Validated Screening tools for the Assessment of Cachexia, Sarcopenia and Malnutrition

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Validated screening tools for the assessment of Cachexia, Sarcopenia and Malnutrition: A systematic review

  

Abstract

 

Introduction

There is a great deal of overlap between the presentation of cachexia, sarcopenia and malnutrition in the clinical setting. It is difficult to distinguish between these three conditions but the ability to do so would allow for better targeted treatment for patients. There are currently over 70 different screening tools described but a definitive, validated tool to assess all three simultaneously is lacking.

Aim

To systematically review validated screening tools for cachexia, sarcopenia and malnutrition in the generalised adult population and, if a combined tool is absent, to make suggestions for the generation of a novel screening tool.

Methods

A systematic search was performed in Ovid MEDLINE, EMBASE, CINAHL (Cumulative index to Nursing and Allied Health Literature) and Web of Science. Relevant articles were identified by title and abstract, and two reviewers performed data extraction independently. Each tool was judged for validity against a reference method, and psychometric evaluation was performed. The ability of the tool to assess the patient against the agreed consensus definition for each condition was also appraised.

Results

Thirty studies described 22 validated screening tools.

The CASCO was the only screening tool for cachexia that had been validated. It performed well against diagnostic criteria (Fearon 2011), but sensitivities and specificities were not recorded.

Only two tools assessed sarcopenia (the SPSM and the SARC-F) and scored well against the agreed definition (Baumgartner 1998). However, the SPSM required a large amount of equipment and the SARC-F had a very low sensitivity.

Nineteen tools screened for malnutrition. The 3 MinNS proved to be the best, scoring well against the consensus definition (ESPEN) as well as having sensitivities and specificities >80%.

All tools, however, showed inconsistent results and no tool contained all the currently accepted components required to screen for all three conditions. Furthermore, none of the tools has been measured against cross-sectional imaging, a clinical tool that is gaining wider interest as a means of body composition analysis.

Conclusion

No one validated screening tool can be implemented for the simultaneous assessment of cachexia, sarcopenia and malnutrition. The development of a tool that encompasses current consensus definition criteria and directs clinicians towards the specific underlying diagnosis would be optimal in order to target treatment and improve outcomes. We propose that such a future tool should incorporate a stepwise assessment of nutritional status; oral intake; disease status; patient age; muscle mass/function; and metabolic derangement.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Introduction

Unintentional weight loss (UWL) as a form of nutritional depletion is commonly seen in ageing, cancer and many chronic diseases. The main subtypes can be categorised into three primary syndromes: cachexia, age-related sarcopenia and malnutrition; however, it is not clear whether existing screening tools are able to distinguish between these three conditions. This is due in part to the complex overlap between them. There are many definitions for each condition, with nutritional depletion playing a part in each, therefore making it difficult to separate them out [1,2,3,4]. These conditions are also often not noticed in their earlier phases but do become apparent following a critical event or development of disability[5].

More than 70 nutritional screening tools for use in hospitals have been developed to facilitate easy screening or assessment of a patient’s nutritional status or to predict poor clinical outcome related to UWL. Despite increasing research, there appears to be a lack of a practical and implementable clinical screening tool to support diagnosis. Some tools have been endorsed by international nutrition societies: for example, the European Society for Clinical Nutrition and Metabolism advises the use of MUST [6,7], NRS-2002 [8] in the general community and hospital settings, and the MNA (-SF) for the elderly [9,10]. Some tools claim to have been developed to screen in specific target groups however, there are currently no disease specific recommendations. There is no international consensus on a single ‘best tool’ to identify all three syndromes across populations. The use of different tools in different studies hinders their comparison and meta-analyses, and makes drawing any conclusions difficult.

Current diagnostic methods for sarcopenia and cachexia include the assessment of body anthropometry using either body mass index (BMI) or estimated weight loss, or by direct assessment of muscle and fat mass using dual-energy X-Ray absorptiometry (DEXA), bioelectrical impedance analysis (BIA), CT or MRI scanning. Whilst the latter two radiographic modalities are accurate, they are impractical, expensive and some expose the patient to radiation. This diagnostic approach to detect the presence of sarcopenia is time consuming, expensive and requires highly specialised equipment [11]. Therefore, a screening strategy that is implementable in a larger population that allows for early detection is important. This approach would highlight the potential for further assessment with early biomarkers, thus allowing prophylactic intervention in malnutrition and driving further research in sarcopenia and cachexia.

