The objective of this chapter is to estimate the burden of osteoporosis in terms of QALYs lost and total costs in the countries of the European Union in 2010. Fracture burden is also projected to year 2025 based on expected demographic changes.
Key messages of this chapter are:
The cost of osteoporosis, including pharmacological intervention in the EU in 2010 was estimated at €37 billion. Costs of treating incident fractures represented 66 % of this cost, pharmacological prevention 5 % and long-term fracture care 29 %.
Excluding cost of pharmacological prevention, hip fractures represented 54 % of the costs, “other fractures” represented 39 %, and vertebral and forearm fractures represented 5 % and 1 %, respectively.
The estimated number of life-years lost in the EU due to incident fractures was approximately 26,300 in 2010.
The total health burden, measured in terms of lost QALYs, was estimated at 1,180,000 QALYs for the EU. Twice as many QALYs were lost in women compared to men.
The majority of the QALYs lost were a consequence of prior fractures.
Assigning a QALY the value of 2xGDP, the total value of QALYs lost in 2010 was estimated at €60.4 billion.
Due to changes in population demography the number of men and women with osteoporosis, using the diagnostic criterion of the WHO, will rise from 27.5 million in 2010 to 33.9 million in 2025, corresponding to an increase of 23 %.
The annual number of fractures will rise from 3.5 million in 2010 to 4.5 million in 2025, corresponding to an increase of 28 %.
The number of QALYs lost annually due to fractures will increase from 1.2 million in 2010 to 1.4 million in 2025, corresponding to an increase of 20 %.
The total cost including values of QALYs lost (valued at 2 × GDP per capita) in the EU27 will rise from €98 billion in 2010 to €121 billion in 2025, corresponding to an increase of 22 %.
Disease burden is the impact of a health problem measured by mortality, morbidity, financial cost or other measures. In the case of osteoporosis, burden can inter alia be quantified as the number of fractures, the number of people suffering the consequences of a fracture, or life years lost due to fracture. Cost of illness is a measure of burden quantified in monetary terms. Costs are generally classified as direct, indirect and intangible. Direct costs constitute healthcare and non-healthcare costs, indirect costs arise from productivity losses, and intangible costs constitute the monetary value of reduced health [1, 2].
Cost of illness studies provide no direct guidance on how resources should be allocated, but may provide relevant information concerning the consequences of a disease that may inform policy. Such studies may aid decisions concerning societal resource allocation for research, development, and funding of new treatments. Results from cost of illness studies can also be utilised to assess the long term consequences and value of medical progress.
The main objective of this chapter is to estimate the current cost of osteoporosis in the countries of the European Union and to estimate the projected cost of osteoporosis in the European Union up to 2025.
4.2 Methods and materials
A cost of illness study can take a healthcare payer perspective (includes all costs carried by the health care system) or a societal perspective (includes all cost carried by society). The present study included costs from a societal perspective as far as possible and the costs of osteoporosis were estimated from the cost consequences of incident and prior fractures, costs associated with pharmacological fracture prevention, and a monetary value of QALYs lost. The cost of osteoporosis is presented with and without intangible costs (i.e., the monetary value of QALYs lost).
Costs of fracture-related productivity losses were not included in the study given that they are only incurred in patients below the retirement age—median age 60 years in Europe—and have previously been estimated to be limited in osteoporosis. For example, productivity losses were estimated to account for less than 5 % of the cost of osteoporosis in Australia , 2.8 % of the cost of osteoporosis in Austria  and less than 1 % of hip fracture cost in Sweden . Omitting costs of productivity loss underestimates the economic burden of fractures. This is especially true for fractures with a higher incidence at younger ages such as forearm fractures.
A model previously used to estimate the cost of osteoporosis in Sweden and the EU5 [6, 7] was adapted to include the countries in the present study. A literature search was performed to identify the best available health utility, epidemiological, and economic data with which to populate the model. The epidemiological data used in the model are described in Chapter 3.
The three most common sites of fragility fracture (hip, vertebral and forearm) were included in the model as well as a combination of other fragility fractures (pelvis, rib, humerus, tibia, fibula, clavicle, scapula, sternum, and lower femur).
Once growth has ceased, skeletal mass is relatively constant until the age of 50 years , so that the prevalence of osteoporosis—as defined by the WHO diagnostic criterion—and the risk of fractures are low below the age of 50 years [5, 8, 9]. Given the low number of fragility fractures in patients under 50 years and the dearth of cost and health utility implications of fractures in this population, the model was run on a population aged 50 years or above. Whilst it is difficult to assess the impact of the restriction based on the available data, it is likely to be small given the low risk of fragility fractures under the age of 50 years.
4.2.1 Model design
The model employs a prevalence-based bottom-up approach  that uses the number of cases within a defined period of time multiplied by the corresponding disease-related consequences. Fractures often lead to increased costs and morbidity for several years after the fracture occurs. The consequences related to fracture can therefore be divided into an acute or incident phase and a long-term disability phase. In the acute phase (in this report defined as the first year after fracture), costs are higher and health effects worse than in the following long term phase (defined as the period beyond the first year after fracture). Therefore, the relevant fracture related costs and health effects were captured within a defined time period for both incident fractures (i.e., fractures that occur within the year of analysis) and prior fractures (i.e., fractures that occurred in previous years but still have an impact on costs and quality of life during the study period). The same method was applied by Ström et al., reporting the economic burden of osteoporosis estimation in the EU5 and Sweden .
