The clinical utility of bone marker measurements in osteoporosis
© Wheater et al.; licensee BioMed Central Ltd. 2013
Received: 11 February 2013
Accepted: 21 August 2013
Published: 29 August 2013
Osteoporosis is characterised by low bone mass and structural deterioration of bone tissue, resulting in increased fragility and susceptibility to fracture. Osteoporotic fractures are a significant cause of morbidity and mortality. Direct medical costs from such fractures in the UK are currently estimated at over two billion pounds per year, resulting in a substantial healthcare burden that is expected to rise exponentially due to increasing life expectancy. Currently bone mineral density is the WHO standard for diagnosis of osteoporosis, but poor sensitivity means that potential fractures will be missed if it is used alone. During the past decade considerable progress has been made in the identification and characterisation of specific biomarkers to aid the management of metabolic bone disease. Technological developments have greatly enhanced assay performance producing reliable, rapid, non-invasive cost effective assays with improved sensitivity and specificity. We now have a greater understanding of the need to regulate pre-analytical sample collection to minimise the effects of biological variation. However, bone turnover markers (BTMs) still have limited clinical utility. It is not routinely recommended to use BTMs to select those at risk of fractures, but baseline measurements of resorption markers are useful before commencement of anti-resorptive treatment and can be checked 3–6 months later to monitor response and adherence to treatment. Similarly, formation markers can be used to monitor bone forming agents. BTMs may also be useful when monitoring patients during treatment holidays and aid in the decision as to when therapy should be recommenced. Recent recommendations by the Bone Marker Standards Working Group propose to standardise research and include a specific marker of bone resorption (CTX) and bone formation (P1NP) in all future studies. It is hoped that improved research in turn will lead to optimised markers for the clinical management of osteoporosis and other bone diseases.
KeywordsBone turnover markers Bone formation Bone resorption Osteoporosis Biological variability
Under normal conditions bone formation and resorption are tightly linked through a variety of regulatory signals. Osteoporosis occurs when bone resorption is the more active resulting in a low bone mass and micro-architectural deterioration of bone tissue, leading to increased bone fragility and consequent increase in fracture risk. Osteoporotic fractures are a significant cause of morbidity and mortality, in the year 2010 there were an estimated 300,000 osteoporotic fractures in the UK and direct medical costs from such fractures were estimated at over two billion pounds . Osteoporosis may be either primary (idiopathic) or secondary to a large number of conditions. These include hypogonadism, hyperthyroidism, skeletal metastases, multiple myeloma, anticonvulsant or oral corticosteroid use and alcohol abuse. Up to 30% of women and 55% of men with symptomatic vertebral crush fractures have an underlying cause of secondary osteoporosis . The prevalence of osteoporosis increases with age, bone loss is reportedly more rapid in females in the first few years post menopause and is influenced by oestrogen deficiency , but it is also thought to increase in ageing men . The World Health Organisation (WHO) has defined osteoporosis as a bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA) 2.5 standard deviations (SD) or more below the mean peak bone mass of premenopausal females (T-score ≤ −2.5 SD) . Technical developments in the measurement of BMD have led to its adoption as the standard for diagnosis of osteoporosis, however the relatively poor sensitivity contrasting with high specificity means that many potential fractures will be missed if BMD assessment is used alone .
In recent years cellular components of the bone matrix have been identified and categorised as either markers of bone formation or resorption. Reliable, rapid, non-invasive, cost effective assays have been developed with improved sensitivity and specificity. Although these markers have been used in research for a long time they are only now being recognised as tools in the clinical management of bone disease. Technological advances have greatly enhanced the accuracy and reliability of bone marker measurement, although assays still vary significantly. In this review we will summarise the most widely used bone turnover makers (BTMs), briefly look at more novel markers and discuss their strengths, weaknesses and their clinical utility in the management of osteoporosis.
Commonly used markers of bone turnover
Major sources of variability in biochemical markers of bone turnover
Bone marker (Abbreviation)
Analysis and sample type
Bone Alkaline Phosphatase (BAP)
Enzyme present in osteoblast plasma membranes
Enzymatic degradation of the mineralisation inhibitor pyrophosphate at alkaline pH
Up to 20% cross reactivity with liver isoforms  Changes with therapy minimal i.e. less than LSC of 25%  2 peaks at 14:00 and 23:30 hrs Nadir 30% ↓at 06:30  Multiple methodologies, can measure mass or activity 
Automated and manual immunoassays Serum, EDTA plasma
Major non-collagen bone Gla protein. Produced by osteoblasts during bone formation and bound to hydroxyapatite
Influences osteoid mineralisation Provides negative feedback during remodelling process
Intact molecule unstable  Large inter-lab variation  Released during formation and resorption  Short half-life of a few minutes [22, 23] Influenced by Vit K status, renal function and circadian variability [15, 17] OC gene regulated at transcriptional level by 1,25-OH2 Vit D Vit K essential co-factor for γ-carboxylation of OC resulting in ↑ affinity for Ca and hydroxyapatite 
Automated and manual immunoassays Multiplex microarray Serum, EDTA plasma
Procollagen type 1 Carboxy-terminal Propeptide (P1CP)
Specific product of proliferating osteoblasts and fibroblasts.
Cleaved from type 1 pro-collagen by proteases during type 1 collagen formation
Quantitative measure of newly formed type 1 collagen Thermostability 
Short half-life 6-8mins  Cleared in liver by mannose receptor so sensitive to thyroid hormones and IGF-1  Highest levels 01:30 – 04:30, up to 20% higher than nadir 11:00 – 15:00  Lacks sensitivity to changes during menopause 
Automated and manual immunoassays Serum, EDTA plasma
*Procollagen type 1 amiNo-terminal Propeptide (P1NP)
Specific product of proliferating osteoblasts and fibroblasts.
