Keywords osteoporosis - menopause - FRAX - NOGG - sarcopenia
Palavras-chave osteoporose - menopausa - FRAX - NOGG - sarcopenia
Introduction
An increase in life expectancy and an aging population are associated with a higher
prevalence of osteoporosis and fragility fractures. This certainly occurs in Brazil,
where life expectancy has increased from 50 years in 1952 to 71 in 2010, and is estimated
to be 80 years by 2050.[1 ]
[2 ]
One of the main challenges in osteoporosis care is the identification of individuals
at a higher risk of incurring in fractures and, accordingly, the establishment of
a preventive therapeutic approach. In last few years, clinical tools, associated or
not to dual-energy X-ray absorptiometry (DXA), have been developed to improve the
accuracy of fracture identification. The use of calcaneal quantitative ultrasound
(QUS), a method more practical and less expensive than DXA, to predict the risk of
fracture is also recommended. According to the World Health Organization (WHO), QUS
cannot be used to diagnose osteoporosis or to monitor the effectiveness of the therapy.
There are, however, studies[3 ]
[4 ] that confirm that QUS can predict fractures in elderly women, such as the one by
Moayyeri et al.[3 ] (2012) a meta-analysis with a total follow-up of 279,124 people.
Clinical tools such as the Garvan fracture risk calculator, the QFracture risk calculator,
and the Fracture Risk Assessment Tool (FRAX; https://www.sheffield.ac.uk/FRAX/ ) combine age and gender with clinical risk factors to estimate the risk of fracture
in the next 5 or 10 years. There are also tools for osteoporosis screening, mainly
for women younger than 65 years of age, as DXA is not universally recommended. Tools
such as the Simple Calculated Osteoporosis Risk Estimate (SCORE), the Osteoporosis
Self-Assessment Tool (OST), and the Osteoporosis Risk Assessment Instrument (ORAI),
and even the FRAX, may be mentioned, as there is no standard for the analysis of this
population.[5 ]
[6 ]
Brazilian guidelines recommend the use of the FRAX associated to the strategy for
screening of the National Osteoporosis Guideline Group (NOGG), which enables the classification
of individuals into high-, medium- and low-risk groups for fragility fractures. Those
in the high-risk group should receive pharmacological treatment, those in the medium-risk
group should undergo DXA as screening for osteoporosis, and those in the low-risk
group should be advised on their lifestyle habits.[7 ]
[8 ]
Although these strategies are recommended, very few studies[9 ] have evaluated their accuracy in identifying the risk of fracture and in tracking
osteoporosis in the Brazilian population. In the young American postmenopausal population,
the performance of the FRAX in identifying women with a risk of incurring in fractures
was poor.[12 ] Simpler tools than the FRAX, such as the OST, have shown a better specificity, but
they also demonstrate low sensitivity.[9 ]
[10 ]
[11 ]
[12 ]
The progressive loss of skeletal muscle mass and function in conjunction with aging
is known as sarcopenia. It is considered a component of frailty syndrome leading to
a higher risk of falling and fragility fractures. Its diagnosis is based on the assessment
of muscle force and physical performance. The identification of individuals at risk
of developing sarcopenia is simple, and it can be performed in ambulatory care.[13 ]
[14 ]
[15 ]
Osteoporosis and sarcopenia are usually connected to one another and both contribute
to disability and frailty in the elderly. Nevertheless, clinical signs of sarcopenia
or muscular mass evaluations are not incorporated in the clinical tools for the assessment
of the risk of fracture.[15 ]
Therefore, the present study aims to evaluate the performance of the FRAX associated
with skeletal muscular mass analyses in screening and diagnosing postmenopausal osteoporosis.
Methods
Population
In the present cross-sectional study, clinical data and supplementary exams were reviewed,
after they were collected during the XXII Maratona da Saúde e Cidadania Dr. Claudio
Zago, a health fair health held on April 13th, 2019, by the São Bernardo do Campo
Rotary Club. In this event, the department of obstetrics and gynecology of Faculdade
de Medicina do ABC (FMABC) invited postmenopausal women aged 50 years or older to
take part in the activities in their booth. The activities comprised the application
of structured clinical questionnaires on sarcopenia and osteoporosis, assessments
of the height, weight, and circumferences of the arm, thigh, and calf, a walking speed
test, the handgrip strength test, and the performance of a calcaneal QUS. The present
study was approved by the Ethics in Research Committee of FMABC.
