Abstract
Background
Evidence states that persons with hemophilia are frequently affected by low bone mineral density (BMD). Data assessing the relationship between severity of hemophilia and occurrence of osteoporosis are lacking.
Objectives
This prospective cohort study aimed to assess the impact of hemophilia severity on BMD and to investigate trabecular bone score (TBS) and fracture risk (FRAX).
Methods
This prospective cohort study evaluated the BMD, TBS, and FRAX in 255 persons with hemophilia using dual x-ray absorptiometry. The International Society for Clinical Densitometry guidelines were used for classification: osteoporosis (T-score <−2.5), osteopenia (T-score <−1.0), normal (T-score >−1.0). Patients younger than 50 years of age with a Z-score of <−2.0 were considered below the expected range for age.
Results
Of 255 persons with hemophilia (mild: n = 52, moderate: n = 53, severe: n = 150) aged 43 ± 15 years (mean ± SD), 63.1% showed reduced BMD. Even 11.9% of persons with hemophilia aged <50 years were classified as below the expected range for age. Neck BMD decreased linearly with severity (mild: 0.907 ± 0.229, moderate: 0.867 ± 0.131, severe: 0.799 ± 0.143; P = .01). TBS was classified as “normal” in n = 178 (81.3%) with a mean value of 1.403 ± 0.136, and there were no differences between severity levels (P = .54). The FRAX was 4.4% ± 3.0%. After adjustment of TBS, it was 2.8% ± 3.7%.
Conclusion
The present study shows that BMD is decreased in 63.1% of persons with hemophilia also depending on the severity of hemophilia. However, the largely normal TBS implies that the microarchitecture of the bone does not seem to be affected. It is recommended to include osteoporosis screening, including TBS analysis, in the comprehensive diagnostic work-up of persons with hemophilia, especially as they age.
Keywords: bone mineral density, fracture risk, prevalence, severity phenotype, trabecular bone score
Essentials
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Data on the link between hemophilia severity and reduced BMD are lacking.
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Examination including dual x-ray absorptiometry was performed at the University Hospital Bonn.
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This study shows that 63.1% of persons with hemophilia have decreased BMD, linked to hemophilia severity.
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Osteoporosis screening, including the evaluation of trabecular bone, is recommended.
1. Introduction
Persons with hemophilia have either a lack of factor (F)VIII (hemophilia A) or FIX (hemophilia B), which can both cause spontaneous bleeding into muscles and joints. Repetitive hemarthroses lead to arthropathy, which is associated with restricted joint function [1]. However, already in 1994, it has been emphasized that next to hemophilic arthropathy, the comorbidity osteoporosis occurs frequently in hemophilic populations [[2], [3], [4]]. Prior literature has shown that coagulation factors FVIII and FIX can also affect the patient’s bone mineral density (BMD) [5,6]. Findings of animal research highlighted that mice lacking FVIII show a higher prevalence of decreased BMD [5]. It has further been emphasized that the presence of severe hemarthroses and arthropathy trigger local molecular processes, which have been shown to impact bone metabolism [7,8]. Additionally, persons with hemophilia are often affected by viral comorbidities (HIV, hepatitis), which are suspected to be potential risk factors for the development of osteoporosis [3,9,10]. Although the reduced BMD is often seen in persons with hemophilia, no direct causal relationship, especially considering the severity of hemophilia has been drawn so far [11].
Generally, osteoporosis is a result of an imbalance between bone formation and bone resorption, which causes a reduced BMD. Hereby, aging is a major risk factor for developing osteoporosis. It is a common phenomenon in postmenopausal women due to a deficiency of estrogen [12]. In Europe, about 19.8% of women are diagnosed with osteoporosis, while only 9.7% of men are affected [13]. In the male population, the deficiency of testosterone represents a further key factor in developing osteoporosis [9,14]. The disease is characterized by an increased incidence of fractures as well as deformity of vertebral bodies. However, there are several more factors, such as physical activity, vitamin D status, smoking, or organic comorbidities that need to be considered for investigating osteoporosis [9,15].
