Introduction
Osteoporosis is a devastating disease resulting in substantial health care costs and increased mortality. In Europe, osteoporotic fractures affect one in two women and one in five men aged 50 years and older [
1]. In Europe, total health care costs associated with these fractures have been estimated to be around €30 billion [
1]. In 2000, an estimated 5.8 million disability-adjusted life years were caused by osteoporotic fractures worldwide [
2]. Among patients who have sustained a hip fracture, one in five will die within the first year after the fracture, whilst one in three of those surviving needs assistance with walking [
3,
4]. Because of this huge burden, assessment of an individual's risk of fracture is important so that a prophylactic intervention can be effectively targeted.
As of July 1, 2010, the FRAX® tool has been calibrated to the total Dutch population (
http://www.sheffield.ac.uk/FRAX). FRAX uses easily obtainable clinical risk factors, with or without femoral neck bone mineral density (BMD), to estimate 10-year fracture probability [
5]. It has been constructed using primary data from nine population-based cohorts around the world. The gradients of fracture risk have been validated externally in 11 independent cohorts with a similar geographic distribution [
6]. FRAX is a platform technology using Poisson models that integrate risk variables, fracture risk, and death risk over a 10-year interval. Using the incidence rates of hip and osteoporotic fractures and mortality rates, FRAX can be calibrated to create a country-specific model [
7]. With the introduction of the online Dutch FRAX tool, it is important to understand the origin of the data for further validation if needed. Furthermore, the possibilities of the Dutch FRAX tool and its strengths/limitations compared to other Dutch models need to be discussed. The objective of this paper is to describe the data used to develop the current Dutch FRAX model.
Results
Table
1 shows 1-year age- and gender-stratified incidence rates of hip fracture for the Netherlands (2004 and 2005), as well as the incidence of osteoporotic fractures, based on the Malmö transformation. Hip fracture incidence was lowest in patients aged 50–54 years old (per 10,000 inhabitants: 2.3 for men and 2.1 for women) and highest among the oldest subjects (95–99 years) (169.0 of 10,000 and 267.3 of 10,000 for men and women, respectively). With increasing age, there was a rise in proportion of all fractures primarily accounted for by hip fractures, with the highest proportion in the oldest patients (among osteoporotic fractures, 57.1% were hip fractures in males, 56.3% in females).
Table 1
Dutch age- and gender-stratified 1-year incidence rates of hip fracture (true data; 2004/2005) and (imputed) osteoporotic fracture (imputed using Swedish data) per 10,000 inhabitants in 2004/2005 as modeled in FRAX
50–54 | 2.3 | 2.1 | 16.8 | 23.3 |
55–59 | 3.0 | 4.2 | 17.1 | 33.0 |
60–64 | 4.6 | 8.1 | 17.5 | 46.5 |
65–69 | 8.9 | 15.3 | 28.3 | 68.1 |
70–74 | 16.9 | 28.6 | 45.9 | 99.8 |
75–79 | 32.3 | 53.6 | 74.4 | 146.2 |
80–84 | 61.6 | 100.5 | 120.5 | 214.1 |
85–89 | 117.6 | 188.2 | 195.4 | 313.6 |
90–94 | 141.0 | 224.3 | 240.4 | 385.9 |
95–99 | 169.0 | 267.3 | 295.8 | 474.9 |
Age- and gender-stratified mortality rates for the total Dutch population are shown in Table
2. Mortality rates increased with higher ages, with rates of 4,245 per 10,000 male inhabitants and 3,532 per 10,000 female residents in the oldest age category (≥95 years).
Table 2
Dutch age- and gender-stratified mortality rates (per 10,000 inhabitants) in 2005
50–54 | 41.0 | 31.1 |
55–59 | 65.1 | 46.5 |
60–64 | 113.7 | 69.4 |
65–69 | 190.9 | 103.1 |
70–74 | 330.6 | 181.5 |
75–79 | 584.7 | 328.2 |
80–84 | 1,005.2 | 607.6 |
85–89 | 1,710.1 | 1,193.8 |
90–94 | 2,690.0 | 2,085.7 |
≥95 | 4,245.0 | 3,532.0 |
In Table
3, 10-year probabilities of osteoporotic fractures are shown for Dutch men and women per age and gender category in the absence or presence of at least a single clinical risk factor (each row), without entering information on BMD, keeping BMI constant at 25 kg/m
2. Parental history of hip fracture was the strongest clinical risk factor in the elderly: a 90-year-old woman with a BMI of 25 kg/m
2, and a parental hip fracture as single clinical risk factor, had a 26% 10-year probability of osteoporotic fracture (20% for hip fracture), whilst the risk was only 13% for a female of equal age and BMI without a parental hip fracture. When compared to a male patient with the same clinical risk factors, the 10-year probability of fracture was halved (13% for osteoporotic fracture, 11% for hip fracture). In younger age categories, much smaller differences between the two genders were observed: the 10-year probability of osteoporotic fracture was 3.7% in a 50-year-old female with a BMI of 25 kg/m
2 and a parental hip fracture as single clinical risk factor (0.2% for hip fracture), as compared to 3.0% in a 50-year-old male with comparable clinical risk factors (0.1% for hip fracture).
