Performance of Five Phalangeal QUS Parameters in the Evaluation of Gonadal-Status, Age and Vertebral Fracture Risk Compared with DXA

Ultrasound in Med. & Biol., Vol. 35, No. 4, pp. 537–544, 2009 Copyright © 2009 World Federation for Ultrasound in Medicine & Biology Printed in the USA. All rights reserved 0301-5629/09/$–see front matter

doi:10.1016/j.ultrasmedbio.2008.09.027

● Original Contribution PERFORMANCE OF FIVE PHALANGEAL QUS PARAMETERS IN THE EVALUATION OF GONADAL-STATUS, AGE AND VERTEBRAL FRACTURE RISK COMPARED WITH DXA CARLINA V. ALBANESE,* CHIARA CEPOLLARO,† FRANCESCA DE TERLIZZI,‡ MARIA LUISA BRANDI,† and ROBERTO PASSARIELLO* *Service of Bone Densitometry and Ultrasound, Department of Radiological Sciences, University of Rome “Sapienza” School of Medicine, Rome; †Department of Internal Medicine, University of Florence, Florence; and ‡ IGEA Biophysics Laboratory, Carpi, MO, Italy (Received 28 April 2008; revised 8 September 2008; in final form 29 September 2008)

Abstract—The aim of this cross-sectional study was to study the value of five different quantified ultrasound (QUS) parameters—amplitude-dependent speed of sound (AD-SoS), Ultrasound Bone Profile Index (UBPI), fast-wave amplitude (FWA), bone transmission time (BTT) and signal dynamic (SDY)—measured at the phalanges of the hand in discriminating women with vertebral fracture and their relationship with some determinants of bone mass, in particular age and gonadal status compared with lumbar spine and hip dual-energy x-ray absorptiometry (DXA). We included 791 women aged 35– 84 y, divided into premenopause, early menopause and late postmenopause groups on the basis of gonadal status and years since menopause (YSM). The presence of vertebral fracture was evaluated radiographically. All QUS parameters were very sensitive to changes in early postmenopause, with a doubled decrease in early postmenopausal with respect to late postmenopause. In particular AD-SoS and BTT decreases were markedly high in the early postmenopause group. In the late menopause group, similar decreases were observed for AD-SoS, UBPI and hip bone mineral density (BMD). In the multiple logistic model, DXA and QUS significantly discriminate women with and without fractures (p < 0.0001); odds ratio (OR) was higher at lumbar spine BMD (OR 4.01), FWA (OR 3.88), AD-SoS (OR 3.81) and total hip BMD (OR 3.77). Even adjusting the logistic model for age, height, weight, lumbar spine and total hip BMD, all QUS parameters remained significantly predictive of vertebral fracture. AD-SoS showed the best performances both in terms of OR and ROC analysis. QUS parameters show a different behavior in evaluating the effect on bone mass of the time since menopause; AD-SoS and BTT showed a high sensitivity to first changes in bone tissue after menopause. After correction for potential confounders, AD-SoS showed the same ability of lumbar spine BMD in discriminating women with or without vertebral fractures and in the prediction of fracture risk. (E-mail: [email protected]) © 2009 World Federation for Ultrasound in Medicine & Biology. Key Words: QUS, DXA, Osteoporosis, Risk factors, Vertebral fractures.

INTRODUCTION AND LITERATURE

expectancy in developed countries, osteoporosis and related fractures represent one of the major health problems in elderly women (Melton et al. 1997). Demographic studies also indicate a continuing increase in the number of women over 50 years of age, and this population group will dominate in coming decades. In postmenopausal women, a preventive approach in an early phase, before the first fracture has occurred, is likely to slow disease progression, and many fractures may be prevented (Eastell 1998). A reliable diagnostic technique to identify women at risk for fracture is therefore of great importance and could favor a more rational allocation of resources. There are several methods that measure bone mineral density (BMD) and predict the relative fracture risk

Osteoporosis is a systemic skeletal disease characterized by low bone mass and microarchitectural deterioration of bone tissue, with a consequent increase in bone fragility and susceptibility to fracture (Consensus Development Conference 1993). Osteoporosis-related fractures lead to significant morbidity and mortality, reduce the quality of life for affected individuals, and are responsible for greater costs in health care systems (Ensrud et al. 2000; Cooper et al. 1997). With the progressive increase in life Address correspondence to: Carlina V. Albanese, Service of Bone Densitometry and Ultrasound, Department of Radiological Sciences, University of Rome “Sapienza” School of Medicine, V.le R. Elena, 324. 00161 Rome Italy. E-mail: [email protected] 537

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by using ionizing radiation (Genant et al. 1996). Quantitative computed tomography (QCT) and dual x-ray absorptiometry (DXA) are to date considered the best available predictor of osteoporotic fracture (Cummings et al. 1995). However, this technique explains only about 60 – 80% of the variation in bone strength; yet there is evidence that other mechanical aspects of bone are also important in the determination of fracture risk (Hayes et al. 1991). These other factors most likely include microarchitectural parameters that are not assessed by densitometry techniques, such as elasticity, geometry or structure (Gluer et al. 1994). Quantitative ultrasound (QUS) methods have been developed in recent years for the indirect assessment of bone quality and skeletal status on the basis of a variety of experiences, suggesting that ultrasound parameters provide information not only about bone density but also about architecture and elasticity (Kaufman and Einhorn 1993; Njeh et al. 1997; Fuerst et al. 1995). The interest in this technology stems mostly from its practical advantages compared with conventional photon- or x-ray– based methods, i.e., it is relatively inexpensive, free of ionizing radiation and the scanning time is faster, so QUS can be a cost-effective diagnostic choice for osteoporosis screening. The QUS systems that are commercially available can be applied to different peripheral sites such as calcaneus, proximal phalanges of the hand and diaphysis of the tibia. QUS at the phalanges has shown particular interest because it is possible to analyze the ultrasound waveform once it has propagated through the bone (Njeh et al. 1997). The analysis of the ultrasound wave could provide further information on the characteristics of the bone tissue, which are different and independent of bone density alone. The aims of this study were: (i) to evaluate the performance of amplitude-dependent speed of sound (AD-SoS), ultrasound bone profile index (UBPI) and the QUS parameters obtained by the analysis of the ultrasound waveform such as fast-wave amplitude (FWA), bone transmission time (BTT) and signal dynamic (SDY) in identifying women with or without osteoporotic vertebral fractures; and (ii) to compare the performance of QUS parameters with spine and hip DXA and to evaluate the potential role of QUS method in diagnostic evaluation of osteoporosis risk in relation to age and gonadal status. MATERIALS AND METHODS Study population We enrolled 791 healthy Italian women aged 35– 84 y in this cross-sectional study. All of them were of Italian origin, thus Caucasian. The selected population was divided into three groups according to gonadal status and

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years since menopause (YSM): premenopause with menstrual histories indicating current and prior menstrual regularity (11 to 13 cycles/y); early postmenopause with 1–5 YSM (ⱖ12 mo from their last menstrual bleeding); late postmenopause with ⬎5 y after menopause. Weight and height were measured in all participants. The body mass index (BMI) was calculated as the weight in kilograms divided by square height in meters (kg/m2) (Flory 1970). In addition, we required participants to be healthy as assessed by a standard biochemical screening program (blood test: hemoglobin, hematocrit, erythrocytes, leucocytes, platelets, VES, azotemia, creatinine, glycemia, glutamic oxaloacetic transaminase and glutamic pyruvic transaminase, total bilirubin, proteinic electrophoresis, alkaline phosphatases, serum calcium). Our exclusion criteria were conditions likely to influence bone metabolism such as rheumatoid arthritis, impaired renal function (plasma creatinine ⬎120 ␮M), chronic obstructive pulmonary disease, present or previous hyperparathyroidism or hyperhypothyroidism, diabetes mellitus, cancer, intestinal malabsorption, inflammatory bowel disease, granulomatous disease, nutritional disorders, neurologic disease, chronic use of corticosteroids, drug or alcohol abuse, anticonvulsants and diuretic treatment within the last five years. In addition, we excluded women if they received treatment with bone-active agents including calcitonin, estrogen, raloxifene, bisphosphonates, strontium ranelate, anabolic agents, teriparatide, calcium and vitamin D. Participants with history of severe trauma or with previous traumatic fractures were also excluded. Recruitment of studied subjects We recruited a cohort of 2889 females by public announcements in the district of Rome from November 2003 to September 2004 and they were examined at our research Institute. Subjects willing to participate were asked to fill in a short questionnaire concerning previous menstrual cycle irregularity, menopausal status, medical condition, traumatic fractures and accidental muscular–skeletal trauma. On the basis of their answers, we excluded 1892 as not fulfilling the participation criteria mentioned above. Forty-three subjects were excluded because they declined to perform the subsequent medical visit and diagnostic test. The remaining 954 women were screened in our outpatient department, and 791 of these were included in the study. Written informed consent was obtained from each volunteer before examination. The study was approved by the local ethics committee. Bone densitometry Bone densitometry was performed in all subjects by a well-trained technologist (E.M.), using a DXA device

QUS parameters in the evaluation of gonadal-status ● C. V. ALBANESE et al.

in posterior–anterior projection (Hologic QDR 2000 plus, Bedford, MA, USA) at the lumbar spine and proximal femur including femoral neck (neck), greater trochanter (troch) and total hip (total hip). Bone densitometer Hologic QDR 2000 is a device that can be used both as pencil and fan-beam mode. In this study we used the fan-beam geometry to increase scan speed and reduce acquisition time (Faulkner et al. 1993). Subjects for whom less than three vertebrae could be evaluated were excluded from the analysis. Lumbar fractured vertebrae and severely degenerative vertebral bodies identified by x-ray were excluded from the analysis to avoid a false increase of BMD. To calculate the T-score values at lumbar spine and proximal femur, the manufacturer’s reference databases were used. The results are expressed as BMD (in g/cm2) obtained by the mineral content of a region-of-interest divided by the area of that region. Each individual was classified on the basis of her T-scores as normal (T-scores ⬎ ⫺1.0), osteopenic (T-scores from ⬍ ⫺1.0 to ⫺2.5) or osteoporotic (T-scores ⱕ ⫺2.5), according to the World Health Organization (1994). Longterm precision (coefficient of variation) of DXA was determined by repeating two scans within five weeks in 80 women (age range 30 to 55 y). QUS measurement Ultrasound measurements were performed in all subjects at the proximal phalanx metaphysis of the last four fingers of the hand using a DBM Sonic device (Igea, Carpi, Italy). Measurements were performed on the nondominant hand of the study subjects, although in this connection, no significant differences have been observed between the two hands (Ventura et al. 1996). Two probes mounted on a precision caliper, one acting as generator of the signal, the other as receiver, are positioned on the lateral and medial surface of each finger. The emitter probe generates an ultrasound signal with a frequency of 1.25 MHz, the receiver probe receives the ultrasound pulse crossing the phalanx. The coupling of the probes with the skin is mediated by standard ultrasound gel. The device calculates the speed-of-sound (SoS in meters per second [m/s]) through the phalanx by measuring the width of the finger (including soft tissues) divided by the time-of-flight, defined as the time from emitted pulse to received signal, considering the signal that reaches a predetermined minimum amplitude value (2mV) for the first time; thus, the assessed ultrasound velocity is amplitude-dependent speed-of-sound (ADSoS) (Cadossi and Canè 1996). We also evaluated three ultrasound parameters calculated by signal analysis technique on the ultrasound signal received once it transmitted through the phalanx: fast-wave amplitude (FWA) is the amplitude of the first ultrasound pulse received at the receiving probe once the ultrasound pulse has propagated

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throughout the phalanx, bone transmission time (BTT) is the time needed for ultrasound wave to propagate through the bone tissue alone (Wuster et al. 2000) and signal dynamic (SDY) (Wuster et al. 2000) is the sharpness of the first two ultrasound pulses received at the receiving probe and is calculated as the second derivative of the amplitude by time. They have been investigated by Wuster et al. (2000) in a population of postmenopausal women and combined in an optimized model to obtain the Ultrasound Bone Profile Index (UBPI) for the discrimination between fractured and nonfractured subjects (Wuster et al. 2000). To quantify the reproducibility of the device, the interoperator and intraoperator coefficients of variation (CV) were calculated. Precision was assessed as interoperator CV and obtained by having two different operators each performing a set of six sequential measurements on the same subject. Assessment of vertebral fractures To evaluate the presence of a vertebral fracture (low trauma or spontaneous fractures), lateral spinal radiographs performed with the same x-ray equipment as the thoracic and the lumbar spine were taken on all study participants using standardized procedures (Banks et al. 1995). To avoid the problem of poor visualization of vertebrae at the extremes of radiograph, the “breathing technique” was used. In this technique, the patient is instructed to hold their breath, used to show the lower thoracic vertebrae on lateral thoracic films, and then to stop expiration, to show the lower thoracic/upper lumbar vertebra on the lumbar views. The radiographs were evaluated by two independent radiologists, according to the semiquantitative method proposed by Genant et al. (1993). Because the number of grade I fractures was very low (n ⫽ 3), and in two of these some uncertainties were raised among radiologists regarding the correct evaluation, we decided to exclude them from the analysis. Only the established factures grade II (n ⫽ 41) and grade III (n ⫽ 11) as 25– 40% and 40% or greater reduction, respectively, of the anterior, middle or posterior height compared with the same or adjacent vertebrae, were considered. Severe degenerative deformities were not counted as fracture. Quality assurance Additional quality controls were done every morning for DXA and QUS devices according to the manufacturer’s guideline to verify the stability of the respective systems. In particular the calibration of the US device was performed with a standard Plexiglas phantom provided by the manufacturer; amplitude calibration was performed each 6 months by manufacturer personnel with a particular “amplitude phantom” provided by

