutr. 2004;23:227–32. doi: 10.1080/07315724.2004.10719365 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref023] 23.Edington J, Boorman J, Durrant ER, Perkins A, Giffin CV, James R, et al. Prevalence of malnutrition on admission to four hospitals in England. The Malnutrition Prevalence Group. Clin Nutr. 2000;19:191–5. doi: 10.1054/clnu.1999.0121 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref024] 24.Correia MI, Waitzberg DL. The impact of malnutrition on morbidity, mortality, length of hospital stay and costs evaluated through a multivariate model analysis. Clin Nutr. 2003;22:235–9. doi: 10.1016/s0261-5614(02)00215-7 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref025] 25.Bahat G, Oren MM, Yilmaz O, Kılıç C, Aydin K, Karan MA. Comparing SARC-F with SARC-CalF to Screen Sarcopenia in Community Living Older Adults. J Nutr Health Aging. 2018;22:1034–8. doi: 10.1007/s12603-018-1072-y [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref026] 26.Barbosa-Silva TG, Menezes AM, Bielemann RM, Malmstrom TK, Gonzalez MC. Enhancing SARC-F: Improving Sarcopenia Screening in the Clinical Practice. J Am Med Dir Assoc. 2016;17:1136–41. doi: 10.1016/j.jamda.2016.08.004 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref027] 27.Yu SC, Khow KS, Jadczak AD, Visvanathan R. Clinical Screening Tools for Sarcopenia and Its Management. Curr Gerontol Geriatr Res. 2016;2016:5978523. doi: 10.1155/2016/5978523 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref028] 28.Kaiser MJ, Bauer JM, Ramsch C, Uter W, Guigoz Y, Cederholm T, et al. Validation of the Mini Nutritional Assessment short-form (MNA-SF): a practical tool for identification of nutritional status. J Nutr Health Aging. 2009;13:782–8. doi: 10.1007/s12603-009-0214-7 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref029] 29.Rubenstein LZ, Harker JO, Salva A, Guigoz Y, Vellas B. Screening for undernutrition in geriatric practice: developing the short-form mini-nutritional assessment (MNA-SF). J Gerontol A Biol Sci Med Sci. 2001;56:M366–72. doi: 10.1093/gerona/56.6.m366 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref030] 30.Limpawattana P, Kotruchin P, Pongchaiyakul C. Sarcopenia in Asia. Osteoporosis Sarcopenia. 2015;1:92–7. [Google Scholar]

[pone.0257672.ref031] 31.Limpawattana P. Frailty and Sarcopenia. In: Assantachai P, Niamhom S, Thongnuam N, editors. Guidelines for management of Geriatric syndromes: Institute of Geriatric Medicine, Department of Medical Service, Ministry of Public health. August Publishing Ltd; Nonthaburi, Thailand, 2015. pp. 39–51. [in Thai] [Google Scholar]

[pone.0257672.ref032] 32.Cruz-Jentoft AJ, Landi F, Schneider SM, Zúñiga C, Arai H, Boirie Y, et al. Prevalence of and interventions for sarcopenia in ageing adults: a systematic review. Report of the International Sarcopenia Initiative (EWGSOP and IWGS). Age Ageing. 2014;43:748–59. doi: 10.1093/ageing/afu115 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref033] 33.Khongsri N, Tongsuntud S, Limampai P, Kuptniratsaikul V. The prevalence of sarcopenia and related factors in a community-dwelling elders Thai population. Osteoporosis Sarcopenia. 2016;2:110–5. doi: 10.1016/j.afos.2016.05.001 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref034] 34.Fukuda Y, Yamamoto K, Hirao M, Nishikawa K, Nagatsuma Y, Nakayama T, et al. Sarcopenia is associated with severe postoperative complications in elderly gastric cancer patients undergoing gastrectomy. Gastric Cancer. 2016;19:986–93. doi: 10.1007/s10120-015-0546-4 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref035] 35.Bahat G, İlhan B. Sarcopenia and the cardiometabolic syndrome: A narrative review. Eur Geriatr Med. 2016;7:220–3. [Google Scholar]