We aimed to generate an overview of validated screening tools for the general adult population to enable clinicians to distinguish between the three syndromes. The specific strengths and limitations of each tool were assessed, as was the appropriateness of the validation population. Through psychometric evaluation and assessment of the tools against the agreed consensus definitions, we also investigated if any one single tool could be used for the simultaneous assessment of all three.

 

 

 

 

 

 

Methods

Methods for conducting systematic reviews of the effectiveness of interventions have been well described. In accordance with PRISMA guidelines [12] we applied the principles to systematically reviewing validated screening tools used in the assessment of cachexia, sarcopenia and malnutrition.

Literature review

A systematic search was performed on 26th September 2017 in Ovid MEDLINE (1946-2017), EMBASE (1974-2017), CINAHL (Cumulative index to Nursing and Allied Health Literature) and Web of Science. Relevant articles were identified by title and abstract. Reference lists of review articles were also hand searched. Double data extraction was performed by two reviewers.

The basic search strategy was “Sarcopenia” OR “Cachexia” OR “Malnutrition” AND “screening” AND “validation study” using MeSH terms and keywords appropriate to each database. No language restriction was imposed. The search was designed to be broad to ensure all validated tools were identified. A full copy of the search used for MEDLINE can be found in appendix I. There were no disease specific limits.

Inclusion and exclusion criteria

Studies were included if they had developed a screening tool which had been validated for the screening of either cachexia, sarcopenia or malnutrition in adults. (Table I) Disease specific tools were included. Papers were excluded if the tools had not been validated or if they assessed malnutrition in children or obesity in adults. Studies which described modified versions of pre-existing tools were also excluded as this was out with the scope of this review. It was intended that studies that included less than 25 patients should be excluded as they were unlikely to yield robust, generalisable psychometric results, however no studies with numbers smaller than this were found.

Assessment of Validity

Studies had to have evaluation of at least two of the following psychometric characteristics:

  • Content validity
  • Construct validity e.g. including convergent validity, discriminant validity
  • Test-retest reliability
  • Internal consistency
  • Responsiveness
  • Factor analysis
  • Criterion validity

Primary criteria used to evaluate the tools were construct validity and responsiveness.

Criterion and construct validity, reference method

Studying the validity of a tool usually compares to a gold standard. Although many research groups are now using cross sectional imaging to investigate UWL there is currently the absence of a perfect gold standard. Studies used different reference methods to validate their tools e.g. DEXA and assessment by a health professional.

The term criterion validity was used for these comparisons. The following reference methods were therefore considered to be less valid:

  • Other screening tools as they require further assessment by a professional
  • Blood tests such as albumin as they can be influenced by other factors such as acute disease and are therefore not a true reflection of long term nutritional state [13]

For these comparisons, we use the term construct validity. Still, many studies have used these less valid methods as a reference. Since an ideal gold standard is missing, and (research) groups may differ in their opinion on the optimal reference method, we included all validated studies.

Predictive validity

Predictive validity was assessed as the ability of the tool to predict the probability of a better or worse clinical outcome due to nutritional risk.

Table 1 Inclusion criteria

Types of participants

Adult hospital patients (>18 years) undergoing routine screening for cachexia, sarcopenia, or malnutrition

Includes patients with advanced cancer, end stage cardiac, renal and liver disease
Types of tools

Validated, quantitative measurements of cachexia, sarcopenia or malnutrition

Tools developed for clinical or research purposes. Completed by health care professionals
Psychometric evaluation

Content Validity

Construct validity, including convergent validity, discriminant validity

Test-retest reliability

Internal consistency

Responsiveness

Factor analysis

Criterion validity

Demonstration of at least 2 criteria:

Breadth of scope of tool; to what extent does it appear to capture the relevant aspects of unintentional weight loss; are there gaps?

How well the tool relates to other measures of the same construct; lack of correlation with dissimilar or unrelated constructs or variables

How consistent an individual’s scores are over a defined time-period presuming weight stays constant

How closely related are the different items in the tool?

Ability to detect clinically meaningful change for individuals

For a tool comprising several items, a way of grouping them into factors which may tap into a particular construct

A shortened version of a scale, concurrent validity with the longer version which has been validated

Diagnostic criteria

Tools were also assessed for their ability to identify the risk of cachexia, sarcopenia or malnutrition by comparison of their components against the components of each set of diagnostic criteria.

Table II Summary of proposed diagnostic criteria for identification of cachexia, sarcopenia and malnutrition

Syndrome Diagnostic criteria
Cachexia Weight loss greater than 5%, or weight loss greater than 2% in individuals already showing depletion according to current bodyweight and height (body-mass index [BMI] <20 kg/m2) or skeletal muscle mass (sarcopenia) [3]
Sarcopenia Loss of function – 6-minute walk < 400m OR gait speed <1.0m/s

Muscle mass – low appendicular lean mass/height [2](2 standard deviations below the mean diagnostic on DXA) [1,2]

Malnutrition Protein/energy deficiency – risk indicated by low BMI <18.5 kg/m2 OR weight loss >10% (indefinite time)/5% over last 3 months AND BMI <20 (if <70 years)/ <22 (if>70 years) or FFMI < 15 and 17 kg/m2 in men and women respectively [4]

Secondary criteria

Secondary criteria included face validity, development and content validity, factor analysis, test-retest reliability, internal consistency, respondent and administrative burden (the time and effort required to complete the tool). These are also summarised in table I. Data were extracted concerning the study participants, the tool used and psychometric evaluations (Inclusion criteria Table I).

 

Results

Records identified through database searching (n=4781)

Additional records identified through other sources
(n = 8)

Identification

Duplicates removed
(n = 1361)

Screening

Records screened
(n = 3428)

Records excluded
(n =3350)

Full-text articles assessed for eligibility
(n =78)

Full-text articles excluded
(n = 48)

Eligibility

Studies included in qualitative synthesis
(n =30)

Included

Figure I PRISMA flow diagram [12]

Number of screening tools included
(n =22)

Table III Description of tools to measure unintentional weight loss

  Author Tool Description Validation population Validation reference Strengths Limitations
Sarcopenia Woo et al (14)

Miller et al (15)

SARC-F

SPSM

A questionnaire regarding ability to carry a heavy load, walking, rising from a chair, climbing stairs and falls frequency

Portable measure that combines estimates of muscle quantity and function into a single scale

Community dwelling Chinese (n=4000)

Community dwelling African Americans (n=998)

3 consensus definitions of sarcopenia

DEXA

Not dependent on cut off values

Portable

No assessment of muscle mass, not validated in hospital populations

Time consuming, equipment dependent, muscle mass not measured

Cachexia Argiles et al (16) CASCO Score to classify cachectic patients into three different groups. Includes five components: body weight loss & composition, inflammation/metabolic disturbances/immunosuppression, physical performance, anorexia and quality of life Cancer patients (n=186) Assessment by oncologist Encompasses all diagnostic criteria Involves many questions and measurements, does not include questions on disease state
Malnutrition Weekes et al (17)

Mimiram et al (18)

Laporte et al (19)

Ignacio et al (20)

Guerra et al (21)

Abd-El-Gawad et al (22)

Tammam et al (23)

Ferguson et al (24)

Isenring et al (25)

Neelemaat et al (26)

Nursal et al (27)

Young et al (28)

Wu et al (29)

Ji-Yeon et al (30)

Boleo-Tome et al (31)

Leistra et al (32)

Sharma et al (33)

Neelemaat et al (26)

Kyle et al (34)

Young et al (28)

Almedia et al (35)

Velasco et al (36)

Prasad et al (37)

Faramarzi et al (38)

Neelemaat et al (26)

Kyle et al (34)

Young et al (28)

Almedia et al (35)

Bauer et al (39)

Velasco et al (36)

Soederhamn et al (40)

Duerksen et al (41)

Cooper et al (42)

Moriana et al (43)

Kruizenga et al (44)

Leistra et al (32)

Harada et al (45)

Neelemaat et al (26)

Young et al (28)

Susetyowati et al (46)

Wong et al (47)

Xia et al (48)

Lim et al (49)

BAPEN

BNST

CNST

CONUT

EDC

GNRI

INSYST

MST

MSTC

MUST

NRI

NRS-2002

NUFFE

SGA

SNAQ

SNST

Spinal NST

R-NST

3-MinNS

Tool based on four nutritional parameters (weight, height, recent unintentional weight loss and appetite)

Score based on UWL, unintentional eating loss and being unable to eat for >5 days

Tool containing two items: Weight loss and decreased food intake

Evaluates nutrition using albumin, cholesterol and lymphocyte count. Automated system

Screening tool based on ESPEN criteria for diagnosis malnutrition

Modified nutritional risk index for geriatric patients (based on albumin, current and previous weight)

Two-tiered tool – first is a simple pre-screen aiming to establish if malnourished, second provides a more detailed evaluation

Two questions regarding appetite and unintentional weight loss

Tool based on intake change, weight loss, ECOG performance status and BMI

Five step tool including BMI, unplanned weight loss and presence of acute disease

Derived from serum albumin concentration and ratio of usual to present weight

Tool containing nutritional components of the MUST along with disease severity

Three-point ordinal scale with 15 items assessing weight loss, dietary history, appetite and general activity

Assessment of nutritional status based on history and examination

26 questions related to eating and drinking difficulties, defecation, condition and pain

Six questions including weight loss, appetite and health status

Tool which assesses eight criteria including appetite, weight loss and level of spinal cord injury

Nine questions assessing malnutrition risk/symptoms combined with albumin, CRP and urea

Questionnaire based on diagnostic criteria for malnutrition and muscle wastage

Acute medical and elderly care wards (n=100)

Medical and surgical (n=446)

Medical and surgical (n=150)

Medical and surgical inpatients (n=53)

Medical and surgical inpatients (n=632)

Acute geriatrics ward (n=131)

Medical, surgical and oncological inpatients (n=61)

Medical and surgical inpatients (n=408)

Oncology outpatients (n=51)

Acute hospitalised (n=193)

Medical and surgical inpatients (n=2211)

Elderly medical inpatients (n=134)

Elderly inpatients (n=157)

Oncology inpatients (n=1057)

Oncology inpatients (n=450)

Medical and surgical outpatients (n=2236)

Acute medical inpatients (n=132)

Elderly inpatients (n=198)

Medical and surgical (n=995)

Medical inpatients (n=134)

Surgical inpatients (n=300)

Medical and surgical (n=400)

Peritoneal dialysis patients (n=283)

Colorectal cancer (n=52)

Elderly inpatients (n=198)

Medical and surgical (n=995)

Elderly medical patients (n=134)

Surgical inpatients (n=300)

Acute geriatrics ward (n=121)

Medical and surgical (n=400)

Elderly care rehab ward (n=114)

Acute elderly care and elderly rehab (n=95)

End stage renal disease (n=76)

Medical and surgical inpatients (n=197)

Medical, surgical and oncological inpatients (n=291)

Medical and surgical outpatients (n=2236)

Oncology outpatients undergoing chemotherapy (n=300)

Medical and surgical inpatients (n=2211)

Elderly medical inpatients (n=134)

Medical and surgical inpatients (n=495)

Spinal cord injury patients (n=150)

Renal inpatients (n=122)

Medical and surgical inpatients (n=818)

Dietician

Dietician

SGA

SGA

PG-SGA

MNA

MUST and MNA

SGA

PG-SGA

Malnutrition definition

PG-SGA

PG-SGA

Malnutrition definition

SGA

Definition of malnutrition

SGA

MNA

Geriatric and internal medicine resident, Total body Nitrogen, Anthropometric and biochemical data

Malnutrition criteria, CONUT

SGA

Dietetic assessment

SGA

SGA

Quick and easy

Easily completed by nursing staff

Very brief, can be completed by non-trained rater

Simple, automated

Includes FFM assessment

Good prognosticator, does not require capacity

Doesn’t require height and BMI, quick and easy

Very quick, does not require calculations

Cancer specific

Quick, easy

Assesses dialysis patients at risk

Includes disease severity therefore applicable in ITU

Simple as lacks anthropometric measurements

Current gold standard

Corresponds to ESPEN criteria

Can be done by non-trained staff

Disease specific

Renal specific

Quick and easy

Percentage weight loss not quantified

Low importance given to amount of weight loss

Assessed on admission only. Validity of re-screening unknown

Markers vary depending on disease state, only done on patients who have bloods taken

Very low sensitivity

Diseases associated with high mortality or hypoalbuminaemia excluded

Ease of completing dependent on patient’s cognitive state

Non-specific

Designed to be performed by dieticians, not nurses

Does not pick up patients with normal BMI who are malnourished, UWL reported by patients is subjective

Relies on previous weight – limited use with changes in fluid status

Ease of completing dependent on patient’s cognitive state

Many confounding factors in questionnaire

Reproducibility less than in non-elderly, unable to predict severe malnutrition in ESRD, requires experienced operator to carry out

High NPV, no outcome data

No anthropometric assessment, all subjective

Requires specialised scales to measure paralysed patients

Patients picked up for conditions other than malnutrition e.g. hyperkalaemia

Dependent on cognitive state

SPSM (Short Portable Sarcopenia Measure), CASCO (Cachexia Score), BAPEN (British Association for Parenteral and Enteral Nutrition, BNST (British Nutrition Screening Tool), CNST (Canadian Nutrition Screening Tool), CONUT (Controlling Nutritional Status), EDC (ESPEN Diagnostic Criteria for Malnutrition), GNRI (Geriatric Nutrition Risk Index), INSYST (Imperial Nutritional Screening System), MST (Malnutrition Screening Tool), MSTC (Malnutrition Screening Tool for Cancer), NRI (Nutritional Risk Index), NRS-2002 (Nutritional Risk Screening), NUFFE (Nutritional Form For the Elderly), SGA (Subjective Global Assessment), SNAQ (Short Nutritional Assessment Questionnaire), Spinal NST (Spinal Nutritional Screening Tool) R-NST (Renal Nutritional Screening Tool), 3-MinNS (3 Minute Nutrition Screening)

 

 

 

 

 

 

 

 

 

 

 

Table IV Psychometric evaluation of tools to measure unintentional weight loss

Scale Environment Context (OP/IP) Face validity Content validity Factor analysis Construct validity Discriminant validity Predictive validity Test-retest Internal consistency Responsiveness Acceptability Time to complete
Sarcopenia SARC-F

SPSM

Community dwelling

Community dwelling

Outpatients

Outpatients

X

Cachexia CASCO Oncology Outpatients
Malnutrition BAPEN

BNST

CNST

CONUT

EDC

GNRI

INSYST

MST

MSTC

MUST

NRI

NRS-2002

NUFFE

R-NST

SGA

SNAQ

SNST

Spinal NST

3-MinNS

Acute medical and elderly care

Spinal cord injuries

Medical and surgical

Medical and surgical

Medical and surgical

Acute geriatrics

Medical, surgical and oncology

Medical, surgical and oncology

Oncology

Medical, surgical and oncology

Peritoneal dialysis and colorectal cancer

Elderly, medical and surgical

Elderly care rehab

Renal

Elderly, renal, medical and surgical

Medical, surgical and oncology

Medical and surgical

Spinal cord injuries

Medical and surgical

Inpatients

Inpatients

Inpatients

Inpatients

Inpatients

Outpatients

Inpatients

Inpatients

Outpatients

Inpatients

Inpatients

Outpatients

Inpatients

Inpatients

Inpatients

Outpatients

Inpatients

Inpatients

Inpatients

Outpatients

Inpatients

Inpatients

Inpatients

X

X

X

X

X

 = tool assessed for and found to be valid   X = tool assessed for and found not to be valid – = tool not assessed for/not enough information provided