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Table 1. Clinical characteristics, bone density at spine and hip, and phalangeal ultrasound measurements of all subjects divided according to gonadal status

No. subjects Age (y) Weight (kg) Height (cm) BMI (kg/m2) YSM (y) BMD lumbar spine (g/cm2) BMD neck (g/cm2) BMD troch (g/cm2) BMD total hip (g/cm2) AD-SoS (m/s) UBPI (U) FWA (V) BTT (␮s) SDY (V/␮s2)

Premenopause

Early post-

Late post-

99 48.8 ⫾ 3.8 64.0 ⫾ 10.3 161.7 ⫾ 6.6 24.4 ⫾ 3.3 — 1.023 ⫾ 0.138 0.791 ⫾ 0.111 0.667 ⫾ 0.100 0.729 ⫾ 0.100 2067 ⫾ 62 0.83 ⫾ 0.12 57.0 ⫾ 10.5 1.49 ⫾ 0.20 –60 ⫾ 125

190 53.6 ⫾ 3.7 65.3 ⫾ 9.7 161.1 ⫾ 5.6 25.1 ⫾ 3.4 3.0 ⫾ 1.4 0.938 ⫾ 0.133 0.738 ⫾ 0.102 0.632 ⫾ 0.092 0.685 ⫾ 0.090 2016 ⫾ 70 0.70 ⫾ 0.17 50.0 ⫾ 10.6 1.36 ⫾ 0.27 –159 ⫾ 176

502 63.0 ⫾ 6.6 66.5 ⫾ 10.6 160.0 ⫾ 6.0 26.0 ⫾ 3.9 15.1 ⫾ 7.2 0.870 ⫾ 0.139 0.688 ⫾ 0.104 0.585 ⫾ 0.094 0.637 ⫾ 0.093 1968 ⫾ 65 0.58 ⫾ 0.16 43.9 ⫾ 7.4 1.25 ⫾ 0.23 –272 ⫾ 161

t-test Prep⬍ n.s. n.s. n.s. — p⬍ p⬍ p⬍ p⬍ p⬍ p⬍ p⬍ p⬍ p⬍

vs. early 0.0001

0.0001 0.0001 0.01 0.001 0.0001 0.0001 0.0001 0.0001 0.0001

Early vs. late p ⬍ 0.0001 n.s. p ⬍ 0.05 p ⬍ 0.05 p ⬍ 0.0001 p ⬍ 0.0001 p ⬍ 0.0001 p ⬍ 0.0001 p ⬍ 0.0001 p ⬍ 0.0001 p ⬍ 0.0001 p ⬍ 0.0001 p ⬍ 0.0001 p ⬍ 0.0001

BMI ⫽ Body mass index; YSM ⫽ years since menopause. All parameters are given as mean ⫾ SD.