[pone.0257672.ref036] 36.Malmstrom TK, Morley JE. SARC-F: a simple questionnaire to rapidly diagnose sarcopenia. J Am Med Dir Assoc. 2013;14:531–2. doi: 10.1016/j.jamda.2013.05.018 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref037] 37.Woo J, Leung J, Morley JE. Validating the SARC-F: a suitable community screening tool for sarcopenia? J Am Med Dir Assoc. 2014;15:630–4. doi: 10.1016/j.jamda.2014.04.021 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref038] 38.Ishii S, Tanaka T, Shibasaki K, Ouchi Y, Kikutani T, Higashiguchi T, et al. Development of a simple screening test for sarcopenia in older adults. Geriatr Gerontol Int. 2014;14Suppl 1:93–101. doi: 10.1111/ggi.12197 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref039] 39.Goodman MJ, Ghate SR, Mavros P, Sen S, Marcus RL, Joy E, et al. Development of a practical screening tool to predict low muscle mass using NHANES 1999–2004. J Cachexia Sarcopenia Muscle. 2013;4:187–97. doi: 10.1007/s13539-013-0107-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref040] 40.Visvanathan R, Yu S, Field J, Chapman I, Adams R, Wittert G, et al. Appendicular Skeletal Muscle Mass: Development and Validation of Anthropometric Prediction Equations. J Frailty Aging. 2012;1:147–51. doi: 10.14283/jfa.2012.23 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref041] 41.Yu S, Appleton S, Chapman I, Adams R, Wittert G, Visvanathan T, et al. An anthropometric prediction equation for appendicular skeletal muscle mass in combination with a measure of muscle function to screen for sarcopenia in primary and aged care. J Am Med Dir Assoc. 2015;16:25–30. doi: 10.1016/j.jamda.2014.06.018 [DOI] [PubMed] [Google Scholar]

[pone.0257672.ref042] 42.Santilli V, Bernetti A, Mangone M, Paoloni M. Clinical definition of sarcopenia. Clin Cases Miner Bone Metab. 2014;11:177–80. [PMC free article] [PubMed] [Google Scholar]

[pone.0257672.ref043] 43.Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gómez JM, et al. Bioelectrical impedance analysis—part I: review of principles and methods. Clin Nutr. 2004;23:1226–43. doi: 10.1016/j.clnu.2004.06.004 [DOI] [PubMed] [Google Scholar]

PERMALINK

A simpler screening tool for sarcopenia in surgical patients

Onuma Chaiwat

Mingkwan Wongyingsinn

Weerasak Muangpaisan

Chalobol Chalermsri

Arunotai Siriussawakul

Pornpoj Pramyothin

Poungkaew Thitisakulchai

Panita Limpawattana

Chayanan Thanakiattiwibun

Roles

Abstract

Background

Methods

Results

Conclusion

Background

Materials and methods

Design

Study population

Measurement instruments and data collection

Fig 1. Flow chart of malnutrition and sarcopenia screening.

Design of a simple tool for sarcopenia diagnosis

Table 1. Combinations used to diagnose sarcopenia.

Statistical analysis

Results

Diagnosis of sarcopenia

Factors associated with sarcopenia

Table 2. Demographic, clinical, and surgical characteristics and outcomes.

Table 3. Independent risk factors associated with preoperative sarcopenia.

Screening performance of the tool

Table 4. Validity of combinations used to diagnose sarcopenia.

Sarcopenia and clinical outcomes

Discussion

Fig 2. Algorithm for proposed sarcopenia screening in older-adult, surgical oncology patients.

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Jamie Males

Roles

Author response to Decision Letter 0

Decision Letter 1

Joao Felipe Mota

Roles

Author response to Decision Letter 1

Decision Letter 2

Joao Felipe Mota

Roles

Acceptance letter

Joao Felipe Mota

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases