Description:
Using low-dose X-rays of two different energy levels, whole-body dual-energy X-ray absorptiometry (DXA) measures lean tissue mass, total and regional body fat, as well as bone density. DXA scans have become a tool for research on body composition (e.g., as a more convenient replacement for underwater weighing). This evidence review addresses potential applications in clinical care rather than research use of the technology.

For individuals who have a clinical condition associated with abnormal body composition who receive DXA body composition studies, the evidence includes systematic reviews and several cross-sectional studies comparing DXA with other techniques. The relevant outcomes are symptoms and change in disease status. The available studies were primarily conducted in research settings and often used DXA body composition studies as a reference standard; these studies do not permit conclusions about the accuracy of DXA for measuring body composition. A systematic review exploring the clinical validity of DXA against reference methods for the quantification of intra-abdominal adipose tissue raised concerns regarding precision and reliability. More importantly, no studies were identified in which DXA body composition measurements were actively used in patient management. The evidence is insufficient to determine the effects of the technology on health outcomes.

For individuals who have a clinical condition managed by monitoring changes in body composition over time who receive serial DXA body composition studies, the evidence includes several prospective studies monitoring patients over time. The relevant outcomes are symptoms and change in disease status. The studies used DXA as a tool to measure body composition and were not designed to assess the accuracy of DXA. None of the studies used DXA findings to make patient management decisions or addressed how serial body composition assessment might improve health outcomes. The evidence is insufficient to determine the effects of the technology on health outcomes.

Background
Body Composition Measurement
Body composition measurements can be used to quantify and assess the relative proportions of specific body compartments such as fat and lean mass (e.g., bones, tissues, organs, muscles). These measurements may be more useful in informing diagnosis, prognosis, or therapy than standard assessments (e.g., body weight, body mass index) that do not identify the contributions of individual body compartments or their particular relationships with health and disease. While these body composition measurements have been most frequently utilized for research purposes, they may be useful in clinical settings to:

• Evaluate the health status of undernourished patients, those impacted by certain disease states (e.g., anorexia nervosa, cachexia), or those undergoing certain treatments (e.g., antiretroviral therapy, bariatric surgery).
• Evaluate the risk of heart disease or diabetes by measuring visceral fat vs total body fat.
• Assess body composition changes related to growth and development (e.g., infancy, childhood), aging (e.g., sarcopenia), and in certain disease states (e.g., HIV, diabetes).
• Evaluate patients in situations where body mass index is suspected to be discordant with total fat mass (e.g., body-building, edema).

A variety of techniques has been researched, including most commonly, anthropomorphic measures, bioelectrical impedance, and dual-energy X-ray absorptiometry (DXA). All of these techniques are based in part on assumptions about the distribution of different body compartments and their density, and all rely on formulas to convert the measured parameter into an estimate of body composition. Therefore, all techniques will introduce variation based on how the underlying assumptions and formulas apply to different populations of subjects (i.e., different age groups, ethnicities, or underlying conditions). Techniques using anthropomorphics, bioelectrical impedance, underwater weighing, and DXA are briefly reviewed below. 

Anthropomorphic Techniques
Anthropomorphic techniques for the estimation of body composition include measurements of skinfold thickness at various sites, bone dimensions, and limb circumference. These measurements are used in various equations to predict body density and body fat. Due to its ease of use, measurement of skinfold thickness is one of the most common techniques. The technique is based on the assumption that the subcutaneous adipose layer reflects total body fat but this association may vary with age and sex.

Bioelectrical Impedance
Bioelectrical impedance analysis is based on the relation among the volume of the conductor (ie, human body), the conductor's length (i.e., height), the components of the conductor (i.e., fat and fat-free mass), and its impedance. Estimates of body composition are based on the assumption that the overall conductivity of the human body is closely related to lean tissue. The impedance value is then combined with anthropomorphic data to give body compartment measures. The technique involves attaching surface electrodes to various locations on the arm and foot. Alternatively, the patient can stand on the pad electrodes.

Underwater Weighing
Underwater weighing requires the use of a specially constructed tank in which the subject is seated on a suspended chair. The subject is then submerged in the water while exhaling. While valued as a research tool, weighing people underwater is typically not suitable for routine clinical use. This technique is based on the assumption the body can be divided into two compartments with constant densities: adipose tissue, with a density of 0.9 g/cm³, and lean body mass (i.e., muscle and bone), with a density of 1.1 g/cm³. One limitation of the underlying assumption is the variability in density between muscle and bone, e.g., bone has a higher density than muscle, and bone mineral density varies with age and other conditions. Also, the density of body fat may vary, depending on the relative components of its constituents (e.g., glycerides, sterols, glycolipids).