Procedures
Questionnaires
The subjects answered three specific questionnaires: the first one involved personal
and clinical data, the second one was regarding the risk of bone fracture in 10 years
(FRAX), and the third one was on the risk of developing sarcopenia. All questionnaires
were applied by trained medicine students.
Clinical Questionnaire
The subjects were asked about their age, weight, height, ethnicity, time since the
onset of menopause, previous use of hormone replacement therapy, smoking and/or drinking
habits, the regularity of physical activity and muscle mass performance.
Sarcopenia Questionnaire
The subjects answered the Strength, assistance with walking, rising from a chair,
climbing stairs, and falls (SARC-F) questionnaire. Developed by American researchers,
it identifies people with increased risk of developing sarcopenia through five questions
approaching the areas in its name: strength, assistance with walking, rising from
a chair, climbing stairs, and falls. Each answer is scored from 0 to 2, resulting
in a final score ranging from 0 to 10. Scores ≥ 6 indicate a higher risk of developing
sarcopenia.[14 ]
[16 ]
FRAX Questionnaire
All subjects were submitted to the FRAX-Brazil quationnaire. This clinical tool developed
by the WHO matches clinical data and estimates the percentage risk of hip fracture
and major fractures (clinical spinal, forearm, hip and shoulder fractures) for the
following 10 years. In the present study, a risk of major osteoporotic fracture (MOF)
≥ 8.5% on the FRAX was adopted as the criteria to perform a supplementary bone densitometry
exam.[17 ]
NOGG Grading
Using the NOGG tool (available at https://www.sheffield.ac.uk/NOGG/ ), the subjects were classified in low-, medium- and high-risk groups. The NOGG tool
recommends that people in the medium-risk group should undergo the bone density test
to screen for osteoporosis. In the present study, we chose to group the individuals
classified as medium- and high-risk according to the NOGG tool, considering that this
is the population for whom densiometry should be requested or who should undergo pharmacological
treatment.
Anthropometric and Muscle Mass Measurements
The measurements of height, weight and of the circumferences of the arm, thigh and
calf were made with a measuring tape and a Geratherm scale. During weighing, the patients
were guided to take off their coats and bags. The measurment of the circumferences
was standardized as follows:[13 ]
[17 ]
[18 ]
[19 ]
[20 ]
[21 ]
[22 ]
[23 ]
[24 ]
[25 ]
[26 ]
[27 ]
[28 ]
Arm – midpoint between the lateral projection of the acromion process of the scapula
and the lower margin of the ulnar olecranon.
Calf – at its widest point.
Thigh – midpoint on the trochanteric and the margin of the kneecap.
Assessment of Sarcopenia
The subjects were assessed according to the definition of sarcopenia of the European
Working Group on Sarcopenia in Older People (EWGSOP).[14 ]
[16 ] To calculate the muscle mass (MM) in kilos (Kg) recomended by the EWGSOP, the predictive
equation described by Lee et al. [18 ] (2000) was used, in which:
In the equation, Ht refers to the height in centimeters (cm), AC, to the arm circumference
in cm, TC, to the thigh circumference in cm, and CC, to the calf circumference in
cm. Regarding gender, the value of 1 is considered for men, and 0 for women; as for
race, the values are -2.0 for Asians, 1.1 for African-Americans, and 0 for Whites
or Hispanics. In the present study, the race score was adapted, considering -2.0 for
Asians, 1.1 for people who considered themselves black or brown (pardo or negro , in Portuguese) and 0 for people who considered themselves white (branco , in Portuguese).
The skeletal MM index was calculated as MM divided by the squared height. Subjects
with values between 5.5 kg/m2 and 6.76 kg/m2 were considered at risk of developing sarcopenia. The muscle strength was evaluated
using an electronic handgrip, which estimates the person's muscle strength in kg based
on the maximum strength reached in palm pressure. The measurements were recorded using
the dominant arm, with the woman standing up straight, with both arms straight down
and equidistant feet. The gadget was previously calibrated for females aged ∼ 60 years.
Women with results bellow 20 kg were considered at risk of developing sarcopenia.[19 ]
[20 ]
[21 ]
Finally, a walking speed test was used. The women would walk a distance of 6 m, in
which the first meter was used to increase the walking speed, the 4 following meters
were for timing the normal walking speed, and the last meter, for deceleration. Those
with a time ≥ 0.8m/s were considered at risk of developing sarcopenia.