Cleaved from type 1 pro-collagen by proteases during type 1 collagen formation
Low intra-individual variability Small circadian rhythm Stable at room temp Good assay precision Superior for PMO monitoring - change from baseline ↑up to 80% with anti-resorptive and ↓up to 200% with PTH medication within 3months
Total assay affected by delayed clearance of monomeric fraction e.g. in renal failure or metastatic bone disease Expensive
Automated and manual immunoassays Multiplex microarray Total or Intact fractions Serum, EDTA plasma
Resorption markers Collagen derived
*Carboxy-Terminal cross-linked telopeptides of type 1 collagen (CTX)
Type 1 collagen mainly bone Isomerisation to β aspartyl occurs in mature collagen
Cleaved from type 1 collagen by cathepsin-K during bone resorption
Large circadian variation – highest 01:30 – 04:30 approx 2x nadir 11:00–15:00
Automated and manual immunoassays Multiplex microarray Urine, serum, EDTA plasma
Carboxy-Terminal cross-linked telopeptides of type 1 collagen (ICTP or CTX-MMP)
Newly synthesised type 1 collagen predominantly bone
Cleaved from type 1 collagen by MMP during bone resorption
amiNo-Terminal cross-linked telopeptides of type 1 collagen (NTX)
Type 1 collagen mainly bone
Cleaved from type 1 collagen by cathepsin-K during bone resorption
Automated and manual immunoassays Urine, serum, EDTA plasma
Type 1 collagen alpha 1 helicoidal peptide (HELP)
Type 1 collagen Amino acid 620–633 sequence of the α chain
Cleaved from helical region of type 1 collagen by cathepsin-K during bone resorption
High correlation to other markers of collagen degradation 
24 hr collection – hard to collect 2nd morning void with creatinine correction – additional analytical variability Clinical validity needs further investigation
Manual immunoassay Urinary marker
Mature type 1 collagen
Cross link released when mature type 1 collagen breaks down Mechanically stabilise the molecule
24 hr collection – hard to collect 2nd morning void with creatinine correction – additional analytical variability Circadian variation 
Automated and manual immunoassays Urinary marker
Mature type 1 and 11 collagen
Cross link released when mature collagen type 1 and 11 breaks down Mechanically stabilise the molecule
Reflect degradation of mature collagen only Independent of dietary sources 
Automated and manual immunoassays Urinary marker
Resorption markers Osteoclastic Enzymes
Tartrate Resistant Acid Phosphatase –isoform 5b (TRAP5b)
Isoform of acid phosphatase, resistant to tartrate, cleaved by proteases into 5b, present in ruffled border of osteoclasts
Cleaves type 1 collagen into fragments
Characteristic of osteoclastic activity 
Automated and manual immunoassays Serum
Cysteine protease present in ruffled border of actively resorbing osteoclasts
Cleaves telopeptide and helical regions of type 1 collagen
Specific biomarker of osteoclastic activity 
Unstable at room temp Clinical validity needs further investigation
Manual immunoassay Serum, EDTA plasma
Osteocyte activity markers
Receptor Activator of Nuclear factor Kappa B Ligand (RANKL)
Produced by osteoblasts, activated by B and T cells
Binds to RANK, which is expressed on osteoclasts and their precursors, stimulating their differentiation and activity
Novel biomarker Provide safety, efficacy and pharmacokinetics data to confirm drug mechanisms and mode of action for future use
Analytical problems Can measure free or OPG-bound  Circulating levels may not reflect bone microenvironment  Affected by thyroid function  Research method only Clinical and analytical validity needs further investigation
Manual research –grade immunoassay Total or soluble forms in serum
Secreted by osteoblasts
Decoy receptor to RANKL reduces bone resorption by binding to RANK and preventing osteoclastogenesis
Novel biomarker Provide safety, efficacy and pharmacokinetics data to confirm drug mechanisms and mode of action for future use
Affected by thyroid function  Research method only Clinical and analytical validity needs further investigation
Manual research-grade immunoassay Serum
Dickkopf-related protein 1 (DKK1)
Produced by osteocytes
Inhibition of Wnt signalling pathway through binding to LRP5/6, blocking the Wnt effects on osteoblasts and decreasing bone formation
Key role in regulation of bone turnover
Research method only Clinical and analytical validity needs further investigation
Manual research –grade immunoassay Serum
Secreted by osteocytes
Inhibition of Wnt signalling pathway through binding to LRP5/6, blocking the Wnt effects on osteoblasts and decreasing bone formation
Significant ↓ with PTH therapy 
Manual research-grade immunoassaySerum
Markers of bone formation
Markers of bone formation are either by-products of active osteoblasts expressed during the various phases of their development or osteoblastic enzymes. The most widely used markers of bone formation are measured in serum or plasma and include: bone specific alkaline phosphatase (BSAP), osteocalcin and the carboxy- and amino-terminal propeptides of type 1 collagen (P1CP, P1NP). P1NP has several functional advantages and has been recommended by the Bone Marker Standards Working Group; it has low inter-individual variability  and is relatively stable in serum at room temperature . P1NP is cleared by liver endothelial cells via a macrophage receptor species, the scavenger receptor, that recognises and endocytoses modified proteins . P1NP is released as a trimeric structure, but is rapidly broken down to a monomeric form by thermal degradation . Current immunoassays detect either the trimeric ‘intact’ molecule (automated IDS iSYS assay) or can measure both fractions and are thus called ‘total’ P1NP assays (automated Roche Elecsys assay).
Markers of bone resorption
The majority of bone resorption markers are degradation products of bone collagen, the exception being tartrate-resistant acid phosphatase (TRAP5b). Earlier research into bone metabolism relied primarily on urinary markers such as pyridinoline (PYD) and deoxypyridinoline (DPD), which were time-consuming and cumbersome and relied on complete twenty-four hour urine collections or second morning void/ creatinine ratios, increasing the imprecision of the measurement. However, now that serum/ plasma markers are available these have become the preferred means of measuring resorption. Examples include carboxy-terminal and amino-terminal cross-linked telopeptide of type 1 collagen (CTX and NTX respectively), of which CTX is considered the marker of choice . CTX is generated by cathepsin K activity, the CTX epitope contains an aspartyl-glycine motif that is susceptible to spontaneous isomerisation and racemisation generating four isoforms ; the α-aspartic acid converts to the β-form as the bone ages. Two automated immunoassays are available that target βCTX indicative of the breakdown of mature type 1 collagen (IDS iSYS and Roche Elecsys). The major disadvantage of CTX is its large circadian variation necessitating a morning fasting sample for accurate interpretation . The choice of marker in clinical practice needs to be made on pragmatic grounds. Urine NTX may be the preferred marker in the clinic setting as unlike plasma CTX, it is not as sensitive to circadian changes and is not affected by food intake, it also avoids the invasive venepuncture associated with a blood sample and may be preferred by patients . However the various drugs licensed for the treatment of osteoporosis have a differing spectrum of effects on BTMs and not all markers respond by the same amount for a given degree of bone resorption. Amongst the bone resorption markers, plasma CTX tends to change more than urine NTX which tends to change more than TRAP5b .
Markers of osteoclastogenesis
Osteoclast regulatory proteins are commonly measured in research, but have yet to find a niche clinically. The discovery of the OPG/RANK/RANKL system has clarified a major component of the bone remodelling cycle. RANKL is expressed in vivo in either membrane-bound or soluble form (sRANKL) and is also present in serum as a free or OPG-bound molecule, as a consequence design differences between immunoassays have created difficulties in comparing research and interpreting clinical data . Furthermore circulating levels may not reflect the bone microenvironment . Research into the relationship between circulating levels of OPG and sRANKL to BMD in postmenopausal osteoporosis are controversial, some studies reporting an inverse relationship , while others have found no association . Rigorous testing of commercial assays and identification of the sources of variability are required before they can be adapted to routine clinical practice.
Over the last decade research has focused mainly on the role of osteoclasts and osteoblasts in osteoporosis, more recently however, osteocytes have been found to play a key role in the regulation of bone turnover. Osteocytes are fully differentiated osteoblasts and lie in lacunae in the mineralized matrix and osteoid tissue of bone . Osteocytes are able to detect changes in bone morphology, particularly micro-fractures through their sensitivity to mechanical forces, acting like bone mechanoreceptors . They regulate bone turnover both through direct physical contact with other bone cells and by producing various factors which affect bone formation and can be measured in blood such as, sclerostin (SCL), dickkopf-related protein 1 (DKK1), dentin matrix protein 1 (DMP1) and matrix extracellular phosphoglycoprotein (MEPE).
DKK1 and SCL are secreted osteocyte markers acting as inhibitors to the Wnt signalling pathway through binding to low density lipoprotein receptor-related protein 5 and 6 (LRP5/6) and hence blocking the Wnt effects on osteoblasts decreasing bone formation (Figure 2) [44, 45]. In vivo studies have shown that osteocyte depletion results in profound loss of trabecular bone mass [46–48] and suggest a close interaction between osteocytes and other bone cells, highlighting their role in the regulation of both bone formation and resorption.