In short, the calculation of the costs and QALYs lost due to osteoporosis in 2010 was performed in the following way: the number of acute fractures was estimated from fracture incidence and population data for each country (described in Chapter 3). Subsequently, country-specific costs and generic health utility multipliers (described below) were assigned to the number of fractures to derive the cost and health utility implications for acute fractures. Given that 1 year costs and health utility implications were applied to all fractures in 2010, the resulting estimates can be interpreted as the one-year burden of incident fractures in 2010. The number of prior fractures in people above the age of 50 years was simulated under the assumption of constant population size and age- and sex distribution, fracture incidence, general population mortality and excess mortality after fractures. Please see Chapter 3 for further details on number of incident and prior fractures. Subsequently, country-specific costs and generic health utility multipliers (described below) were assigned to the number of prior fractures to derive the cost and health utility implications of those fractures. Further details on the method for calculating the burden of fractures can be found in Ström et al.  and Borgström et al. .
4.2.2 Cost of fracture and imputations methods
First-year costs after fracture were obtained from a literature review where Medline was searched for articles using the keywords “[Country]” and “Fracture” and “Cost”. Titles and abstracts identified by the search were screened and potentially relevant articles retrieved in full text. Furthermore, all abstracts presented at the IOF and ECCEO conferences since 2000 were screened for additional data. Where costs of fractures were not available, those were imputed as described below. Table 38 provides a summary of references and imputation methods by fracture type and country.
For hip fractures, cost estimates were available for Belgium , Czech Republic , Denmark [13, 14], Finland , Germany, Italy , the Netherlands , Slovenia , Sweden  and the UK, [20, 21]. Where only hospital costs of hip fracture were found (Austria , Czech Republic , Ireland , and Portugal ), the ratio between hospital cost and the total direct costs for hip fractures observed in the Swedish KOFOR study was used to obtain estimates of the first-year cost. For countries where fracture costs were not found, the costs were imputed from the nearest country available by adjusting for differences in healthcare price levels between the relevant countries . Following the completion of this report, we were forwarded data on fracture costs from Slovakia . These are used as a sensitivity analysis in the country specific report published in the same issue of Archives in Osteoporosis
For vertebral fractures, studies reporting on costs of treating fractures in both inpatient and outpatient settings were available for Denmark, Germany , Slovenia , Sweden and the UK . For countries where only hospitalised clinical fractures costs were found, as for countries without cost estimates, the costs were derived via morbidity equivalents as estimated by Kanis et al. . Morbidity equivalents can roughly be described as the morbidity a fracture type confers compared to that of a hip fracture, and costs were assumed to follow the same pattern. This assumption has been shown to be appropriate, at least in a US setting .
For forearm fractures, inpatient and outpatient cost estimates were available for Denmark , Slovenia , Sweden  and the UK . For countries where forearm fractures costs were not found, costs were derived via morbidity equivalents as described for vertebral fractures above.
When calculating the Swedish cost of fractures grouped as “other fractures” (pelvis, rib, humerus, tibia, fibula, clavicle, scapula, sternum, and lower femur), it was assumed that lower leg and pelvic fractures were equivalent to hip fractures; humerus fractures were assumed to be equivalent to vertebral fractures; and fractures of the rib, clavicle, scapula, and sternum were assumed to be equivalent to forearm fractures . Costs were then adjusted to represent the age distribution of these fractures. For other countries, the costs of “other fractures” were calculated as a share of the first-year hip fracture costs by assuming the same ratio of first-year hip fracture costs and “other fracture” costs observed in Sweden. Swedish costs were stratified by age, and therefore the imputed costs of other fractures also differed by age group.
Acute hip fracture costs in Europe ranged from approximately €2,000 in Bulgaria (estimated from Slovenian cost using PPP) to about €25,000 in Denmark. As a consequence of imputation, Bulgaria also had the lowest costs for vertebral fractures (€404), forearm (€112) and other fractures (€929). The lowest cost of hip fracture for a country with an original reference was Slovenia (€5,306). The highest costs for vertebral and forearm fractures were found in Sweden at €11,413 and €2,401 respectively whereas the highest costs for “other fractures” were found in Denmark (€12,749). Where applicable, costs were inflated to 2010 year prices using the consumer price index (CPI) . First year fracture costs for all fracture types are shown in Table 39.
There are currently no published estimates of long-term fracture costs based on empirical patient samples. For the purposes of this report, we conservatively assumed that fractures other than those at the hip did not incur any long-term costs. Hip fracture costs in the second and following years after the event are usually based on the proportion of patients that become institutionalised for the long-term [33, 34]. With increasing age, an increasing proportion of patients transition from independent living to long-term care 1 year after fracture . Patients who at the time of fracture already resided in long-term care were assumed not to have any additional long-term fracture related costs and the rates were down-adjusted accordingly. Moreover, the proportion admitted to long-term care 1 year after fracture was also down-adjusted to account for the risk of being admitted due to causes not related to the hip fracture itself. The annual risk of being institutionalised in long-term care in the general population in Sweden is approximately 0.1 %, 0.5 %, and 2 % for 65-, 75- and 85-year old individuals, respectively . When individuals transitioned from independent living to long-term care, it was assumed that they remained dependent until death. Data on the proportion of patients who transition to nursing home after a hip fracture and on the probability of transition to nursing homes in the general population are scarce, and Swedish data were therefore used for all countries. This is a reasonable proxy for countries in Northern Europe, e.g., Scotland , but may be an overestimate for countries in other parts of Europe, where long-term care to a larger extent is provided by informal care givers (e.g., a spouse or child). Informal care is however also associated with societal costs such as productivity losses, lost leisure time, and out-of-pocket expenses. In this report, we assumed that the costs of long-term care of hip fractures are similar irrespective of whether they are incurred by informal or formal care. Swedish risks of transitioning to nursing homes are thus used as a proxy for the risk of being disabled in the long-term after a hip fracture.
The annual hip fracture cost beyond the first year after fracture was obtained by multiplying the yearly cost of residing in a nursing home with the simulated number of prior fractures transferring to nursing homes adjusted for proportions described above. For countries where yearly cost of residing in a nursing home was not found, costs were imputed from the nearest country available by adjusting for differences in healthcare price levels between the relevant countries . Table 40 lists the costs, references and imputation methods by country.
4.2.3 Costs of pharmacological prevention of fracture
In addition to the first and subsequent year costs of fracture detailed above, patients with established osteoporosis may be prescribed bone protective treatment. The number of prescribed daily doses per country (2010) for each relevant pharmaceutical intervention (alendronate, risedronate, etidronate, ibandronate, raloxifene, zoledronic acid, strontium ranelate, teriparatide and PTH) were obtained from IMS Health and multiplied by the unit costs for respective drug in each country . In addition to costs for pharmaceuticals, patients on therapy were assumed to incur costs for an annual physician visit and a BMD measurement every second year. The cost of DXA was taken from two IOF audits  . Furthermore, there may also be other costs related to pharmacological treatment of osteoporosis such as costs for medication to treat side effects. However, those were not included in the analysis.
Costs for first and second line treatment per year (weighted on price and market share in each country) are presented in Table 41 together with unit costs for BMD measurement and physician visits.
4.2.4 Health utility and QALY implications of fracture
The health burden of osteoporosis can be measured in terms QALYs lost. The QALY is a multi-dimensional outcome measure frequently employed in health economic analysis that incorporates both the quality (health related) and quantity (length) of life. QALYs are derived by multiplying the duration of life (years) with a health utility between 0 (death) and 1 (perfect health) . For example, a person who lives for 5 years with a health utility of 0.8 would accrue four QALYs during those 5 years.
Health utility can be measured using the EQ-5D instrument, which rates health status grouped by physical, social and mental aspects in five dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) with a three level answer for each dimension, resulting in a total of 243 (35) possible EQ-5D health states. Each EQ-5D health state may be converted to health utility by applying a formula that attaches weights to each of the levels in each dimension. This formula is based on the valuations of the health states from general population samples. Whilst a pan-Europe EQ-5D has been developed using a visual analogue scale, preference based valuation sets are preferable in economic studies and these have only been derived for the UK, Denmark, Germany, the Netherlands, Spain and Sweden, with the UK valuation set having been deemed the most robust . Consequently, the preference based UK valuation set and normal population health utility were used for all countries.
Fracture can result in loss of health in all EQ-5D dimensions. Effects on the physical dimensions include factors such as increased pain, loss of mobility and capability of self-care. The perception of social role and impact on activities can also be affected in the social dimension. There is also a mental dimension which can be affected by, for example, depression, anxiety or loss of self-esteem . Consequently, fractures result in reduced health utility and reductions differ substantially among the fracture types, and likely between countries . Hip and vertebral fractures have the greatest impact on health utility whereas forearm fractures are associated with less health utility loss over a shorter period of time; most patients return to their pre-fracture utility after 12 months . The loss of health utility is greatest for all fractures in the first year and decreases in subsequent years .
The health utility in the first year after hip, clinical vertebral and forearm fracture relative to the age-specific health utility in the normal population has been estimated at 0.70, 0.59 and 0.96, respectively . Other fractures were assigned 85 % of the age specific health utility. Age-specific health utilities after fracture were derived by multiplying the health utility of the general population of the relevant age by the health utility multipliers for fracture. For example, a 75 year old man (average health utility of in men aged 75 years is 0.72) who sustains a hip fracture has a health utility loss of 0.216 (=0.72 × (1–0.70)) in the first year after fracture, resulting in a loss of 0.216 QALYs (=1 × 0.216).
The health effects of fractures may extend beyond the first year after fracture. Hip and vertebral fractures have been shown to have long-lasting effects on health and were modelled to reduce health utility to 80 %  and 94 %  of that of non-fractured individuals beyond the first year after fracture. Conservatively, neither forearm, nor “other fractures” were modelled to have long-term effects on health utility.