Calcaneal Quantitative Ultrasound (QUS)
All subjects underwent calcaneal QUS, with the GE Lunar Achilles Express ultrasonometer
(GE Healthcare, Chicasgo, IL, US), through which the standard deviation values of
bone mass related to the young adult population (T-score) can be obtained, as well
as those with the same age (Z-score). In the present study, subjects with T-scores
≤ -1.8 sd were considered at risk of developing osteoporosis, and those with scores
≤ -2.5 sd, at risk of incurring in fractures.[29 ]
Statistical Analysis
The Microsoft Excel 2018 (Microsoft Corp. Redmond, WA, US), version 1910, was used
to organize the data obtained, and the MedCalc Statistical Software (MedCalc Software
bv, Ostend, Belgium), version 19.1, was used to conduct the statistical analysis.
The Kolmogorov-Smirnov test was used to test the normal distribution of the numeric
data. The continuous numeric data was expressed as means ± standard deviations, and
the categorical data, as frequencies and percentages. The comparison of the groups
was performed using the Student t -test for independent samples when the continuous numeric data followed a normal distribution,
and the Wilcoxon test, for the data which did not follow a normal distribution. For
the categorical data, the comparisons were made using the Chi-squared test. The diagnostic
accuracy was evaluated through the area under the curve (AUC), following the methodology
described by DeLong et al.[30 ] In all scenarios, a level of significance of 5% was adopted.
Results
A total of 200 patients were evaluated, 2 of whom were excluded for having weight
higher than that allowed by the FRAX. The median age was of 64 ± 7.7 years, the median
body mass index (BMI) was of 27.3 ± 5.3 kg/m2 , and the median T-score in the QUS was od -1.3 sd, ([Table 1 ]). In the comparison of age groups, the population aged ≥ 65 years obtained inferior
values, which was statistically significant, in the parameters related to fat, lean
and bone mass, as well as in the SARC-F and physical performance ([Table 1 ]).
Table 1
Clinical and anthropometric characteristics, diagnostic parameters of sarcopenia,
and bone density of the study sample and comparison when divided by age group
TOTAL
AGE
≤ 65 years (N = 115)
> 65 years (N = 83)
p *
Mean ± standard deviation
Mean ± standard deviation
Mean ± standard deviation
Weight (Kg)
65.8 ± 13.1
67.6 ± 14.1
63.8 ± 10.8
0.0170
Height (m)
1.5 ± 0.1
1.55 ± 0.1
1.5 ± 0.1
< 0.0001
BMI (Kg/m2 )
27.3 ± 5.3
27.7 ± 5.8
26.8 ± 4.4
< 0.0001
AC (cm)
30 ± 4.4
30 ± 4.3
29 ± 4.4
< 0.0001
TC (cm)
50 ± 6.3
51 ± 6.1
49.5 ± 6.5
< 0.0001
CC (cm)
36 ± 4.0
37 ± 4.0
35 ± 4.0
< 0.0001
MM (Kg)
27.7 ± 5.9
28.8 ± 5.9
26.1 ± 5.2
< 0.0001
SMMI (Kg/m2 )
11.3 ± 2.3
11.8 ± 2.3
10.92 ± 2.0
< 0.0001
Handgrip (Kg)
21 ± 5.5
22.3 ± 5.3
19.4 ± 5.5
< 0.0001
GS (m/s)
0.89 ± 0.2
0.9 ± 0.2
0.85 ± 0.2
< 0.0001
T-score on the calcaneal QUS
-1.3 ± 1.3
-1 ± 1.2
-1.6 ± 1.2
< 0.0001
SARC-F
2 ± 2.3
1 ± 2.4
2 ± 2.2
< 0.0001
n (%)
n (%)
n (%)
p
**
Ethnicity
White
119 (60.1)
64 (55.7)
55 (66.3)
0.124
Brown or Black
68 (34.3)
46 (40)
22 (26.5)
Asian
11 (5.5)
5 (4.3)
6 (7.2)
Level of schooling
Illiterate
3 (1.5)
2 (1.7)
1 (1.2)
0.259
Incomplete Primary Education
47 (23.7)
29 (25.2)
18 (21.7)
Complete Primary Education
31 (15.6)
15 (13.0)
16 (19.3)
Incomplete High School
72 (36.3)
47 (40.9)
25 (30.1)
Complete High School
16 (8.0)
10 (8.7)
6 (7.2)
Higher Education
29 (14.6)
12 (10.4)
17 (20.5)
SARC-F ≥ 6
Yes
23 (11.6)
12 (10.4)
8 (9.6)
0.956
No
174 (88.3)
103 (89.6)
75 (90.4)
T-score ≤ -1.8 sd
Yes
58 (29.3)
23 (20)
35 (42.2)
0.001
No
140 (70.7)
92 (80)
48 (57.9)
Z-score ≤ -2.5 sd
Yes
27 (13.6%)
9 (7.8)
18 (21.7)
0.005
No
171 (86.4%)
106 (92.2)
65 (78.3)
; AC, arm circumference; BMI, body mass index, CC, calf circumference; MM, muscle
mass; SMMI, skeletal muscle mass index; VM - gait speed; QUS, quantitative ultrasound;
SARC-F, Strength, assistance with walking, rising from a chair, climbing stairs, and
falls questionnaire; TC, thigh circumference.