 

 

 

 

Table V Domains assessed by tools to measure relevant parameters required to identify risks of malnutrition, sarcopenia and cachexia

Patient reported weight loss BMI & FFM measurements Nutritional intake Assessment of muscle mass and function Disease state Measures of metabolic derangement Quality of life
Disease Screening tool Weight loss quantified within specified time frame Weight loss quantified without timeframe Weight loss unquantified with time frame Weight loss unquantified, without time frame UWL specified Muscle mass BMI FFMI Loss of appetite Poor dietary intake/ intake decline Supplemental feeding in use? Symptoms that would prevent eating e.g. vomiting, ulcers Physical performance Muscle strength Presence of illness Fatigue Increased inflammatory markers Anaemia Low serum albumin Other blood

Tests e.g. glucose/urea

QOL
Sarcopenia SARC-F

SPSM

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Cachexia CASCO X X X X X X X X X
Malnutrition BAPEN

BNST

CNST

CONUT

EDC

GNRI

INSYST

MST

MSTC

MUST

NRI

NRS-2002

NUFFE

R-NST

SGA

SNAQ

SNST

SpinalNST

3-MinNS

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

x

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

 

 

Table VI Sensitivity, specificity, predictive values, and reproducibility of the studies included in the systematic review

Author Screening tool Sensitivity Specificity PPV NPV Agreement
Woo et al

Miller et al

SARC-F

SPSM

3.8-9.9

94.2-99.1

8.4-54.8

78.4-94.9

0.78-0.90

Argiles et al CASCO
Weekes et al

Mirmiram et al

Laporte et al

Ignacio et al

Guerra et al

Abd-El-Gawad et al

Tammam et al

Ji-Yeon et al

Ferguson et al

Isenring et al

Neelemaat et al

Nursal et al

Young et al

Wu et al

Ji-Yeon et al

Boleotome et al               Leistra et al                    Sharma et al

Neelemaat et al

Kyle et al

Young et al

Almedia et al

Velasco et al

Prasad et al

Faramarzi et al

Neelemaat et al                             Kyle et al                              Young et al                       Almeida et al                       Bauer et al                       Velasco et al

Soederhamn et al

Xia et al

Duerksen et al

Cooper et al

Moriana et al

Kruizenga et al

Leistra et al

Harada et al

Neelemaat et al

Young et al

Susetyowati et al

Wong et al

Li et al

BAPEN

BNST

CNST

CONUT

EDC

GNRI

INSYST

MST

MSTC

MUST

NRI

NRS-2002

NUFFE

R-NST

SGA

SNAQ

SNST

Spinal NST

3-MinNS

86.7

72.6

92.3

17.1

83.1

95-100

93

100

67

49

73

73

39

94

80

75

69.7

96

61

87

85

72

92.9

66

92

62

90

80

70

74

71

97.3

59-68

79

43

43

75

79

97

85.7

86

61.7

85.1

85

98.3

51.2

65-83

93

92

86

86

55

70

93

84.2

89

94

75.8

80

79

86

93

90

32.39

60

85

93

83

89

85

87

86

74.4

61-65

83

99

99

84

90

80

76.1

83

79.1

81.2

89.1

78.95

98.4

80

67.8

100

43

75.4

80.41

64

88.0

41-42

70

78

78

62

67

73.1

77.0

58.9

58.33

72.7

100

97.6

100

98

70.1

60.53

62

93.6

70-83

89

96

92

92

94

0.77

0.74

0.88

0.488

0.803

0.713

0.73

0.7

0.83

0.53

0.33

0.28

0.21

0.70

0.49

0.63

0.267

0.95

0.6

0.57

Discussion

 

Whilst recent systematic reviews have described the results of studies examining malnutrition screening tools, to our knowledge this is the first review to examine tools that have been validated against another to assess cachexia, sarcopenia and malnutrition. There has only been one prior review on tools for cachexia, sarcopenia and malnutrition [50]. This review did not include psychometric evaluation, did not comment on the validity of the tools, nor compare them to the agreed consensus definitions. Existing systematic reviews of malnutrition screening tools have been limited to describing tools that are non-disease specific and ‘quick and easy’ or have been narrative in nature.

