Correlation between bone quality and microvascular damage in systemic sclerosis patients

Correlation between bone quality and microvascular damage in systemic sclerosis patients Abstract Objectives SSc patients are recognized as presenting an increased risk of altered bone mass. The aim of this study was to assess the bone quality, by trabecular bone score (TBS), in SSc patients in correlation with different levels of microvascular damage, as evaluated by nailfold videocapillaroscopy (NVC), and to compare the results regarding bone quality with RA patients and healthy subjects (CNT). Methods Eighty-four SSc patients, 98 RA patients and 60 CNT, were studied. BMD (g/cm2) of the lumbar spine (L1–L4) was analysed by DXA scan. Lumbar spine bone quality was derived from each spine DXA examination using the TBS analysis. NVC patterns were analysed. Results A total of 56/84 SSc patients (66%) as well as 78/98 RA patients (80%) showed bone loss at DXA and BMD was found to be significantly lower than in the CNT (P < 0.001). Similarly, lumbar spine TBS was found to be significantly lower in SSc and RA patients than in CNT (P < 0.001). TBS values were found to be lower in SSc with a late NVC pattern, compared with the active or early pattern (late vs active and early pattern, P < 0.001). There was no statistically significant difference in the mean lumbar spine TBS between SSc and RA patients (P = 0.238). Conclusion The data obtained showed significantly lower bone quality (lower TBS and BMD) in SSc and RA patients compared with CNT. The bone quality seemed lower in SSc patients with more altered microvasculature (late NVC pattern). osteoporosis, systemic sclerosis, rheumatoid arthritis, bone mineral density, trabecular bone score, connective tissue diseases Rheumatology key messages SSc and RA patients might present an increased risk of low bone mass. Trabecular bone score allows information about bone microstructure of SSc patients to be obtained. Trabecular bone score values are decreased in SSc patients with late nailfold videocapillaroscopic pattern. Introduction Osteoporosis (OP) is a progressive systemic disease, characterized by low bone mass and microarchitecture deterioration of the bone tissue, with a consequent increase in bone fragility and fracture risk. Treatment of this disease often necessitates a multidisciplinary approach [1–3]. OP may be classified as either primary or secondary. Primary OP is bone loss associated with the ageing process in both men and women. Although the rate of activation of skeletal bone remodelling units in primary OP is normal, the filling of bone resorption pits is incomplete. Secondary OP is bone loss due to a variety of chronic medical conditions, such as medication effects or nutritional deficiencies. Most types of secondary OP show an increase in the activation rate of skeletal bone remodelling units at least initially, to such an extent that an increased proportion of the skeleton is undergoing remodelling at any one time [1–3]. Several studies have demonstrated that patients with rheumatic inflammatory diseases present an increased risk of low bone mass [4, 5]. In rheumatic diseases, for example SSc and RA, the aetiology of bone loss is multi-factorial, resulting from disability, age, longstanding diseases, low BMI, chronic systemic inflammation and low vitamin D serum concentrations [6–12]. SSc is a chronic autoimmune CTD, characterized by microvascular damage and progressive fibrosis of the skin and internal organs [13]. The severity of the microvascular impairment might be quantified by nailfold videocapillaroscopy (NVC) patterns [14–16]. It has been reported that there is a higher incidence of OP and bone fractures in SSc patients than in healthy controls [17, 18]. RA is commonly associated with secondary OP, but has recently been taken into account also as an independent risk factor in the assessment of bone fracture risk [19, 20]. In 1994, the WHO established operational definitions of OP and osteopenia in postmenopausal white women based on BMD to help researchers and clinicians to classify degrees of bone loss. Currently, the clinical practice gold standard for the diagnosis of OP, including secondary causes, is the analysis of BMD with DXA [21–23]. There are different limitations in BMD sensitivity, for example BMD takes into account both trabecular and cortical compartments and does not detect all of the factors that contribute to bone strength, such as bone quality [21–23]. In the past few years several studies have demonstrated that the bone microarchitecture plays a determinant role in bone strength. The trabecular bone score (TBS) was developed to meet the need for an index able to assess bone microarchitecture. TBS is based on standard DXA images and provides additional skeletal information to the standard BMD results [24, 25]. The TBS provides an indirect measurement of bone axial microarchitecture and bone quality since cancellous bone microarchitecture cannot be measured by DXA [24, 25]. This study aimed to assess bone mass and bone quality in female postmenopausal patients affected by SSc in comparison with a high-risk population affected by RA and a control group, by evaluating the TBS. To the best of our knowledge, this is the first study to evaluate the use of TBS in SSc patients with different nailfold videocapillaroscopy (NVC) pattern. Methods Study population Eighty-four SSc patients [mean age 65 (9) years] and 98 RA patients [mean age 61 (8) years] were enrolled, during routine clinical assessment in our Rheumatology Department from January 2013 to November 2016. Sixty healthy controls [mean age 64 (11) years] were also evaluated. All subjects with SSc, RA and CNT were women in the postmenopausal period (see Table 1). The SSc patients met either LeRoy’s criteria for the classification of early SSc or the ACR/EULAR 2013 criteria for SSc [26, 27]. Table 1 Characteristics of the SSc and RA patients and controls Clinical characteristics SSc (n = 84) RA (n = 98) Control (n = 60) Age, mean (s.d.), years 65 (9) 61 (8) 64 (11) BMI, mean (s.d.), kg/m2 25.2 (3.9) 23.9 (4.2) 23.7 (3.2) Age of menopause, mean (s.d.), years 47.4 (5.1) 48.2 (4.6) 49.1 (3.8) Disease duration, mean (s.d.), years 9.8 (7.9) 17.1 (11.2) NA Smoking status, current, % 6.2 5.9 12.4 Alcohol intake, current, % 5.8 5.1 6.8 ALP bone, mean (s.d.), U/l 7.46 (2.06) 12.13 (5.3) 18.45 (4.51) 25(OH)D, mean (s.d.), ng/ml 14.2 (7.4) 19.1 (6.2) 32.8 (2.3) Clinical characteristics SSc (n = 84) RA (n = 98) Control (n = 60) Age, mean (s.d.), years 65 (9) 61 (8) 64 (11) BMI, mean (s.d.), kg/m2 25.2 (3.9) 23.9 (4.2) 23.7 (3.2) Age of menopause, mean (s.d.), years 47.4 (5.1) 48.2 (4.6) 49.1 (3.8) Disease duration, mean (s.d.), years 9.8 (7.9) 17.1 (11.2) NA Smoking status, current, % 6.2 5.9 12.4 Alcohol intake, current, % 5.8 5.1 6.8 ALP bone, mean (s.d.), U/l 7.46 (2.06) 12.13 (5.3) 18.45 (4.51) 25(OH)D, mean (s.d.), ng/ml 14.2 (7.4) 19.1 (6.2) 32.8 (2.3) ALP bone: bone alkaline phosphatase; NA: not applicable. Table 1 Characteristics of the SSc and RA patients and controls Clinical characteristics SSc (n = 84) RA (n = 98) Control (n = 60) Age, mean (s.d.), years 65 (9) 61 (8) 64 (11) BMI, mean (s.d.), kg/m2 25.2 (3.9) 23.9 (4.2) 23.7 (3.2) Age of menopause, mean (s.d.), years 47.4 (5.1) 48.2 (4.6) 49.1 (3.8) Disease duration, mean (s.d.), years 9.8 (7.9) 17.1 (11.2) NA Smoking status, current, % 6.2 5.9 12.4 Alcohol intake, current, % 5.8 5.1 6.8 ALP bone, mean (s.d.), U/l 7.46 (2.06) 12.13 (5.3) 18.45 (4.51) 25(OH)D, mean (s.d.), ng/ml 14.2 (7.4) 19.1 (6.2) 32.8 (2.3) Clinical characteristics SSc (n = 84) RA (n = 98) Control (n = 60) Age, mean (s.d.), years 65 (9) 61 (8) 64 (11) BMI, mean (s.d.), kg/m2 25.2 (3.9) 23.9 (4.2) 23.7 (3.2) Age of menopause, mean (s.d.), years 47.4 (5.1) 48.2 (4.6) 49.1 (3.8) Disease duration, mean (s.d.), years 9.8 (7.9) 17.1 (11.2) NA Smoking status, current, % 6.2 5.9 12.4 Alcohol intake, current, % 5.8 5.1 6.8 ALP bone, mean (s.d.), U/l 7.46 (2.06) 12.13 (5.3) 18.45 (4.51) 25(OH)D, mean (s.d.), ng/ml 14.2 (7.4) 19.1 (6.2) 32.8 (2.3) ALP bone: bone alkaline phosphatase; NA: not applicable. The severity of skin involvement was quantified by the modified Rodnan skin score in each SSc patient and was used to differentiate the two principal subsets of skin involvement, that is lcSSc confined to face and extremities and dcSSc [28]. All the RA patients fulfilled the ACR/EULAR 2010 criteria for RA [29]. A complete medical history was collected and a clinical examination was performed for all study participants. Demographic data, such as age, gender, height, weight and BMI, were recorded for all subjects. All patients were not affected by secondary causes of OP, such as metabolic and endocrinological diseases or drug-induced OP. The data reported in our retrospective study were obtained during routine clinical imaging examinations performed in clinical practice, and therefore no ethical approval was necessary. We obtained patients’ written informed consent to use their imaging pictures and the demographic data as educational material and for publications. The inclusion criteria were patients with a diagnosis of SSc or RA; all patients presenting to our Department are usually given routine OP screening during evaluation. Moreover, all patients had been on a stable drug regimen for at least 2 months prior to study entry. The exclusion