Dual-Energy X-Ray Absorptiometry
While the cited techniques assume two body compartments, DXA can estimate three body compartments consisting of fat mass, lean body mass, and bone mass. DXA systems use a source that generates X-rays at two energies. The differential attenuation of the two energies is used to estimate the bone mineral content and soft tissue composition. When two X-ray energies are used, only two tissue compartments can be measured; therefore, soft tissue measurements (i.e., fat and lean body mass) can only be measured in areas in which no bone is present. DXA can also determine body composition in defined regions (i.e., the arms, legs, and trunk). DXA measurements are based in part on the assumption that the hydration of fat-free mass remains constant at 73%. Hydration, however, can vary from 67% to 85% and can vary by disease state. Other assumptions used to derive body composition estimates are considered proprietary by DXA manufacturers. The use of DXA for bone mineral density assessment in patients diagnosed with or at risk of osteoporosis is addressed separately in evidence review 60101. Vertebral fracture assessment with densitometry by DXA is addressed separately in evidence review 60144.

REGULATORY STATUS
Body composition software for several bone densitometer systems have been approved by the U.S. Food and Drug Administration through the premarket approval process. They include the Lunar iDXA systems (GE Healthcare, Madison, WI), Hologic DXA systems (Hologic, Bedford, MA), and Norland DXA systems (Norland, at Swissray, Fort Atkinson, WI).

Policy:
Dual X-ray absorptiometry (DEXA) body composition studies are investigational and/or unproven and is therefore considered NOT MEDICALLY NECESSARY.

Policy Guidelines 
Coding
Please see the Codes table for details.

Benefit Application
BlueCard/National Account Issues
State or federal mandates (e.g., FEP) may dictate that all devices approved by the U.S. Food and Drug Administration (FDA) may not be considered investigational, and thus these devices may be assessed only on the basis of their medical necessity.

Rationale 
Evidence reviews assess whether a medical test is clinically useful. A useful test provides information to make a clinical management decision that improves the net health outcome. That is, the balance of benefits and harms is better when the test is used to manage the condition than when another test or no test is used to manage the condition.

The first step in assessing a medical test is to formulate the clinical context and purpose of the test. The test must be technically reliable, clinically valid, and clinically useful for that purpose. Evidence reviews assess the evidence on whether a test is clinically valid and clinically useful. Technical reliability is outside the scope of these reviews, and credible information on technical reliability is available from other sources.

Promotion of greater diversity and inclusion in clinical research of historically marginalized groups (e.g., People of Color [African-American, Asian, Black, Latino and Native American]; LGBTQIA (Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, Asexual); Women; and People with Disabilities [Physical and Invisible]) allows policy populations to be more reflective of and findings more applicable to our diverse members. While we also strive to use inclusive language related to these groups in our policies, use of gender-specific nouns (e.g., women, men, sisters, etc.) will continue when reflective of language used in publications describing study populations.

Dual-energy X-ray Absorptiometry as a Test to Detect Abnormal Body Composition
Clinical Context and Test Purpose
The purpose of dual-energy x-ray absorptiometry (DXA) body composition studies is to improve the diagnosis and management of patients who have a clinical condition associated with abnormal body composition.

The following PICO was used to select literature to inform this review.

Populations
The relevant population of interest is individuals with clinical conditions associated with abnormal body composition.

Interventions
The test being considered is DXA body composition studies.

Comparators
The following practices are currently being used to make decisions in this patient group: standard of care without DXA or an alternative method of body composition analysis.

Outcomes
The general outcomes of interest include symptom management and change in disease status. For patients with human immunodeficiency virus (HIV) who are treated with antiretroviral therapy, outcomes of interest would include lipodystrophy.

Study Selection Criteria
For the evaluation of clinical validity of DXA body composition testing, studies that meet the following eligibility criteria were considered:

• Reported on the accuracy of the marketed version of the technology (including any algorithms used to calculate scores)
• Included a suitable reference standard
• Patient/sample clinical characteristics were described
• Patient/sample selection criteria were described.

Clinically Valid
A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).

Review of Evidence
Systematic Reviews
A systematic review and meta-analysis comparing the accuracy of alternative comparators versus reference standard computed tomography (CT) and magnetic resonance imaging (MRI) methods for the quantification of intra-abdominal adipose tissue (IAAT) was published by Murphy et al (2019).3, This systematic review assessed the performance of DXA for IAAT volume quantification and compared the performance of both DXA and bioelectric impedance analysis (BIA) approaches for IAAT area quantification. The American Society for Parenteral and Enteral Nutrition (ASPEN) also conducted a systematic review to evaluate the validity of relevant body composition methods in various clinical populations.4, The use of DXA, ultrasound, and BIA for body composition analysis was investigated. Fifteen studies featuring comparisons of DXA to reference standard methods (eg, MRI and CT) were identified. Nine studies using CT or MRI to validate DXA measures of abdominal fat mass (FM) or total body FM were used for pooled analyses. Characteristics and results of these meta-analyses are summarized in Tables 1 and 2.

Table 1. Systematic Review & Meta-Analysis Characteristics

ASPEN: American Society for Parenteral and Enteral Nutrition; BIA: bioelectrical impedance analysis; CT: computed tomography; CVD: cardiovascular disease; DXA: dual-energy x-ray absorptiometry; FM: fat mass; HIV: human immunodeficiency virus; IAAT: intra-abdominal adipose tissue; MRI: magnetic resonance imaging; NR: not reported; PCOS: polycystic ovarian syndrome; SD: standard deviation; US: ultrasound. 
1 Key study eligibility criteria and demographics of included subgroup participants.
* 3 of 9 trials were sampled twice for a total of 12 result sets due to use of multiple techniques for IAAT quantification via BIA. 
** 1 of 8 trials was categorized as an outlier and excluded from pooled analysis. 

Table 2. Systematic Review & Meta-Analysis Results

ASPEN: American Society for Parenteral and Enteral Nutrition; BIA: bioelectrical impedance analysis; CI: confidence interval; CT: computed tomography; CVD: cardiovascular disease; DXA: dual-energy x-ray absorptiometry; FM: fat mass; IAAT: intra-abdominal adipose tissue; LoA: limits of agreement; MRI: magnetic resonance imaging; US: ultrasound; VAT: visceral adipose tissue. 
* Results following the removal of a study due to identification as an outlier. 

Because the analysis by Murphy et al (2019) aimed to evaluate agreement between DXA and CT or MRI, direct effects on key health outcomes were not explored and patient populations included for analysis displayed extensive heterogeneity and largely featured healthy populations. Measurements of IAAT volume via DXA were deemed comparable to the reference methods, however, 95% limits of agreement (LoA) were wide and these results were not seen until the removal of an outlying study. Performance of DXA for the measurement of IAAT volume also varied significantly between male and female subgroups. Furthermore, included studies did not pre-determine clinically meaningful LoA. The authors further caution that DXA measurement of IAAT volume has the capacity to differ from reference methods by more than 100%, however, the clinical significance of these margins of error are uncertain in individuals with obesity. While IAAT area cutoff points have been described for the determination of metabolic risk and visceral obesity based on single-slice CT, the authors do not recommend utilization of DXA IAAT area measurements for this purpose due to wide LoA. The clinical utility of existing IAAT area cutpoints is also uncertain as these parameters were found to have applicability for women and cannot necessarily be extrapolated to mixed populations.

Calella et al (2019) performed a systematic review exploring various methods for body composition analysis in patients with cystic fibrosis (CF).5, A previous systematic review by Calella et al (2018) presented on differences in body composition between patients with CF and healthy controls evaluated by DXA and other methods.6, DXA was most frequently used to measure lean body or fat-free mass which was significantly reduced in CF patients. While several included studies showed a correlation between lower fat-free mass and impaired pulmonary function, application, and use of this measure in patient management and its impact on health outcomes was not explored and requires further clarification. Since these reviews featured qualitative analyses, data on clinical validity could not be extracted.

A systematic review by Bundred et al (2019) evaluated body composition assessment and sarcopenia in patients with pancreatic ductal adenocarcinoma.7, Meta-analyses revealed that sarcopenia was associated with lower overall survival in both operable (harms ratio, 1.95; 95% confidence interval [CI], 1.35 to 2.81; p<.001) and unresectable patients (harms ratio, 2.49; 95% CI, 1.38 to 4.48; p=.002). However, of the 42 included studies, only 1 utilized measurements obtained by DXA, limiting the relevance of the overall findings to this technology and preventing extraction of pertinent clinical validity data. Furthermore, the authors caution that many studies failed to account for variation introduced by gender, race, tumor stage, and other factors. Additionally, clear criteria for the diagnosis of sarcopenia or cachexia via body composition assessments with DXA are lacking.

Cross-Sectional Studies
Most of the literature on DXA as a diagnostic test to detect abnormal body composition involves the use of the technology in the research setting, often as a reference test; studies have been conducted in different populations of patients and underlying disorders.8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,In some cases, studies have compared other techniques with DXA to identify simpler methods of determining body composition. In general, these studies have shown that DXA is highly correlated to various methods of body composition assessment. For example, a study by Alves et al (2014) compared 2 bioelectrical impedance devices with DXA for the evaluation of body composition in heart failure.8, Ziai et al (2014) compared bioelectric impedance analysis with DXA for evaluating body composition in adults with CF.9, The literature on DXA in population-based cohorts (eg, National Health and Nutrition Examination Survey [NHANES], Prospective Epidemiological Risk Factor Study)24,25, involves the use of the technology to predict risk of overall mortality or cancer incidence. These studies often use DXA as a reference test to assess whether agreement with anthropometric measures (eg, body mass index [BMI], relative fat mass [RFM]) is present.24, or absent.25, Whether or not a DXA scan is considered the reference standard, the key consideration regarding its routine clinical use is whether the results of the scan can be used to manage patients and improve health outcomes.