Hip and vertebral fractures are also associated with increased mortality and studies suggest that approximately 30 % of the excess mortality observed after fracture may be directly attributable to the fracture event [102–104]. “Other fractures” have also been associated with increased mortality directly attributable to the fracture and were modelled to increase risk of mortality by 12 % . Because deaths attributable to fracture may not occur immediately after the fracture, they do not result in one whole life year lost in the index year (2010). Based on data from the Swedish Inpatient and Cause of Death Registries presented in Borgström et al. , we modelled that deaths attributable to fracture occurred 140 days after fracture, resulting in approximately 2/3 life years lost in 2010. QALYs lost to due post-fracture mortality are fewer than life years lost due to post-fracture mortality reflecting that individuals with fracture are not in perfect health. Life years lost resulting from deaths attributable to fractures occurring prior to 2010 were not incorporated into the model.
Similar to the methodology used to estimate costs described above, the estimate of total QALYs lost comprised QALYs lost due to incident fracture (i.e., QALYs lost due to fractures in the index year (2010)) and QALYs lost due to prior fracture (i.e. QALYs lost due fractures incurred prior to the index year, but which resulted in health utility loss in 2010). This prevalence model only account for QALYs lost due to death in the incident year, and thus substantially underestimates QALYs lost compared to an incidence model. The latter should account for all life years lost in the case of fracture compared to no fracture.
4.2.5 Societal value of QALYs
The value of a QALY may differ between and within countries due to a number of factors including degree of prosperity, cultural attitudes and the opportunity costs of resources devoted to obtain a marginal QALY .
There are two methods to elicit the value of a QALY: stated preferences and implicit valuation. In the stated preference approach, people are directly asked for their preferences whereas in implicit valuation preferences are elicited from actual choices, e.g., the premium wage a job with an increased risk of mortality or morbidity commands .
Valuing health as a function of GDP allows for variations in ability to pay for health between countries and the WHO Commission on Macroeconomics and Health has suggested that one averted DALY can be valued at three times GDP per capita . This criterion has been used in health economics studies. For example, Murray et al.  classified treatments based on the cost per healthy life year gained as very cost-effective at ≤ 1× GDP per capita and as cost-effective at ≤ 3 × GDP per capita. Whereas DALYs and QALYs are conceptually similar, they are based on different methodologies and are therefore not directly comparable . However, a comparison of available estimates for different disease areas for the two outcome measures does not suggest a substantial difference in terms of GDP per capita valuation [106–108]. Consequently, we followed the approach of Borgström et al.  and Strom et al.  and set the value of a QALY at 2 × GDP per capita.
4.3.1 Costs of osteoporosis excluding values of QALYs lost
Several factors affect the cost of osteoporosis excluding the value of QALYs lost in a country, including age specific fracture risks, population size, age and sex distribution, fracture-related costs and the cost of pharmacological intervention. Three cost components are included in the model: cost first year after fracture, cost subsequent years after fracture, and cost of pharmacological fracture prevention including administration and monitoring costs.
The cost of osteoporosis, excluding value of QALYs lost in the EU27, amounted to €37.4 billion in 2010. First year, subsequent year, and pharmacological costs accounted for 66 %, 29 % and 6 % of the costs, respectively. Whilst the proportion of costs for pharmacological prevention to total costs was low on average, some inter-country variation was observed: the lowest proportion of costs attributable to pharmacological intervention was observed in Sweden (2 %) and the highest costs in Cyprus (22 %). The high cost share in Cyprus might be explained by Cyprus having the highest number of doses of anti-osteoporosis drugs sold per person. In addition, the highest price of alendronate in the EU27 was observed in Cyprus. The cost of osteoporosis stratified by the three cost categories for each EU27 country in 2010 is presented in Table 42 below.
Hip fractures were estimated to account for 54 % of the total costs, other fractures 39 %, vertebral fractures 5 %, and forearm fractures 2 % (Fig. 27). The estimate of 39 % for other fractures may be perceived as a high figure given that most health economic evaluations of fracture prevention mainly focus on hip and vertebral fractures [14, 110–112]. However, such studies usually evaluate treatment in elderly women where the risks of hip and vertebral fractures are greater than that of the risk of “other fractures”. By contrast, the current study captured all fractures in all patients aged 50 years or more. Note that costs attributable to fractures in Fig. 27 do not incorporate costs of pharmaceutical intervention.
Fig. 27 Share (%) of 2010 cost of osteoporosis in EU27 (excluding value of QALYs lost and cost of pharmacological intervention) by fracture site
The highest costs were incurred by fractures occurring in individuals aged 80–89 years. Hip and “other” fracture costs peaked in this age group, while costs for forearm and vertebral fractures peaked in individuals aged 70–79 years. Fracture costs by site and age are given in Table 43.
The total costs for osteoporosis (excluding the value of QALYs lost) were compared to total healthcare spending in the respective country (Table 44). Healthcare spending varied markedly between countries, ranging from €500 million in Malta to €281 billion in Germany. The total spend on healthcare in the European Union amounted to €1,260 billion, with the cost of osteoporotic fractures representing 3 %. The share varied across countries, and the extremes were represented by Cyprus where fracture burden represented approximately 5 % of the total healthcare spending and Luxembourg where the corresponding number was approximately 1 %. It should be noted; however, that not all fracture related costs come from the healthcare budgets of the countries (e.g., long-term care).