criteria were being on a drug regimen that could potentially influence bone turnover such bisphosphonate, and dosage of glucocorticoid (prednisone equivalent) ⩾7.5 mg/day. The patients’ history included information about vertebral and non-vertebral fractures assessed with lateral spinal radiographs of the thoracic and lumbar spine and other areas when possible. BMD X-ray absorptiometry (DXA scan, Lunar Prodigy, GE Lunar, Madison, WI, USA) was used to obtain BMD (g/cm2) in all SSc and RA patients, as well as in controls. Both lumbar spines (L1–L4) and the left hip (femoral neck, Ward’s triangle, trochanter, total hip) were examined and the instruments were calibrated daily, according to the manufacturer’s instructions. The weight, height, age and gender of each patient were used to estimate BMD (expressed as g/cm2 with s.d.) and compared with the BMD values of controls. BMD values were expressed as a T-score, which shows the amount of bone present compared with a young adult of the same gender with peak bone mass [21–23]. A score above −1 is considered normal in BMD T-scores obtained at the femur and lumbar spine, a score between −1 and −2.5 is classified as osteopenia (low bone mass) and a score below −2.5 is defined as OP. We also calculated the Z-score. This number reflects the amount of bone present compared with other people in the same age group, of the same size and gender. If this score is unusually high or low, further medical tests may be advisable [21–23]. TBS The TBS is a relatively new tool that allows for evaluation of the bone microarchitecture through the acquisition and measurement of the pixel variations that correspond to the attenuation of the X-ray beam of each single point represented by greyscale images in the DXA of the lumbar spine. The variations in the greyscale measured on DXA 2D images reflect the absorption property variations that are characteristic and the different microarchitectural 3D conformations of the trabecular tissue, allowing for a direct comparison with the BMD score and application to existing datasets [23, 24]. Although TBS is not a direct measurement of bone microarchitecture, it is related to 3D bone characteristics, such as the trabecular number, trabecular separation, connectivity density and Parfitt parameters [23, 24, 30–32]. A steep variogram slope with a high TBS value is associated with better bone structure, whereas low TBS values indicate a worse bone structure. TBS is typically measured at the lumbar spine and is determined by using the same region of interest as the BMD measurement, so that vertebrae excluded from the BMD calculation, for example vertebrae with fractures or OA, are also excluded from the TBS analysis. Although the TBS result is given for each vertebra, the TBS value reported represents the average of L1–L4 [23, 24, 30–32]. Vertebrae are mainly constituted of trabecular bone. A normal range for TBS values in postmenopausal women has been proposed: a TBS of 1.350 or more is considered normal; a TBS between 1.200 and 1.350 is considered consistent with partially degraded microarchitecture and a TBS of 1.200 or less defines degraded microarchitecture. These cutoff points were established by analogy with the three BMD categories, that is normal bone mass, osteopenia and OP. Interestingly, a normal range for TBS in men has not yet been proposed [23, 24, 30–32]. The lumbar spine L1–L4 TBS was calculated on each spine DXA examination blinded to clinical parameters and outcomes using TBS iNsight (Medimaps Group/GE Healthcare Needham, MA, USA, software version 2.1.0.0) [23, 24, 30–32]. As mentioned, TBS is a grey-level measure of texture using a modified experimental variogram that can be extracted from DXA images and provides an indirect measurement of bone axial microarchitecture and information on bone quality [19, 22]. The manufacturer’s cross-calibration for TBS was on each device before the software was installed. TBS is a texture analysis parameter correlated to the bone microarchitecture Parfitt parameters [23, 24, 30–32]. Bone parameters After informed consent had been obtained, a complete blood chemistry evaluation of bone metabolism was made [serum alkaline phosphatase (ALP), parathormone, 25-hydroxyvitamin D (25(OH)D), calcium and phosphorus] [7–12] for all groups. NVC In order to place the SSc patients into groups according to the correct microangiopathy pattern (early, active or late), as previously reported by Cutolo and colleagues [14–16, 33, 34], NVC was performed using an optical probe equipped with a ×200 contact lens, connected to image analysis software (Videocap, DS Medica, Milan, Italy). There were 18 SSc patients with an early, 18 with an active and 48 with a late NVC pattern. Statistical analysis Statistical analysis were performed using Prism version 5.02 (GraphPad Software, La Jolla, CA, USA). Non-parametric tests were used for the statistical analysis. The Mann–Whitney U-test was performed to compare unpaired groups of variables and the Kruskal–Wallis test to compare continuous variables with nominal variables with more than two levels. The Spearman rank correlation test was used to search for any relationships between variables, along with linear regression tests. P < 0.05 was considered statistically significant. The results are reported as mean along with s.d. Results BMD was significantly lower in both SSc and RA patients than in the control group (P < 0.001) (see Table 2). No significant difference was observed in the mean lumbar spine BMD between patients with SSc and RA (P = 0.238). Table 2 TBS and BMD values in SSc and RA patients and controls Tests SSc (n = 84) RA (n = 98) CNT (n = 60) P-value TBS 1.032 (0.163) 0.904 (0.148) 1.361 (0.126) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.998 (0.161) 0.862 (0.194) 1.240 (0.932) <0.001 Femoral neck BMD, g/cm2 0.784 (0.212) 0.668 (0.141) 0.845 (0.164) <0.001 Ward’s triangle BMD, g/cm2 0.563 (0.173) 0.486 (0.221) 0.657 (0.106) <0.001 Trochanter BMD, g/cm2 0.666 (0.104) 0.589 (0.231) 0.725 (0.143) <0.001 Total hip BMD, g/cm2 0.827 (0.182) 0.764 (0.244) 1.033 (0.161) <0.001 Tests SSc (n = 84) RA (n = 98) CNT (n = 60) P-value TBS 1.032 (0.163) 0.904 (0.148) 1.361 (0.126) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.998 (0.161) 0.862 (0.194) 1.240 (0.932) <0.001 Femoral neck BMD, g/cm2 0.784 (0.212) 0.668 (0.141) 0.845 (0.164) <0.001 Ward’s triangle BMD, g/cm2 0.563 (0.173) 0.486 (0.221) 0.657 (0.106) <0.001 Trochanter BMD, g/cm2 0.666 (0.104) 0.589 (0.231) 0.725 (0.143) <0.001 Total hip BMD, g/cm2 0.827 (0.182) 0.764 (0.244) 1.033 (0.161) <0.001 Values are stated as mean (s.d.). CNT: control; TBS: trabecular bone score. Table 2 TBS and BMD values in SSc and RA patients and controls Tests SSc (n = 84) RA (n = 98) CNT (n = 60) P-value TBS 1.032 (0.163) 0.904 (0.148) 1.361 (0.126) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.998 (0.161) 0.862 (0.194) 1.240 (0.932) <0.001 Femoral neck BMD, g/cm2 0.784 (0.212) 0.668 (0.141) 0.845 (0.164) <0.001 Ward’s triangle BMD, g/cm2 0.563 (0.173) 0.486 (0.221) 0.657 (0.106) <0.001 Trochanter BMD, g/cm2 0.666 (0.104) 0.589 (0.231) 0.725 (0.143) <0.001 Total hip BMD, g/cm2 0.827 (0.182) 0.764 (0.244) 1.033 (0.161) <0.001 Tests SSc (n = 84) RA (n = 98) CNT (n = 60) P-value TBS 1.032 (0.163) 0.904 (0.148) 1.361 (0.126) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.998 (0.161) 0.862 (0.194) 1.240 (0.932) <0.001 Femoral neck BMD, g/cm2 0.784 (0.212) 0.668 (0.141) 0.845 (0.164) <0.001 Ward’s triangle BMD, g/cm2 0.563 (0.173) 0.486 (0.221) 0.657 (0.106) <0.001 Trochanter BMD, g/cm2 0.666 (0.104) 0.589 (0.231) 0.725 (0.143) <0.001 Total hip BMD, g/cm2 0.827 (0.182) 0.764 (0.244) 1.033 (0.161) <0.001 Values are stated as mean (s.d.). CNT: control; TBS: trabecular bone score. Lumbar spine TBS was significantly lower in SSc and RA patients than in the control group [respectively, 1.032 (0.163) and 0.904 (0.148) vs 1.361 (0.126), both P < 0.001]. There was no statistically significant difference in mean lumbar spine TBS between patients with SSc and those with RA (P = 0.238). It is noteworthy that the TBS values in the scleroderma patients correlated positively with the values of the measured BMD at the level of the spine (P = 0.04), femoral neck (P < 0.01) and whole femur (P < 0.01). When the three categories of capillaroscopic patterns were compared for the SSc patients, it was observed that the TBS values were lower in the group of patients with a late pattern, compared with the groups with an active or early pattern (late vs active and early pattern, P < 0.001). Interestingly, there was no statistically significant difference in the BMD values, measured on the column, femoral neck and whole femur (late vs active and early pattern, P = 0.07) (see Table 3). Table 3 TBS, BMD and bone parameters in SSc patients with different NVC patterns Tests Early (n = 18) Active (n = 18) Late (n = 48) P-value TBS 1.182 (0.09) 1.101 (0.80) 1.074 (0.10) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.989 (0.161) 1.064 (0.027) 0.968 (0.145) >0.05 Femoral neck BMD, g/cm2 0.774 (0.087) 0.841 ( 0.108) 0.745 (0.118) >0.05 Ward’s triangle BMD, g/cm2 0.597 (0.102) 0.601 (0.101) 0.562 (0.118) >0.05 Trochanter BMD, g/cm2 0.681 (0.064) 0.731 (0.129) 0.654 (0.095) >0.05 Total hip BMD, g/cm2 0.858 (0.124) 0.882 (0.127) 0.798 (0.133) >0.05 25(OH)D, ng/ml 19.14 (7.5) 15.14 (5.3) 12.14 (7.10) 0.002 ALP osse, U/l 