Case-Control Studies
As a single diagnostic measure, it is important to establish diagnostic cutoff points for normal and abnormal values. This is problematic because normal values will require the development of normative databases for the different components of body composition (ie, bone, fat, lean mass) for different populations of patients at different ages. Regarding measuring bone mineral density (BMD), normative databases have largely focused on postmenopausal White women, and these values cannot necessarily be extrapolated to men or to different races. DXA determinations of BMD are primarily used for fracture risk assessment in postmenopausal women and to select candidates for various pharmacologic therapies to reduce fracture risk. In an example regarding lean mass, Reina et al (2019) conducted a case-control study to assess the correlation of BMI or serum albumin levels to DXA-derived parameters of nutritional status and sarcopenia in women (N=89) with rheumatoid arthritis.26, While 44% of cases met diagnostic criteria for sarcopenia based on quantification of the skeletal muscle index, a reference technique was not clearly identified in this study. Skeletal muscle index is calculated by dividing appendicular skeletal muscle mass by the square of the patient's height. A previously identified threshold of ≤5.75 kg/m2 in women was applied, however, this metric was established through the use of BIA in a slightly older patient population. Given that DXA provides measures of lean mass which may be influenced by body compartments other than skeletal muscle, the relevance of this diagnostic cutoff point is uncertain. Furthermore, the study utilized a control group composed of patients affected by non-inflammatory rheumatic disorders as opposed to healthy controls, further limiting the relevance of applied cutoff points. In addition to the aforementioned uncertainties of establishing and applying normal values for components of body composition, it also is unclear how a single measure of body composition would be used in patient management. Studies discussing appropriate use and determination of DXA-derived lean mass cutoffs for sarcopenia in various populations of patients and underlying disorders continue to be featured in the literature.27,28,

Clinically Useful
A test is clinically useful if the use of the results informs management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.

Direct Evidence
Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from randomized controlled trials (RCTs).

No RCTs were identified to support the utility of DXA for this indication.

Chain of Evidence
Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.

Pooled analyses indicate that there is generally strong correlation between estimates of FM as assessed by DXA versus CT or MRI, particularly in populations with clinical conditions for which risk of adverse outcomes associated with visceral adiposity may be of particular importance.4, In a broader population, including healthy individuals, while there remains a strong overall correlation between these methods of FM estimation, significant variability suggests that there are some subpopulations in whom DXA may perform poorly as an estimate of adiposity compared to CT or MRI.3, Additionally, there is a lack of evidence to indicate that evaluation of body composition via DXA changes clinical management.

Section Summary: Dual-energy X-ray Absorptiometry as a Test to Detect Abnormal Body Composition
The available evidence was generated primarily in research settings and often used DXA body composition studies as a reference standard; these studies do not permit conclusions about the accuracy of DXA for measuring body composition. Systematic reviews with meta-analyses exploring the clinical validity of DXA measurements against reference methods for the quantification of FM indicate strong overall agreement between these modalities, but raise concerns regarding precision and reliability in some populations, particularly those without existing clinical conditions for which risk of adverse outcomes is influenced by abnormal visceral adiposity. Additionally, no studies were identified in which DXA body composition measurements were actively used in patient management.

Dual-energy X-ray Absorptiometry as a Test to Monitor Changes in Body Composition
Clinical Context and Test Purpose
The purpose of serial DXA body composition studies in patients who have a clinical condition managed by monitoring body composition changes over time is to improve disease management.

The following PICO was used to select literature to inform this review.

Populations
The relevant population of interest is individuals with clinical conditions managed by monitoring body composition changes over time.

Interventions
The test being considered is serial DXA body composition studies.

Comparators
The following practices are currently being used to make decisions in this patient group: standard of care without DXA or an alternative method of body composition analysis.

Outcomes
The general outcomes of interest include symptom management and change in disease status. For patients with anorexia nervosa, outcomes of interest would include disease-related morbidity, disease-related mortality, and rate of remission.

Study Selection Criteria
For the evaluation of clinical validity of DXA body composition testing, studies that meet the following eligibility criteria were considered:

• Reported on the accuracy of the marketed version of the technology (including any algorithms used to calculate scores)
• Included a suitable reference standard
• Patient/sample clinical characteristics were described
• Patient/sample selection criteria were described.

Clinically Valid
A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).