The cost of osteoporosis per capita, shown in Table 45 is in part related to the incidence of fracture (r = 0.67, p = 0.001) and the healthcare spend per capita (r = 0.63, p = 0.004). Denmark has the highest cost of osteoporosis per capita with €190 per year, whereas Romania and Bulgaria had the lowest cost per capita at approximately €6 per year.
Fig. 28 Estimated cost of osteporosis (excluding values of QALYs lost) per capita (€, 2010)
4.3.2 Life-years lost due to fracture
As mentioned, hip, vertebral, and other fractures are associated with increased mortality and approximately 30 % of the excess mortality may be attributable directly to the fracture with each death resulting in approximately 2/3 life years lost.
The total number of deaths after fracture in the EU27 in 2010 was estimated at about 143,000, with 43,000 (30 %) directly attributable to the fracture, resulting in 26,000 life years lost (i.e., 2/3 of the 43,000 attributable deaths). The number of deaths after fracture, deaths directly attributable to fracture, and resulting life years lost are shown in Table 45.
4.3.3 QALYs lost due to osteoporosis
QALYs lost due to osteoporosis incorporate both the HRQoL and life years lost due to fracture (downwards adjusted to reflect the average health utility at the age in which the death attributable to fracture occurred). The number of QALYs lost in 2010 was derived by applying the health utility weights for incident and prior fractures to the number of incident and prior fractures. Thereafter, the health utility weighted life years lost were added.
Approximately 1,165,000 QALYs were lost due to osteoporosis in the EU27 in 2010. Women and men suffered approximately 781,000 and 384,000 QALYs lost, respectively. Prior fractures were the main driver of QALYs lost, accounting for approximately 58 % and 50 % of the loss in women and men respectively. The higher proportion of QALYs lost due to prior fractures in women than in men reflects higher absolute mortality after fracture in men, a pattern also observed in the number of prior fractures described in Chapter 3. Germany was the individual country where most QALYs were lost in both men and women, followed by Italy for women and the UK for men. The number of QALYs lost due to incident (including QALYs lost due to deaths directly attributable to fracture) and prior fractures for women and men in each of the EU27 countries is shown in Table 46.
Hip fractures, vertebral, forearm and “other fractures” incurred approximately 600,000, 344,000, 19,000, and 202,000 QALYs lost, respectively. For hip and vertebral fractures, approximately 79 % and 59 % of the QALYs lost were incurred by prior fractures. Given that no long-term health utility loss was assumed for forearm and other fracture, all QALYs lost for these fracture types resulted from incident fractures. The greatest number of QALYs lost in the EU27 in 2010 was incurred in people aged 80 to 90 years with 426,000 QALYS lost representing 37 % of the total. In this group, the fracture type incurring highest number of QALYs lost was prior hip fractures. The number of QALYs lost stratified by age and fracture type is presented in Table 47.
QALYs lost from fracture related deaths were included in the estimate for incident fractures, reflecting that increased mortality is accounted for within the first year after fracture. These deaths amounted to approximately 26,000 life-years lost which corresponded to a loss of about 13,000 QALYs, representing approximately 2.5 % of the QALYs lost due to incident fractures and 1 % of all QALYs lost.
Even though common, forearm fractures only represented a marginal share (1 %) of the estimated fracture-related QALYs lost. The negligible impact of forearm fracture on QALYs lost in the total population is due to its relatively small impact on health utility during the first year after fracture, no associated mortality and the complete long-term recuperation after fracture assumed in the model. The proportion of QALYs lost by incident and prior fracture are shown in Fig. 29.
Fig. 29 Proportion of QALYs lost by incident and prior fracture in the EU27 2010
4.3.4 Value of QALYs lost due to osteoporosis
Valuing a QALY at 2 x GDP/capita resulted in a value of QALYs lost due to osteoporotic fractures in 2010 of €60 billion. Country specific estimates of value of QALYs lost ranged from €24 million in Malta to €15 billion in Germany (Table 48).
Valuing a QALY at 2 x GDP/capita resulted in an estimated cost of €121 for QALYs lost per capita in the EU27 in 2010. Country specific estimates ranged from €16 in Romania and Bulgaria to €307 in Denmark (Fig. 30).
Fig. 30 Value of QALYs lost (valued at 2 × 2010 GDP/capita per QALY) per capita (€)
4.3.5 Cost of osteoporosis including value of QALYs lost
When the cost of osteoporosis was combined with the value for QALYs lost, valued at 2 x GDP, the cost of osteoporosis amounted to €98 billion in the EU27 in 2010. The cost ranged from €41 million in Malta to €24 billion in Germany.
QALYs lost accounted for 62 % of the total cost of osteoporosis including values of QALYs lost in the EU27 in 2010, ranging from 50 % in Portugal to 87 % in Luxembourg. Incident fractures, prior fractures and pharmacological intervention accounted for 25 %, 11 % and 2 %, respectively, of the cost of osteoporosis including values of QALYs lost. The cost of osteoporosis including the value of QALYs lost and the proportion attributable to the different cost categories are presented in Table 49.
4.3.6 Cost of osteoporosis compared to other diseases
The estimated cost of osteoporosis may be compared to the cost of other diseases. However, given that the EU27 is a relatively new construct, few directly comparable studies exist. Furthermore, methodological differences may render studies difficult to compare. However, a few studies conducted on a similar geographic area with comparable methodology exist.
