Article Information

Marwa A Besar^1*, Youssef Abulatta², Mohamed Hussein², Mahmoud Abdelhadi²

¹Lecturer of Internal medicine, Rheumatology& Immunology unit, Faculty of medicine, Mansoura University, Mansoura, Egypt

²House officer at Mansoura University Hospital MMMP (Mansoura Manchester Medical program), Faculty of medicine, Mansoura University, Mansoura, Egypt

^*Corresponding Author: Marwa A Besar, Lecturer of Internal medicine, Rheumatology& Immunology unit, Faculty of medicine, Mansoura University, Mansoura, Egypt.

Received: 21 December 2023; Accepted: 06 January 2024; Published: 30 January 2024.

Citation: Marwa A Besar, Youssef Abulatta, Mohamed Hussein, Mahmoud Abdelhadi. Validation of Osteoporosis Scores with Urinary N-telopeptide Bone Marker in Assessment Bone Mineral Density in Autoimmune Rheumatic Diseases Patients. Fortune Journal of Rheumatology 6 (2024): 01-07.

Abstract

Keywords

Osteoporosis, Autoimmune Diseases, Fracture Risk Assessment (Frax), Bone mineral density (Bmd), Dual energy X-ray absorptiometry (Dexa).

Article Details

1. Introduction

Osteoporosis is a condition characterised by decreased bone strength that culminates in an increased risk of fractures in response to minimal or low velocity force in autoimmune rheumatic diseases due to many factors; the disease itself, the age and side effect of medication used in treatment especially corticosteroid [16]. Many tools used to assess the osteoporosis in them e.g Dual-energy x-ray absorptiometry (DXA) san, is the gold standard test for diagnosing osteoporosis and monitoring its treatment [14]. It depends on the amount of x-ray energy passing through bone and correlates it with the amount of mineral present, so DXA is a valuable tool in assessment of quantity in bone, but it is poor assessment of quality of bone.  Another important point; DXA is unquestionably a useful tool to detect early bone loss that fracture risk which can occur at any T-score [2].So; incorporation anew tool in evolution the risk of fracture in these vulnerable group based on clinical history to assess the risk factor e.g the Fracture Risk Assessment Tool (FRAX) [9]. FRAX has worldwide applicability and validation in different countries. Its calculations may be part of a DXA report, or clinicians may use web-based tools to run the calculations. It provides an intervention threshold for decision analysis. [8] it allows the use of trabecular bone score data to help calculate intervention thresholds for major and hip osteoporotic fractures [12] but it isn’t validated to assess patients under the age of 40 years, may be restricted to specific geographic populations and they do not quantify factors in the calculations such as duration and amount of glucocorticoid use and the severity of secondary diseases [6]. Bone resorption markers are important indicators of disease activity in patients with osteoporosis. Urinary N-telopeptide has been used for monitoring treatment for osteoporosis for a long time [7], but now, clinicians are using it to predict the onset of osteoporosis. Urinary N-telopeptide is a sensitive and specific marker of bone resorption.

Aim of the work:

This study was conducted to validity of WHO fracture risk assessment tool (FRAX) and Dual-energy x-ray absorptiometry (DXA) scan in assessment of osteoporosis risk in autoimmune diseases. Beside assessment the role of serum Vitamin D and urinary telopeptide in predication of osteoporosis in them.

2. Patients and Methods

A cross sectional observational study where a total of (180) autoimmune rheumatic patients were assessed for osteoporosis during one-year duration in the rheumatology and immunology outpatient clinic, Mansoura University Hospital (MUH).

2.1 Methods

Thorough autoimmune and rheumatic history (which one, duration, line of management and disease activity at that time).Osteoporosis assessment (DXA, FRAX score assessment) and Line of management (whether anabolic or antiresorptive therapy, duration and response to prescribed medication).Serum vitamin D and uric acid and Twenty-four hours urine was collected in a sterile plastic container and sent for analysis of urinary telopeptide.

2.2 Inclusion criteria

All patients diagnosed as autoimmune rheumatic diseases patients who fulfil the criteria of definition of osteoporosis attending Rheumatology &Immunology unit in internal medicine department and outpatient’s clinic during the duration of the study.

2.3 Statistical analysis

Data were entered and statistically analyzed using the Statistical Package for Social Sciences (SPSS) version 23. Qualitative data were described as numbers and percentages. Quantitative data were described as means (SD) or medians, after testing for normality by Kolmogorov-Smirnov test.