To diagnose osteoporosis, the BMD is determined, using dual x-ray absorptiometry (DXA) of the lumbar spine and hip, including risk of fractures based on the Fracture Risk Assessment Tool (FRAX). Moreover, the microarchitecture of the skeletal bones can be measured using trabecular bone score (TBS), predicting fracture risk independently of the BMD and providing information on the overall bone quality. It has been found that patients with lower TBS have an increased risk for fractures [16]. However, only little research has been done investigating TBS and hemophilia [17].
In general, different studies and meta-analyses describe an association, especially between severe hemophilia and low bone mineral density [2,3,11,18,19]. Still, data assessing the relationship between severity of hemophilia and occurrence of osteoporosis is lacking [20,21]. Thus, this study aimed to depict the prevalence of osteoporosis as well as FRAX and TBS in a representative sample size of 250 patients with either mild (n = 50), moderate (n = 50), or severe (n = 150) hemophilia A or B.
2. Methods
2.1. Study design and participants
This study was conducted as a single-center prospective cohort study at the University Hospital Bonn. Adult male patients suffering from mild, moderate, or severe hemophilia A or B were included. Patients who experienced joint bleeding in the past 2 weeks were excluded from this investigation as the Haemophilia Joint Health Score (HJHS) manual demands [22]. This study was conducted in accordance with the principles of good clinical and ethical practice and after approval by the local ethics committee (339/19). Along with the Declaration of Helsinki, all participants gave written informed consent after being informed about the study’s protocol. The study was registered at clinicaltrials.gov (ID: NCT04524481).
2.2. Data acquisition
In accordance with the German guidelines for osteoporosis, all patients underwent densitometry using Horizon (Hologic) of the spine (vertebrae bodies 1-4) and both femoral necks [15]. Both exact values of BMD (g/cm2) and T-scores (standard deviation of average BMD of healthy young (aged 30 years) population of the same ethnicity) were gathered and automatically calculated by the Horizon software. According to the World Health Organization, the lowest T-score of either femoral neck or spine (sum of vertebrae bodies 1-4), assessed with DXA, was used for classification into the following categories: normal (T-score, ≥−1.0), osteopenia (T-score range, −1.0 to −2.4) or osteoporosis (T-score ≤−2.5) [15,23]. Patients younger than 50 years, having a Z-score <−2.0 are considered as “below expected range for age” [24]. The Z-score compares the BMD results with the average BMD of people of the same age. In addition, based on BMD results and individual data on medical and family history, the FRAX is calculated by the Horizon software. This algorithm depicts a 10-year probability of experiencing fractures in patients aged ≥30 years. However, the score has been validated in patients aged >40 years [25].
TBS was calculated using TBS iNsight (V. 3.1.2. Medi-Maps). This score expresses the homogeneity bone microarchitecture of the lumbar spine and can, in combination with BMD results, provide an additional and more sensitive fracture risk estimate [26,27]. It is recommended to use the score for subjects with a body mass index of <37 kg/m2 [28,29]. Next to a densitometry, relevant blood parameters (vitamin D, calcium, testosterone) were examined to both capture risk factors for osteoporosis and to differentiate from secondary osteoporosis or further morbidities (ie, osteomalacia or malignancies) [15,30]. The serum blood samples were determined in the central laboratory of the University Hospital Bonn.
Supplementary anamnesis including medical history and any pharmacological treatment regime was collected. To objectively evaluate patients’ daily physical activity level, the patients were given an electronic activity tracker (Fitbit Alta Hr, Fitbit Inc) that was worn at the wrist for 7 consecutive days after clinical assessment. The total number of steps taken within a week was used for further analysis.