Notes: *Correlation between age and the evaluated data through the Wilcoxon correlation
test; **comparison between age over 65 years and ≤ 65 years by the Chi-squared test.
The accuracy of using the FRAX with a MOF risk ≥ 8.5% for osteoporosis screening (T-score
≤ -1.8 sd) was poor ([Fig. 1 ], [Fig. 2 ], [Table 2 ] and [Table 3 ]), with an AUC of 0.604 (95% confidence interval [95%CI]: 0.509–0.694) for women
under 65 years of age, and of 0.642 (95%CI: 0.571–0.709) when age was not considered.
Including MM data in the statistical analysis led to a significant improvement in
the group of women under 65 years of age, with an AUC of 0.705 (95%CI: 0.612–0.786).
Fig. 1 Performance of the Fracture Risk Assessment Tool (FRAX) regarding the risk of major
osteoporotic fracture (MOF) taken in isolation and associated with circumference measurements
to identify women under 65 years of age with T-score ≤ -1.8 sd on calcaneal quantitative
ultrasound (QUS).
Fig. 2 Performance of the FRAX regarding the MOF risk taken in isolation and associated
with circumference measurements to identify women with a QUS T-score ≤ -1,8 sd without
considering age.
Table 2
Area under the curve
Standard Error
95% Confidence Interval
FRAX MOF
0.604
0.059
0.509–0.694
FRAX MOF + CC
0.705
0.058
0.612–0.786
Abbreviations: CC, circumferences; FRAX, Fracture Risk Assessment Tool; MOF, major
osteoporotic fracture.
Table 3
AUC
Standard Error
95% CI
FRAX MOF
0.642
0.041
0.571–0.709
FRAX MOF + CC
0.654
0.043
0.583–0.720
Abbreviations: 95%CI, 95% confidence interval; AUC, area under the curve; CC, circumferences;
FRAX, Fracture Risk Assessment Tool; MOF, major osteoporotic fracture.
[Table 4 ] shows that the NOGG tool had a sensitivity of 17% to identify individuals with QUS
T-score ≤ -1.8 sd, as well as a specificity of 84%, a positive predictive value of
31%, and a negative predictive value of 71%.
Table 4
Comparison between medium- or high-risk and low-risk subjects in the NOGG clinical
guideline to identify individuals with T-score ≤ -1,8 sd on calcaneal qualitative
ultrasound
T-score ≤ -1,8
n (%)
T-score > -1,8
n (%)
p *
Medium- or high-risk on the NOGGclinical guideline
10 (5)
22 (11)
0.7910
Low-risk on the NOGG clinical guideline
48 (24)
118 (60)
Abbreviation: NOGG, National Osteoporosis Guideline Group.
Discussion
In the present study, e observed that the ability to identify low bone mass in women
under 65 years of age was greater when measurements of the circumferences of the arm,
calf, and thigh were associated with the FRAX with a MOF risk ≥ 8.5%.
Although studies are scare, especially regarding the population under 65 years of
age, the relationship between MM measurements and and the risk of fracture has already
been evaluated. Faulkner et al.[32 ] analyzed 8,074 women aged 67 years or older during 1,6 years, and found a correlation
between the length of the hip axis and increased risk of trochanteric fracture (odds
ratio [OR] = 1.6; 95%CI: 1.0–2.4) and femoral neck fracture (OR = 1.9; 95% CI 1.3–3.0).