3. Results

Our work target about 180 Rheumatic patients with the mean age of them was 46±12.6 years old, 92.8% (167/180) were female, more than fifty 57.2 (103/180) of studied patients were RA, 33 % (60/180) were SLE and less than 10% of them were Behcet 4.4%, Scleroderma 0.6%, Sjogren syndrome 1.7%, Vascuilitis 0.6% and 2.2% PSA. Most of them 86.1% (155/180) were controlled and 67.2% (121/180) of them had no complication. Majority of studied group 77.8% (140/180) were treated with DMARDs, 89.4% (161/180) were treated with corticosteroid Table (2). The median of height of studied patients was 160 (154-165) cm, weight 85 (75-95)kg, BMI  33.7 (29.4-37.8)cm/kg2, S Uric acid 6 (5-7)ng/dl, S vitamin D 26 (13.3-32)ng/dl, urinary Telopeptide 105 (89-175) nm BCE. It was noticed that more than Fifty of studied Rheumatic patients had normal bone density, 34% had osteopenia and about 14% of them had osteoporosis Figure (1), where Lt femur neck T score -0.9 (-1.5…-0.3), Lt femur neck z score -0.6 (-1.2….0), Lt forearm T score -0.8 (-1.7….-0.1), Lt forearm Z score -0.5 (-1.3…….0.3), osteoporosis 2 (1-2), FRAX score osteoporosis % 3.7 (2.6-7.5), FRAX score hip fracture % 0.2 (0.1-0.6) and risk hip fracture 1 (1-1). The mean of BMI (10-year probability of fracture) was 33.5±6.6, lumbar spine T score -1.1±1.3 and lumbar spine Z score -1.1±1.3 Table (1). Type of Osteoporosis treatment received by our studied patients varied where Bisphosphonate was used in 47.2%, Densoumab 5%, Tripeptide 2.2% while Calcium and vitamin D supplement was used alone in 37.2% and one year duration was used in 57.8% of treated patients, two year duration in 31.1% while three year duration was only in 7.8% of them. Majority of treated patients 91.1% had stationary course, fortunately no major osteoporotic fracture in majority of them 96.1% with mild side effect in the form FHMA and hypocalcaemia in about 35.6% Table (2). With correlation of osteoporosis score with other parameter, there was highly significant negatively correlated with age, percentage of FRAX score osteoporosis and BMI (10year probability of fractur), but positively significant correlation with risk hip fracture. Weight and BMI were positively significant correlated with age, BMI (10year probability of fractur) and risk hip fracture, but significant negatively correlated with percentage of FRAX score hip fracture. S Uric acid was positively significant correlated with age, percentage of FRAX score osteoporosis and FRAX score hip fracture, but significant negatively correlated with osteoporosis and S. vitamin D. S. Vitamin D was significant negatively correlated with percentage of FRAX score osteoporosis and FRAX score hip fracture and S. uric acid but significant positively correlated osteoporosis.  Left femur neck T score was significant negatively correlated with age, S uric acid, S vitamin D, percentage of FRAX score osteoporosis and FRAX score hip fracture, but positively significant correlated with osteoporosis and risk hip fracture. Left femur neck Z score was significant negatively correlated with S uric acid and S vitamin D, but positively significant correlated with osteoporosis. Left forearm T score was significant negatively correlated with age, S uric acid, percentage of FRAX score osteoporosis and FRAX score hip fracture, but positively significant correlated with S vitamin D, osteoporosis, risk hip fracture and BMI (10year probability of fractur). Left forearm Z score was significant negatively correlated with S uric acid, percentage of FRAX score osteoporosis and FRAX score hip fracture, but positively significant correlated with osteoporosis, S vitamin D and BMI (10year probability of fractur). Lumbar T score was significant negatively correlated with age, S uric acid, percentage of FRAX score osteoporosis and FRAX score hip fracture, but positively significant correlated with S vitamin D and osteoporosis, risk hip fracture. Lumbar Z score was significant positively correlated with age, S vitamin D, percentage of FRAX score osteoporosis and FRAX score hip fracture, but negatively significant correlated with S uric acid and risk hip fracture. Table (3)

Figure 1: Percentage of osteoporosis among studied patients (n=180)

Table 1: Characteristics of studied patients (n=180):

Table 2: demographic data of studied patients (n=180):