IGEA. Once every two years, a maintenance control is foreseen by the manufacturer for overall quality control. Statistical analysis Data analysis was performed with SPSS 13.0 software (SPSS Inc., Chicago IL, USA). The results are expressed as mean ⫾ SD. Comparison of the data between groups and the presence of vertebral fracture was determined using an unpaired two-tailed Student’s t-test. Linear regression analysis by Pearson’s formula was performed to determine the correlation coefficient between the different variables. To estimate and compare the longitudinal sensitivity of the methods, we calculated the ratio of annual change (the slope of the regression line between variable and age, expressed as unit/year) and precision error for each variable. Multiple logistic regression analysis was used to estimate the odds ratio (OR) for vertebral fracture and the corresponding 95% confidence interval (CI). Odds ratios were adjusted for the resulting significant anthropometric variables—age, weight and height—to calculate the risk of fracture for one SD decrease of each considered variable of DXA and QUS parameters. Furthermore, for QUS parameters, ORs were also adjusted for lumbar spine BMD and total hip BMD. The area under a receiver operating characteristic (ROC) curve was used to determine the ability of different variables in the discrimination of subjects with vertebral fractures from nonfractured subjects. The area under the curve (AUC) and the standard errors were obtained and p-values were calculated using the method of Hanley and McNeil (1982, 1983). The values of p ⬍ 0.05, p ⬍ 0.005 and p ⬍ 0.0005 were considered significant, very significant and extremely significant, respectively.

RESULTS Quality control (QC) data of both devices did not show any shift or drift during the entire study period. The devices used in the present study were therefore characterized as stable. Precision of the techniques and 95% CI were calculated for DXA: 1.0% (0.9 to 1.1%), 1.6% (1.0 to 2.3%), 1.9% (1.0 to 2.6%) and 1.8% (1.0 to 2.6%) for the spine, neck, troch and total hip, respectively. For QUS parameters, the precision was 0.7% (0.6 to 0.9%) for AD-SoS, 2.4% (2.1 to 2.9%) for UBPI, 4.0% (2.7 to 5.9%) for FWA, 0.7% (0.5 to 0.9%) for BTT and 18% (4 to 36%) for SDY. The characteristics of the whole population are: mean age 59.0 ⫾ 7.9 y (range 35 to 84); mean weight 65.9 ⫾ 10.4 kg (range 42 to 110); mean height 160.4 ⫾ 6.0 cm (range 143 to 178); mean BMI 25.6 ⫾ 3.7 kg/m2 (range 17 to 42). A group of 99 subjects were in premenopause; 190 subjects were in early postmenopause; and 502 subjects were in late postmenopause. Table 1 shows the demographic characteristics of the three groups of women identified by gonadal status and YSM according to the variables and parameters determined. The early postmenopausal group was matched vs. preand late postmenopausal groups. The early and premenopausal women differed by age and by all QUS and DXA parameters (p ⬍ 0.0001; BMD total hip p ⬍ 0.001; BMD troch p ⬍ 0.01), whereas between the two postmenopausal groups, a significant difference was also found for height and BMI (p ⬍ 0.05). Influence of age and YSM on QUS and DXA parameters Correlation coefficients for BMD, AD-SoS and UBPI versus age were evaluated on the basis of different

QUS parameters in the evaluation of gonadal-status ● C. V. ALBANESE et al.

Table 2. Annual changes in early and late postmenopause, normalized for precision of the measurements Annual change adjusted for precision error (1/y)