8.95 (2.35) 8.35 (1.40) 6.65 (1.81) <0.0001 Tests Early (n = 18) Active (n = 18) Late (n = 48) P-value TBS 1.182 (0.09) 1.101 (0.80) 1.074 (0.10) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.989 (0.161) 1.064 (0.027) 0.968 (0.145) >0.05 Femoral neck BMD, g/cm2 0.774 (0.087) 0.841 ( 0.108) 0.745 (0.118) >0.05 Ward’s triangle BMD, g/cm2 0.597 (0.102) 0.601 (0.101) 0.562 (0.118) >0.05 Trochanter BMD, g/cm2 0.681 (0.064) 0.731 (0.129) 0.654 (0.095) >0.05 Total hip BMD, g/cm2 0.858 (0.124) 0.882 (0.127) 0.798 (0.133) >0.05 25(OH)D, ng/ml 19.14 (7.5) 15.14 (5.3) 12.14 (7.10) 0.002 ALP osse, U/l 8.95 (2.35) 8.35 (1.40) 6.65 (1.81) <0.0001 NVC: nailfold videocapillaroscopy; TBS: trabecular bone score. Table 3 TBS, BMD and bone parameters in SSc patients with different NVC patterns Tests Early (n = 18) Active (n = 18) Late (n = 48) P-value TBS 1.182 (0.09) 1.101 (0.80) 1.074 (0.10) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.989 (0.161) 1.064 (0.027) 0.968 (0.145) >0.05 Femoral neck BMD, g/cm2 0.774 (0.087) 0.841 ( 0.108) 0.745 (0.118) >0.05 Ward’s triangle BMD, g/cm2 0.597 (0.102) 0.601 (0.101) 0.562 (0.118) >0.05 Trochanter BMD, g/cm2 0.681 (0.064) 0.731 (0.129) 0.654 (0.095) >0.05 Total hip BMD, g/cm2 0.858 (0.124) 0.882 (0.127) 0.798 (0.133) >0.05 25(OH)D, ng/ml 19.14 (7.5) 15.14 (5.3) 12.14 (7.10) 0.002 ALP osse, U/l 8.95 (2.35) 8.35 (1.40) 6.65 (1.81) <0.0001 Tests Early (n = 18) Active (n = 18) Late (n = 48) P-value TBS 1.182 (0.09) 1.101 (0.80) 1.074 (0.10) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.989 (0.161) 1.064 (0.027) 0.968 (0.145) >0.05 Femoral neck BMD, g/cm2 0.774 (0.087) 0.841 ( 0.108) 0.745 (0.118) >0.05 Ward’s triangle BMD, g/cm2 0.597 (0.102) 0.601 (0.101) 0.562 (0.118) >0.05 Trochanter BMD, g/cm2 0.681 (0.064) 0.731 (0.129) 0.654 (0.095) >0.05 Total hip BMD, g/cm2 0.858 (0.124) 0.882 (0.127) 0.798 (0.133) >0.05 25(OH)D, ng/ml 19.14 (7.5) 15.14 (5.3) 12.14 (7.10) 0.002 ALP osse, U/l 8.95 (2.35) 8.35 (1.40) 6.65 (1.81) <0.0001 NVC: nailfold videocapillaroscopy; TBS: trabecular bone score. Serum levels of 25(OH)D were statistically significantly lower in patients with SSc than in the control group [14.2 (7.4) vs 32.8 (2.3) ng/ml, P < 0.001]. Bone ALP level was lower in the SSc group than in the control group [7.46 (2.06) vs 18.45 (4.51) U/l; P < 0.001]. There was a positive correlation between the TBS values and the bone ALP values (P < 0.0001) and a negative correlation with the duration in terms of years of RP in the SSc patients (P < 0.01). There was no statistically significant correlation between the TBS values and serum PTH, 25(OH)D, calcium, phosphorus or SSc disease duration in years. A statistically significant difference between the three different capillaroscopic patterns was observed in the 25(OH)D values, bone ALP and duration of RP. There was no statistically significant difference in the PTH, calcium or phosphorus serum concentrations (see Table 3). There was a positive correlation between the TBS values and bone ALP values (respectively, late P = 0.002; active P = 0.003; early P = 0.004) for all three groups, while only in the late pattern group was a negative correlation observed between the TBS and SSc duration, in years, of RP (P < 0.0001). There was no correlation between the TBS values in the three groups and the BMD measured at the spine, femoral neck and level of the whole femur or between the vitamin D values. Furthers subdividing the scleroderma patient groups into three subgroups on the basis of the presence/absence of previous vertebral fractures, this study demonstrated that 20/29 (68%) patients with previous vertebral fractures had a late pattern, 6 (21%) an active pattern and 3 (11%) an early pattern. Moreover, 44% of all the patient groups had OP and 56% osteopenia. A total of 29 SSc patients (34%) had had a previous vertebral fracture and it was observed that all the patients with previous vertebral fracture had a low bone mass and that 13 (44%) had OP and 16 (56%) osteopenia. The TBS values were significantly lower in the subgroup of SSc patients with previous vertebral fractures than in those without fractures [0.990 (0.07) vs 1.178 (0.07); P < 0.0001]. The vitamin D values were statistically lower in the subgroup of SSc patients with previous fractures than the subgroup of patients without vertebral fractures [8.51 (12.6) vs 17.16 (7.25) ng/ml; P < 0.0001]. The BMD measured at the spine and the whole femur were statistically significantly lower in the facture subgroup than the subgroup without fractures [respectively, column BMD 0.982 (0.16) vs 1.016 (0.14) g/cm2, P = 0.006; BMD femur entire 0.755 (0.13) vs 0.851 (0.12) g/cm2; P = 0.0009]. Discussion Decreased BMD and TBS values in SSc and RA patients compared with healthy matched controls were observed in this study. It was also demonstrated that SSc patients with a late nailfold capillaroscopy pattern showed lower TBS values than patients with an early or active pattern. Interestingly, no difference in BMD values was observed for the three groups. In addition, our study confirmed that patients with chronic rheumatic inflammatory diseases have a higher OP and osteopenia risk associated with the BMD obtained by DXA, as established in 1994 by the WHO [21–23]. However, several studies have reported various limitations in BMD sensitivity, such as BMD not being able to detect bone quality [21–23]. Recently it was demonstrated that bone microarchitecture plays a determinant rule in bone strength. The TBS is novel and based on an imaging technique that uses standard DXA images. Evidence to date indicates that it is an index of bone texture that provides skeletal information additional to that obtained by the standard BMD [24, 25]. Our study confirmed that TBS, evaluated at the lumbar spine, with lumbar and femoral BMD, is able to discriminate patients with altered bone microstructure. The authors propose it be used as a clinical tool in the general diagnosis of OP in chronic inflammatory rheumatic diseases, such as SSc and RA, in line with other reports [4, 5, 35]. Although there are other imaging techniques able to provide direct information on trabecular bone microarchitecture, for example magnetic resonance and CT, these are not simple to use in routine practice since they are expensive and not always available and can examine only peripheral area bone. Bone damage may have multi-factorial underlying causes: disability, age, longstanding diseases, a low BMI, chronic systemic inflammation, low vitamin D levels and some treatment regimes [6–12]. In SSc patients, the presence of lower serum 25(OH)D levels than those observed in the control groups and the fact that it is lower in late pattern patients than in active or early ones may be related to a reduced vitamin D intestinal absorption [7, 8, 10–12]. Furthermore, the 25(OH)D value correlated with TBS but not with BMD, as already observed by Koumakis et al. [35]. These data confirmed that the two techniques evaluated different aspects of bone and that they may be used together to enhance evaluation of bone damage. Moreover, there were statistically significant lower ALP levels in SSc patients than in the control group. It is noteworthy that this value was lower in patients with a late pattern than in those with an active or early one, with a probable correlation to a reduced bone turnover and bone neoformation [36]. Finally, it was demonstrated that there is a negative correlation between the reduced bone microarchitecture, evaluated by TBS, and the progression of microvascular damage, studied by NVC; this observation suggests that the microvascular damage is correlated with systemic SSc clinical complications, including bone impairment [37–40]. A limitation to the present study might be that the number of subjects was not identical in all groups, due to a single centre recruitment and the use of exclusion criteria. However, the total sample size was considered sufficient. Moreover, almost 70% of the RA cases were treated with low dose glucocorticoids (<5 mg prednisone/day) but we have no data as to the patients’ cumulative prednisone dosage. In conclusion, this study confirmed that TBS (and BMD) may well represent a complementary tool for the evaluation of bone quality and the risk of fracture in various diseases, as well as in SSc patients [18, 35, 41–43]. The bone quality seems lower in SSc patients with more altered microcirculation (NVC patterns). Therefore, TBS may represent a further marker to estimate the general clinical status in chronic rheumatic diseases at least in SSc. Acknowledgements The authors would like to thank Barbara Wade, contract Professor at the University of Torino, for her linguistic advice. Barbara Ruaro is supported by a Grant from the Italian Society of Rheumatology. Vanessa Smith is a Senior Clinical Investigator of the Research Foundation—Flanders (Belgium) (FWO) [1802915N]. Funding: No specific funding was received from any bodies in the public, commercial or not-for-profit sectors to carry out the work described in this manuscript. Disclosure statement: The authors have declared no conflicts of interest. References 1 Lane NE. Epidemiology, etiology, and diagnosis of osteoporosis . Am J Obstet Gynecol 2006 ; 194 (Suppl 2) : 3 – 11 . Google Scholar CrossRef Search ADS 2 Hiligsmann M , Dellaert BG , Dirksen CD et al. Patients' preferences for anti-osteoporosis drug treatment: a cross-European discrete choice experiment . Rheumatology 2017 ; 56 : 1167 – 76 . Google Scholar CrossRef Search ADS PubMed 3 Lems WF , Dreinhöfer KE , Bischoff-Ferrari H et al. EULAR/EFORT recommendations for management of patients older than 50 years with a fragility fracture and prevention of subsequent fractures . Ann Rheum Dis 2017 ; 76 : 802 – 10 . Google Scholar CrossRef Search ADS PubMed 4 Maruotti N , Corrado A , Cantatore FP. Osteoporosis and rheumatic diseases . Reumatismo 2014 ; 66 : 125 – 35 . Google Scholar CrossRef Search ADS PubMed 5 Sinigaglia L , Varenna M , Girasole G , Bianchi G. Epidemiology of osteoporosis in rheumatic diseases . Rheum Dis Clin North Am 2006 ; 32 : 631 – 58 . Google Scholar CrossRef Search ADS PubMed 6 Avouac J , Koumakis E , Toth E et al. Increased risk of osteoporosis and fracture in women with systemic sclerosis: a comparative study with rheumatoid arthritis . Arthritis Care Res 2012 ; 64 : 1871 – 8 . Google Scholar CrossRef Search ADS 7 Cutolo M , Otsa K , Paolino S et al. Vitamin D involvement in rheumatoid arthritis and systemic lupus erythaematosus . Ann Rheum Dis 2009 ; 68 : 446 – 7 . Google Scholar CrossRef Search ADS PubMed 8 Cutolo M , Paolino S , Sulli A et al. Vitamin D, steroid hormones, and autoimmunity . Ann N Y Acad Sci 2014 ; 1317 : 39 – 46 . Google Scholar CrossRef Search ADS PubMed 9 Seriolo B , Paolino S , Casabella A et al. Osteoporosis in the elderly . Aging Clin Exp Res 2013 ; 25 (Suppl 1) : 27 – 9 . Google Scholar CrossRef Search ADS 10 Cutolo M , Pizzorni C , Sulli A. Vitamin D endocrine system involvement in autoimmune rheumatic diseases . Autoimmun Rev 2011 ; 11 : 84 – 7 . Google Scholar CrossRef Search ADS PubMed 11 Trombetta AC , Smith V , Gotelli E et al. Vitamin D deficiency and clinical correlations in systemic sclerosis patients: a retrospective analysis for possible future developments . PLoS One 2017 ; 12 : e0179062 . Google Scholar CrossRef Search ADS PubMed 12 Seriolo B , Molfetta L , Cutolo M. Seasonal variations in serum levels of 25-hydroxyvitamin D in patients with systemic sclerosis . Clin Rheumatol 2011 ; 30 : 445 – 6 . Google Scholar CrossRef Search ADS PubMed 13 Gabrielli A , Avvedimento EV , Krieg T. Scleroderma . N Engl J Med 2009 ; 360 : 1989 – 2003 . Google Scholar CrossRef Search ADS PubMed 14 Cutolo M , Smith V. State of the art on nailfold capillaroscopy: a reliable diagnostic tool and putative biomarker in rheumatology? Rheumatology 2013 ; 52 : 1933 – 40 . Google Scholar CrossRef Search ADS PubMed 15 Cutolo M , Pizzorni C , Tuccio M et al. Nailfold videocapillaroscopic patterns and serum autoantibodies in systemic sclerosis . Rheumatology 2004 ; 43 : 719 – 26 . Google Scholar CrossRef Search ADS PubMed 16 Cutolo M , Ruaro B , Smith V. Macrocirculation versus microcirculation and digital ulcers in systemic sclerosis patients . Rheumatology 2017 ; 56 : 1834 – 6 . Google Scholar CrossRef Search ADS PubMed 17 Atteritano M , Sorbara S , Bagnato G et al. Bone mineral density, bone turnover markers and fractures in patients with systemic sclerosis: a case control study . PLoS One 2013 ; 8 : e66991 . Google Scholar CrossRef Search ADS PubMed 18 Omair MA , Pagnoux C , McDonald-Blumer H , Johnson SR. Low bone density in systemic sclerosis. A systematic review . J Rheumatol 2013 ; 40 : 1881 – 90 . Google Scholar CrossRef Search ADS PubMed 19 van Staa TP , Geusens P , Bijlsma JW , Leufkens HG , Cooper C. Clinical assessment of the long-term risk of fracture in patients with rheumatoid arthritis . Arthritis Rheum 2006 ; 54 : 3104 – 12 . Google Scholar CrossRef Search ADS PubMed 20 Kaz Kaz H , Johnson D , Kerry S et al. Fall-related risk factors and osteoporosis in women with rheumatoid arthritis . Rheumatology 2004 ; 43 : 1267 – 71 . Google Scholar CrossRef Search ADS PubMed 21 Lewiecki EM. Review of guidelines for bone mineral density testing and treatment of osteoporosis . Curr Osteoporos Rep 2005 ; 3 : 75 – 83 . Google Scholar CrossRef Search ADS PubMed 22 Chun KJ. Bone densitometry . Semin Nucl Med 2011 ; 41 : 220 – 8 . Google Scholar CrossRef Search ADS PubMed 23 El Maghraoui A , Roux C. DXA scanning in clinical practice . QJM 2008 ; 101 : 605 – 17 . Google Scholar CrossRef Search ADS PubMed 24 Silva BC , Leslie WD , Resch H et al. Trabecular bone score: a noninvasive analytical method based upon the DXA image . J Bone Miner Res 2014 ; 29 : 518 – 30 . Google Scholar CrossRef Search ADS PubMed 25 Kang KY , Goo HY , Park SH , Hong YS. Trabecular bone score as an assessment tool to identify the risk of osteoporosis in axial spondyloarthritis: a case-control study . Rheumatology 2018 ; 57 : 462 – 9 . Google Scholar CrossRef Search ADS PubMed 26 LeRoy EC , Meedsger TA Jr. Criteria for the classification of early systemic sclerosis . J Rheumatol 2001 ; 28 : 1573 – 6 . Google Scholar PubMed 27 van den Hoogen F , Khanna D , Fransen J et al. 2013 classification criteria for systemic sclerosis: an American College of Rheumatology/European League Against Rheumatism collaborative initiative . Ann Rheum Dis 2013 ; 72 : 1747 – 55 . Google Scholar CrossRef Search ADS PubMed 28 Clements P , Lachenbruch P , Siebold J et al. Inter and intraobserver variability of total skin thickness score (modified Rodnan TSS) in systemic sclerosis . J Rheumatol 1995 ; 22 : 1281 – 5 . Google Scholar PubMed 29 Aletaha D , Neogi T , Silman AJ et al. 2010 rheumatoid arthritis classification criteria: an American College of Rheumatology/European League against Rheumatism Collaborative Initiative . Ann Rheum Dis 2010 ; 69 : 1580 – 8 . Google Scholar CrossRef Search ADS PubMed 30 Parfitt AM , Mathews CH , Villanueva AR et al. Relationships between surface, volume, and thickness of iliac trabecular bone in aging and in osteoporosis. Implications for the microanatomic and cellular mechanisms of bone loss . J Clin Invest 1983 ; 72 : 1396 – 409 . Google Scholar CrossRef Search ADS PubMed 31 Hans D , Goertzen AL , Krieg MA , Leslie WD. Bone microarchitecture assessed by TBS predicts osteoporotic fractures indipendent of bone density: the Manitoba study . J Bone Miner Res 2011 ; 26 : 2762 – 9 . Google Scholar CrossRef Search ADS PubMed 32 Harvey NC , Glüer CC , Binkley N et al. Trabecular bone score (TBS) as a new complementary approach for osteoporosis evaluation in clinical practice . Bone 2015 ; 78 : 216 – 24 . Google Scholar CrossRef Search ADS PubMed 33 Cutolo M , Sulli A , Secchi ME , Paolino S , Pizzorni C. Nailfold capillaroscopy is useful for the diagnosis and follow-up of autoimmune rheumatic diseases. A future tool for the analysis of microvascular heart involvement? Rheumatology 2006 ; 45 (Suppl 4) : 43 – 6 . Google Scholar CrossRef Search ADS 34 Ruaro B , Sulli A , Pizzorni C et al. Correlations between skin blood perfusion values and nailfold capillaroscopy scores in systemic sclerosis patients . Microvasc Res 2016 ; 105 : 119 – 24 . Google Scholar CrossRef Search ADS PubMed 35 Koumakis E , Avouac J , Winzenrieth R et al. Trabecular bone score in female patients with systemic sclerosis: comparison with rheumatoid arthritis and influence of glucocorticoid exposure . J Rheumatol 2015 ; 42 : 228 – 35 . Google Scholar CrossRef Search ADS PubMed 36 Smith V , Riccieri V , Pizzorni C et al. Nailfold capillaroscopy for prediction of novel future severe organ involvement in systemic sclerosis . J Rheumatol 2013 ; 40 : 2023 – 8 . Google Scholar CrossRef Search ADS PubMed 37 Ingegnoli F , Ardoino I , Boracchi P , Cutolo M et al. Nailfold capillaroscopy in systemic sclerosis: data from the EULAR scleroderma trials and research (EUSTAR) database . Microvasc Res 2013 ; 89 : 122 – 8 . Google Scholar CrossRef Search ADS PubMed 38 Riccieri V , Vasile M , Iannace N et al. Systemic sclerosis patients with and without pulmonary arterial hypertension: a nailfold capillaroscopy study . Rheumatology 2013 ; 52 : 1525 – 8 . Google Scholar CrossRef Search ADS PubMed 39 Cutolo M , Herrick AL , Distler O et al. Nailfold videocapillaroscopic features and other clinical risk factors for digital ulcers in systemic sclerosis: a multicenter, prospective cohort study . Arthritis Rheumatol 2016 ; 68 : 2527 – 39 . Google Scholar CrossRef Search ADS PubMed 40 Corrado A , Correale M , Mansueto N et al. Nailfold capillaroscopic changes in patients with idiopathic pulmonary arterial hypertension and systemic sclerosis-related pulmonary arterial hypertension . Microvasc Res 2017 ; 114 : 46 – 51 . Google Scholar CrossRef Search ADS PubMed 41 Burmester GR , Bijlsma JWJ , Cutolo M , McInnes IB. Managing rheumatic and musculoskeletal diseases—past, present and future . Nat Rev Rheumatol 2017 ; 13 : 443 – 8 . Google Scholar CrossRef Search ADS PubMed 42 Olsson A , Oturai AB , Søndergaard HB , Sellebjerg F , Oturai PS. Bone microarchitecture and bone mineral density in multiple sclerosis . Acta Neurol Scand 2018 ; 137 : 363 – 9 . Google Scholar CrossRef Search ADS PubMed 43 Heise V , Galli-Lysak I , Villiger PM , Aeberli D. Increased bone mineral density at the hypoxia prone site of the juxta-articular metacarpal bone in patients with limited systemic sclerosis: a cross-sectional study . J Musculoskelet Neuronal Interact 2014 ; 14 : 189 – 94 . Google Scholar PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. 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Correlation between bone quality and microvascular damage in systemic sclerosis patients