Orthopedic joint status was assessed using the HJHS (version 2.1; maximum score 124 points, 20 points × 6 joints, plus 4 points assigned to global gait), which assesses the elbows, knees, and ankles in regard to swelling, muscle atrophy, crepitation, stability, and range of motion. High values indicate a worse clinical joint status. The recruitment of persons with hemophilia and their examination was conducted by 3 research fellows (J.H., M.B., P.R.) between September 2019 and October 2022.
2.3. Statistics
Statistical evaluation was performed to analyze the prevalence of osteopenia and osteoporosis within the different hemophilia severities. The IBM Statistical Package for the Social Sciences 29 (IBM) for Mac was used for calculations.
Given nonparametric data, a Kruskal–Wallis test compared the means between the hemophilia severities. In case of significant differences, Bonferroni correction was used to account for multiple comparisons for post-hoc testing. Multiple linear regression analysis was calculated to examine potential predictors (severity phenotype, age, presence of viral comorbidities, smoking, physical activity, HJHS) of BMD (left femoral neck). A general significance level of P = .05 (95% CI) was established.
3. Results
In total, 260 patients were recruited. Data from 255 patients, aged 43.4 ± 15.4 (mean ± SD) years (median = 42, range: 18-79) with either mild (n = 52), moderate (n = 53) or severe (n = 155) hemophilia A or B was analyzed (Table 1). Five patients with severe hemophilia dropped out due to unusable data of the DXA scan. Patients were either treated on-demand (35.7%) or with prophylactic treatment (64.3%). Details on the treatment regimen, of the patients treated on prophylaxis are shown in Table 2.
Table 1.
Anthropometric and descriptive data of persons with hemophilia included in this study.
| Variables | Severe (n = 150) | Moderate (n = 53) | Mild (n = 52) | Total (n = 255) | P value |
|---|---|---|---|---|---|
| Age (y) | .16 | ||||
| Mean ± SD | 41.7 ± 14.6 | 46.3 ± 15.2 | 45.3 ± 17.5 | 43.4 ± 15.4 | |
| Median (IQ1, IQ3) | 40 (29.0, 54.0) | 49.0 (31.5, 58.5) | 47.5 (29.2, 58.0) | 42.0 (30.0, 56.0) | |
| Weight (kg) | .15 | ||||
| Mean ± SD | 84.9 ± 18.5 | 89.3 ± 17.6 | 86.4 ± 13.9 | 86.1 ± 17.5 | |
| Median (IQ1, IQ3) | 81.0 (73.7, 91.0) | 86.0 (78.0, 95.0) | 83.5 (78.0, 93.7) | 83.0 (75.0, 93.0) | |
| Height (m) | .34 | ||||
| Mean ± SD | 1.80 ± 0.1 | 1.82 ± 0.1 | 1.79 ± 0.1 | 1.80 ± 0.1 | |
| Median (IQ1, IQ3) | 1.80 (1.75, 1.84) | 1.80 (1.76, 1.89) | 1.80 (1.76, 1.84) | 1.80 (1.76, 1.85) | |
| BMI (kg/m2) | .34 | ||||
| Mean ± SD | 26.2 ± 5.2 | 26.7 ± 5.0 | 26.8 ± 4.4 | 26.4 ± 5.0 | |
| Median (IQ1, IQ3) | 25.2 (23.4, 27.8) | 25.8 (23.4, 28.2) | 26.0 (23.9, 28.9) | 25.5 (23.5, 28.0) | |
| Caucasian ethnicity, n (%) | 150 (100) | 53 (100) | 52 (100) | 255 (100) | n/a |
| Hemophilia A, n (%) | 134 (89.3) | 42 (79.2) | 45 (86.5) | 221 (86.7) | n/a |
| Hemophilia B, n (%) | 16 (10.7) | 11 (20.8) | 7 (13.7) | 34 (13.3) | n/a |
| HIV, n (%) | 32 (21.3) | 3 (5.7) | 3 (5.8) | 38 (14.9) | n/a |
| Hepatitis C, n (%) | 17 (11.3) | 2 (3.8) | 1 (2.0) | 20 (4.6) | n/a |
| HJHS (score points) | <.001a | ||||
| Mean ± SD | 22.7 ± 18.7a | 10.0 ± 8.2a | 9.9 ± 9.4a | 17.5 ± 16.6 | |