Early postmenopause

Late postmenopause

⫺0.300 ⫺0.653 ⫺0.299 ⫺0.671 ⫺0.387 ⫺0.364 ⫺0.370 ⫺0.303 ⫺0.278

⫺0.125 ⫺0.351 ⫺0.127 ⫺0.479 ⫺0.176 ⫺0.182 ⫺0.278 ⫺0.303 ⫺0.278

AD-SoS UBPI FWA BTT SDY BMD lumbar spine BMD neck BMD troch BMD total hip

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fracture (grade II or III). We compared the vertebral fractured group with the remaining 640 postmenopausal women without fractures. Fractured subjects were older, weighed less and had a low BMI, compared with nonfractured women (p ⬍ 0.05). Both DXA and QUS measurements could discriminate postmenopausal women with and without fractures (Table 3). In the multiple logistic model, all measurements by DXA and QUS showed a significant contribution to discriminating between the two groups with and without fractures (p ⬍ 0.0001) (Table 3). However, the OR, which indicates the increase of fracture risk for 1 SD decrease of bone measurement, was higher at lumbar spine BMD (OR 4.01), followed by FWA (OR 3.88), AD-SoS (OR 3.81) and total hip BMD (OR 3.77), respectively. BTT featured the lowest OR (1.95), followed by UBPI (OR 2.45) and trochanter BMD (OR 2.76). The highest clinical value of lumbar spine BMD (OR 4.10) and AD-SoS (OR 4.20) to discriminate the group at risk of vertebral fractures was also confirmed when the OR was age-, weight- and height-adjusted. Also, FWA showed an extremely high OR (4.18). The poorest gradient of risk was observed at BTT (1.84) and troch BMD (OR 2.42), respectively. When we applied ROC analysis to subjects with and without vertebral fractures, the best discriminative performance was seen again for lumbar spine (AUC 0.84 ⫾ 0.03), followed with the same discriminative ability by total hip BMD (AUC 0.81 ⫾ 0.03), AD-SoS (AUC 0.79 ⫾ 0.03) and neck BMD (AUC 0.79 ⫾ 0.03), p ⫽ n.s. among methods (Table 3 and Fig. 1). The multiple logistic model has also been applied to adjust relative ORs of QUS parameters for lumbar spine and total hip BMD. All QUS parameters remain significantly predictive of fracture occurrence (p ⬍ 0.005), as reported in Table 4.

Measurements were calculated as the ratio between absolute annual change and standard deviation of repeated measurement (precision). Data are expressed in 1/year.

gonadal status. In the postmenopausal groups, we also evaluated the correlation of DXA and QUS with YSM. In premenopause, only neck BMD is positively related to age (p ⬍ 0.05). In early postmenopause AD-SoS (p ⬍ 0.0001), UBPI (p ⬍ 0.0001), FWA (p ⬍ 0.001) and SDY (p ⬍ 0.0001) are negatively associated with age; in late postmenopause, all variables are significantly related to age (p ⬍ 0.05). AD-SoS (p ⬍ 0.0001), UBPI (p ⬍ 0.0001), FWA (p ⬍ 0.001) and SDY (p ⬍ 0.0001) are also associated with YSM, both in early and late postmenopause. In particular, UBPI and BTT decreases are markedly high in early postmenopause. Neck and troch BMD are significantly related to YSM only in late postmenopause (p ⬍ 0.005), and lumbar BMD is related to YSM only in early postmenopause (p ⬍ 0.005). In Table 2, the annual changes adjusted for precision error of each variable are reported in early and late postmenopause. Fracture discrimination Among the postmenopausal women affected by osteoporosis, 52 subjects (7.5%) had at least one vertebral

Table 3. Comparison of age, anthropometric, lumbar spine and hip bone density and ultrasonography parameters between postmenopausal women with and without fractures No Fracture Mean ⫾ SD BMD lumbar spine BMD neck BMD troch BMD total hip AD-SoS UBPI FWA BTT SDY

Fractured Mean ⫾ SD

0.901 ⫾ 0.134 0.736 ⫾ 0.124 0.710 ⫾ 0.104 0.606 ⫾ 0.089 0.604 ⫾ 0.093 0.516 ⫾ 0.083 0.657 ⫾ 0.092 0.561 ⫾ 0.081 1987 ⫾ 65 1905 ⫾ 74 0.62 ⫾ 0.16 0.46 ⫾ 0.16 46.0 ⫾ 8.8 40.5 ⫾ 7.7 1.30 ⫾ 0.24 1.09 ⫾ 0.24 ⫺231 ⫾ 169 ⫺360 ⫾ 171

t-test p p p p p p p p p

⬍ ⬍ ⬍ ⬍ ⬍ ⬍ ⬍ ⬍ ⬍

0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001

Odds ratio 4.01 3.62 2.76 3.77 3.81 2.45 3.88 1.95 8.54

95% CI

Odds ratio adj. for age, weight and height

95% CI

AUC

p-value

2.77–5.81 2.47–5.32 1.98–3.84 2.55–5.57 2.72–5.33 1.85–3.24 2.09–7.21 1.54–2.48 3.65–19.98

4.10 3.38 2.42 3.60 4.20 2.54 4.18 1.84 8.28

2.72–6.19 2.18–5.24 1.67–3.51 2.28–5.71 2.91–6.08 1.86–3.47 2.08–8.41 1.44–2.35 3.23–21.23

0.84 ⫾ 0.03 0.79 ⫾ 0.03 0.78 ⫾ 0.03 0.81 ⫾ 0.03 0.79 ⫾ 0.03 0.77 ⫾ 0.03 0.67 ⫾ 0.03 0.74 ⫾ 0.03 0.71 ⫾ 0.04

⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001

Simple odds ratios; odds ratios adjusted for age, weight and height (with 95% confidence intervals); area under the ROC curve (with p-value) for all densitometric parameters.