In another study, Farmer et al.,[31 ] who evaluated a population aged between 40 and 77 years, found a relationship of
the arm muscle area and the thickness of the triceps skinfold with an increased risk
for hip fractures.[12 ]
[31 ]
[32 ]
It stands out that the absolute risk of fracture for any bone density value among
young postmenopausal women is small compared with the risk for those aged over 65
years. According to Doherty et al.,[33 ] the probability of vertebral or hip fracture at 5 years is of 03% and 0% respectively
among women aged between 50 and 54 years, of 0.5% and 0.2% among those aged between
55 and 59 years, and of 1% and 0.2% among women aged between 55 and 64 years. The
performance of universal screening with the bone densitometry test for all women over
50 years of age is an expensive and ineffective strategy. Accordingly, providing a
more accurate screening alternative is critical as a public health strategy.
Currently, although numerous diagnosis tools have already been developed, there is
no consensus as to which should be used, or even as to which guideline should be followed
to identify low bone mass in young postmenopausal women. In 2014, Crandall et al[12 ] evaluated the diagnostic tools for this population, and obtained a FRAX AUC value
of 0,60, which is considered low, and is similar to that found in the present study
(0,604). When comparing it to other screening methods, the authors[12 ] found that the sensitivity and specificity of the OST, which uses only age and weight,
was higher than those of the FRAX with a MOF risk ≥ 8.4%.
The mean of age of 64 years shows that the sample of the present study is representative
of young postmenopausal women, the focus of the study, who, as expected, showed better
performance, strength and MM. Despite this, 20% of this population presented T-scores
≤ -1.8 sd and 7.8% ≤ -2.5 sd in the QUS. This finding differs from the small fracture
rate expected among this population in 5 years, as documented by Doherty et al.[33 ] in 2001, and it can be explained by the fact that the sample was not chosen at random,
but consisted of women who saught medical assistance at a health fair.
The low performance of the NOGG tool when compard with the QUS can be explained by
the fact that the majority of the women included in the study was young, with good
bone mass levels. Another relevant factor is that only 32 patients, a low number,
were classified as high-risk. In any case, there are few studies evaluating the performance
of the NOGG tool among the Brazilian population, especially among women aged ≥ 65
years. Even though the QUS is not a standard for the diagnosis of osteoporosis, it
presents high clinical applicability in terms of the prediction of fractures, as confirmed
by Moayyeri et al.[3 ] in a study with a follow-up of more than 200 thousand person-years.
The results of the present study are substantial, considering that the sample comprised
a significant number of the population, people from the community, and not previously
selected, as occurs with patients cared for in outpatient clinics. Nevertheless, the
present research may be considered notable due to the fact that it is, perhaps, the
first Brazilian study to correlate risk factors for sarcopenia with the diagnosis
of osteoporosis or the risk of fracture. The results have a relevant potential for
application in the medical practice.
The present study has several limitations. The ethnic groups included present different
body fat distribution, a factor considered a bias by Lee et al.[18 ] during the development of the equation for the MM analysis. Further, the population
evaluated was overweight, which interfered with the interpretation of the MM and sarcopenia
results. Another fact considered relevant was that the population had anthropometric
measurements taken in a non-standardized way in relation to their clothing, because
it was an event open to the public, with a high flow of people. In addition, it is
known that the QUS, a method used as a parameter to assess bone mass, is not a standard
for the diagnosis. However, it is a tool that may be used at a health fair with a
reasonable degree of accuracy. The present study will be repeated, with the possibility
of inviting patients and applying bone densitometry in the future.
The association of measurements of the calf, arm and thigh improved the accuracy of
the FRAX to detect individuals under 65 years of age with lower bone mass on the QUS.
This demonstrates the importance of evaluating parameters related to MM in the identification
of individuals at risk of developing osteoporosis or incurring in fragility fractures.
Associating such measures with the FRAX tool, improving the performance of these strategies,
has a great potential regarding osteoporosis care, especially among young postmenopausal
women. Further studies are needed to confirm the findings of the present study and
establish new approaches in the screening and diagnosis of the risk of fracture due
to frailty.
Conclusion
The association of arm, thigh, and calf measurements increased the accuracy of the
FRAX to screen for osteoporosis among women under 65 years of age.