| Median (IQ1, IQ3) | 18.5 (6.0, 35.2) | 7.0 (5.0, 13.5) | 7.0 (4.2, 13.0) | 11.0 (5.0, 28.0) | |
| Steps per dayb | .16 | ||||
| Mean ± SD | 7509 ± 3851 | 8653 ± 4246 | 8446 ± 3764 | 7934 ± 3935 | |
| Median (IQ1, IQ3) | 7095 (4757, 9801) | 7049 (5530, 11472) | 8466 (5219, 10785) | 7392 (4981, 10579) | |
| Vitamin D level (ng/mL) | .55 | ||||
| Mean ± SD | 24.2 ± 13.8 | 22.0 ± 9.7 | 22.0 ± 11.3 | 23.3 ± 12.6 | |
| Median (IQ1, IQ3) | 23.6 (13.4, 31.6) | 22.1 (13.1, 29.5) | 19.9 (14.6, 28.2) | 23.0 (13.7, 30.4) | |
| Calcium level (mmol/L) | .08 | ||||
| Mean ± SD | 2.32 ± 0.11 | 2.29 ± 0.08 | 2.30 ± 0.08 | 2.31 ± 0.10 | |
| Median (IQ1, IQ3) | 2.33 (2.26, 2.37) | 2.28 (2.24, 2.43) | 2.29 (2.23, 2.37) | 2.31 (2.25, 2.37) | |
| Smoking daily, n (%) | 45 (31.0) | 11 (20.8) | 12 (23.1) | 68 (27.2) | n/a |
| Alcohol intake,cn (%) | 28 (18.7) | 11 (20.8) | 16 (30.8) | 55 (22.0) | n/a |
BMI, body mass index; HJHS, Haemophilia Joint Health Score (v2.1); n/a, not applicable.
Indicates significant difference at HJHS: severe-mild: P < .001, severe-moderate: P < .001.
Steps per week, steps taken in a week measured by an electronic activity tracker (FitBit Altra HR) for 7 days.
Alcohol intake indicates regular alcohol intake.
Table 2.
Details of replacement treatment regimen of included subjects.
| Variables | Severe (n = 150) | Moderate (n = 53) | Mild (n = 52) | Total (n = 255) | |
|---|---|---|---|---|---|
| Treatment regimen | Prophylaxis,n (%) | 146 (97.3) | 17 (32.1) | 1 (1.9) | 164 (64.3) |
| On-demand,n (%) | 4 (2.7) | 36 (67.9) | 51 (98.1) | 91 (35.7) | |
| Development of inhibitor | Current presence of inhibitor,n (%) | 11 (7.3) | 3 (5.7) | 0 (0.0) | 14 (5.5) |
| Inhibitors successfully treated,n (%) | 25 (16.7) | 1 (1.9) | 2 (3.8) | 28 (11.0) | |
| Never history of inhibitors,n (%) | 114 (76.0) | 49 (92.4) | 50 (96.2) | 213 (83.5) | |
| Patients on prophylactic treatment | Factor consumption per week (IU), mean ± SD | 7234 ± 4670 | 5906 ± 3688 | 12000 | 7130 ± 4589 |
| median (IQ1, IQ3) | 6000 (4000, 9000) | 6000 (2125, 8750) | 6000 (4000, 9000) | ||
| Extended half-life,n (%) | 108 (77.7) | 17 (100) | 1 (100) | 126 (80.3) | |
| Standard half-life,n (%) | 24 (17.3) | — | — | 24 (15.3) | |
| Nonfactor replacement,n (%) | 7 (5.0) | — | — | 7 (4.5) | |
The data of the BMD values of the entire study group and for the different hemophilia severity grades separately shown in Table 3. Comparing BMD values within the 3 severities, the Kruskal–Wallis test revealed that in both, left and right femoral neck, a significant difference was found between patients with mild and severe hemophilia. Bonferroni post-hoc analysis showed that patients with severe hemophilia have lower BMD values in the femoral necks than patients with mild hemophilia (left: P = .008, right: P = .004). There was no significance between moderate and mild or moderate and severe hemophilia. Although a tendency of descending BMD scores within the severities is seen, BMD values at the spine do not differ significantly between the severities (P = .22). Considering the T/Z-scores, a significant difference between the severity phenotypes can be seen revealing that patients with severe hemophilia have a lower score than patients with mild hemophilia (T-score: P = .04, Z-score: P = .008).