Table 3: Correlation of osteoporosis scores: -

Spearman correlation

4. Discussion

Due to impact of autoimmune diseases and medication used in management especially corticosteroid, most of them had low bone density with different degree of fracture, early predication of low bone mineral density is the main preventive tool to prevent fracture in these vulnerable group [19]. Our study revealed that half of studied autoimmune diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Bechet, psoriatic arthritis (PSA), Scleroderma and Sjogren syndrome had low bone mass that in line with(Weitzmann, et al) [18] stated that rapid bone loss and increased fracture risk are implicated in a range of autoimmune diseases. The older age of studied autoimmune patients with average age of them was 46±12.6 years old that put them in high risk for osteoporosis and fracture as in agreement with (Marques A et al) who concluded that Age is a variable in all clinical risk calculators and with aging, fracture rates rise exponentially as bone density decreases. Added that fractures are less likely to occur in younger people than in older people, even with similar bone density measurements. Clinical data show that this paradox reflects age-dependent microarchitecture degradation [11]. It was noticed that S. vitamin D is low, median 6 (5-7)ng/ml that may a risk factor for low bone density in studied patients as mentioned by (Pietschmann, P et al 2016) that Osteoporotic hormones such as 1,25 dihydroxy vitamin D3 (1,25(OH)2 D3), parathyroid hormone (PTH) and prostaglandin E2 (PGE2) are responsible for upregulating expression of RANKL which represents the central process through which bone loss is regulated [13]. It was observed that usefulness of osteoporosis treatment in autoimmune studied patients with stationary course without risk of atypical fracture that in line to A 2019 meta-analysis [1] that Osteoporosis drugs produce a spectrum of changes in vertebral bone density, added that a strong correlation between improvements in BMD and greater reductions in rates of vertebral and hip fracture, reassuring practitioners of the usefulness of DXA to monitor treatment.

Assessment of bone density can be done by different tools; DEXA scan, FRAX score for fracture risk assessment each one has advantage and disadvantage [10]. DEXA scan in autoimmune studied patients detected that osteopenia in 34%, osteoporosis 14% while the median of FRAX score osteoporosis % was 3.7 (2.6-7.5) with high risk for osteoporosis that was in consistent with (Humes, D.H et al) stated that risk of osteoporosis increases significantly in autoimmune patients with each standard deviation below peak bone mass (or 1 unit decrease in T-score), it is reported a woman's risk of fracture approximately doubles [4]. Our studied autoimmune patients had high risk of fracture according to 10-year probability of major osteoporotic fracture and 10-year probability of hip fracture based on thresholds in the USA as described in the National Osteoporosis Foundation (NOF) Clinician’s Guide (Tosteson AN et al) [17] For clinical use, the International Osteoporosis Foundation proposed different markers that reflect bone metabolism or turnover, but these are not diagnostic tools for osteoporosis and are not a substitute for DXA analysis. ( Eastell R et al) [8]. The N-telopeptide is specific to bone due to its unique amino acid sequence. Bone density as measured by DXA provides a static snapshot of bones and does not distinguish if bone loss is ongoing or not (Jayaram N et al). But urinary N-telopeptide is a dynamic measurement of what is happening in bone at any given time [5] The median urinary Telopeptide was high in studied autoimmune patients 105 (89-175) which is important tool in the evaluation of quality of bone and a predicator for fracture as in agreement with (Singer FR et al) [15] stated that urinary N-telopeptide can be considered as a new diagnostic tool for diagnosing osteoporosis.

Conclusion

Although urinary N-telopeptide is a valuable marker for bone metabolism and predication of risk of fracture, it is not a substitute for DXA and FRAX score.  So, If we suspect osteoporosis, it is better to go for urinary N-telopeptide and those who test positive can go for current gold standard DXA scan. Thus, combination of these two diagnostic tests could be useful to improve the identification of high risk for fracture.

Limitations of our analysis: include the cross-sectional nature of the data collected, to some extant small sample size, single Centre experience and lack of long-term follow-up to evaluate the incidence of fractures.

Declarations:

DOI (Declaration of conflict of interest): 

Marwa A Besar, Youssef Abulatta, Mohamed Hussein and Mahmoud Abdelhadi have no conflict of interest.

Ethics approval: Ethical approval was taken by Mansoura Medical Ethics Research committee (MMERC) of faculty of Medicine, IRB Mansoura

Code number: R.22.10.1908 Date: 5/11/2022.

Human Ethics and Consent to participate: Ethical approval from the patients were taken to share their data and for publication.

Availability of data and materials: All data are confidential.

Competing interests:

Marwa A Besar, Youssef Abulatta, Mohamed Hussein and Mahmoud Abdelhadi have not competing interest

Funding: Marwa A Besar, Youssef Abulatta, Mohamed Hussein and Mahmoud Abdelhadi have no external funds.