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© The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com
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Abstract

Abstract Objectives SSc patients are recognized as presenting an increased risk of altered bone mass. The aim of this study was to assess the bone quality, by trabecular bone score (TBS), in SSc patients in correlation with different levels of microvascular damage, as evaluated by nailfold videocapillaroscopy (NVC), and to compare the results regarding bone quality with RA patients and healthy subjects (CNT). Methods Eighty-four SSc patients, 98 RA patients and 60 CNT, were studied. BMD (g/cm2) of the lumbar spine (L1–L4) was analysed by DXA scan. Lumbar spine bone quality was derived from each spine DXA examination using the TBS analysis. NVC patterns were analysed. Results A total of 56/84 SSc patients (66%) as well as 78/98 RA patients (80%) showed bone loss at DXA and BMD was found to be significantly lower than in the CNT (P < 0.001). Similarly, lumbar spine TBS was found to be significantly lower in SSc and RA patients than in CNT (P < 0.001). TBS values were found to be lower in SSc with a late NVC pattern, compared with the active or early pattern (late vs active and early pattern, P < 0.001). There was no statistically significant difference in the mean lumbar spine TBS between SSc and RA patients (P = 0.238). Conclusion The data obtained showed significantly lower bone quality (lower TBS and BMD) in SSc and RA patients compared with CNT. The bone quality seemed lower in SSc patients with more altered microvasculature (late NVC pattern). osteoporosis, systemic sclerosis, rheumatoid arthritis, bone mineral density, trabecular bone score, connective tissue diseases Rheumatology key messages SSc and RA patients might present an increased risk of low bone mass. Trabecular bone score allows information about bone microstructure of SSc patients to be obtained. Trabecular bone score values are decreased in SSc patients with late nailfold videocapillaroscopic pattern. Introduction Osteoporosis (OP) is a progressive systemic disease, characterized by low bone mass and microarchitecture deterioration of the bone tissue, with a consequent increase in bone fragility and fracture risk. Treatment of this disease often necessitates a multidisciplinary approach [1–3]. OP may be classified as either primary or secondary. Primary OP is bone loss associated with the ageing process in both men and women. Although the rate of activation of skeletal bone remodelling units in primary OP is normal, the filling of bone resorption pits is incomplete. Secondary OP is bone loss due to a variety of chronic medical conditions, such as medication effects or nutritional deficiencies. Most types of secondary OP show an increase in the activation rate of skeletal bone remodelling units at least initially, to such an extent that an increased proportion of the skeleton is undergoing remodelling at any one time [1–3]. Several studies have demonstrated that patients with rheumatic inflammatory diseases present an increased risk of low bone mass [4, 5]. In rheumatic diseases, for example SSc and RA, the aetiology of bone loss is multi-factorial, resulting from disability, age, longstanding diseases, low BMI, chronic systemic inflammation and low vitamin D serum concentrations [6–12]. SSc is a chronic autoimmune CTD, characterized by microvascular damage and progressive fibrosis of the skin and internal organs [13]. The severity of the microvascular impairment might be quantified by nailfold videocapillaroscopy (NVC) patterns [14–16]. It has been reported that there is a higher incidence of OP and bone fractures in SSc patients than in healthy controls [17, 18]. RA is commonly associated with secondary OP, but has recently been taken into account also as an independent risk factor in the assessment of bone fracture risk [19, 20]. In 1994, the WHO established operational definitions of OP and osteopenia in postmenopausal white women based on BMD to help researchers and clinicians to classify degrees of bone loss. Currently, the clinical practice gold standard for the diagnosis of OP, including secondary causes, is the analysis of BMD with DXA [21–23]. There are different limitations in BMD sensitivity, for example BMD takes into account both trabecular and cortical compartments and does not detect all of the factors that contribute to bone strength, such as bone quality [21–23]. In the past few years several studies have demonstrated that the bone microarchitecture plays a determinant role in bone strength. The trabecular bone score (TBS) was developed to meet the need for an index able to assess bone microarchitecture. TBS is based on standard DXA images and provides additional skeletal information to the standard BMD results [24, 25]. The TBS provides an indirect measurement of bone axial microarchitecture and bone quality since cancellous bone microarchitecture cannot be measured by DXA [24, 25]. This study aimed to assess bone mass and bone quality in female postmenopausal patients affected by SSc in comparison with a high-risk population affected by RA and a control group, by evaluating the TBS. To the best of our knowledge, this is the first study to evaluate the use of TBS in SSc patients with different nailfold videocapillaroscopy (NVC) pattern. Methods Study population Eighty-four SSc patients [mean age 65 (9) years] and 98 RA patients [mean age 61 (8) years] were enrolled, during routine clinical assessment in our Rheumatology Department from January 2013 to November 2016. Sixty healthy controls [mean age 64 (11) years] were also evaluated. All subjects with SSc, RA and CNT were women in the postmenopausal period (see Table 1). The SSc patients met either LeRoy’s criteria for the classification of early SSc or the ACR/EULAR 2013 criteria for SSc [26, 27]. Table 1 Characteristics of the SSc and RA patients and controls Clinical characteristics SSc (n = 84) RA (n = 98) Control (n = 60) Age, mean (s.d.), years 65 (9) 61 (8) 64 (11) BMI, mean (s.d.), kg/m2 25.2 (3.9) 23.9 (4.2) 23.7 (3.2) Age of menopause, mean (s.d.), years 47.4 (5.1) 48.2 (4.6) 49.1 (3.8) Disease duration, mean (s.d.), years 9.8 (7.9) 17.1 (11.2) NA Smoking status, current, % 6.2 5.9 12.4 Alcohol intake, current, % 5.8 5.1 6.8 ALP bone, mean (s.d.), U/l 7.46 (2.06) 12.13 (5.3) 18.45 (4.51) 25(OH)D, mean (s.d.), ng/ml 14.2 (7.4) 19.1 (6.2) 32.8 (2.3) Clinical characteristics SSc (n = 84) RA (n = 98) Control (n = 60) Age, mean (s.d.), years 65 (9) 61 (8) 64 (11) BMI, mean (s.d.), kg/m2 25.2 (3.9) 23.9 (4.2) 23.7 (3.2) Age of menopause, mean (s.d.), years 47.4 (5.1) 48.2 (4.6) 49.1 (3.8) Disease duration, mean (s.d.), years 9.8 (7.9) 17.1 (11.2) NA Smoking status, current, % 6.2 5.9 12.4 Alcohol intake, current, % 5.8 5.1 6.8 ALP bone, mean (s.d.), U/l 7.46 (2.06) 12.13 (5.3) 18.45 (4.51) 25(OH)D, mean (s.d.), ng/ml 14.2 (7.4) 19.1 (6.2) 32.8 (2.3) ALP bone: bone alkaline phosphatase; NA: not applicable. Table 1 Characteristics of the SSc and RA patients and controls Clinical characteristics SSc (n = 84) RA (n = 98) Control (n = 60) Age, mean (s.d.), years 65 (9) 61 (8) 64 (11) BMI, mean (s.d.), kg/m2 25.2 (3.9) 23.9 (4.2) 23.7 (3.2) Age of menopause, mean (s.d.), years 47.4 (5.1) 48.2 (4.6) 49.1 (3.8) Disease duration, mean (s.d.), years 9.8 (7.9) 17.1 (11.2) NA Smoking status, current, % 6.2 5.9 12.4 Alcohol intake, current, % 5.8 5.1 6.8 ALP bone, mean (s.d.), U/l 7.46 (2.06) 12.13 (5.3) 18.45 (4.51) 25(OH)D, mean (s.d.), ng/ml 14.2 (7.4) 19.1 (6.2) 32.8 (2.3) Clinical characteristics SSc (n = 84) RA (n = 98) Control (n = 60) Age, mean (s.d.), years 65 (9) 61 (8) 64 (11) BMI, mean (s.d.), kg/m2 25.2 (3.9) 23.9 (4.2) 23.7 (3.2) Age of menopause, mean (s.d.), years 47.4 (5.1) 48.2 (4.6) 49.1 (3.8) Disease duration, mean (s.d.), years 9.8 (7.9) 17.1 (11.2) NA Smoking status, current, % 6.2 5.9 12.4 Alcohol intake, current, % 5.8 5.1 6.8 ALP bone, mean (s.d.), U/l 7.46 (2.06) 12.13 (5.3) 18.45 (4.51) 25(OH)D, mean (s.d.), ng/ml 14.2 (7.4) 19.1 (6.2) 32.8 (2.3) ALP bone: bone alkaline phosphatase; NA: not applicable. The severity of skin involvement was quantified by the modified Rodnan skin score in each SSc patient and was used to differentiate the two principal subsets of skin involvement, that is lcSSc confined to face and extremities and dcSSc [28]. All the RA patients fulfilled the ACR/EULAR 2010 criteria for RA [29]. A complete medical history was collected and a clinical examination was performed for all study participants. Demographic data, such as age, gender, height, weight and BMI, were recorded for all subjects. All patients were not affected by secondary causes of OP, such as metabolic and endocrinological diseases or drug-induced OP. The data reported in our retrospective study were obtained during routine clinical imaging examinations performed in clinical practice, and therefore no ethical approval was necessary. We obtained patients’ written informed consent to use their imaging pictures and the demographic data as educational material and for publications. The inclusion criteria were patients with a diagnosis of SSc or RA; all patients presenting to our Department are usually given routine OP screening during evaluation. Moreover, all patients had been on a stable drug regimen for at least 2 months prior to study entry. The exclusion criteria