The ability to detect a change in body composition over time is related in part to the precision of the technique, defined as the degree to which repeated measurements of the same variable give the same value. For example, DXA measurements of bone mass are thought to have a precision error of 1% to 3% and, given the slow rate of change in BMD in postmenopausal women treated for osteoporosis, it is likely that DXA scans would only be able to detect a significant change in BMD in the typical patient after 2 years of therapy. Of course, changes in body composition are anticipated to be larger and more rapid than changes in BMD in postmenopausal women; therefore, precision errors in DXA scans become less critical in interpreting results. However, precision errors for other body compartments such as lean and fat mass may differ and impact clinical validity. Coefficients of variation as high as 42.2% have been reported for FM.29,

Review of Evidence
Prospective Studies
Several studies have reported on DXA measurement of body composition changes over time in clinical populations; none of these studies used DXA findings to make patient management decisions and few addressed how serial body composition assessment might improve health outcomes.30,31,29,32,33,34, A long-term prospective study assessing the association between body fat and breast cancer risk in postmenopausal women with a normal BMI was published by Iyengar et al (2019), featuring the ad hoc secondary analysis of results from the Women's Health Initiative RCT and observational study cohorts.32, Women (N=3460) were assessed at baseline and during years 1, 3, 6, and 9 for BMI and via DXA. Multivariable-adjusted hazard ratios (HR) for the association of various body fat measures with the risk of developing invasive or estrogen receptor positive (ER+) breast cancer were reported. Median follow-up duration was 16.9 years. Characteristics and results of clinical validity for breast cancer risk assessment are summarized in Tables 3 and 4.

Table 3. Study Characteristics of Clinical Validity of Risk Assessment

BMI: body mass index; NR: not reported; RCT: randomized controlled trial.
a Note 2 aspects of design: prospective, retrospective or nonconcurrent prospective and sample selection random or consecutive
b Note other characteristics that could cause bias or limit relevance such as timeframe or practice setting.

Table 4. Clinical Validity of Breast Cancer Risk Assessment with Dual-Energy X-ray Absorptiometry

CI: confidence interval; DXA: dual-energy x-ray absorptiometry; ER+: estrogen receptor-positive; HR: hazard ratio; NR: not reported. 
* Excluded cases were lost to follow-up with ER+ status not reported. 

These results suggest that standard BMI categorization may be inadequate for the risk assessment of invasive breast cancers in postmenopausal women. However, the clinical utility of DXA findings on patient management protocols and health outcomes requires further study.

Arthur et al (2020) published additional results from the Women's Health Initiative cohort of postmenopausal women (N=10,931), reporting additional associations between DXA-derived measures of body fat and breast cancer risk.35, The multivariable-adjusted HR for risk of invasive breast cancer per standard deviation (SD) increase in trunk fat mass was 1.21 (95% CI, 1.12 to 1.31) and whole body fat mass was 1.21 (95% CI, 1.12 to 1.30). The multivariable-adjusted HR for risk of ER+ breast cancer per SD increase in trunk fat mass was 1.21 (95% CI, 1.11 to 1.31) and whole body fat mass was 1.22 (95% CI, 1.11 to 1.33). Multivariable-adjusted HR for invasive breast cancer per SD increase in BMI was also significant, with an HR of 1.19 (95% CI, 1.10 to 1.28). Trends of time-dependent analyses of anthropometric measures and overall ER + incident breast cancer cases were significant for BMI (p <.001) and waist circumference (p<.001). Therefore, the added clinical utility of DXA-derived fat measures is unclear for this population.

Relevance and study design and conduct limitations are summarized in Tables 5 and 6.

Table 5. Study Relevance Limitations

DXA: dual-energy x-ray absorptiometry; RCT: randomized controlled trial.
The study limitations stated in this table are those notable in the current review; this is not a comprehensive gaps assessment.
a Population key: 1. Intended use population unclear; 2. Clinical context is unclear; 3. Study population is unclear; 4. Study population not representative of intended use.
b Intervention key: 1. Classification thresholds not defined; 2. Version used unclear; 3. Not intervention of interest.
c Comparator key: 1. Classification thresholds not defined; 2. Not compared to credible reference standard; 3. Not compared to other tests in use for same purpose.
d Outcomes key: 1. Study does not directly assess a key health outcome; 2. Evidence chain or decision model not explicated; 3. Key clinical validity outcomes not reported (sensitivity, specificity, and predictive values); 4. Reclassification of diagnostic or risk categories not reported; 5. Adverse events of the test not described (excluding minor discomforts and inconvenience of venipuncture or noninvasive tests).
e Follow-Up key: 1. Follow-up duration not sufficient with respect to natural history of disease (true-positives, true-negatives, false-positives, false-negatives cannot be determined).

Table 6. Study Design and Conduct Limitations

Direct Evidence
Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from RCTs.

No RCTs were identified to support the utility of DXA for this indication.

Chain of Evidence
Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.

Because the clinical validity of DXA for this population cannot be established, a chain of evidence cannot be constructed.

Section Summary: Dual-Energy X-ray Absorptiometry as a Test to Monitor Changes in Body Composition
Studies assessing serial DXA used it as a tool to measure body composition and were not designed to assess the accuracy of DXA. None of the studies used DXA findings to make patient management decisions or addressed how serial body composition assessment might improve health outcomes.

The purpose of the following information is to provide reference material. Inclusion does not imply endorsement or alignment with the evidence review conclusions.