Although widely used in research, their diagnostic importance remains to be validated due in part to their analytical and biological variability. In healthy adults, SCL levels correlate positively with age, BMI, and bone mineral content and negatively with osteocalcin and calcium . SCL is increased in type 2 diabetes. Moreover, the transcriptional suppression of SCL production by PTH might be impaired in type 1 and type 2 diabetes . SCL levels are significantly lower in osteoporotic compared to non-osteoporotic patients with type 2 diabetes . The Wnt signalling pathway has recently been identified as central to the development of disuse osteoporosis . Mechanical unloading in long-term immobilized patients causes up regulation of SCL and therefore inhibits bone formation via suppressed osteoblast activity and survival . Circulating SCL reflects the severity of bone loss and is a candidate biomarker of osteoporosis severity in chronic spinal cord injury . Higher serum SCL levels are associated with a greater risk of hip fractures in older women. In addition, the risk of hip fracture is amplified when high SCL levels are combined with lower BMD . Serum SCL levels are regulated by both estrogens and PTH in postmenopausal women . Serum SCL is decreased in women with postmenopausal osteoporosis compared with non-osteoporotic early postmenopausal women and positively correlated to lumbar spine BMD. Furthermore, levels are increased after 6 months treatment with risedronate, but remain essentially unchanged after 6 months teriparatide treatment . However, serum or plasma SCL concentrations should be interpreted with caution as current assays produce very different results. Standardization of sclerostin assays is necessary before being introduced into general clinical laboratory use .
Variability in markers of bone turnover
An understanding of the source and magnitude of the absolute inter and intra-person variability, including biological, pre-analytic and analytical variation, of each marker is necessary to interpret serial measurements and individualise treatment.
Bone turnover shows a circadian rhythm, this is more obvious in the serum and urinary markers of bone resorption. βCTX for example is highest between 01:30 and 04:30 hours and may be more than twice that at the nadir between 11:00 and 15:00 hours , this may be attenuated by several factors such as; age, gender, ethnicity, menopausal status, osteoporotic stage and anti-resorptive agents or calcium supplementation , but the disparity is diminished with fasting . All bone markers are significantly lower in the fed state with the exception of BSAP, this may be due to several factors including the clearance rate of individual markers or food composition  and may be partly explained by variation in serum insulin . Osteocalcin and P1CP follow the same diurnal pattern but show only twenty percent difference and BSAP has two peaks at 14:00 and 23:30 hours with a nadir thirty percent reduced at 06:30 . Therefore timing of the sample collection and fasting status should be tightly controlled.
The existence of intra-individual low-frequency biological rhythms, imply that biomarkers can also vary between consecutive days, this is more noticeable in the urinary resorption markers . There is a degree of controversy regarding seasonal variation with some researchers suggesting that overall seasonal changes are insignificant , whilst others have found a substantial wintertime increase , which may be due in part to reduced levels of vitamin D. Physical activity is also significant, TRAP and to a lesser extent BSAP and CTX are reduced immediately after plyometrics, but return to pre concentrations within two hours. Interestingly similar changes were found in PTH . Details of exercise in the previous twenty-four hours should therefore be recorded.
Bone turnover varies with the menstrual cycle, research suggests that osteoblastic activity is higher during the luteal period  and bone resorption is increased during the follicular phase . Pregnancy affects all BTMs due in part to the calcium requirements of the foetus, but also to changes in maternal glomerular filtration rate (GFR) affecting renal clearance. However the time change is contentious, one study following ten women at regular intervals reported an increase in urinary resorption markers throughout pregnancy with a significant increase in bone formation in the third trimester . A more recent study measured serum OPG, RANKL, osteocalcin and CTX in twenty six different women at each trimester. The study found increased bone formation in the first trimester and increased resorption in the second which surprisingly decreased again in the third trimester . Postpartum, levels gradually start to decrease but may still be higher than pre-pregnancy levels for up to a year .
A comprehensive drug history should also be taken into account when interpreting bone marker results. Anti-resorptive drugs such as bisphosphonates  and hormone replacement therapy (HRT)  have a major effect on markers of bone resorption and long-term corticosteroid therapy is known to suppress bone formation .
Inflammatory conditions are major precipitators for bone loss, especially rheumatoid arthritis (RA) which is further aggravated by decreased functional activity and the use of glucocorticoids . In a prior study, we found that B-cell depletion increases bone formation and decreases bone resorption in RA patients. This may be a direct effect on osteoblasts and osteoclasts respectively and be at least partially explained by the decreased inflammation and disease activity . In diabetes serum osteocalcin is negatively correlated with glucose levels and advanced glycation end products (AGEs) are known to have a negative impact on bone . Thyroid disorders such as thyrotoxicosis are well known to affect bone turnover. Thyroid stimulating hormone (TSH) receptors are present in both osteoblasts and osteoclasts and the low TSH levels observed in thyroidectomised patients on L-thyroxine are associated with an increase in OPG and decrease in RANKL and are significantly correlated with vertebral fractures . Bone markers are cleared through the liver or kidneys and are also influenced by diseases affecting these systems, decreased GFR for example will decrease the urinary excretion of CTX and therefore increase serum levels. They are also affected by any disease states leading to increased periods of bed rest and immobility. Research has shown that microgravity induces significant and progressive bone loss, a consequence of increased bone resorption and retardation of bone formation . Certainly levels of all bone markers increase significantly in the first few weeks after fracture and may remain elevated for up to a year. The rate of increase is dependent on the location, severity and size of the fracture and the age of the patient. BTM’s can be elevated for up to 6 months after minor fractures e.g. forearm fractures but up to one year after a hip fracture and needs to be taken into consideration when measuring them [19, 69]. However, they fall gradually over time and using a reduction of 50% in bone resorption when using anti-resorptives as a good indicator of response would be greater than any reduction that might otherwise occur.
In light of the above evidence it can be seen that to use bone turnover to monitor change can be quite difficult. In order to minimise problems it is best to measure the BTMs in as similar a set of circumstances as possible. Particular attention should be paid to the time of day and hence research studies tend to use early morning fasted samples. One way in which to help overcome within person variability in serial measurements and to monitor therapy is to use the ‘least significant change’ (LSC) model . LSC at a significance level of p=<0.05 is defined as 1.96*√2*√ (CV12+CVA2); where CV1 is the within-subject coefficient of variation and CVA is the total analytical imprecision. LSC identifies the true physiological change in the marker. In general a change of more than twenty percent is considered significant for formation markers , similarly between twenty-seven to thirty-six percent is significant for markers of bone resorption .
Over the last decade many of the traditional BTM immunoassays have been automated, improving technical performance and increasing their availability. Nevertheless, analytical aspects such as within and between batch precision, accuracy and standardisation, remain problematic. Inter-laboratory variation is also crucial; a European study in 2001, measuring pooled samples of serum and urine in seventy-three laboratories concluded that even with identical assays results for the majority of the markers were significantly different . Similarly an American study in 2010 comparing six commercial laboratories over an eight month period concluded that reproducibility varied substantially for urine NTX and serum BSAP . Moreover there is an extensive list of bone markers being offered making it very difficult to compare research evidence. Consequently, the International Osteoporosis Foundation (IOF), the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC)  and the National Bone Health Alliance (NBHA) , have recommended that a marker of bone formation and resorption, namely P1NP and CTX, are used as reference analytes in clinical studies. They go on to stipulate that these markers should be measured by standardised assays to minimise immunochemical heterogeneity and recommend that manufacturers adopt international reference standards and minimise batch to batch variability .