Table 3.
Overview of bone mineral density within the hemophilia severities.
| Variables | Severe (n = 150) | Moderate (n = 53) | Mild (n = 52) | Total (n = 255) | P value |
|---|---|---|---|---|---|
| BMD femoral neck left (g/cm2) | .01a | ||||
| Mean ± SD | 0.799 ± 0.143a | 0.826 ± 0.131 | 0.907 ± 0.229a | 0.828 ± 0.167 | |
| median (IQ1, IQ3) | 0.779 (0.696, 0.896) | 0.807 (0.727, 0.933) | 0.871 (0.748, 1.002) | 0.807 (0.711, 0.929) | |
| BMD femoral neck right (g/cm2) | .005a | ||||
| Mean ± SD | 0.807 ± 0.148a | 0.830 ± 0.147 | 0.906 ± 0.180a | 0.831 ± 0.159 | |
| Median (IQ1, IQ3) | 0.802 (0.703, 0.896) | 0.826 (0.735, 0.916) | 0.863 (0.756, 1.038) | 0.821 (0.720, 0.923) | |
| BMD lumbar spine (g/cm2) | .22 | ||||
| Mean ± SD | 0.986 ± 0.126 | 1.013 ± 0.146 | 1.021 ± 0.150 | 0.999 ± 0.136 | |
| Median (IQ1, IQ3) | 0.990 (0.904, 1.07) | 1.009 (0.913, 1.100) | 1.040 (0.931, 1.086) | 1.005 (0.905, 1.077) | |
| Lowest T-score | .04a | ||||
| Mean ± SD | −1.8 ± 0.9a | −1.4 ± 1.0 | −1.0 ± 1.2a | −1.5 ± 1.0 | |
| Median (IQ1, IQ3) | −1.8 (−2.4,−1.1) | −1.5 (−2.1, −0.4) | −1.2 (−2.0, −0.4) | −1.6 (−2.2, −0.9) | |
| Lowest Z-score | .006a | ||||
| Mean ± SD | −0.9 ± 0.8a | −0.8 ± 1.0 | −0.5 ± 1.1a | 0.8 ± 0.9 | |
| Median (IQ1, IQ3) | −0.9 (−1.6, −0.4) | −0.7 (−1.3, −0.5) | −0.5 (−1.2, −0.1) | −0.9 (−1.5, −0.2) |
Mean and standard deviation displayed; Kruskal–Wallis test was conducted to assess mean differences between the severities. Sample sizes differ based on age groups (T-score [persons with hemophilia aged >50 years]: severe, n = 54; moderate, n = 24; mild, n = 26; total, n = 104; Z-score [persons with hemophilia aged <50 years]: severe, n = 96; moderate, n = 29; mild, n = 26; total, n = 151).
BMD, bone mineral density.
Indicates significant difference at BMD neck left: severe-mild, P = .008; BMD neck right: severe-mild, P = .004; lowest T-score: severe-mild, P = .04; lowest Z-score: severe-mild, P = .008.