were being on a drug regimen that could potentially influence bone turnover such bisphosphonate, and dosage of glucocorticoid (prednisone equivalent) ⩾7.5 mg/day. The patients’ history included information about vertebral and non-vertebral fractures assessed with lateral spinal radiographs of the thoracic and lumbar spine and other areas when possible. BMD X-ray absorptiometry (DXA scan, Lunar Prodigy, GE Lunar, Madison, WI, USA) was used to obtain BMD (g/cm2) in all SSc and RA patients, as well as in controls. Both lumbar spines (L1–L4) and the left hip (femoral neck, Ward’s triangle, trochanter, total hip) were examined and the instruments were calibrated daily, according to the manufacturer’s instructions. The weight, height, age and gender of each patient were used to estimate BMD (expressed as g/cm2 with s.d.) and compared with the BMD values of controls. BMD values were expressed as a T-score, which shows the amount of bone present compared with a young adult of the same gender with peak bone mass [21–23]. A score above −1 is considered normal in BMD T-scores obtained at the femur and lumbar spine, a score between −1 and −2.5 is classified as osteopenia (low bone mass) and a score below −2.5 is defined as OP. We also calculated the Z-score. This number reflects the amount of bone present compared with other people in the same age group, of the same size and gender. If this score is unusually high or low, further medical tests may be advisable [21–23]. TBS The TBS is a relatively new tool that allows for evaluation of the bone microarchitecture through the acquisition and measurement of the pixel variations that correspond to the attenuation of the X-ray beam of each single point represented by greyscale images in the DXA of the lumbar spine. The variations in the greyscale measured on DXA 2D images reflect the absorption property variations that are characteristic and the different microarchitectural 3D conformations of the trabecular tissue, allowing for a direct comparison with the BMD score and application to existing datasets [23, 24]. Although TBS is not a direct measurement of bone microarchitecture, it is related to 3D bone characteristics, such as the trabecular number, trabecular separation, connectivity density and Parfitt parameters [23, 24, 30–32]. A steep variogram slope with a high TBS value is associated with better bone structure, whereas low TBS values indicate a worse bone structure. TBS is typically measured at the lumbar spine and is determined by using the same region of interest as the BMD measurement, so that vertebrae excluded from the BMD calculation, for example vertebrae with fractures or OA, are also excluded from the TBS analysis. Although the TBS result is given for each vertebra, the TBS value reported represents the average of L1–L4 [23, 24, 30–32]. Vertebrae are mainly constituted of trabecular bone. A normal range for TBS values in postmenopausal women has been proposed: a TBS of 1.350 or more is considered normal; a TBS between 1.200 and 1.350 is considered consistent with partially degraded microarchitecture and a TBS of 1.200 or less defines degraded microarchitecture. These cutoff points were established by analogy with the three BMD categories, that is normal bone mass, osteopenia and OP. Interestingly, a normal range for TBS in men has not yet been proposed [23, 24, 30–32]. The lumbar spine L1–L4 TBS was calculated on each spine DXA examination blinded to clinical parameters and outcomes using TBS iNsight (Medimaps Group/GE Healthcare Needham, MA, USA, software version 2.1.0.0) [23, 24, 30–32]. As mentioned, TBS is a grey-level measure of texture using a modified experimental variogram that can be extracted from DXA images and provides an indirect measurement of bone axial microarchitecture and information on bone quality [19, 22]. The manufacturer’s cross-calibration for TBS was on each device before the software was installed. TBS is a texture analysis parameter correlated to the bone microarchitecture Parfitt parameters [23, 24, 30–32]. Bone parameters After informed consent had been obtained, a complete blood chemistry evaluation of bone metabolism was made [serum alkaline phosphatase (ALP), parathormone, 25-hydroxyvitamin D (25(OH)D), calcium and phosphorus] [7–12] for all groups. NVC In order to place the SSc patients into groups according to the correct microangiopathy pattern (early, active or late), as previously reported by Cutolo and colleagues [14–16, 33, 34], NVC was performed using an optical probe equipped with a ×200 contact lens, connected to image analysis software (Videocap, DS Medica, Milan, Italy). There were 18 SSc patients with an early, 18 with an active and 48 with a late NVC pattern. Statistical analysis Statistical analysis were performed using Prism version 5.02 (GraphPad Software, La Jolla, CA, USA). Non-parametric tests were used for the statistical analysis. The Mann–Whitney U-test was performed to compare unpaired groups of variables and the Kruskal–Wallis test to compare continuous variables with nominal variables with more than two levels. The Spearman rank correlation test was used to search for any relationships between variables, along with linear regression tests. P < 0.05 was considered statistically significant. The results are reported as mean along with s.d. Results BMD was significantly lower in both SSc and RA patients than in the control group (P < 0.001) (see Table 2). No significant difference was observed in the mean lumbar spine BMD between patients with SSc and RA (P = 0.238). Table 2 TBS and BMD values in SSc and RA patients and controls Tests SSc (n = 84) RA (n = 98) CNT (n = 60) P-value TBS 1.032 (0.163) 0.904 (0.148) 1.361 (0.126) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.998 (0.161) 0.862 (0.194) 1.240 (0.932) <0.001 Femoral neck BMD, g/cm2 0.784 (0.212) 0.668 (0.141) 0.845 (0.164) <0.001 Ward’s triangle BMD, g/cm2 0.563 (0.173) 0.486 (0.221) 0.657 (0.106) <0.001 Trochanter BMD, g/cm2 0.666 (0.104) 0.589 (0.231) 0.725 (0.143) <0.001 Total hip BMD, g/cm2 0.827 (0.182) 0.764 (0.244) 1.033 (0.161) <0.001 Tests SSc (n = 84) RA (n = 98) CNT (n = 60) P-value TBS 1.032 (0.163) 0.904 (0.148) 1.361 (0.126) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.998 (0.161) 0.862 (0.194) 1.240 (0.932) <0.001 Femoral neck BMD, g/cm2 0.784 (0.212) 0.668 (0.141) 0.845 (0.164) <0.001 Ward’s triangle BMD, g/cm2 0.563 (0.173) 0.486 (0.221) 0.657 (0.106) <0.001 Trochanter BMD, g/cm2 0.666 (0.104) 0.589 (0.231) 0.725 (0.143) <0.001 Total hip BMD, g/cm2 0.827 (0.182) 0.764 (0.244) 1.033 (0.161) <0.001 Values are stated as mean (s.d.). CNT: control; TBS: trabecular bone score. Table 2 TBS and BMD values in SSc and RA patients and controls Tests SSc (n = 84) RA (n = 98) CNT (n = 60) P-value TBS 1.032 (0.163) 0.904 (0.148) 1.361 (0.126) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.998 (0.161) 0.862 (0.194) 1.240 (0.932) <0.001 Femoral neck BMD, g/cm2 0.784 (0.212) 0.668 (0.141) 0.845 (0.164) <0.001 Ward’s triangle BMD, g/cm2 0.563 (0.173) 0.486 (0.221) 0.657 (0.106) <0.001 Trochanter BMD, g/cm2 0.666 (0.104) 0.589 (0.231) 0.725 (0.143) <0.001 Total hip BMD, g/cm2 0.827 (0.182) 0.764 (0.244) 1.033 (0.161) <0.001 Tests SSc (n = 84) RA (n = 98) CNT (n = 60) P-value TBS 1.032 (0.163) 0.904 (0.148) 1.361 (0.126) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.998 (0.161) 0.862 (0.194) 1.240 (0.932) <0.001 Femoral neck BMD, g/cm2 0.784 (0.212) 0.668 (0.141) 0.845 (0.164) <0.001 Ward’s triangle BMD, g/cm2 0.563 (0.173) 0.486 (0.221) 0.657 (0.106) <0.001 Trochanter BMD, g/cm2 0.666 (0.104) 0.589 (0.231) 0.725 (0.143) <0.001 Total hip BMD, g/cm2 0.827 (0.182) 0.764 (0.244) 1.033 (0.161) <0.001 Values are stated as mean (s.d.). CNT: control; TBS: trabecular bone score. Lumbar spine TBS was significantly lower in SSc and RA patients than in the control group [respectively, 1.032 (0.163) and 0.904 (0.148) vs 1.361 (0.126), both P < 0.001]. There was no statistically significant difference in mean lumbar spine TBS between patients with SSc and those with RA (P = 0.238). It is noteworthy that the TBS values in the scleroderma patients correlated positively with the values of the measured BMD at the level of the spine (P = 0.04), femoral neck (P < 0.01) and whole femur (P < 0.01). When the three categories of capillaroscopic patterns were compared for the SSc patients, it was observed that the TBS values were lower in the group of patients with a late pattern, compared with the groups with an active or early pattern (late vs active and early pattern, P < 0.001). Interestingly, there was no statistically significant difference in the BMD values, measured on the column, femoral neck and whole femur (late vs active and early pattern, P = 0.07) (see Table 3). Table 3 TBS, BMD and bone parameters in SSc patients with different NVC patterns Tests Early (n = 18) Active (n = 18) Late (n = 48) P-value TBS 1.182 (0.09) 1.101 (0.80) 1.074 (0.10) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.989 (0.161) 1.064 (0.027) 0.968 (0.145) >0.05 Femoral neck BMD, g/cm2 0.774 (0.087) 0.841 ( 0.108) 0.745 (0.118) >0.05 Ward’s triangle BMD, g/cm2 0.597 (0.102) 0.601 (0.101) 0.562 (0.118) >0.05 Trochanter BMD, g/cm2 0.681 (0.064) 0.731 (0.129) 0.654 (0.095) >0.05 Total hip BMD, g/cm2 0.858 (0.124) 0.882 (0.127) 0.798 (0.133) >0.05 25(OH)D, ng/ml 19.14 (7.5) 15.14 (5.3) 12.14 (7.10) 0.002 ALP osse, U/l 8.95 (2.35) 8.35 (1.40) 6.65 (1.81) <0.0001 Tests Early (n = 18) Active (n = 18) Late (n = 48) P-value TBS 1.182 (0.09) 1.101 (0.80) 1.074 (0.10) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.989 (0.161) 1.064 (0.027) 0.968 (0.145) >0.05 Femoral neck BMD, g/cm2 0.774 (0.087) 0.841 ( 0.108) 0.745 (0.118) >0.05 Ward’s triangle BMD, g/cm2 0.597 (0.102) 0.601 (0.101) 0.562 (0.118) >0.05 Trochanter BMD, g/cm2 0.681 (0.064) 0.731 (0.129) 0.654 (0.095) >0.05 Total hip BMD, g/cm2 0.858 (0.124) 0.882 (0.127) 0.798 (0.133) >0.05 25(OH)D, ng/ml 19.14 (7.5) 15.14 (5.3) 12.14 (7.10) 0.002 ALP osse, U/l 8.95 (2.35) 8.35 (1.40) 6.65 (1.81) <0.0001 NVC: nailfold videocapillaroscopy; TBS: trabecular bone score. Table 3 TBS, BMD and bone parameters in SSc patients with different NVC patterns Tests Early (n = 18) Active (n = 18) Late (n = 48) P-value TBS 1.182 (0.09) 1.101 (0.80) 1.074 (0.10) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.989 (0.161) 1.064 (0.027) 0.968 (0.145) >0.05 Femoral neck BMD, g/cm2 0.774 (0.087) 0.841 ( 0.108) 0.745 (0.118) >0.05 Ward’s triangle BMD, g/cm2 0.597 (0.102) 0.601 (0.101) 0.562 (0.118) >0.05 Trochanter BMD, g/cm2 0.681 (0.064) 0.731 (0.129) 0.654 (0.095) >0.05 Total hip BMD, g/cm2 0.858 (0.124) 0.882 (0.127) 0.798 (0.133) >0.05 25(OH)D, ng/ml 19.14 (7.5) 15.14 (5.3) 12.14 (7.10) 0.002 ALP osse, U/l 8.95 (2.35) 8.35 (1.40) 6.65 (1.81) <0.0001 Tests Early (n = 18) Active (n = 18) Late (n = 48) P-value TBS 1.182 (0.09) 1.101 (0.80) 1.074 (0.10) <0.001 Lumbar spine (L1–L4) BMD, g/cm2 0.989 (0.161) 1.064 (0.027) 0.968 (0.145) >0.05 Femoral neck BMD, g/cm2 0.774 (0.087) 0.841 ( 0.108) 0.745 (0.118) >0.05 Ward’s triangle BMD, g/cm2 0.597 (0.102) 0.601 (0.101) 0.562 (0.118) >0.05 Trochanter BMD, g/cm2 0.681 (0.064) 0.731 (0.129) 0.654 (0.095) >0.05 Total hip BMD, g/cm2 0.858 (0.124) 0.882 (0.127) 0.798 (0.133) >0.05 25(OH)D, ng/ml 19.14 (7.5) 15.14 (5.3) 12.14 (7.10) 0.002 ALP osse, U/l 8.95 (2.35) 8.35 (1.40) 6.65 (1.81) <0.0001 NVC: nailfold videocapillaroscopy; TBS: trabecular bone score. Serum levels of 25(OH)D were statistically significantly lower in patients with SSc than in the control group [14.2 (7.4) vs 32.8 (2.3) ng/ml, P < 0.001]. Bone ALP level was lower in the SSc group than in the control group [7.46 (2.06) vs 18.45 (4.51) U/l; P < 0.001]. There was a positive correlation between the TBS values and the bone ALP values (P < 0.0001) and a negative correlation with the duration in terms of years of RP in the SSc patients (P < 0.01). There was no statistically significant correlation between the TBS values and serum PTH, 25(OH)D, calcium, phosphorus or SSc disease duration in years. A statistically significant difference between the three different capillaroscopic patterns was observed in the 25(OH)D values, bone ALP and duration of RP. There was no statistically significant difference in the PTH, calcium or phosphorus serum concentrations (see Table 3). There was a positive correlation between the TBS values and bone ALP values (respectively, late P = 0.002; active P = 0.003; early P = 0.004) for all three groups, while only in the late pattern group was a negative correlation observed between the TBS and SSc duration, in years, of RP (P < 0.0001). There was no correlation between the TBS values in the three groups and the BMD measured at the spine, femoral neck and level of the whole femur or between the vitamin D values. Furthers subdividing the scleroderma patient groups into three subgroups on the basis of the presence/absence of previous vertebral fractures, this study demonstrated that 20/29 (68%) patients with previous vertebral fractures had a late pattern, 6 (21%) an active pattern and 3 (11%) an early pattern. Moreover, 44% of all the patient groups had OP and 56% osteopenia. A total of 29 SSc patients (34%) had had a previous vertebral fracture and it was observed that all the patients with previous vertebral fracture had a low bone mass and that 13 (44%) had OP and 16 (56%) osteopenia. The TBS values were significantly lower in the subgroup of SSc patients with previous vertebral fractures than in those without fractures [0.990 (0.07) vs 1.178 (0.07); P < 0.0001]. The vitamin D values were statistically lower in the subgroup of SSc patients with previous fractures than the subgroup of patients without vertebral fractures [8.51 (12.6) vs 17.16 (7.25) ng/ml; P < 0.0001]. The BMD measured at the spine and the whole femur were statistically significantly lower in the facture subgroup than the subgroup without fractures [respectively, column BMD 0.982 (0.16) vs 1.016 (0.14) g/cm2, P = 0.006; BMD femur entire 0.755 (0.13) vs 0.851 (0.12) g/cm2; P = 0.0009]. Discussion Decreased BMD and TBS values in SSc and RA patients compared with healthy matched controls were observed in this study. It was also demonstrated that SSc patients with a late nailfold capillaroscopy pattern showed lower TBS values than patients with an early or active pattern. Interestingly, no difference in BMD values was observed for the three groups. In addition, our study confirmed that patients with chronic rheumatic inflammatory diseases have a higher OP and osteopenia risk associated with the BMD obtained by DXA, as established in 1994 by the WHO [21–23]. However, several studies have reported various limitations in BMD sensitivity, such as BMD not being able to detect bone quality [21–23]. Recently it was demonstrated that bone microarchitecture plays a determinant rule in bone strength. The TBS is novel and based on an imaging technique that uses standard DXA images. Evidence to date indicates that it is an index of bone texture that provides skeletal information additional to that obtained by the standard BMD [24, 25]. Our study confirmed that TBS, evaluated at the lumbar spine, with lumbar and femoral BMD, is able to discriminate patients with altered bone microstructure. The authors propose it be used as a clinical tool in the general diagnosis of OP in chronic inflammatory rheumatic diseases, such as SSc and RA, in line with other reports [4, 5, 35]. Although there are other imaging techniques able to provide direct information on trabecular bone microarchitecture, for example magnetic resonance and CT, these are not simple to use in routine practice since they are expensive and not always available and can examine only peripheral area bone. Bone damage may have multi-factorial underlying causes: disability, age, longstanding diseases, a low BMI, chronic systemic inflammation, low vitamin D levels and some treatment regimes [6–12]. In SSc patients, the presence of lower serum 25(OH)D levels than those observed in the control groups and the fact that it is lower in late pattern patients than in active or early ones may be related to a reduced vitamin D intestinal absorption [7, 8, 10–12]. Furthermore, the 25(OH)D value correlated with TBS but not with BMD, as already observed by Koumakis et al. [35]. These data confirmed that the two techniques evaluated different aspects of bone and that they may be used together to enhance evaluation of bone damage. Moreover, there were statistically significant lower ALP levels in SSc patients than in the control group. It is noteworthy that this value was lower in patients with a late pattern than in those with an active or early one, with a probable correlation to a reduced bone turnover and bone neoformation [36]. Finally, it was demonstrated that there is a negative correlation between the reduced bone microarchitecture, evaluated by TBS, and the progression of microvascular damage, studied by NVC; this observation suggests that the microvascular damage is correlated with systemic SSc clinical complications, including bone impairment [37–40]. A limitation to the present study might be that the number of subjects was not identical in all groups, due to a single centre recruitment and the use of exclusion criteria. However, the total sample size was considered sufficient. Moreover, almost 70% of the RA cases were treated with low dose glucocorticoids (<5 mg prednisone/day) but we have no data as to the patients’ cumulative prednisone dosage. In conclusion, this study confirmed that TBS (and BMD) may well represent a complementary tool for the evaluation of bone quality and the risk of fracture in various diseases, as well as in SSc patients [18, 35, 41–43]. The bone quality seems lower in SSc patients with more altered microcirculation (NVC patterns). Therefore, TBS may represent a further marker to estimate the general clinical status in chronic rheumatic diseases at least in SSc. Acknowledgements The authors would like to thank Barbara Wade, contract Professor at the University of Torino, for her linguistic advice. Barbara Ruaro is supported by a Grant from the Italian Society of Rheumatology. Vanessa Smith is a Senior Clinical Investigator of the Research Foundation—Flanders (Belgium) (FWO) [1802915N]. Funding: No specific funding was received from any bodies in the public, commercial or not-for-profit sectors to carry out the work described in this manuscript. Disclosure statement: The authors have declared no conflicts of interest. References 1 Lane NE. Epidemiology, etiology, and diagnosis of osteoporosis . Am J Obstet Gynecol 2006 ; 194 (Suppl 2) : 3 – 11 . Google Scholar CrossRef Search ADS 2 Hiligsmann M , Dellaert BG , Dirksen CD et al. Patients' preferences for anti-osteoporosis drug treatment: a cross-European