Practice Guidelines and Position Statements
Guidelines or position statements will be considered for inclusion in ‘Supplemental Information' if they were issued by, or jointly by, a US professional society, an international society with US representation, or National Institute for Health and Care Excellence (NICE). Priority will be given to guidelines that are informed by a systematic review, include strength of evidence ratings, and include a description of management of conflict of interest.

American Association of Clinical Endocrinology et al
The American Association of Clinical Endocrinology (AACE) and American College of Endocrinology (ACE) clinical practice guideline on obesity was updated in 2016.36, Table 7 describes relevant recommendations for the diagnosis of overweight and obesity from the AACE/ACE guideline. The authors also state that "The DEXA [dual x-ray absorptiometry] scan also allows for calculation of the fat mass index (total body fat mass [kg] divided by height [m2]), which is a physiologic relevant measure of adiposity. The clinical utility of these measures is limited by availability, cost, and lack of outcomes data, but they have been applied extensively in research settings. Body fat percentage cut points for obesity have been proposed by the World Health Organization (WHO) to be 25% for men and 35% for women."

Table 7. American Association of Clinical Endocrinology/American College of Endocrinology Recommendations for Diagnosis of Overweight and Obesity

BMI: body mass index; WC: waist circumference.
aEvidence quality 2 indicates intermediate-level evidence, including meta-analyses of nonrandomized prospective or case-controlled trials, nonrandomized controlled trials, prospective cohort studies, and/or retrospective case-control studies.
bGrade A, B, and C indicate strong, intermediate, and weak recommendations, respectively.

American College of Radiology et al
The American College of Radiology (ACR), the Society for Pediatric Radiology (SPR), and the Society of Skeletal Radiology (SRR) (2018) issued a collaborative practice parameter to assist practitioners in providing appropriate radiologic care for their patients.37, Dual-energy x-ray absorptiometry (DXA) was described as a "clinically proven, accurate and reproducible method of measuring bone mineral density (BMD) in the lumbar spine, proximal femur, forearm, and whole body," that "may also be used to measure whole-body composition, including nonbone lean mass (LM) and fat mass (FM)." DXA measurement of BMD, LM, or FM is indicated whenever a clinical decision is likely to be directly influenced by the test result. In particular, LM and FM may be useful in assessing conditions such as sarcopenia and cachexia. Specifically, DXA may be indicated as a tool for the measurement of regional and whole body FM and LM in patients afflicted with conditions such as malabsorption, cancer, or eating disorders.

American Society for Parenteral and Enteral Nutrition
The American Society for Parenteral and Enteral Nutrition (ASPEN) published clinical guidelines on the validity of body composition assessment in clinical populations in 2019, as a complement to the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition (described below).4, The systematic review with meta-analysis used to develop these guidelines is described above. The target population of the guideline was adults "with a potentially inflammatory condition or pathological end point associated with a specific disease or clinical condition such as cancer, cardiovascular disease (CVD), cardiac failure, diabetes, hepatic or renal disease, human immunodeficiency virus, or possessing a condition that requires surgical intervention." The target population did not include healthy individuals or those with obesity, except when "linked to a clinical condition such as metabolic syndrome, hypertension, etc." Studies evaluated for guideline development involved specific body composition assessment methodologies (DXA, bioelectrical impedance analysis, or ultrasound) and were required to use a more precise comparator; for studies evaluating DXA, these included computed tomography, magnetic resonance imaging, or multicompartment models. Anthropometric measurements "were not included since these are considered surrogate measures of body composition." Table 8 describes relevant recommendations from the ASPEN guideline.

Table 8. American Society for Parenteral and Enteral Nutrition Clinical Guideline Recommendations for Body Composition Assessment in Adult Clinical Populations

DXA: dual-energy x-ray absorptiometry.
 
International Society for Clinical Densitometry
The International Society for Clinical Densitometry (2019) updated its statements on the use of DXA for body composition.38, Use of DXA for measurement of body composition was suggested for use in the following clinical conditions:

• To assess fat distribution in patients with human immunodeficiency virus (HIV) who are using antiretroviral agents known to increase the risk of lipoatrophy.

• To assess fat and lean mass changes in obese patients undergoing bariatric surgery (or medical, diet, or weight loss regimens with anticipated large weight loss) when weight loss exceeds approximately 10%. The statement noted that the impact of DXA studies on clinical outcomes in these patients is uncertain.

• To assess fat and lean mass in patients with muscle weakness and poor physical functioning. The impact on clinical outcomes is uncertain.

Of note, pregnancy is a contraindication to use of DXA to measure body composition. The statement also adds that the clinical utility of DXA measurements of adiposity and lean mass (eg, visceral adipose tissue, lean mass index, fat mass index) is uncertain. Furthermore, while the use of DXA adiposity measures such as fat mass index may be useful in risk-stratifying patients for cardio-metabolic outcomes, specific thresholds to define obesity have not been established.