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Fig. 1. Representation of the ROC curves for all densitometric variables. (a) DXA; (b) QUS.

DISCUSSION In this paper we report the results of a cross-sectional study conducted on a large untreated Caucasian Italian population in which five different QUS parameters, as well as DXA at the lumbar spine and proximal hip, were tested to evaluate their ability in the discrimination of osteoporotic vertebral fractures, and to investigate their behavior in relation to age and menopause. The results of the present study suggest that in our cohort of women, BMD of the lumbar spine and femoral neck, as well as phalangeal QUS parameters, are able to discriminate postmenopausal women with vertebral fractures, even adjusting for age, menopause and anthropometric variables. A large number of studies have examined the relationship between DXA and QUS measured at various sites and fracture risk; the available data up to 1997 have been summarized in a review article by Gregg et al.

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(1997). The discriminatory potential to classify subjects with or without vertebral fractures has been tested crosssectionally, with different QUS devices including ultrasound at the phalanges and DXA in a population-based sample of elderly postmenopausal women (Hartl et al. 2002). The performance of five quantitative ultrasound devices and their associations with prevalent vertebral fractures, in comparison with DXA in a population-based sample of different ages from younger to older women, has also been reported (Gluer et al. 2004). Furthermore, the utility of both QUS of the phalanges and DXA to identify the subjects with spine fracture or low BMD, assessed also in relation to BMI on the QUS parameters in healthy postmenopausal women, has recently been reported (Alexandersen et al. 2005). However, one advantage of this study is that for the first time five different QUS parameters measured at the phalanges—AD-SoS, UBPI, FWA, BTT and SDY—were tested in a large population from premenopausal to elderly women to evaluate their performances not only in the discrimination of fractured and nonfractured women, but also in their relationships with their climacteric condition (Albanese et al. 1996; Kanis et al. 2002). It has been observed that in premenopause, age did not influence the bone measurements of either DXA or QUS, with the exception of a significant positive correlation with femoral neck. This confirms the results reported by Slemenda et al. (1996) and supports the evidence that bone density is usually stable before menopause in healthy women. Our results point out the high sensitivity of QUS parameters in the detection of changes in the bone tissue in early postmenopause, especially for what concerns UBPI and BTT, which show the highest adjusted annual change in this period (Table 2). AD-SoS, UBPI, FWA and SDY decreases in early postmenopause are double, with respect to late postmenopause (Table 2), similar to lumbar spine BMD, but different from hip BMD. This observation argues strongly in favor of previous reports on the relationship between menstrual cycle regularity and US velocity decrease at the phalanges (Ventura et al. 1996; Rico et al. 2001). Those reports showed that phalangeal QUS is significantly affected by the hormonal

Table 4. Odds ratios adjusted for age, weight, height, BMD lumbar spine and BMD total hip (with 95% confidence intervals)

AD-SoS UBPI FWA BTT SDY

Adj. odds ratio

95% CI

p-value

3.50 1.95 3.06 1.60 4.89

2.32–5.30 1.38–2.75 1.47–6.35 1.21–2.10 1.74–13.74

⬍ 0.0001 ⬍ 0.0001 0.003 0.001 0.003

QUS parameters in the evaluation of gonadal-status ● C. V. ALBANESE et al.