Appropriate control of sample collection and preparation is vital for successful BTM measurement. Several BTMs, especially osteocalcin and TRAP5b, are sensitive to thermo degradation and levels can be significantly reduced after only a few hours at room temperature [22, 23]. TRAP5b activity is also reduced during storage, samples must be kept at −70°C or lower and multiple freeze-thaw cycles should be avoided. No significant decrease has been detected in CTX stored at −20°C or lower for up to three years, nevertheless it rapidly decreases in serum at both 4°C and 37°C. The molecular mechanism is unknown but this decrease is minimised by ethylenediaminetetraacetic acid (EDTA) . CTX is reportedly stable in EDTA blood tubes before separation for up to forty-eight hours, likewise osteocalcin becomes stable for up to eight hours at room temperature . Consequently blood should be collected into EDTA tubes and separated as soon as possible, if samples are not analysed immediately they should be stored at −20°C or lower. Both P1NP and BSAP were found to be stable in any sample type . Notably current TRAP5b assays are not affected by haemolysis, but erythrocytes are known to contain proteases which degrade osteocalcin. Grossly haemolysed samples in general should always be avoided.
Clinical usefulness of bone turnover markers in osteoporosis
BTMs are frequently used in clinical trials and provide valuable information on the efficacy of osteoporotic treatments, but their predictive value is limited by their large biological variation and diagnostically they are less often used for individualized patient care. Other routine laboratory investigations are frequently used to identify or exclude secondary causes of osteoporosis such as hyperparathyroidism, vitamin D status, thyrotoxicosis and hypogonadism .
Currently the WHO recommends the use of BMD of the spine and proximal femur measured by DXA as the gold standard to diagnose osteoporosis and its severity . Although BMD has methodological limitations especially in the elderly due in part to degenerative changes in the lumbar spine , BTMs alone would not be suitable to estimate bone loss.
Prediction of bone loss
Women generally lose about one to two percent of their bone per year after the menopause, however thirty percent lose bone at a faster rate . Longitudinal studies of post-menopausal women have demonstrated two characteristic groups; high bone turnover and normal or low bone turnover. Serial BTM measurements are effective in identifying those women who lose bone most rapidly, this is important because this group respond more readily to anti-resorptive medication . Furthermore a meta-analysis of eighty-five studies reported a significant correlation between serial levels of BTMs and BMD measurements during bisphosphonate treatment , the association becomes stronger with advancing age . However, BTMs should only be used to supplement BMD not measured in isolation.
Prediction of fracture risk
BMD is widely used to predict osteoporotic fractures but approximately thirty to fifty percent of patients with fragility fractures have T-scores above the osteoporotic threshold . There is evidence that high bone turnover, as measured by a single or combination of BTMs, is associated with an increased fracture risk , but their use alone to predict fracture has yet to be established. Two clinical risk assessment algorithms have been validated for use in the UK to predict fracture incidence over ten years , namely FRAX and QFracture, currently they do not include all risk factors. BTMs have not been included because of their inconsistency in research studies so far. There is a need for studies confirming whether the addition of BTMs to FRAX would result in increased sensitivity and specificity.
Treatment selection and monitoring
BMD and BTMs are independent predictors of fracture risk, recent evidence does not support the use of BTMs to select the optimal treatment, but BTMs can be used to monitor treatment efficacy before BMD changes can be evaluated. Additionally early changes in BTMs can be used to measure the clinical efficacy of an anti-resorptive treatment and to reinforce patient compliance . The effectiveness of osteoporotic therapy can be assessed by serial BMD measurements usually by DXA, but quantifiable changes in bone mass are small and are only apparent after twelve to twenty-four months, furthermore they only measure net balance in a very small portion of the skeleton. DXA reproducibility is also affected by machine and operator error plus patient variability (weight or degenerative changes) . The minimum acceptable precision for an individual technician is 1.9% (LSC 5.3%) at the lumbar spine and 1.8% (LSC 5.0%) at the total hip. Intervals between measurements depend on the patient’s clinical status, but given the need to exceed the LSC and the relatively modest changes in BMD observed with most treatments it is generally going to be a minimum of two years before a significant change can be observed. Indeed, there are trends for a variety of reasons towards less frequent measurement of BMD to three or even five year intervals .
Meta-regression analysis has found no evidence of a relationship between BMD changes and reduction in risk of fractures among patients receiving calcium with or without vitamin D supplementation. Calcium and/or Vitamin D may reduce fracture rates through a mechanism independent of bone density . BTMs on the other hand show a substantial and more immediate global effect, they measure both bone formation and resorption rate and can classify patients into low or high remodelling groups. Osteoporosis treatments such as bisphosphonates, strontium ranelate, denosumab, hormone replacement therapy (HRT) and selective estrogen receptor moderators (SERMs) act by reducing BTM levels by forty to sixty percent within three to six months . Thus one use of BTMs is to give an early indication of the success of the treatment. Baseline measurements can be repeated at the next follow up appointment say three to six months later. A significant change in BTMs as assessed by the LSC method can then be used to judge success of the treatment and will hopefully be reflected by an increase in BMD in the fullness of time. In the meantime the change in BTM supplies reassurance to the clinician and can be used to encourage the patient. Unfortunately, as BTMs are highly variable this is at best only an indication.
There has been considerable discussion about how long to treat with bisphosphonates, because these drugs accumulate in the skeleton, leading to a reservoir that continues to be released for months or years after treatment has stopped. These medications also result in a low bone turnover state over time with both resorption and formation reduced. This combined with concerns over microfracture, the possibility that they may prevent bone healing and the association with atypical femoral shaft fractures has led to the belief that it may not be wise to continue these medications indefinitely. It is generally accepted that the need to continue bisphosphonates be reviewed after 5 years and kept under review until ten years of treatment. Depending on the individual circumstances a decision to stop treatment, give a drug holiday or change treatment may be made. If a drug holiday is decided upon then BTMs could be checked at regular intervals, e.g. annually. Once these are rising again and especially on return to pre-treatment levels therapy could be restarted. Such an approach may be particularly useful with longer acting agents such as zoledronic acid . The BTMs should be used in conjunction with the clinical circumstances and with repeated BMD after appropriate time intervals.
More recently anabolic agents such as PTH, e.g. teriparatide, have become available which stimulate osteoblastic activity. Markers of bone formation increase early after the initiation of teriparatide therapy with a delayed, but significant, increase in resorption markers . It has been proposed clinically to measure P1NP at baseline and three months post treatment a positive response is defined as a change of greater than 10 μg/L .
During the last decade significant advances have been made in the identification and characterisation of specific BTMs for use in clinical drug trials and to aid in the therapeutic management of osteoporosis. Technological developments have greatly enhanced assay performance producing reliable, rapid, non-invasive cost effective assays with improved sensitivity and specificity. We now have a greater understanding of the need to regulate pre-analytical sample collection to minimise the effects of biological variation. The use of BTMs to select those at risk of fractures is not routinely recommended partly due to their degree of variability. However, baseline measurements of resorption markers are useful before commencement of anti-resorptive treatment e.g. bisphosphonates or denosumab and can be checked 3–6 months later to check response and adherence to treatment. Similarly a formation marker such as P1NP can be used to monitor bone forming agents such as PTH analogues. BTMs may also be useful when monitoring patients during treatment holidays and aid in the decision as to when therapy should be recommenced. The recent recommendations by the Bone Marker Standards Working Group aim to standardise research and include a marker of bone resorption (CTX) and formation (P1NP) in all future studies. They anticipate that manufacturers will calibrate their assays in future using an international reference standard to establish robust reference ranges. It is hoped that improved research in turn will lead to optimise markers for the clinical management of osteoporosis and other bone diseases. The biochemical assessment, utilizing BSAP, is now the mainstay of the diagnosis and management of metabolic bone disease in chronic kidney disease.