Authors' contributions:

Main author; Corresponding author; (Marwa A Besar) Marwa Abo Elmaaty Besar; Lecturer of Internal medicine, Rheumatology& Immunology unit. Collected main data wrote, main paper and added supplementary data. besarmarwa@mans.edu.eg

Co-authors:

(Youssef Abulatta) Youssef Mohammed Metwally Abulatta: House officer at Mansoura University Hospital MMMP (Mansoura Manchester Medical program), help collected the data and approved the submitted final version. Yabuelatta@gmail.com

(Mohamed Hussein) Mohamed IssamHafez Hussein, House officer at Mansoura University Hospital MMMP (Mansoura Manchester Medical program), help collected the data and approved the submitted final version. m.essam.hafez977@gmail.com

(Mahmoud Abdelhadi) Mahmoud Ali Ali Abdelhadi: House officer at Mansoura University Hospital MMMP (Mansoura Manchester Medical program), help collected the data and approved the submitted final version. Mahmoud.abdulhady1998@gmail.com.

References

1. Bouxsein ML, Eastell R, Lui LY, et al. FNIH Bone Quality Project. Change in bone density and reduction in fracture risk: a meta regression of published trials. J Bone Miner Res 34 (2019): 632-642.
2. Choksi P, Clines GA, Jepsen KJ. The challenges of diagnosing osteoporosis and the limitations of currently available tools. Clin Diabetes Endocrinol 4 (2018): 12.
3. Eastell R, Gossiel F, Naylor KE, et al. Diagnosis of endocrine disease: bone turnover markers: are they clinically useful? Eur J Endocrinol 178 (2018): 19-31.
4. Humes DH. Osteoporosis. In: Humes, D.H. (Ed.), Kelley's Essentials of Internal Medicine. 2ed Lippincott Williams & Wilkins, Philadelphia, PA (2011).
5. Jayaram N, Bijoor AR, Rajagopalan N, et al. The value of serumand urinary n-telopeptide in the diagnosis of osteoporosis. Indian J Orthop 36 (2002): 9-13.
6. Kanis JA, Cooper C, Harvey NC, et al. A systematic review of intervention thresholds based on FRAX: a report prepared for theNational Osteoporosis Guideline Group and the International Osteoporosis Foundation. Arch Osteoporos 11 (2016): 25.
7. Kleerekoper M, Edelson GW, et al. Biochemical studies in the evaluation and management of osteoporosis: current status and future prospects. Endocr Pract 2 (1996): 13-19.
8. Leslie WD, Morin SN, Lix LM, et al. The diagnostic threshold for osteoporosis impedes fracture prevention in women at high risk for fracture: a registry-based cohort study. Bone 114 (2018): 298-303.
9. Lindsay R, Cosman F, et al. Osteoporosis 25 (2014): 2359-2381.
10. Meshcheryakova A, Ellinger I, Föger-Samwald U, et al. Harrison's Principles of Internal Medicine, 19e New York. McGraw-Hill, NY.
11. Marques A, Carmona L, da Silva JA, et al. The accuracy of osteoporotic fracture risk prediction tools: a systematic review and meta-analysis. Ann Rheum Dis 74 (2015): 1958-1967.
12. Martineau P, Leslie WD, Johansson H, et al. Clinical utility of using lumbar spine trabecular bone score to adjust fracture probability: the Manitoba BMD cohort. J Bone Miner Res 32 (2017): 1568-1574.
13. Pietschmann P, Mechtcheriakova D. Immunology of osteoporosis: a mini-review. Gerontology 62 (2016): 128-137.
14. Punda M, Grazio S et al. Bone densitometry–the gold standard for diagnosis of osteoporosis [in Croatian]. Reumatizam 61 (2014): 70-74.
15. Singer FR, Eyre DR et al. Using biochemical markers of bone turnover in clinical practice. Cleve Clin J Med 75 (2008): 739-750.
16. Siris ES, Barrett-Connor E, Miller PD, et al. Identifi cation and fracture outcomes of undiagnosed low bone mineral density in postmenopausal women: results from the National Osteoporosis Risk Assessment. JAMA 286 (2001): 2815-2822.
17. Tosteson AN, Dawson-Hughes B, Melton LJ 3rd et al. Costeffective osteoporosis- treatment thresholds: the United States perspective. Osteoporos Int 19 (2008): 437-447.
18. Weitzmann MN. T-cells and B-cells in osteoporosis. Curr. Opin. Endocrinol. Diabetes Obes 21 (2014): 461-467.
19. Xiao Y, de Groot DC, van Tol MJ, et al. Identification of the common origins of osteoclasts, macrophages, and dendritic cells in human hematopoiesis. Stem Cell Rep 4 (2015): 984-994.