In a report issued by the European Brain Council, the yearly societal costs for a number of brain disorders in the EU27 were estimated at €105 billion for dementia, €43.5 billion for headache, €14.6 billion for multiple sclerosis, and €13.9 billion for Parkinson’s disease [14, 111–113].
The cost of coronary heart disease and cerebrovascular disease in the European Union (25 countries) has been estimated at approximately €45 billion and €34 billion, respectively, at 2003 prices . For coronary heart disease, healthcare costs, productivity losses, and informal care comprised 51 %, 34 % and 15 %, respectively. Costs for pharmacological treatment accounted for 12 % of the total costs, substantially higher than for osteoporosis. For cerebrovascular disease, healthcare costs, productivity losses, and informal care comprised 61 %, 18 % and 21 % respectively. Costs for pharmacological treatment accounted for 3 % of the total costs for cerebrovascular disease , somewhat lower than for osteoporosis.
The cost of epilepsy in the European Union (25 countries) has been estimated at €15.5 billion at 2004 prices. Healthcare costs comprised 18 % of costs, whereas direct medical costs and productivity losses represented 27 % and 55 %, respectively .
Thus, in relation to other common non-communicable diseases osteoporosis has major economic consequences for society.
Osteoporosis shares some features of dementia, in that it is a disease of the elderly population and is expected to take an increasing share of healthcare spending when taking into account the demographic changes expected with an ageing population . However, while large amounts of money are being spent on research and development of new drugs to treat dementia, there has been small or little success in introducing new drugs to the market . The availability of affordable and efficient pharmacological treatment, as well as non-pharmacological fracture risk prevention, provides an opportunity to take immediate action to reduce the future number of osteoporotic fractures
4.4 Burden of osteoporosis up to 2025
Osteoporosis is a disease primarily affecting the elderly; the prevalence of osteoporosis as judged by BMD criteria increases markedly with age. As described in Chapter 3, 6 % of women aged 50–54 years have osteoporosis, and the prevalence increases with age. Among women aged 80 years or older 47 % have a BMD value in the osteoporosis range. The determinants of the future burden of osteoporosis depend on several factors in society, including changes in population, age-specific fracture risk and measures to reduce the risk of fracture. This section presents the projected burden of osteoporosis in the European Union up to 2025 with regard to the expected demographic changes.
4.4.1 Secular trends
Incidence rates can be followed over time using age-standardized incidence rates. Age- and sex- specific risk of fracture has been most completely studied in the case of hip fractures. In general, age- and sex-adjusted hip fracture incidence increased until the mid or end of the 20th century, with a subsequent plateau or even decrease . In Europe, this tendency is best documented for Northern Europe. For example, whilst Swedish crude hip fracture incidence has increased, age-adjusted incidence (independent of demographic trends) remained stable between 1967 and 2001. Palvanen et al.  also described this phenomenon for humeral fractures and report a clear rise in the fracture rate in Finnish women 60 years of age and older from 1970 until the late 1990s followed by stabilisation and even decreased fracture rates in later years. For the UK, hip fracture rates have been reported to stabilise over the period 1989–1998 . The trend has been further confirmed in Germany , the Netherlands , Hungary  and Austria . There are fewer studies available from Southern Europe. A Spanish study reported that the number of hip fractures increased between 1988 and 2002, but no significant change was observed in age-adjusted incidence rates among men or women over this period .
The precise reasons for secular changes are unknown, and both skeletal and non-skeletal mechanisms have been suggested. An example of a non-skeletal factor is a cohort effect towards improved functionality among older women and actions and interventions in preventing and reducing falls. The importance of functionality is exemplified by a recent German study where 256 nursing homes were included in an intervention programme aimed at reducing the risk of residents falling. This was done through measures such as strength and balance training. Compared to control nursing homes, the intervention led to a relative risk of femoral fracture of 0.82 (95 % CI 0.72–0.93) . An example of a risk factor for skeletal health that changes over time is the effect on maternal vitamin D status on offspring bone mass [127, 128].
The increasing use of drugs targeting osteoporosis could also contribute to the decrease in incidence. However, since incidence rates stabilized before treatment uptake rose significantly , increased drug access is unlikely to be the main reason for the secular trends observed.
For the purpose of this report we assume that incidence rates have reached a plateau and will remain stable until 2025 consistent with the findings described above.
4.4.2 Demography up to 2025
The demographic projection in the European Union for the years up to 2025 will translate into an increase in the number of fractures, as age is an important risk factor for fractures and the elderly population is projected to increase in almost all countries. Estimates are based on the UN World Population Projections using the medium variant . In the European Union, the population over 50 years is expected to increase from 183 million in 2010 to 219 million in 2025, corresponding to a rise of approximately 20 %, with the male to female ratio increasing from 84 % to 87 %. When stratifying the population by age groups, the highest growth is forecast for the population aged 80 years or more (32 % increase). Given a greater increase in life expectancy in men than in women, the ratio of men to women in the population over 80 years is forecast to increase from 51 % to 60 % over the period. UN World Population Projections for the EU-27 are shown in Table 50.