Advanced glycation end products
Bone specific alkaline phosphatase
Beta-isomerised carboxy terminal telopeptide of type I collagen
Bone mineral density
Bone turnover marker
Carboxy-terminal cross-linked telopeptides of type 1 collagen
Total analytical imprecision
Within-subject coefficient of variation
Dickkopf-related protein 1
Dentin matrix protein 1
Dual-energy X-ray absorptiometry
Glomerular filtration rate
Type 1 collagen alpha 1 helicoidal peptide
Hormone replacement therapy
Carboxy-terminal cross-linked telopeptide of type 1 collagen
Immuno-Diagnostic Systems Ltd
International Federation of Clinical Chemistry and Laboratory Medicine
Insulin-like growth factor 1
International Osteoporosis Foundation
Low-density lipoprotein receptor-related protein
Least significant change
Matrix extracellular phosphoglycoprotein
Multiple of the median
Multiple of the median formation marker
Multiple of the median resorption marker
National Bone Health Alliance
Amino-terminal cross-linked telopeptide of type 1 collagen
Procollagen type 1 carboxy-terminal propeptide
Procollagen type 1 amino-terminal propeptide
Parathyroid hormone related peptide
Receptor activator of nuclear factor kappa B
Receptor activator of nuclear factor kappa B ligand
Soluble receptor activator of nuclear factor kappa B ligand
Selective estrogen receptor moderators
Tartrate resistant acid phosphatase
Thyroid stimulating hormone
World Health Organisation
Wingless and Integration-1.
The authors wish to thank staff from the Biochemistry laboratory at the James Cook University Hospital in Middlesbrough who made the reference range study possible. In particular we acknowledge Cheryl Goodrum for analysing the samples.
- Datta HK, Ng FW, Walker JA, Tuck SP, Varanasi SS: The cell biology of bone metabolism-a review. J Clin Path. 2008, 61: 577-587. 10.1136/jcp.2007.048868.View ArticlePubMedGoogle Scholar
- Carey JJ, Licata AA, Delaney MF: Biochemical markers of bone turnover. Clin Rev Bone Miner Metab. 2006, 4 (3): 197-212. 10.1385/BMM:4:3:197.View ArticleGoogle Scholar
- Vega D, Maalouf NM, Sakhaee K: The role of receptor activator of nuclear factor-κB (RANK)/RANK Ligand/Osteoprotegerin: clinical implications. J Clin Endocrinol Metab. 2007, 92 (12): 4514-4521. 10.1210/jc.2007-0646.View ArticlePubMedGoogle Scholar
- Leibbrandt A, Penninger JM: RANK/RANKL: regulators of immune responses and bone physiology. Ann N Y Acad Sci. 2008, 1143: 123-150. 10.1196/annals.1443.016.View ArticlePubMedGoogle Scholar
- Klein-Nulend J, Bakker AD, Bacabac RG, Vatsa A, Weinbaum S: Mechanosensation and transduction in osteocytes. Bone. 2013, 54 (2): 182-190. 10.1016/j.bone.2012.10.013.View ArticlePubMedGoogle Scholar
- Kobayashi Y, Maeda K, Takahashi N: Roles of Wnt signalling in bone formation and resorption. Jpn Dent Sci Rev. 2008, 44: 76-82. 10.1016/j.jdsr.2007.11.002.View ArticleGoogle Scholar
- Bellido T, Saini V, Pajevic PD: Effects of PTH on osteocyte function. Bone. 2013, 54 (2): 250-257. 10.1016/j.bone.2012.09.016.PubMed CentralView ArticlePubMedGoogle Scholar
- National osteoporosis society.http://www.nos.org.uk/page.aspx?pid=328,
- Tuck SP, Francis RM: Osteoporosis. Postgrad Med J. 2002, 78: 526-532. 10.1136/pmj.78.923.526.PubMed CentralView ArticlePubMedGoogle Scholar
- Bongartz TA, Scholmerich J, Straub RH: From Osteoporosis in postmenopausal women. Bone disease in rheumatology. Edited by: Maricic M, Gluck OS. 2005, Arizona: Lippincott Williams and Wilkens, 155-156.Google Scholar
- Bauer D, Garnero P, Harison SL, Cauley JA, Eastell R, Ensrud KE, Orwoll E: Biochemical markers on bone turnover, hip loss and fracture in older men: the MrOS study. J Bone Miner Res. 2009, 24 (12): 2032-2038. 10.1359/jbmr.090526.PubMed CentralView ArticlePubMedGoogle Scholar
- Kanis JA, McCloskey EV, Johansson H, Oden A, Melton LJ, Khaltaev N: A reference standard for the description of osteoporosis. Bone. 2008, 42: 467-475. 10.1016/j.bone.2007.11.001.View ArticlePubMedGoogle Scholar
- Rabinda V, Bruyère O, Reginster JY: Relationship between bone mineral density changes and risk of fractures among patients receiving calcium with or without vitamin D supplementation: a meta-regression. Osteoporos Int. 2011, 22: 893-901. 10.1007/s00198-010-1469-x.View ArticleGoogle Scholar
- Seibel MJ: Biochemical markers of bone turnover: part 1: biochemistry and variability. Clin Biochem Rev. 2005, 26: 97-122.PubMed CentralPubMedGoogle Scholar
- Brown JP, Albert C, Nassar BA, Adachi JD, Cole D, Davison KS, Dooley KC, Don-Wauchope A, Douville P, Hanley DA, Jamal SA, Josse R, Kaiser S, Krahn J, Krause R, Kremer R, Lepage R, Letendre E, Morin S, Ooi DS, Papaioaonnou A, Ste-Marie L-G: Bone turnover markers in the management of osteoporosis. Clin Biochem. 2009, 42: 929-942. 10.1016/j.clinbiochem.2009.04.001.View ArticlePubMedGoogle Scholar
- Clowes JA, Hannon RA, Yap TS, Hoyle NR, Blumsohn A, Eastell R: Effect of feeding on bone turnover markers and its impact on biological variability of measurements. Bone. 2002, 30 (6): 886-890. 10.1016/S8756-3282(02)00728-7.View ArticlePubMedGoogle Scholar
- Swaminathan R: Biochemical markers of bone turnover. Clin Chim Acta. 2001, 313: 95-105. 10.1016/S0009-8981(01)00656-8.View ArticlePubMedGoogle Scholar
- Qvist P, Munk M, Hoyle N, Christiansen C: Serum and plasma fragments of C-telopeptides of type I collagen (CTX) are stable during storage at low temperatures for 3 years. Clin Chim Acta. 2004, 350 (1–2): 167-173.View ArticlePubMedGoogle Scholar
- Hannon R, Eastell R: Preanalytical variability of biochemical markers of bone turnover. Osteoporos Int. 2000, 11 (Suppl 6): S30-44.View ArticlePubMedGoogle Scholar
- Vasikaran S, Eastell R, Bruyère O, Foldes AJ, Garnero P, Griesmacher A, McClung M, Morris HA, Silverman S, Trenti T, Wahl DA, Cooper C, Kanis JA, for the IOF-IFCC Bone Marker Standards Working Group: Markers of bone turnover for the prediction of fracture risk and monitoring of osteoporosis treatment: a need for international reference standards. Osteoporos Int. 2011, 22: 391-420. 10.1007/s00198-010-1501-1.View ArticlePubMedGoogle Scholar