Thirty studies describing 22 tools were identified and judged for validity against a reference method. In the absence of a generally recognised gold standard for screening, assessment by a professional, DEXA, CT, MRI, anthropometry or the screening tools SGA and MNA were considered ‘valid’ reference methods by our research group [13,41-43]. Although cross sectional imaging is now used routinely for body composition analysis, no tools identified in the initial search were validated against CT or MRI. The heterogeneity in populations, age groups, tools and reference methods was large, and therefore pooling of results was impossible. Most tools had only been tested in one population making the drawing of any definitive conclusions difficult. There were too few disease-specific tools to conclude which would be superior for different disease processes.

For the generalised adult population, all tools showed inconsistent results regarding their validity. The SGA which is often considered to be the industry standard [51] and against which many tools are validated has not itself been well validated. It performed well against the diagnostic criteria but sensitivities and specificities were either not recorded or poor. Arguably the most well-known tools ‘MUST’ and ‘NRS-2002’ showed a variation in results from poor to good [26,28,31-36,39], and consistency between groups in which the tools were studied was poor. The less well-known NUFFE showed good validity, but it has been described in only a small volume of literature and is not implemented widely [40]. The “quick and easy” screening tools, including SNAQ and MST performed reasonably (sensitivities <80%) in most studies in which they were used [24-29,32,44,45]. Of note because these tools are quick, they require a further detailed assessment by a qualified health professional if screening is positive. They also miss approximately 20% of at risk patients at initial screen and therefore may be more useful in screening high risk patients.

The tool which performed the best for malnutrition was the 3MinNS [49]. It showed high sensitivity and specificity (>80%) and accurately encompassed the correct diagnostic criteria (percentage weight loss over specified time and measurement of BMI) for malnutrition. It was validated in acute medical and surgical patients and proved quick and easy to complete. It has only been validated in one paper and therefore it cannot be assumed that it would perform as well in different patient populations. Both tools which assessed sarcopenia (SPSM, SARC-F) scored well against the agreed definition [14,15]. However, the SPSM required transport of equipment and the SARC-F had a very low sensitivity [13,14]. The CASCO was the only validated screening tool for cachexia [16]. It performed well against diagnostic criteria, but sensitivities and specificities were not recorded. It has also only been validated in the cancer setting; more work would be needed to validate the tool in other cachectic populations or the general adult population.

Most tools were validated in the adult hospital inpatient setting. Tools for sarcopenia have only been validated in the healthy, community dwelling [14,15]. Length of hospital stay is diminishing worldwide and outpatient nutritional screening is advocated to pick up patients at risk. In this review, we identified eight studies in which outpatients were included. More studies focussing on the construct and predictive validity of tools for outpatient screening are warranted, especially since care is shifting to this setting.

The tool which appeared to have the broadest coverage was the CASCO [16]. It is the only tool which screens for cachexia, but also picks up many of the variables required for a diagnosis of malnutrition. However, assessment of muscle mass or function (required for sarcopenia) is not included. One previous review showed that 20 screening tools appeared relevant for starvation, but none contained all the currently accepted components needed to screen for sarcopenia and cachexia risk [50]. Our study supports this.

A screening tool therefore needs to be developed that encompasses the criteria to pick up all three possible syndromes. This concept is supported by the notion that, in the human being, there may be no “pure” phenotype of cachexia, as it is usually associated with reduced food intake (potential for malnutrition) and increasing age (increasing sarcopenia) [52]. There is also currently a lack of agreement as to the diagnostic criteria of each syndrome and the relative importance of body composition analysis and the nature of depleted tissue within each definition We hypothesised that the overlap between syndromes could be illustrated as in figure II along with the identified best performing tools for each aspect.