The estimated demographic changes differ for the individual countries (Figs. 31 and 32). In Bulgaria for example, the male population above 50 years is expected to decrease by 1 %, whereas for all other countries the male population is expected to increase in all age groups. In women aged 50–74 years, the changes range from a 3 % decrease in Bulgaria to a 43 % increase in Luxembourg. In women aged 75 years and above, the corresponding numbers are a 7 % increase in Latvia to a 63 % increase in Cyprus. Spain and Malta are projected to have the highest increase in men aged 50–74 years and 75+ years, respectively. The projections expressed in relative change for countries with very small populations are uncertain given that numbers are presented in 1000s by the UN.
Fig. 31 Relative change in demography in men by age group and country between 2010 and 2025 (%)
Fig. 32 Relative change in demography in women by age group and country between 2010 and 2025 (%)
Although the total population increases between 2010 and 2025, the population below 50 years is projected to decrease by 7 % during the time period and the population under 65 years is forecast to decrease by approximately 3 % (Table 50). As a consequence, the projected increase in costs of osteoporosis is forecast to be carried by a decreasing population at productive ages.
4.4.3 Prevalence of osteoporosis as defined using the WHO diagnostic criteria up to 2025
Assuming that the prevalence of osteoporosis (described in Chapter 3), defined using the WHO diagnostic criterion, remains constant until 2025, the demographic changes are expected to result in an increase in the number of individuals with osteoporosis from 28 million in 2010 to 34 million in 2025, corresponding to an increase of 23 %. The increase is estimated to be higher in men than in women (29 % vs. 22 %). In the population aged 80 years and over, the overall increase is estimated at 28 % with an even larger difference between men and women (46 % vs. 25 %). The number of people with osteoporosis stratified by five-year age groups is shown in Table 51.
4.4.4 Number of incident fractures up to 2025
Assuming that the incidence rates of fractures (see Chapter 3) remain constant until 2025, the demographic changes are expected to result in an increase in the number of incident osteoporotic fractures from approximately 3.5 million in 2010 to approximately 4.5 million in 2025, corresponding to an increase of 28 %. The absolute increase ranged from about 1,000 fractures in Malta to approximately 203,000 fractures in Germany and the relative increase ranged from 4 % in Bulgaria to 53 % in Ireland. In 2025, Germany is expected to have the largest number of fractures with approximately 928,000 fractures, followed by the UK with approximately 682,000 fractures. The estimated number of fractures in the EU27 in 2010 and 2025 is shown in Table 52.
The number of incident fractures in women and men is expected to increase from approximately 2.3 million in 2010 to 2.9 million (25 %) in women and from 1.2 million to 1.6 million in men (34 %), respectively. Hip fractures are expected to increase at the highest rate in both women (29 %) and men (41 %). However, the increase in the number of fractures is predominately driven by “other fractures”, accounting for 49 % of the increase in women and 61 % of the increase in men. The number of fractures stratified by fracture type and sex in 2010 and 2025 is shown in Table 53.
4.4.5 Cost of osteoporosis up to 2025 excluding QALYs lost
When costs of osteoporosis (excluding values of QALYs lost) are estimated, three cost components are included in the model: costs first year after fracture, costs subsequent years after fracture, and the cost of pharmacological intervention including administration and monitoring costs. Fracture costs are driven by the increased number of fractures. The ratio of pharmacological intervention costs to fracture costs is assumed to remain constant over the forecast period.
The cost of osteoporosis was projected to increase from € 37.4 billion in 2010 to € 46.8 billion in 2025, corresponding to an increase of 25 % (Table 54). The absolute increase ranged from €2 million in Bulgaria to €2.3 billion in Germany and the relative increase ranged from 5 % in Bulgaria to 47 % in Cyprus.
The cost of osteoporosis excluding values of QALYs lost in women and men was projected to increase from €25.8 billion to €31.3 billion (21 %) and from €11.6 billion to €15.5 billion (34 %), respectively. The increase was projected to be most pronounced in men aged 75 years and above (44 %). Whilst the projected growth was most rapid in men, the majority of the cost increase was incurred in women reflecting the substantially higher cost in women than in men in the index year (2010). The cost of osteoporosis stratified by age and sex in the EU27 in 2010 and 2025 is presented in Table 55.
4.4.6 Projection of QALYs lost due to osteoporosis up to 2025
The increased number of fractures reflecting demographic changes will affect the number of QALYs lost due to incident and prior fractures (Table 56). The number of QALYs lost in the European Union was projected to increase from 1.17 million in 2010 to 1.40 million in 2025, corresponding to an increase of approximately 20 %. The absolute increase ranged from approximately 300 in Malta to approximately 50,000 in Germany and the relative increase ranged from 4 % in Bulgaria to 34 % in Ireland.
The number of QALYs lost due to fractures stratified by age, sex and incident and prior fractures in 2010 and 2025 is presented in Table 57. The number of QALYs lost (due to incident and prior fractures jointly) was projected to increase from approximately 781,000 to 911,000 (17 %) in women and from 384,000 to 491,000 (28 %) in men. The number of QALYs lost (in both sexes jointly) was projected to increase from approximately 520,000 to 669,000 (29 %) for the incident fractures and from 645,000 to 734,000 (14 %) for the prior fractures.