Since the T-score is used in patients aged >50 years only, the sample size was divided into 2 groups. Persons with hemophilia aged >50 years (N =104), who are therefore categorized as “normal,” “osteopenia,” or “osteoporosis,” out of which 19.2% (n = 20/104) were diagnosed with osteoporosis and 53.8% (n = 56/104) with osteopenia. And n = 151 persons with hemophilia, younger than 50 years who are classified as either “normal” or “below expected range for age” (Figure 1). Here, 11.9% (n = 18/151) of patients were classified as “below expected range for age.” Within the whole study cohort, 36.9% were classified as “normal” based on the Z/T-score analyses.
Figure 1.
Classification of osteoporosis within the different severities of hemophilia.
As seen in Table 2, 14 patients are currently affected by inhibitors. Regarding their BMD values, it can be seen that, 1 showed is classified as “normal”, while 10 are considered “osteopenic” and 3 “osteoporotic.”
Furthermore, 10% (n = 25/255) of the cohort showed a calcium-deficiency (<2.2 mmol/L), while 19.2% (n = 49/255) had a vitamin D deficiency (<12 ng/mL). There was no significant difference of calcium or vitamin D levels between the severities. Moreover, 5.1% (n = 13) of patients were suspected to be affected by secondary osteoporosis given the intake of cortisone, antiepileptics, or the presence of diseases, such as hypogonadism.
A multiple linear regression was conducted to examine the influence of the following parameter on BMD: severity phenotype, age, HJHS, HIV, hepatitis C, smoking, and physical activity. Linear regression analysis reveals that age (B= −0.004; 95% CI: −0.005, −0.002; P < .001) predicts the BMD (left femoral neck) best, followed by severity phenotype (B= −0.048; 95% CI: −0.08, −0.02; P = .001) and HJHS (B= −0.002; 95% CI: −0.004, −0.001; P = .02). The presence of viral comorbidities (HIV, hepatitis C), smoking, or physical activity does not seem to predict the BMD (P > .05; see Supplementary Table).
Emphasizing the influence of age, it needs to be highlighted that 32 patients younger than 25 years old were included in this study. A Z-score <−2.0 was present in 18.8% (n = 6/32) of young persons with hemophilia out of which 5 patients had severe and one from moderate hemophilia.
Moreover, the TBS was analyzed in persons with hemophilia with a body mass index of <37 kg/m2 (n = 219). N = 178 showed normal values (TBS >1.31; Figure 2). Mean TBS was 1.403 ± 0.136. TBS decreased significantly with age (P < .001), although no significant difference was observed between the hemophilia severities (P = .54).
Figure 2.
Trabecular bone scores within different severities of hemophilia.
Along with BMD analysis, the FRAX was calculated in patients aged ≥30 years (n = 186). The mean risk of having a fracture in the next 10 years was 4.4% ± 3.0%. After TBS adjustment, the FRAX decreased to 2.8 ± 3.7%. As FRAX is validated in patients aged >40 years, a subanalysis differentiating in persons with hemophilia aged between 30 and 40 years (n = 69) and persons with hemophilia older than 40 years (n = 117), was performed. In patients aged >40 years, the FRAX was 4.8% ± 3.4% and decreased to 3.6% ± 4.2% after TBS adjustment. In patients aged between 30 and 40 years FRAX was 3.7% ± 2.0% and after TBS adjustment 1.5% ± 2.1%.
4. Discussion
This is the first study to exploratively analyze a representative sample of 255 people with hemophilia of all severities with regard to the prevalence of osteoporosis: 19.2% (95% CI: 12.4-27.0) of persons with hemophilia aged >50 years had osteoporosis and 11.9% (95% CI: 7.1-17.1) of persons with hemophilia aged <50 years have a BMD below the expected range for their age. Literature provides prevalence rates of the average male population in Europe of 9.7% (95% CI: 4.4-18.5), further specified 2.4% (no 95% CI given) in men aged 50 to 60 years, although no data are present for men aged <50 years [13,15].