Figure II. Diagram to show overlap between cachexia, sarcopenia and malnutrition

There are clearly many existing validated screening tools (at least for malnutrition). It is unlikely that any further novel tools will be devised without breakthroughs in biomarker development. We therefore suggest that the ideal composite tool should be an adaptation of existing tools, and incorporate a stepwise assessment of nutritional status; oral intake; disease status; patient age; muscle mass/function; and metabolic derangement. The presence of underlying disease is a key question in order to stratify the syndromes. Suggested components for use in developing existing screening tools or creating a new tool are depicted below in figure III.

Figure III Suggested stepwise components to be included in a screening tool for cachexia, sarcopenia and malnutrition

 

By screening for all three syndromes, it will allow for a more targeted intervention. Screening for cachexia, sarcopenia or malnutrition is not warranted unless it is accompanied by an intervening care plan. It would be expected that an adequate intervention would prevent any further decline in health status and therefore lead to a positive effect on disease outcome. Most studies did not comment on intervention, which depending on the balance of the three syndromes may need to include varying attention to nutrition, exercise and measures to combat inflammation.

One of the strengths of this review is that it provides a complete overview of tools that have been validated for cachexia, sarcopenia and malnutrition. We did not describe reliability, repeatability or other clinical outcome measures in any great detail. The review used the consensus definitions of each syndrome, we are aware however that many other definitions exist. However, there were a number of study limitations. There was a risk of bias when assessing each tool for their predictive validity. Clinical outcome is known to be affected by many factors other than nutritional status, especially disease severity or stage. Studies may have been biased if they did not adjust for these variables. In addition, nutritional intervention is likely to improve outcomes for malnutrition but potentially not for age-related sarcopenia or established cachexia. Only a few studies discussed whether they did this. There is no agreed ‘gold standard’ tool and therefore we chose cross sectional imaging and the SGA and MNA based on the results of previous studies [13]. Tools that were compared to potentially less valid standards were also included to allow a wider analysis. Full nutrition assessments were different in each study ranging from anthropometric to biochemical measures and full assessment by a medical professional. Conclusions from this study were based upon the original papers in which there may have been varying definitions with regards to the subject group, syndrome or assessment undertaken. Not all studies that assessed predictive validity adjusted for other prognostic factors which may influence outcome and therefore could be considered less valid. Another potential limitation is that we excluded modified versions of pre-existing tools. They were excluded as reliability and validity data would only relate to the modified tool and it was therefore difficult to assess improvements from the original. It is possible that these tools were being improved or evaluated more thoroughly.

One of the strengths of this review is that it provides a complete overview of tools which have been validated for cachexia, sarcopenia and malnutrition. We did not describe reliability, repeatability or other clinical outcome measures in any great detail. The review used the consensus definitions of each syndrome, we are aware however that many other definitions exist.

Conclusion

 

There is no one validated screening tool which can be implemented for the assessment of cachexia, sarcopenia and malnutrition. The adaptation of existing screening tools incorporating all relevant criteria described in this review would be optimal for diagnosis and to direct the content of complex interventions.

Ethical statement

 

This manuscript does not contain clinical studies or patient data. The authors certify that they comply with the ethical guidelines for authorship and publishing of the Journal of Cachexia, Sarcopenia and Muscle [53].

Conflict of interest

The authors declare no conflicts of interest

Acknowledgements

 

Yorkshire Cancer Research endowment programme have funded the open access publishing of this article

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Appendix I: Search criteria used in MEDLINE

  1. Cachexia/ or sarcopenia/ or starvation/ or malnutrition/ or protein-energy malnutrition/ or wasting syndrome/ or muscle strength/ or anorexia/ or fatigue
  2. (cachexia or cachectic or sarcopen* or sarcopaen* or starvation or malnutrition or malnourish* or undernutrition or undernourish* or wast* or unintentional weight loss or muscle wastage or muscle strength or muscle mass).mp
  3. 1 or 2
  4. (nutrition* or malnutrition*).mp and (mass screening/ or nutrition assessment/)
  5. ((malnutrition* or nutrition*)adj3(screen* or assess*)).mp
  6. 4 or 5
  7. questionnaires/
  8. (tool* or criter* or questionnaire*).mp
  9. 7 or 8
  10. validation studies/
  11. 9 or 10
  12. 3 and 6 and 9 and 11 [50]

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