U.S. Preventive Services Task Force Recommendations
No U.S. Preventive Services Task Force recommendations for whole-body DXA have been identified.

Ongoing and Unpublished Clinical Trials
Some currently unpublished trials that might influence this review are listed in Table 9.

Table 9. Summary of Key Trials

NCT: national clinical trial.
a Denotes industry-sponsored or cosponsored trial.

References:

1. Murphy J, Bacon SL, Morais JA, et al. Intra-Abdominal Adipose Tissue Quantification by Alternative Versus Reference Methods: A Systematic Review and Meta-Analysis. Obesity (Silver Spring). Jul 2019; 27(7): 1115-1122. PMID 31131996
2. Sheean P, Gonzalez MC, Prado CM, et al. American Society for Parenteral and Enteral Nutrition Clinical Guidelines: The Validity of Body Composition Assessment in Clinical Populations. JPEN J Parenter Enteral Nutr. Jan 2020; 44(1): 12-43. PMID 31216070
3. Calella P, Valerio G, Brodlie M, et al. Tools and Methods Used for the Assessment of Body Composition in Patients With Cystic Fibrosis: A Systematic Review. Nutr Clin Pract. Oct 2019; 34(5): 701-714. PMID 30729571
4. Calella P, Valerio G, Brodlie M, et al. Cystic fibrosis, body composition, and health outcomes: a systematic review. Nutrition. Nov 2018; 55-56: 131-139. PMID 29981489
5. Bundred J, Kamarajah SK, Roberts KJ. Body composition assessment and sarcopenia in patients with pancreatic cancer: a systematic review and meta-analysis. HPB (Oxford). Dec 2019; 21(12): 1603-1612. PMID 31266698
6. Alves FD, Souza GC, Biolo A, et al. Comparison of two bioelectrical impedance devices and dual-energy X-ray absorptiometry to evaluate body composition in heart failure. J Hum Nutr Diet. Dec 2014; 27(6): 632-8. PMID 24684316
7. Ziai S, Coriati A, Chabot K, et al. Agreement of bioelectric impedance analysis and dual-energy X-ray absorptiometry for body composition evaluation in adults with cystic fibrosis. J Cyst Fibros. Sep 2014; 13(5): 585-8. PMID 24522087
8. Elkan AC, Engvall IL, Tengstrand B, et al. Malnutrition in women with rheumatoid arthritis is not revealed by clinical anthropometrical measurements or nutritional evaluation tools. Eur J Clin Nutr. Oct 2008; 62(10): 1239-47. PMID 17637600
9. Jensky-Squires NE, Dieli-Conwright CM, Rossuello A, et al. Validity and reliability of body composition analysers in children and adults. Br J Nutr. Oct 2008; 100(4): 859-65. PMID 18346304
10. Kullberg J, Brandberg J, Angelhed JE, et al. Whole-body adipose tissue analysis: comparison of MRI, CT and dual energy X-ray absorptiometry. Br J Radiol. Feb 2009; 82(974): 123-30. PMID 19168691
11. Liem ET, De Lucia Rolfe E, L'Abee C, et al. Measuring abdominal adiposity in 6 to 7-year-old children. Eur J Clin Nutr. Jul 2009; 63(7): 835-41. PMID 19127281
12. Bedogni G, Agosti F, De Col A, et al. Comparison of dual-energy X-ray absorptiometry, air displacement plethysmography and bioelectrical impedance analysis for the assessment of body composition in morbidly obese women. Eur J Clin Nutr. Nov 2013; 67(11): 1129-32. PMID 24022260
13. Monteiro PA, Antunes Bde M, Silveira LS, et al. Body composition variables as predictors of NAFLD by ultrasound in obese children and adolescents. BMC Pediatr. Jan 29 2014; 14: 25. PMID 24476029
14. Tompuri TT, Lakka TA, Hakulinen M, et al. Assessment of body composition by dual-energy X-ray absorptiometry, bioimpedance analysis and anthropometrics in children: the Physical Activity and Nutrition in Children study. Clin Physiol Funct Imaging. Jan 2015; 35(1): 21-33. PMID 24325400
15. Alves Junior CAS, de Lima LRA, de Souza MC, et al. Anthropometric measures associated with fat mass estimation in children and adolescents with HIV. Appl Physiol Nutr Metab. May 2019; 44(5): 493-498. PMID 30286302
16. Barr RD, Inglis D, Athale U, et al. The Influence of Body Composition on Bone Health in Long-term Survivors of Acute Lymphoblastic Leukemia in Childhood and Adolescence: Analyses by Dual-energy X-ray Absorptiometry and Peripheral Quantitative Computed Tomography. J Pediatr Hematol Oncol. Apr 27 2022. PMID 35482464
17. Chang CC, Chen YK, Chiu HC, et al. Assessment of Sarcopenia and Obesity in Patients with Myasthenia Gravis Using Dual-Energy X-ray Absorptiometry: A Cross-Sectional Study. J Pers Med. Nov 03 2021; 11(11). PMID 34834491