Low BMD was observed in both femoral necks and the lumbar spine, with the femoral necks being more affected than the lumbar spine. These results and a general discrepancy of BMD in these 2 body areas are consistent with previous research in persons with and without hemophilia [17,31,32]. In this study the lumbar spine shows a tendency to have higher BMD values. One reason could be due to methodological measurement errors of the DXA such as falsely high t-values due to degenerative sclerosis of lumbar vertebral bodies.
The present data show significant differences between the prevalence of osteoporosis in dependence with hemophilia severity. Patients with mild hemophilia seem to be less affected by reduction of BMD. Within literature several approaches deal with explaining this observation. Recent animal research revealed a correlation of FVIII or FIX deficiency and reduction of BMD [5,6]. This finding can be supported by the present observation of an increased prevalence of patients with osteopenia within the subgroup of patients with current positive inhibitor status. However, the sample size of 14 persons with hemophilia within the present study cohort is too small to draw further conclusions. The impact of inhibitors and history of inhibitors should be investigated further to examine the influence of FVIII and FIX on bone health. Moreover, not only inhibitor status but also the factor level, considering precise pharmacokinetic data of the individual should be focused on in future studies.
Previous literature highlighted the relation of a poor joint status and low BMD in persons with hemophilia [17,19,33] and these findings can be confirmed by the present results. Generally, patients with mild hemophilia show a better joint status and less affection of hemophilic arthropathy than patients with moderate or severe hemophilia. Through synovial tissue, it has been shown, that persons with hemophilic arthropathy show higher RANK and RANKL and decreased osteoprotegerin than healthy controls [7]. These molecular markers control bone turnover and cause an increase of osteoclastic activation, leading to a reduction in BMD [7,34]. Even in young persons with hemophilia, who are affected by reduction of BMD, increased serum levels of RANKL and decreased osteoprotegerin were overserved [20,35]. Within the present study cohort, 18.8% (n = 6/32) of young patients (aged <25 years) are “below expected range for age.” Previous studies that investigated the relationship of young persons with hemophilia and their fracture incidence, pointed toward an increased fracture incidence compared with healthy control subjects [36].
Noteworthy, although BMD scores are reduced in persons with hemophilia, TBS is largely normal and thus the microarchitecture of the bones does not seem to be affected. Compared with the German population, which shows an average FRAX of 7.2% in males aged ≥50 years, this study cohort shows rather low FRAX of 4.4% and a TBS-adjusted FRAX of 2.8%, respectively [37]. Meaning that despite the prevalence of osteoporosis was increased in this cohort of persons with hemophilia, yet FRAX was lower than in the normal population. This is in line with observations from hemophilia care centers, which report that persons with hemophilia rarely experience fractures [38]. It appears that, aside from low BMD, persons with hemophilia do not present many other risk factors for fractures. However, given the innovative nature of TBS analysis, future research is needed in study cohorts of both persons with and without hemophilia to prove the significance and generalizability of the TBS.
Multiple linear regression analysis revealed further predictors for BMD (left femoral neck). It was shown that the presence of viral comorbidities does not seem to impact the BMD. It needs to be emphasized that the sample size of the investigated persons with hemophilia affected by HIV (n = 34) or hepatitis C (n = 20) is rather small. Hence, the evidence of this analysis is limited. Previous research revealed a correlation between viral comorbidities and reduced BMD, although there is no consensus in literature [2,39,40]. Despite the decline of viral comorbidities in persons with hemophilia, clinicians should be aware of the possible correlation to control for osteoporosis in patients who have viral comorbidities. No significant correlations were found between physical activity and BMD. With use of an objective activity tracker, an insight into daily physical activity level over a period of 7 days was gathered. It needs to be emphasized that the strain triggered by walking on the bone might not be enough to influence bone metabolism [41]. Nonetheless, an active lifestyle can prevent the reduction of BMD. Emphasizing that previous research found that the duration and intensity of physical activity only play a minor role, although the type of activity is decisive [42].