- Stokes FJ, Ivanov P, Bailey LM, Fraser WD: The effects of sampling procedures and storage conditions on short-term stability of blood-based biochemical markers of bone metabolism. Clin Chem. 2011, 57 (1): 138-140. 10.1373/clinchem.2010.157289.View ArticlePubMedGoogle Scholar
- Blumsohn A, Hannon RA, Eastell R: Apparent instability of osteocalcin in serum as measured with different commercially available immunoassays. Clin Chem. 1995, 41: 318-319.PubMedGoogle Scholar
- Halleen JM, Alatalo SL, Suominen H, Cheng S, Janckila AJ, Väänänen HK: Tartrate-resistant acid phosphatase 5b: a novel serum marker of bone resorption. J Bone Miner Res. 2000, 15 (7): 1337-1345. 10.1359/jbmr.2000.15.7.1337.View ArticlePubMedGoogle Scholar
- Marin L, Koivula M-K, Jukkola-Vuorinen A, Leino A, Risteli J: Comparison of total and intact aminoterminal propeptide of type 1 procollagen assays in patients with breast cancer with or without bone metastases. Ann Clin Biochem. 2011, 48: 447-451. 10.1258/acb.2011.011040.View ArticlePubMedGoogle Scholar
- Bjarnason NH, Henriksen EEG, Alexandersen P, Christgau S, Henriksen DB, Christiansen C: Mechanism of circadian variation in bone resorption. Bone. 2002, 30: 307-313. 10.1016/S8756-3282(01)00662-7.View ArticlePubMedGoogle Scholar
- Bergmann P, Body JJ, Boonen S, Boutsen Y, Devogelaer JP, Goemaere S, Kaufman JM, Reginster JY, Gangji V, Members of the Advisory Board on Bone Markers: Evidence-based guidelines for the use of biochemical markers of bone turnover in the selection and monitoring of bisphosphonate treatment in osteoporosis: a consensus document of the Belgian bone club. Int J Clin Pract. 2009, 63 (1): 19-26. 10.1111/j.1742-1241.2008.01911.x.PubMed CentralView ArticlePubMedGoogle Scholar
- Wichers M, Schmidt E, Bidlingmaier F, Klingmüller D: Diurnal rhythm of cross laps in human serum. Clin Chem. 1999, 45: 1858-1860.PubMedGoogle Scholar
- Garnero P, Sornay-Rendu E, Claustrat B, Delmas PD: Biochemical markers of bone turnover, endogenous hormones and the risk of fractures in postmenopausal women: the OFELY study. J Bone Miner Res. 2000, 15: 1526-1536. 10.1359/jbmr.2000.15.8.1526.View ArticlePubMedGoogle Scholar
- Rogers RS, Dawson AW, Wang Z, Thyfault JP, Hinton PS: Acute response of plasma markers of bone turnover to a single bout of resistance training or plyometrics. J Appl Physiol. 2011, 111: 1353-1360. 10.1152/japplphysiol.00333.2011.View ArticlePubMedGoogle Scholar
- Bowsher RR, Sailstad JM: Insights in the application of research-grade diagnostic kits for biomarker assessments in support of clinical drug development: Bioanalysis of circulating concentrations of soluble receptor activator of nuclear factor κB ligand. J Pharm Biomed Anal. 2008, 48 (5): 1282-1289. 10.1016/j.jpba.2008.09.026.View ArticlePubMedGoogle Scholar
- Kearns AE, Khosla S, Kostenuik PJ: Receptor activator of nuclear factor κB ligand and osteoprotegerin regulation of bone remodelling in health and disease. Endocr Rev. 2008, 29 (2): 155-192.PubMed CentralView ArticlePubMedGoogle Scholar
- Nicholls JJ, Brassill MJ, Williams GR, Duncan Bassett JH: The skeletal consequences of thyrotoxicosis. J Endocrinol. 2012, 213 (3): 209-221. 10.1530/JOE-12-0059.View ArticlePubMedGoogle Scholar
- Drake MT, Srinivasan B, Mödder UI, Peterson JM, McCready LK, Riggs BL, Dwyer D, Stolina M, Kostenuik P, Khosla S: Effects of parathyroid hormone treatment on circulating sclerostin levels in postmenopausal women. J Clin Endocrinol Metab. 2010, 95 (11): 5056-5062. 10.1210/jc.2010-0720.PubMed CentralView ArticlePubMedGoogle Scholar
- Gaudio A, Pennisi P, Bratengeier C, Torrisi V, Lindner B, Mangiafico RA, Pulvirenti I, Hawa G, Tringali G, Fiore CE: Increased sclerostin serum levels associated with bone formation and resorption markers in patients with immobilization-induced bone loss. J Clin Endocrinol Metab. 2010, 95 (5): 2248-2253. 10.1210/jc.2010-0067.View ArticlePubMedGoogle Scholar
- Gennari L, Merlotti D, Valenti R, Ceccarelli E, Ruvio M, Pietrini MG, Capodarca C, Franci MB, Campagna MS, Calabrò A, Cataldo D, Stolakis K, Dotta F, Nuti R: Circulating sclerostin levels and bone turnover in type 1 and type 2 diabetes. J Clin Endocrinol Metab. 2012, 97 (5): 1737-1744. 10.1210/jc.2011-2958.View ArticlePubMedGoogle Scholar
- Garcia-Martin A, Rozas-Moreno P, Reyes-Garcia R, Morales-Santana S, Garcia-Fontana B, Garcia-salcedo JA, Muñoz-Torres M: Circulating levels of sclerostin are increased in patients with type 2 diabetes mellitus. J Clin Endocrinol Metab. 2012, 97 (1): 234-241. 10.1210/jc.2011-2186.View ArticlePubMedGoogle Scholar
- Melkko J, Hellevik T, Risteli L, Risteli J, Smedsrød S: Clearance of NH2-terminal propeptides of types I and III Procollagen is a physiological function of the scavenger receptor in liver endothelial cells. J Exp Med. 1994, 179: 405-412. 10.1084/jem.179.2.405.View ArticlePubMedGoogle Scholar
- Brandt J, Krogh TN, Jensen CH, Frederiksen JK, Teisner B: Thermal instability of the trimeric structure of the N-terminal propeptide of human Procollagen type I in relation to assay technology. Clin Chem. 1999, 45 (1): 47-53.PubMedGoogle Scholar
- Baxter I, Rogers A, Eastell R, Peel N: Evaluation of urinary N-telopeptide of type I collagen measurements in the management of osteoporosis in clinical practice. Osteoporos Int. 2013, 24: 941-947. 10.1007/s00198-012-2097-4.View ArticlePubMedGoogle Scholar
- Jabbar S, Drury J, Fordham JN, Datta HK, Francis RM, Tuck SP: Osteoprotegerin, RANKL and bone turnover in postmenopausal osteoporosis. J Clin Pathol. 2011, 64: 354-357. 10.1136/jcp.2010.086595.View ArticlePubMedGoogle Scholar
- Liu JM, Zhao HY, Ning G, Zhao YJ, Chen Y, Zhang Z, Sun LH, Xu M-Y, Chen JL: Relationships between the changes of serum levels of OPG and RANKL with age, menopause, bone biochemical markers and bone mineral density in Chinese women aged 20–75. Calcif Tissue Int. 2005, 76 (1): 1-6. 10.1007/s00223-004-0007-2.View ArticlePubMedGoogle Scholar
- Noble BS: The osteocyte lineage. Arch Biochem Biophys. 2008, 473 (2): 106-11. 10.1016/j.abb.2008.04.009.View ArticlePubMedGoogle Scholar