changes occurring in early postmenopause, following the decline in gonadal activity. Although the limitation of the cross-sectional design of this study does not allow us to reach a definitive conclusion, it suggests, as with other studies (Alexandersen et al. 2005; Camozzi et al. 2007), that QUS at the phalanges may represent an index of bone tissue condition that could be used to evaluate the degree of bone mineralization after estrogen decreases in the early postmenopause. The analysis of fracture discrimination revealed that QUS has an ability quite similar to neck BMD to identify vertebral fracture. Furthermore, when adjusting for age, weight and height, the increase of risk for 1 SD decrease reaches the value of 4.20 for AD-SoS and 4.18 for FWA, almost equivalent to that of lumbar spine BMD. UBPI and SDY show OR values similar to trochanter BMD, whereas BTT shows a lower value (OR 1.84). Other studies (Hartl et al. 2002; Gluer et al. 2004; Gnudi et al. 2004) have shown lower ORs in the discrimination of vertebral fractures, which may be a result of differences in the characteristics of the investigated populations: it should be noted that in all these studies the same result was obtained in terms of comparison between DXA and QUS—indeed the ORs are similar between the two techniques in these studies as well as in our experience. Only in the OPUS study (Gluer et al. 2004) a slightly but significantly lower AUC was found for AD-SoS compared with lumbar spine BMD in the discrimination of subjects with vertebral fractures. Alexandersen et al. (2005) reported for AD-SoS and UBPI similar performances of lumbar spine, distal radius and total body BMD in the discrimination of vertebral fractures, but lower than total hip of the femoral neck BMD. No studies are available reporting OR for the QUS parameters FWA, SDY and BTT, probably because they are usually evaluated together in the UBPI, because it is a mathematical combination of those three parameters. Regarding the discriminatory ability, in our study FWA showed the best performance in terms of OR, both unadjusted and adjusted for age, height and weight. Its OR is similar to that obtained by AD-SoS and lumbar spine BMD. Conversely, ROC analysis revealed a lower discriminatory ability with respect to all other QUS parameters, even if it was already highly significant. In general, ROC analysis showed a lower AUC for all three parameters (i.e., FWA, BTT and SDY). When adjusted also for lumbar spine and total hip BMD, all QUS parameters are highly significant predictors of vertebral fractures and AD-SoS again showed the highest OR, followed by FWA, SDY and UBPI. BTT showed the poorest performance, probably because of the low sensitivity of this parameter to the changes of bone tissue that are mainly reflected by attenuation, like FWA and SDY. It should be noted that several studies have shown that its main char-

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acteristic is the stability over time and independence on soft tissue thickness, and these facts have contributed to reach a sufficient longitudinal sensitivity in monitoring the effects of pharmaceutical interventions (Mauloni et al. 2000; Ingle et al. 2005; Gonnelli et al. 2006). At first glance, FWA and SDY seemed to perform better than UBPI in fracture discrimination, but when looking at the ROC analysis, it is clear that UBPI has a better performance with respect to FWA and SDY. Furthermore, the better precision of UBPI with respect to FWA and especially SDY makes the parameter more suitable in clinical practice. The limitations of the study can be ascribed mainly to the lack of information regarding other important risk factors for osteoporosis, not related only to menopause, age and anthropometry. Furthermore, this work was a cross-sectional study on a large population that needs to be further validated in a prospective design. In conclusion, in our study group, QUS parameters show a different sensitivity in evaluating the effect on bone mass of some of the main risk factors for osteoporosis such as gonadal status and age. AD-SoS seems to be more sensitive to bone changes in relation to gonadal status, whereas UBPI reflects bone alterations because of aging. Lastly, AD-SoS showed sensitivity as good as DXA at lumbar spine for the discrimination between nonfractured women and women with osteoporotic vertebral fractures. The other QUS parameters significantly discriminate between fractured and nonfractured subjects, even when adjusted for age, weight, height, lumbar spine BMD and total hip BMD, i.e., they have a prediction ability of fracture that is independent on BMD alone. The best performance is always obtained by AD-SoS. Further longitudinal studies are needed to define the role of AD-SoS and namely of other parameters calculated by signal analysis technique on the ultrasound signal received once transmitted through the phalanx, in the prediction of fracture and their potential use in monitoring the effect of estrogen failure and age on bone mineralization. REFERENCES Albanese CV, Civitelli R, Tibollo FG, Masciangelo R, Mango D. Endocrine and physical determinants of bone mass in late postmenopause. Exp Clin Endocrinol Diabetes 1996;104:263–270. Alexandersen P, de Terlizzi F, Tankó LB, Bagger YZ, Christiansen C. Comparison of quantitative ultrasound of the phalanges with conventional bone densitometry in healthy postmenopausal women. Osteoporos Int 2005;16:1071–1078. Banks LM, van Kuij C, Genant HR. Radiographic technique for assessing osteoporotic vertebral deformity. In: Genant HR, Jergas M, van Kuij C, editors. Vertebral Fracture in Osteoporosis. Berkeley, CA: University of California Press, 1995:131–147. Cadossi R, Canè V. Pathways of trasmission of ulrasound energy through the distal metaphysis of the second phalanx of pigs: an in vitro study. Osteoporosis Int 1996;6:196 –206.

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