Moreover, this study revealed a vitamin D deficiency in 19.2% of persons with hemophilia. In comparison, the male adult German population shows a vitamin D deficiency prevalence of 30.8% [30]. A limitation of this study is that subjective information on vitamin D supplementation based on the anamnesis questionnaire lacks in details. Hence, the expressiveness of the information on the level of vitamin D is limited and is assumed to be lower than the present results reveal. Examining vitamin D status and a respective supplementation is recommended [9].
5. Conclusion
The present study found that 63.1% of persons with hemophilia have decreased BMD, either in the form of osteoporosis, osteopenia, or “below expected range for age,” depending on the severity of hemophilia. The orthopedic joint status is directly associated with lower BMD. However, the largely normal TBS indicates that the microarchitecture of the bone does not appear to be affected. Accordingly, a TBS adjustment reduces FRAX by a delta of 1.6%. These findings should be considered in clinical routine to ensure best care and to protect persons with hemophilia from the consequences of undiagnosed osteoporosis, such as fracture risk, reduced mobility, and spine misalignments. In particular, persons with hemophilia are at higher risk of developing osteoporosis, especially with increasing age, calling for action to include screening for osteoporosis in clinical routine at age 30 and older, including vitamin D supplementation if necessary.
Acknowledgments
Funding
This work has been carried out at the University Hospital Bonn. This study was financially supported by Bayer Vital GmbH.
Author contributions
P.R., J.H., and M.B. generated and analyzed the data. F.S., M.J., and F.T. contributed scientifically to the study. G.G. and J.O. supported with the participant recruitment process. T.H. supervised the project. A.S. supervised and developed the project.
Relationship Disclosure
P.R. received speakers’ fees and travel support from Takeda Pharmaceuticals as well as travel support from Swedish Orphan Biovitrum GmbH. M.B. revived travel support from Takeda Pharmaceuticals as well as travel support from Swedish Orphan Biovitrum GmbH. F.T. received speaker’s fees and travel support from Takeda and received an educational grant from Swedish Orphan Biovitrum GmbH. M.J. received speakers fee from Implantcast GmbH and a research grant from Peter Brehm GmbH. G.G. has received funding for lectures by Swedish Orphan Biovitrum GmbH, Takeda, Bayer, Octapharma, Novo Nordisk, Biotest, Roche, BPL, LFB, and further support for attending meetings by Swedish Orphan Biovitrum GmbH, Novo Nordisk, and Biotest. T.H. received research funding from Biotest, Chugai, CSL Behring, Intersero, Roche, Swedish Orphan Biovitrum, and Takeda. Travel expenses, speaker or scientific advisory board honoraria from Bayer, Biotest, CSL Behring, Chugai, NovoNordisk, Pfizer, Roche, Sanofi, Swedish Orphan Biovitrum, and Takeda. J.O. has received research funding from Bayer, Biotest, CSL Behring, Octapharma, Pfizer, Swedish Orphao Biovitrum, and Takeda. Consultancy, speaker’s bureau, honoraria, scientific advisory board, and/or travel expenses from Bayer, Biogen Idee, BioMarin, Biotest, Chugai, CSL Behring, Freeline, Grifols, LFB, Novo Nordisk, Octapharma, Pfizer, Roche, Sanofi, Spark Therapeutics, Swedish Orphan Biovitrum, and Takeda. A.S. has received research funding from Bayer, Swedish Orphan Biovitrum, and Takeda and has received consultancy, speaker’s bureau, honoraria, scientific advisory board, and travel expenses from Bayer, Biotest, CSL Behring, Novo Nordisk, Swedish Orphan Biovitrum, and Takeda. J.H. and F.S. have no competing interests to declare.
Footnotes
Handling Editor: Johnny Mahlangu
The online version contains supplementary material available at https://doi.org/10.1016/j.rpth.2024.102624
Supplementary material
References
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