- Bonewald LF: Osteocytes: a proposed multifunctional bone cell. J Musculoskelet Neuronal Interact. 2002, 2 (3): 239-41.PubMedGoogle Scholar
- Zhang Y, Wang Y, Li X, Zhang J, Mao J, Li Z, Zhang J, Li L, Harris S, Wu D: The LRP5 high-bone-mass G171V mutation disrupts LRP5 interaction with Mesd. Mol Cell Biol. 2004, 24 (11): 4677-4684. 10.1128/MCB.24.11.4677-4684.2004.PubMed CentralView ArticlePubMedGoogle Scholar
- Li X, Zhang Y, Kang H, Liu W, Liu P, Zhang J, Harris SE, Wu D: Sclerostin binds to LRP5/6 and antagonizes canonical Wnt signalling. J Biol Chem. 2005, 280: 19883-19887. 10.1074/jbc.M413274200.View ArticlePubMedGoogle Scholar
- You L, Temiyasathit S, Lee P, Kim CH, Tummala P, Yao W, Kingery W, Malone AM, Kwon RY, Jacobs CR: Osteocytes as mechanosensors in the inhibition of bone resorption due to mechanical loading. Bone. 2008, 42 (1): 172-179. 10.1016/j.bone.2007.09.047.PubMed CentralView ArticlePubMedGoogle Scholar
- Gross TS, King KA, Rabaia NA, Pathare P, Srinivasan S: Upregulation of osteopontin by osteocytes deprived of mechanical loading or oxygen. J Bone Miner Res. 2005, 20 (2): 250-256.PubMed CentralView ArticlePubMedGoogle Scholar
- Noble BS, Peet N, Stevens HY, Brabbs A, Mosley JR, Reilly GC, Reave J, Skerry TM, Lanyon LE: Mechanical loading: biphasic osteocyte survival and targeting of osteoclasts for bone destruction in rat cortical bone. Am J Physiol Cell Physiol. 2003, 284: C934-C943. 10.1152/ajpcell.00234.2002.View ArticlePubMedGoogle Scholar
- Amrein K, Amrein S, Drexler C, Dimai HP, Dobnig H, Pfeifer K, Tomaschitz A, Pieber TR, Fahrleitner-Pammer A: Sclerostin and its association with physical activity, age, gender, body composition and bone mineral content in healthy adults. J Clin Endocrinol Metab. 2012, 97 (1): 148-154. 10.1210/jc.2011-2152.View ArticlePubMedGoogle Scholar
- Lin C, Jiang X, Dai Z, Guo X, Weng T, Wang J, Li Y, Feng G, Gao X, He L: Sclerostin mediates bone response to mechanical unloading through antagonizing Wnt/β-Catenin signalling. J Bone Miner Res. 2009, 24 (10): 1651-1661. 10.1359/jbmr.090411.View ArticlePubMedGoogle Scholar
- Morse LR, Sudhakar S, Lazzari AA, Tun C, Garshick E, Zafonte R, Battaglino RA: Sclerostin: a candidate biomarker of SCI-induced osteoporosis. Osteoporos Int. 2013, 24: 961-968. 10.1007/s00198-012-2072-0.PubMed CentralView ArticlePubMedGoogle Scholar
- Arasu A, Cawthon PM, Lui L-Y, Do TP, Arora PS, Cauley JA, Ensrud KE, Cummings SR: Serum sclerostin and risk of hip fracture in older Caucasian women. J Clin Endocrinol Metab. 2012, 97 (6): 2027-2032. 10.1210/jc.2011-3419.PubMed CentralView ArticlePubMedGoogle Scholar
- Mirza FS, Padhi ID, Raisz LG, Lorenzo JA: Serum sclerostin levels negatively correlate with parathyroid hormone levels and free estrogen index in postmenopausal women. J Clin Endocrinol Metab. 2010, 95 (4): 1991-1997. 10.1210/jc.2009-2283.PubMed CentralView ArticlePubMedGoogle Scholar
- Polyzos SA, Anastasilakis AD, Bratengeier C, Woloszczuk W, Papatheodorou A, Terpos E: Serum sclerostin levels positively correlate with lumbar spinal bone mineral density in postmenopausal women – the six-month effect of risedronate and teriparatide. Osteoporos Int. 2012, 23: 1171-1176. 10.1007/s00198-010-1525-6.View ArticlePubMedGoogle Scholar
- McNulty M, Singh RJ, Li X, Bergstralh EJ, Kumar R: Determination of serum and plasma sclerostin concentrations by enzyme-linked immunoassays. J Clin Endocrinol Metab. 2011, 96 (7): E1159-E1162. 10.1210/jc.2011-0254.PubMed CentralView ArticlePubMedGoogle Scholar
- Blumsohn A, Naylor KE, Timm W, Eagleton AC, Hannon RA, Eastell R: Absence of marked seasonal change in bone turnover: a longitudinal and multicentre cross-sectional study. J Bone Miner Res. 2003, 18: 1274-1281. 10.1359/jbmr.2003.18.7.1274.View ArticlePubMedGoogle Scholar
- Woitge HW, Scheidt-Nave C, Kissling C, Leidig-Bruckner G, Meyer K, Grauer A, Scharla SH, Ziegler R, Seibel MJ: Seasonal variation of biochemical indices of bone turnover: results of a population-based study. J Clin Endocrinol Metab. 1998, 83: 68-75. 10.1210/jc.83.1.68.PubMedGoogle Scholar
- Nielsen HK, Brixen K, Bouillon R, Mosekilde L: Changes in biochemical markers of osteoblastic activity during the menstrual cycle. J Clin Endocrinol Metab. 1990, 70: 1431-1437. 10.1210/jcem-70-5-1431.View ArticlePubMedGoogle Scholar
- Chiu KM, Ju J, Mayes D, Bacchetti P, Weitz S, Arnaud CD: Changes in bone resorption during the menstrual cycle. J Bone Miner Res. 1999, 14 (4): 609-615. 10.1359/jbmr.1922.214.171.1249.View ArticlePubMedGoogle Scholar
- Black AJ, Topping J, Durham B, Farquharson RG, Fraser WD: A detailed assessment of alterations in bone turnover, calcium homeostasis, and bone density in normal pregnancy. J Bone Miner Res. 2000, 15 (3): 557-563.View ArticlePubMedGoogle Scholar
- Dorota D-K, Bogdan KG, Mieczyslaw G, Bozena L-G, Jan O: The concentrations of markers of bone turnover in normal pregnancy and pre-eclampsia. Hypertens Pregnancy. 2012, 31: 166-176. 10.3109/10641955.2010.484084.View ArticlePubMedGoogle Scholar
- Naylor KE, Iqbal P, Fledelius C, Fraser RB, Eastell R: The effect of pregnancy on bone density and turnover. J Bone Miner Res. 2000, 15: 129-137. 10.1359/jbmr.2000.15.1.129.View ArticlePubMedGoogle Scholar
- Hannon R, Blumsohn A, Naylor K, Eastell R: Response of biochemical markers of bone turnover to hormone replacement therapy: impact of biological variability. J Bone Miner Res. 1998, 13 (7): 1124-33. 10.1359/jbmr.19126.96.36.1994.View ArticlePubMedGoogle Scholar
- van Staa TP, Leufkens HG, Cooper C: The epidemiology of corticosteroid-induced osteoporosis: a meta-analysis. Osteoporos Int. 2002, 13: 777-787. 10.1007/s001980200108.View ArticlePubMedGoogle Scholar
- Schett G: Osteoimmunology in rheumatic diseases. Arthritis Res Ther. 2009, 11 (1): 210-10.1186/ar2571.PubMed CentralView ArticlePubMedGoogle Scholar
- Wheater G, Hogan VE, Teng YKO, Tekstra J, Tuck SP, Lafeber FP, Huizinga TWJ, Bijlsma JWJ, Francis RM, Datta HK, van Laar JM: Suppression of bone turnover by B-cell depletion in patients with rheumatoid arthritis. Osteoporos Int. 2011, 12: 3067-3072.View ArticleGoogle Scholar