discrete choice experiment . Rheumatology 2017 ; 56 : 1167 – 76 . Google Scholar CrossRef Search ADS PubMed 3 Lems WF , Dreinhöfer KE , Bischoff-Ferrari H et al. EULAR/EFORT recommendations for management of patients older than 50 years with a fragility fracture and prevention of subsequent fractures . Ann Rheum Dis 2017 ; 76 : 802 – 10 . Google Scholar CrossRef Search ADS PubMed 4 Maruotti N , Corrado A , Cantatore FP. Osteoporosis and rheumatic diseases . Reumatismo 2014 ; 66 : 125 – 35 . Google Scholar CrossRef Search ADS PubMed 5 Sinigaglia L , Varenna M , Girasole G , Bianchi G. Epidemiology of osteoporosis in rheumatic diseases . Rheum Dis Clin North Am 2006 ; 32 : 631 – 58 . Google Scholar CrossRef Search ADS PubMed 6 Avouac J , Koumakis E , Toth E et al. Increased risk of osteoporosis and fracture in women with systemic sclerosis: a comparative study with rheumatoid arthritis . Arthritis Care Res 2012 ; 64 : 1871 – 8 . Google Scholar CrossRef Search ADS 7 Cutolo M , Otsa K , Paolino S et al. Vitamin D involvement in rheumatoid arthritis and systemic lupus erythaematosus . Ann Rheum Dis 2009 ; 68 : 446 – 7 . Google Scholar CrossRef Search ADS PubMed 8 Cutolo M , Paolino S , Sulli A et al. Vitamin D, steroid hormones, and autoimmunity . Ann N Y Acad Sci 2014 ; 1317 : 39 – 46 . Google Scholar CrossRef Search ADS PubMed 9 Seriolo B , Paolino S , Casabella A et al. Osteoporosis in the elderly . Aging Clin Exp Res 2013 ; 25 (Suppl 1) : 27 – 9 . Google Scholar CrossRef Search ADS 10 Cutolo M , Pizzorni C , Sulli A. Vitamin D endocrine system involvement in autoimmune rheumatic diseases . Autoimmun Rev 2011 ; 11 : 84 – 7 . Google Scholar CrossRef Search ADS PubMed 11 Trombetta AC , Smith V , Gotelli E et al. Vitamin D deficiency and clinical correlations in systemic sclerosis patients: a retrospective analysis for possible future developments . PLoS One 2017 ; 12 : e0179062 . Google Scholar CrossRef Search ADS PubMed 12 Seriolo B , Molfetta L , Cutolo M. Seasonal variations in serum levels of 25-hydroxyvitamin D in patients with systemic sclerosis . Clin Rheumatol 2011 ; 30 : 445 – 6 . Google Scholar CrossRef Search ADS PubMed 13 Gabrielli A , Avvedimento EV , Krieg T. Scleroderma . N Engl J Med 2009 ; 360 : 1989 – 2003 . Google Scholar CrossRef Search ADS PubMed 14 Cutolo M , Smith V. State of the art on nailfold capillaroscopy: a reliable diagnostic tool and putative biomarker in rheumatology? Rheumatology 2013 ; 52 : 1933 – 40 . Google Scholar CrossRef Search ADS PubMed 15 Cutolo M , Pizzorni C , Tuccio M et al. Nailfold videocapillaroscopic patterns and serum autoantibodies in systemic sclerosis . Rheumatology 2004 ; 43 : 719 – 26 . Google Scholar CrossRef Search ADS PubMed 16 Cutolo M , Ruaro B , Smith V. Macrocirculation versus microcirculation and digital ulcers in systemic sclerosis patients . Rheumatology 2017 ; 56 : 1834 – 6 . Google Scholar CrossRef Search ADS PubMed 17 Atteritano M , Sorbara S , Bagnato G et al. Bone mineral density, bone turnover markers and fractures in patients with systemic sclerosis: a case control study . PLoS One 2013 ; 8 : e66991 . Google Scholar CrossRef Search ADS PubMed 18 Omair MA , Pagnoux C , McDonald-Blumer H , Johnson SR. Low bone density in systemic sclerosis. A systematic review . J Rheumatol 2013 ; 40 : 1881 – 90 . Google Scholar CrossRef Search ADS PubMed 19 van Staa TP , Geusens P , Bijlsma JW , Leufkens HG , Cooper C. Clinical assessment of the long-term risk of fracture in patients with rheumatoid arthritis . Arthritis Rheum 2006 ; 54 : 3104 – 12 . Google Scholar CrossRef Search ADS PubMed 20 Kaz Kaz H , Johnson D , Kerry S et al. Fall-related risk factors and osteoporosis in women with rheumatoid arthritis . Rheumatology 2004 ; 43 : 1267 – 71 . Google Scholar CrossRef Search ADS PubMed 21 Lewiecki EM. Review of guidelines for bone mineral density testing and treatment of osteoporosis . Curr Osteoporos Rep 2005 ; 3 : 75 – 83 . Google Scholar CrossRef Search ADS PubMed 22 Chun KJ. Bone densitometry . Semin Nucl Med 2011 ; 41 : 220 – 8 . Google Scholar CrossRef Search ADS PubMed 23 El Maghraoui A , Roux C. DXA scanning in clinical practice . QJM 2008 ; 101 : 605 – 17 . Google Scholar CrossRef Search ADS PubMed 24 Silva BC , Leslie WD , Resch H et al. Trabecular bone score: a noninvasive analytical method based upon the DXA image . J Bone Miner Res 2014 ; 29 : 518 – 30 . Google Scholar CrossRef Search ADS PubMed 25 Kang KY , Goo HY , Park SH , Hong YS. Trabecular bone score as an assessment tool to identify the risk of osteoporosis in axial spondyloarthritis: a case-control study . Rheumatology 2018 ; 57 : 462 – 9 . Google Scholar CrossRef Search ADS PubMed 26 LeRoy EC , Meedsger TA Jr. Criteria for the classification of early systemic sclerosis . J Rheumatol 2001 ; 28 : 1573 – 6 . Google Scholar PubMed 27 van den Hoogen F , Khanna D , Fransen J et al. 2013 classification criteria for systemic sclerosis: an American College of Rheumatology/European League Against Rheumatism collaborative initiative . Ann Rheum Dis 2013 ; 72 : 1747 – 55 . Google Scholar CrossRef Search ADS PubMed 28 Clements P , Lachenbruch P , Siebold J et al. Inter and intraobserver variability of total skin thickness score (modified Rodnan TSS) in systemic sclerosis . J Rheumatol 1995 ; 22 : 1281 – 5 . Google Scholar PubMed 29 Aletaha D , Neogi T , Silman AJ et al. 2010 rheumatoid arthritis classification criteria: an American College of Rheumatology/European League against Rheumatism Collaborative Initiative . Ann Rheum Dis 2010 ; 69 : 1580 – 8 . Google Scholar CrossRef Search ADS PubMed 30 Parfitt AM , Mathews CH , Villanueva AR et al. Relationships between surface, volume, and thickness of iliac trabecular bone in aging and in osteoporosis. Implications for the microanatomic and cellular mechanisms of bone loss . J Clin Invest 1983 ; 72 : 1396 – 409 . Google Scholar CrossRef Search ADS PubMed 31 Hans D , Goertzen AL , Krieg MA , Leslie WD. Bone microarchitecture assessed by TBS predicts osteoporotic fractures indipendent of bone density: the Manitoba study . J Bone Miner Res 2011 ; 26 : 2762 – 9 . Google Scholar CrossRef Search ADS PubMed 32 Harvey NC , Glüer CC , Binkley N et al. Trabecular bone score (TBS) as a new complementary approach for osteoporosis evaluation in clinical practice . Bone 2015 ; 78 : 216 – 24 . Google Scholar CrossRef Search ADS PubMed 33 Cutolo M , Sulli A , Secchi ME , Paolino S , Pizzorni C. Nailfold capillaroscopy is useful for the diagnosis and follow-up of autoimmune rheumatic diseases. A future tool for the analysis of microvascular heart involvement? Rheumatology 2006 ; 45 (Suppl 4) : 43 – 6 . Google Scholar CrossRef Search ADS 34 Ruaro B , Sulli A , Pizzorni C et al. Correlations between skin blood perfusion values and nailfold capillaroscopy scores in systemic sclerosis patients . Microvasc Res 2016 ; 105 : 119 – 24 . Google Scholar CrossRef Search ADS PubMed 35 Koumakis E , Avouac J , Winzenrieth R et al. Trabecular bone score in female patients with systemic sclerosis: comparison with rheumatoid arthritis and influence of glucocorticoid exposure . J Rheumatol 2015 ; 42 : 228 – 35 . Google Scholar CrossRef Search ADS PubMed 36 Smith V , Riccieri V , Pizzorni C et al. Nailfold capillaroscopy for prediction of novel future severe organ involvement in systemic sclerosis . J Rheumatol 2013 ; 40 : 2023 – 8 . Google Scholar CrossRef Search ADS PubMed 37 Ingegnoli F , Ardoino I , Boracchi P , Cutolo M et al. Nailfold capillaroscopy in systemic sclerosis: data from the EULAR scleroderma trials and research (EUSTAR) database . Microvasc Res 2013 ; 89 : 122 – 8 . Google Scholar CrossRef Search ADS PubMed 38 Riccieri V , Vasile M , Iannace N et al. Systemic sclerosis patients with and without pulmonary arterial hypertension: a nailfold capillaroscopy study . Rheumatology 2013 ; 52 : 1525 – 8 . Google Scholar CrossRef Search ADS PubMed 39 Cutolo M , Herrick AL , Distler O et al. Nailfold videocapillaroscopic features and other clinical risk factors for digital ulcers in systemic sclerosis: a multicenter, prospective cohort study . Arthritis Rheumatol 2016 ; 68 : 2527 – 39 . Google Scholar CrossRef Search ADS PubMed 40 Corrado A , Correale M , Mansueto N et al. Nailfold capillaroscopic changes in patients with idiopathic pulmonary arterial hypertension and systemic sclerosis-related pulmonary arterial hypertension . Microvasc Res 2017 ; 114 : 46 – 51 . Google Scholar CrossRef Search ADS PubMed 41 Burmester GR , Bijlsma JWJ , Cutolo M , McInnes IB. Managing rheumatic and musculoskeletal diseases—past, present and future . Nat Rev Rheumatol 2017 ; 13 : 443 – 8 . Google Scholar CrossRef Search ADS PubMed 42 Olsson A , Oturai AB , Søndergaard HB , Sellebjerg F , Oturai PS. Bone microarchitecture and bone mineral density in multiple sclerosis . Acta Neurol Scand 2018 ; 137 : 363 – 9 . Google Scholar CrossRef Search ADS PubMed 43 Heise V , Galli-Lysak I , Villiger PM , Aeberli D. Increased bone mineral density at the hypoxia prone site of the juxta-articular metacarpal bone in patients with limited systemic sclerosis: a cross-sectional study . J Musculoskelet Neuronal Interact 2014 ; 14 : 189 – 94 . Google Scholar PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. 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RheumatologyOxford University Press

Published: Sep 1, 2018

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