18. Smoot BJ, Mastick J, Shepherd J, et al. Use of Dual-Energy X-Ray Absorptiometry to Assess Soft Tissue Composition in Breast Cancer Survivors With and Without Lymphedema. Lymphat Res Biol. Nov 18 2021. PMID 34793255
19. Woolcott OO, Bergman RN. Defining cutoffs to diagnose obesity using the relative fat mass (RFM): Association with mortality in NHANES 1999-2014. Int J Obes (Lond). Jun 2020; 44(6): 1301-1310. PMID 31911664
20. Staunstrup LM, Nielsen HB, Pedersen BK, et al. Cancer risk in relation to body fat distribution, evaluated by DXA-scans, in postmenopausal women - the Prospective Epidemiological Risk Factor (PERF) study. Sci Rep. Mar 29 2019; 9(1): 5379. PMID 30926844
21. Reina D, Gomez-Vaquero C, Diaz-Torne C, et al. Assessment of nutritional status by dual X-Ray absorptiometry in women with rheumatoid arthritis: A case-control study. Medicine (Baltimore). Feb 2019; 98(6): e14361. PMID 30732168
22. Sinclair M, Hoermann R, Peterson A, et al. Use of Dual X-ray Absorptiometry in men with advanced cirrhosis to predict sarcopenia-associated mortality risk. Liver Int. Jun 2019; 39(6): 1089-1097. PMID 30746903
23. Lindqvist C, Brismar TB, Majeed A, et al. Assessment of muscle mass depletion in chronic liver disease: Dual-energy x-ray absorptiometry compared with computed tomography. Nutrition. May 2019; 61: 93-98. PMID 30703575
24. Dordevic AL, Bonham M, Ghasem-Zadeh A, et al. Reliability of Compartmental Body Composition Measures in Weight-Stable Adults Using GE iDXA: Implications for Research and Practice. Nutrients. Oct 12 2018; 10(10). PMID 30321991
25. Bazzocchi A, Ponti F, Cariani S, et al. Visceral fat and body composition changes in a female population after RYGBP: a two-year follow-up by DXA. Obes Surg. Mar 2015; 25(3): 443-51. PMID 25218013
26. Franzoni E, Ciccarese F, Di Pietro E, et al. Follow-up of bone mineral density and body composition in adolescents with restrictive anorexia nervosa: role of dual-energy X-ray absorptiometry. Eur J Clin Nutr. Feb 2014; 68(2): 247-52. PMID 24346474
27. Iyengar NM, Arthur R, Manson JE, et al. Association of Body Fat and Risk of Breast Cancer in Postmenopausal Women With Normal Body Mass Index: A Secondary Analysis of a Randomized Clinical Trial and Observational Study. JAMA Oncol. Feb 01 2019; 5(2): 155-163. PMID 30520976
28. Ashby-Thompson M, Heshka S, Rizkalla B, et al. Validity of dual-energy x-ray absorptiometry for estimation of visceral adipose tissue and visceral adipose tissue change after surgery-induced weight loss in women with severe obesity. Obesity (Silver Spring). May 2022; 30(5): 1057-1065. PMID 35384351
29. Arthur RS, Xue X, Kamensky V, et al. The association between DXA-derived body fat measures and breast cancer risk among postmenopausal women in the Women's Health Initiative. Cancer Med. Feb 2020; 9(4): 1581-1599. PMID 31875358
30. American College of Radiology. ACR-SPR-SSR Practice Parameter for the Performance of Dual-energy X-ray Absorptiometry (DXA). 2018; https://www.acr.org/-/media/ACR/Files/Practice-Parameters/DXA.pdf. 
31. International Society for Clinical Densitometry. 2019 ISCD Official Positions - Adult. 2019; https://iscd.org/learn/official-positions/adult-positions/.  
32. Dent E, Morley JE, Cruz-Jentoft AJ, et al. International Clinical Practice Guidelines for Sarcopenia (ICFSR): Screening, Diagnosis and Management. J Nutr Health Aging. 2018; 22(10): 1148-1161. PMID 30498820

Coding Section

Procedure and diagnosis codes on Medical Policy documents are included only as a general reference tool for each policy. They may not be all-inclusive.

This medical policy was developed through consideration of peer-reviewed medical literature generally recognized by the relevant medical community, U.S. FDA approval status, nationally accepted standards of medical practice and accepted standards of medical practice in this community, Blue Cross Blue Shield Association technology assessment program (TEC) and other nonaffiliated technology evaluation centers, reference to federal regulations, other plan medical policies and accredited national guidelines.

"Current Procedural Terminology © American Medical Association. All Rights Reserved" 

History From 2024 Forward     

01012024  NEW POLICY