- Yamaguchi T, Sugimoto T: Bone metabolism and fracture risk in type 2 diabetes mellitus. Endocr J. 2011, 58 (8): 613-624. 10.1507/endocrj.EJ11-0063.View ArticlePubMedGoogle Scholar
- Inque M, Tanaka H, Moriwake T, Oka M, Sekiguchi C, Seino Y: Altered biochemical markers of bone turnover in humans during 120 days of bed rest. Bone. 2000, 26 (3): 281-286. 10.1016/S8756-3282(99)00282-3.View ArticleGoogle Scholar
- Veitch SW, Findlay SC, Hamer AJ, Blumsohn A, Eastell R, Ingle BM: Changes in bone mass and bone turnover following tibial shaft fracture. Osteoporos Int. 2006, 17: 364-372. 10.1007/s00198-005-2025-y.View ArticlePubMedGoogle Scholar
- Vesper H, Cosman F, Endres DB, Garnero P, Hoyle NR, Kleerekoper MK, Mallinak NJS: Application of biochemical markers of bone turnover in the assessment and monitoring of bone diseases; approved guideline. NCCLS document. 2004, 24 (22): 1-37.Google Scholar
- Garnero P, Vergnaud P, Hoyle N: Evaluation of a fully automated serum assay for total N-terminal propeptide of type I collagen in postmenopausal osteoporosis. Clin Chem. 2008, 54 (1): 188-196.View ArticlePubMedGoogle Scholar
- Chubb SAP: Measurement of C-terminal telopeptide of type I collagen (CTX) in serum. Clin Biochem. 2012, 45 (12): 928-935. 10.1016/j.clinbiochem.2012.03.035.View ArticlePubMedGoogle Scholar
- Mora S, Pitukcheewanont P, Kaufman FR, Nelson JC, Gilsanz V: Biochemical markers of bone turnover and the volume and the density of bone in children at different stages of sexual development. J Bone Miner Res. 1999, 14: 1664-1671. 10.1359/jbmr.19188.8.131.524.View ArticlePubMedGoogle Scholar
- Eastell R, Garnero P, Audebert C, Cahall DL: Reference intervals of bone turnover markers in healthy premenopausal women: results from a cross-sectional European study. Bone. 2012, 50 (5): 1141-1147. 10.1016/j.bone.2012.02.003.View ArticlePubMedGoogle Scholar
- Bieglmayer C, Kudlacek S: The bone marker plot: an innovative method to assess bone turnover in women. Eur J Clin Invest. 2009, 39: 230-238. 10.1111/j.1365-2362.2009.02087.x.View ArticlePubMedGoogle Scholar
- Seibel MJ, Lang M, Geilenkeuser W-J: Interlaboratory variation of biochemical markers of bone turnover. Clin Chem. 2001, 47 (8): 1443-1450.PubMedGoogle Scholar
- Schafer AL, Vittinghoff E, Ramachandran R, Mahmoudi N, Bauer DC: Laboratory reproducibility of biochemical markers of bone turnover in clinical practice. Osteoporos Int. 2010, 21: 439-445. 10.1007/s00198-009-0974-2.PubMed CentralView ArticlePubMedGoogle Scholar
- Bauer D, Krege J, Lane N, Leary E, Libanati C, Miller P, Myers G, Silverman S, Vesper HW, Lee D, Payette M, Randall S: National bone health alliance bone turnover marker project: current practices and the need for US harmonization, standardization, and common reference ranges. Osteoporos Int. 2012, 23: 2425-2433. 10.1007/s00198-012-2049-z.PubMed CentralView ArticlePubMedGoogle Scholar
- Lee J, Vasikaran S: Current recommendations for laboratory testing and use of bone turnover markers in management of osteoporosis. Ann Lab Med. 2012, 32: 105-112. 10.3343/alm.2012.32.2.105.PubMed CentralView ArticlePubMedGoogle Scholar
- Steiger P, Cummings SR, Black DM, Spencer NE, Genant HK: Age related decrements in bone mineral density in women over 65. J Bone Miner Res. 1992, 7: 625-632.View ArticlePubMedGoogle Scholar
- Ross PD, Knowlton W: Rapid bone loss is associated with increased levels of biochemical markers. J Bone Miner Res. 1998, 13 (2): 297-302. 10.1359/jbmr.19184.108.40.2067.View ArticlePubMedGoogle Scholar
- Crane M, Davis T, Kaldale R, Black C, Davies R, Devas V, Williams W: Relating increases in bone mineral density and fracture risk reduction with early suppression in biomarkers of bone turnover: a literature-based meta-analysis of bisphosphonates treatments. J Bone Miner Res. 2005, 20 (Suppl 1): S95-Google Scholar
- Delmas PD, Eastell R, Garnero P, Seibel MJ, Stepan J: The use of biochemical markers of bone turnover in osteoporosis. Committee of Scientific Advisors of the International Osteoporosis Foundation. Osteoporos Int. 2000, 11 (Suppl 6): S2-S17.PubMedGoogle Scholar
- Schuit SC, van der Klift M, Weel AE, de Laet CE, Burger H, Seeman E, Hofman A, Uitterlinden AG, van Leeuwen JP, Pols HA: Fracture incidence and association with bone mineral density in elderly men and women: The rotterdam study. Bone. 2004, 34: 195-202. 10.1016/j.bone.2003.10.001.View ArticlePubMedGoogle Scholar
- Osteoporosis: assessing the risk of fragility fracture: NICE Clinical Guideline 146 (August 2012).http://www.nice.org.uk/nicemedia/live/13857/60399/60399.pdf,
- Blank RD, Malone DG, Christian RC, Vallarta-Ast NL, Krueger DC, Drezner MK, Binkley NC, Hansen KE: Patient variables impact lumbar spine dual energy x-ray absorptiometry precision. Osteoporos Int. 2006, 17: 768-774. 10.1007/s00198-005-0050-5.View ArticlePubMedGoogle Scholar
- The international society for clinical densitometry official position. 2007,http://www.iscd.org/official-positions/4th-iscd-position-development-conference-adult/,
- Jordan N, Barry M, Murphy E: Comparative effects of antiresorptive agents on bone mineral density and bone turnover in postmenopausal women. Clin Interv Aging. 2006, 1 (4): 377-387. 10.2147/ciia.2006.1.4.377.PubMed CentralView ArticlePubMedGoogle Scholar
- Watts NB, Diab DL: Long-term use of bispohosphonates in osteoporosis. J Clin Endocrinol Metab. 2010, 95 (4): 1555-1565. 10.1210/jc.2009-1947.View ArticlePubMedGoogle Scholar
- Finkelstein JS, Wyland JJ, Lee H, Neer RM: Effects of teriparatide, alendronate, or both in women with postmenopausal osteoporosis. J Clin Endocrinol Metab. 2010, 95 (4): 1838-1845. 10.1210/jc.2009-1703.PubMed CentralView ArticlePubMedGoogle Scholar
- Meier C, Seibel MJ, Kraenzlin ME: From Biochemical markers of bone turnover – clinical aspects. Contemporary Endocrinology: Osteoporosis: Pathophysiology and Clinical Management. Edited by: Adler RA. 2010, 131-155. Humana PressGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.