Table 3
Age- and gender-stratified 10-year probabilities (percent) of osteoporotic fracture in absence or presence of at least a single clinical risk factor, without information on BMD
Clinical risk factor | 50 | 60 | 70 | 80 | 90 | 50 | 60 | 70 | 80 | 90 |
No risk factor | 1.5 | 2.3 | 3.6 | 5.5 | 5.5 | 1.8 | 3.4 | 6.9 | 12 | 13 |
Previous fracture | 3.2 | 4.7 | 7.0 | 9.0 | 8.8 | 4.1 | 7.1 | 13 | 20 | 21 |
Parental hip fracture | 3.0 | 4.4 | 6.0 | 12 | 13 | 3.7 | 6.6 | 11 | 24 | 26 |
Current smoking | 1.6 | 2.4 | 3.9 | 6.0 | 5.8 | 2.0 | 3.7 | 7.7 | 14 | 14 |
Glucocorticoid usea
| 2.4 | 3.7 | 5.7 | 8.1 | 7.7 | 3.1 | 5.7 | 11 | 20 | 19 |
Rheumatoid arthritis | 2.0 | 3.1 | 5.2 | 8.3 | 8.5 | 2.5 | 4.8 | 9.8 | 18 | 19 |
Secondary osteoporosisb
| 2.0 | 3.1 | 5.2 | 8.3 | 8.5 | 2.5 | 4.8 | 9.8 | 18 | 19 |
Alcohol usec
| 1.8 | 2.8 | 4.6 | 7.3 | 7.5 | 2.2 | 4.2 | 8.7 | 16 | 17 |
Tables
4 and
5 show the effect of BMD on the 10-year probabilities of osteoporotic and hip fracture in men and women aged 60 years old (Table
4) and aged 80 years old (Table
5) with a BMI of 25 kg/m
2, rheumatoid arthritis, and a parental history of hip fracture. Fracture risk increased with decreasing T-score. When BMD was entered into the model, the difference in probabilities between men and women became less marked than without BMD. There was also a large range of probabilities noted as a function of the T-score. Thus, probability was markedly underestimated in individuals with low T-scores (for elderly patients, i.e., 80 years old, only at T-scores below −2 SD), when information on BMD was not used in the model.
Table 4
BMD- and gender-stratified 10-year probabilities of osteoporotic and hip fracture for a 60-year-old patient with a BMI of 25 kg/m2, rheumatoid arthritis, and a parental history of hip fracture
Not taken into account | 5.9 | 0.8 | 8.9 | 1.3 |
1 | 4.5 | 0.1 | 6.1 | 0.1 |
0 | 5.2 | 0.3 | 6.9 | 0.2 |
−1 | 6.6 | 0.7 | 8.1 | 0.5 |
−2 | 9.5 | 2.2 | 11 | 1.6 |
−3 | 15 | 6.5 | 17 | 5.0 |
−4 | 28 | 18 | 29 | 15 |
Table 5
BMD- and gender-stratified 10-year probabilities of osteoporotic and hip fracture for an 80-year-old patient with a BMI of 25 kg/m2, rheumatoid arthritis, and a parental history of hip fracture
Not taken into account | 19 | 16 | 36 | 29 |
1 | 5.6 | 3.1 | 7.1 | 2.3 |
0 | 8.2 | 5.4 | 11 | 4.9 |
−1 | 12 | 9.2 | 17 | 10 |
−2 | 19 | 16 | 27 | 20 |
−3 | 30 | 26 | 45 | 38 |
−4 | 43 | 40 | 67 | 62 |
Table
6 shows that Northern European countries (including the Netherlands) yielded the highest lifetime probabilities for hip fracture (with the highest rate seen in Sweden) in individuals from the age of 50 years. In contrast, much lower incidence rates were recorded in China, Mexico, and Mediterranean countries.
Table 6
Lifetime probability of hip fracture in males and females from the age of 50 years
China | 1.9 | 2.4 |
Mexico | 3.8 | 8.5 |
China (Hong Kong) | 4.1 | 8.8 |
Portugal | 3.6 | 10.1 |
Spain | 4.2 | 12.0 |
France | 3.6 | 12.7 |
UK | 4.8 | 14.0 |
Turkey | 3.5 | 14.6 |
USA | 6.0 | 15.8 |
Netherlands (present study) | 5.2 | 17.3 |
Sweden | 13.1 | 28.5 |
Discussion
In this paper, we describe the FRAX® model developed for the Netherlands, which can be used to assess individual 10-year probabilities of hip fracture, as well as any osteoporotic fracture in Dutch patients. It has been calibrated to the total Dutch population, based on nationwide incidence rates for hip fracture and mortality. The model became available in July 2010 at the FRAX® website (
http://www.sheffield.ac.uk/FRAX).
Previous clinical risk scores in Holland have been developed in cohorts that were representative for only a small Dutch region, and these risk scores have not been validated externally. Pluijm et al. proposed a clinical risk score to estimate fracture risk in Dutch women, using information from two different Dutch cohort studies [
26]. Although the risk score is simple to use, there are some limitations to the model. The cohorts included patients from small regions and may therefore not be representative of the country. Although one of the two models included multiple cities throughout the country, the majority of fracture cases originated from a specific area in the city of Rotterdam, which is not comparable to patients from the general population [
26]. Furthermore, men had not been included in these cohorts, limiting the use of the risk score to women only. Finally, there may have been substantial under-recording of several risk factors for fracture (such as rheumatoid arthritis, smoking, alcohol intake, and oral glucocorticoid use) in these GP-based cohorts. Compared to pharmacy dispensing data (representative sample of the total Dutch population, with a similar age), the prevalence of oral glucocorticoid use was found to be 1.5–2.2-fold lower in these GP-based registries (2%) [
16]. More recently, van Geel et al. developed a fracture risk model in a cohort comprising postmenopausal women, inhabitants of the southern part of the Netherlands [
27]. This clinical risk score is the simplest to use, as it only includes three risk factors in the final model. A major strength, compared to the other Dutch fracture models, is the consideration of the time window in which a prior fracture could have occurred. Like the model described by Pluijm et al., the van Geel model also is limited to women only and may not be representative for the entire country. A third model, introduced by the Dutch Institute for Healthcare Improvement (CBO), aims to identify high-risk patients for fracture by calculating a fracture risk score based on weighted widely recognized risk factors [
28]. However, in contrast to the other Dutch fracture models, these weights are based on expert opinion and have not been developed and validated in clinical studies using Dutch patients' data. Therefore, these estimated weights may not reflect real-life weights. This CBO model is currently used in the national Dutch guidelines for fracture prevention [
28]. The use of FRAX in these guidelines is limited: FRAX risk assessment is only recommended in patients with multiple clinical risk factors (CBO score ≥4), and a T-score between −2.0 SD and −2.5 SD, but without evidence of a recent fracture.
The importance of calibrating FRAX to an individual country is illustrated by the marked differences in lifetime risks of hip fracture in 50-year-old males and females between countries worldwide. In line with previous reports, we found much higher incidences for hip fracture in European countries (including the Netherlands), as compared to those in countries like China, Mexico, and those in the Mediterranean area [
29‐
31]. Possible explanations for this decreased incidence rate in the latter countries as compared to the Netherlands include lower life expectancy, in particular in Latin America (as most hip fractures occur after the age of 65 years) [
30], variations in reversible lifestyle factors, and genetics [
32,
33]. High prevalence rates in Scandinavian countries (including Sweden) may to some degree be explained by icy condition in the winter [
34] and high smoking frequency/alcohol intake (in particular in Denmark) [
35].
The use of FRAX as a clinical tool demands a consideration of intervention thresholds. These thresholds, determined by fracture probability, should be recommended based on clinical imperatives and validated by the cost-effectiveness of a possible FRAX-based strategy. In the UK, the National Osteoporosis Guideline Group has described management algorithms that are based on FRAX [
36]. These guidelines describe fracture risk thresholds at which BMD assessment or osteoporosis treatment should be carried out. In a post hoc analysis, they demonstrated cost-effectiveness of this strategy, based on a willingness to pay (WTP) threshold set at £20,000 for each quality-adjusted life year gained [
37]. However, these intervention thresholds may not apply to the Netherlands, since the cost of osteoporosis and BMD measurement, and the WTP in the Netherlands, may differ from those in the UK. In addition, the willingness to trade-off risks for benefits of fracture prevention may vary among individual patients. Using FRAX, both the clinician and the patient can discuss fracture probability and weigh the risks and benefits of starting fracture prevention (although Dutch cost-effectiveness studies need to be conducted to determine clear intervention thresholds).
As of 2010, it remains unclear whether the implementation of FRAX screening indeed would lead to reduced fracture rates, compared to conventional patient management, though a substantial body of indirect evidence suggests that FRAX identifies individuals who respond to pharmacotherapy [
38]. In order to assess the clinical usefulness of FRAX screening, the “Screening of Older Women for Prevention of Fracture” trial is currently being conducted [
39]. In this British trial, effectiveness (reduction of fracture incidence) and cost-effectiveness of FRAX screening in women aged 70–85 years are being evaluated. In the Netherlands, the Salt Osteoporosis Study is currently being carried out to assess the 3-year efficacy of FRAX-based screening in women aged 65 years or more with at least one clinical risk factor for fracture [
40]. The randomized clinical trial will compare the fracture incidence in patients who have been screened for high fracture risk using FRAX® (and have received treatment options based on this) with the fracture incidence of patients who received care based on current Dutch guidelines.
The major strength of FRAX® is that it has been developed in nine different cohorts and has been externally validated in 14 studies comprising of several million individuals [
6,
41‐
43]. In addition, higher predictive validity for fracture outcome is obtained by combining both data on clinical risk factors and BMD levels. A meta-analysis showed that the combination of clinical risk factors and BMD provides higher specificity and sensitivity than either alone [
6]. Current models are limited to either the use of clinical risk factors or BMD alone, possibly diminishing their predictive validity [
6,
26,
27]. A third strength is the use of a continuous scale for age and body weight, as fracture risk increases even above the fixed age and body weight thresholds used by many other models [
44,
45]. Furthermore, in contrast to the current local Dutch models, the Dutch FRAX tool has been calibrated to the total Dutch population, using nationwide incidence rates for hip fracture and mortality rates.
A limitation of the Dutch FRAX® is that, as of 2010, the tool has not been prospectively validated in the Netherlands (i.e., the predictive value of FRAX in the Netherlands). Notwithstanding, the model is constructed using national rather than regional information on hip fracture and death rates. An additional limitation is that the incidence rates of hip fracture were derived from the year 2004/2005 and were therefore not completely up to date. Unfortunately, Dutch national hip fracture data are no longer reliable after 2005. Due to a change in law, Dutch hospitals are no longer required to record their hospitalization rates by ICD9 code and send them to the national registry [
9]. In order to overcome this limitation, a future study has been designed, in which hip fracture rates will be updated by linkage of various Dutch epidemiological registries.
A third limitation of FRAX in general is that it makes no use of several other important clinical risk factors for fracture (such as previous vertebral fractures, a history of falls, vitamin D deficiency, and use of psychotropic drugs) [
10,
11,
18,
46,
47]. Although the model does take prior fractures into account, the number and recency of these fractures have not been included as predictors in the model, because of the lack of data available in the construct cohorts [
19], but they probably are important. For instance, a Dutch retrospective cohort study showed that the incidence of new clinical fractures was higher among patients who had sustained multiple baseline fractures, when compared to those who had sustained only a single fracture at baseline [
48]. In addition, in the FRAX ® model, current use of oral glucocorticoids was not specified by cumulative or daily dose, which may be more accurate to use in order to predict osteoporotic fractures [
49,
50]. To overcome this limitation, a recent study has shown a methodology to adjust conventional FRAX estimates of hip and osteoporotic fracture probabilities based on knowledge of the daily glucocorticoid dose in an individual patient [
51].
The FRAX model assumes that the weight of each clinical risk factor on the risk of death and fracture is the same as that derived from the cohorts used in the construction of FRAX rather than on empirical data from the Dutch population. In the absence of national data, the assumption is reasonable, particularly since the weight of the clinical risk factors has been validated in an international perspective [
6].
Finally, in contrast to the UK, cost-effectiveness has not been evaluated in the Netherlands, using FRAX® as a decision tool for BMD assessment or to start drug treatment [
36]. Therefore, it is currently unclear at which fracture risk threshold interventions (such as BMD measurement or treatment with calcium and bisphosphonate) should be recommended in the Netherlands. Furthermore, fracture risk estimation by FRAX is limited to treatment-naive patients only.
In conclusion, this paper describes the development of the Dutch FRAX model. This tool allows the estimation of 10-year absolute risks of hip and osteoporotic fracture in Dutch residents. The calibrated model is based on the original FRAX methodology, which has been externally validated in several independent cohorts. It is the first model that has been calibrated to the total Dutch population, using nationwide incidence rates for hip fracture and mortality rates. Despite some limitations [
19,
52], its strengths make the Dutch FRAX tool a good candidate for implementation into clinical practice.