4.4.7 Cost of osteoporosis up to 2025 including QALYs lost
When the costs of osteoporosis were combined with the value for QALYs lost (valued at 2 × GDP), the cost was projected to increase from €98 billion in 2010 to €120 billion, corresponding to an increase of 23 % (Table 58). The EU5 (Germany, France, Italy, Spain and the UK) accounted for 74 % of the increase.
The cost of osteoporosis including QALYs lost in women and men was projected to increase from €66 billion to €79 billion (19 %) and from €31 billion to €41 billion (31 %), respectively. The increase was most pronounced in men aged 75 years and above (43 %). Whilst the projected growth was most rapid in men, the majority of the projected increase was incurred in women reflecting the substantially higher total cost in women than in men in the index year (2010). The cost of osteoporosis including values of QALYs lost stratified by age and sex in 2010 and 2025 is shown in Table 59.
1. Hodgson TA, Meiners MR (1982) Cost-of-illness methodology: a guide to current practices and procedures. Milbank Mem Fund Q Health Soc 60:429–462
2. Hodgson TA (1983) The state of the art of cost-of-illness estimates. Adv Health Econ Health Serv Res 4:129–164
3. Harris H, R C, Watts J, Ebeling P, Crowley S (1998) The burden of illness and the cost of osteoporosis in Australia. In Centre for health program evaluation.
4. Dimai HP, Redlich K, Peretz M, Borgstrom F, Siebert U, Mahlich J (2012) Economic burden of osteoporotic fractures in Austria. Health Econ Rev 2:12
5. Kanis JA, Delmas P, Burckhardt P, Cooper C, Torgerson D (1997) Guidelines for diagnosis and management of osteoporosis. The European Foundation for Osteoporosis and Bone Disease. Osteoporos Int 7:390–406
6. Borgstrom F, Sobocki P, Strom O, Jonsson B (2007) The societal burden of osteoporosis in Sweden. Bone 40:1602–1609
7. Strom O, Borgstrom F, Kanis JA, Compston J, Cooper C, McCloskey EV, Jonsson B (2011) Osteoporosis: burden, health care provision and opportunities in the EU: a report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Arch Osteoporos 6:59–155
8. Sanders KM, Seeman E, Ugoni AM, Pasco JA, Martin TJ, Skoric B, Nicholson GC, Kotowicz MA (1999) Age- and gender-specific rate of fractures in Australia: a population-based study. Osteoporos Int 10:240–247
9. Singer BR, McLauchlan GJ, Robinson CM, Christie J (1998) Epidemiology of fractures in 15,000 adults: the influence of age and gender. J Bone Joint Surg Br 80:243–248
10. Drummond MF (2005) Methods for the economic evaluation of health care programmes. Oxford University Press, Oxford
11. Bouee S, Lafuma A, Fagnani F, Meunier PJ, Reginster JY (2006) Estimation of direct unit costs associated with non-vertebral osteoporotic fractures in five European countries. Rheumatol Int 26:1063–1072
12. Kudrna K, Krska Z (2005) Expense analysis of the proximal femoral fractures treatment. Rozhl Chir 84:631–634
13. Ankjaer-Jensen A, Johnell O (1996) Prevention of osteoporosis: cost-effectiveness of different pharmaceutical treatments. Osteoporos Int 6:265–275
14. Strom O, Borgstrom F, Sen SS, Boonen S, Haentjens P, Johnell O, Kanis JA (2007) Cost-effectiveness of alendronate in the treatment of postmenopausal women in 9 European countries—an economic evaluation based on the fracture intervention trial. Osteoporos Int 18:1047–1061
15. Nurmi I, Narinen A, Luthje P, Tanninen S (2003) Cost analysis of hip fracture treatment among the elderly for the public health services: a 1-year prospective study in 106 consecutive patients. Arch Orthop Trauma Surg 123:551–554
16. Visentin P, Ciravegna R, Fabris F (1997) Estimating the cost per avoided hip fracture by osteoporosis treatment in Italy. Maturitas 26:185–192
17. Jansen JP, Gaugris S, Bergman G, Sen SS (2008) Cost-effectiveness of a fixed dose combination of alendronate and cholecalciferol in the treatment and prevention of osteoporosis in the United Kingdom and The Netherlands. Curr Med Res Opin 24:671–684
18. Dzajkovska B, Wertheimer AI, Mrhar A (2007) The burden-of-illness study on osteoporosis in the Slovenian female population. Pharm World Sci 29:404–411
19. Borgstrom F, Zethraeus N, Johnell O, et al. (2006) Costs and quality of life associated with osteoporosis-related fractures in Sweden. Osteoporos Int 17:637–650
20. Stevenson M, Davis S, Kanis J (2006) The hospitalization costs and outpatient costs of fragility fractures. Women’s Health Medicine 149–151
21. Stevenson M, Davis S (2006) Analyses of the cost-effectiveness of pooled alendronate and risedronate, compared with strontium ranelate, raloxifene, etidronate and teriparatide. http://wwwniceorguk/pageaspx?o=370643.
22. Koeck CM, Schwappach DL, Niemann FM, Strassmann TJ, Ebner H, Klaushofer K (2001) Incidence and costs of osteoporosis-associated hip fractures in Austria. Wien Klin Wochenschr 113:371–377
23. Kudrna K, Krska Z (2005) [Expense analysis of the proximal femoral fractures treatment]. Rozhl Chir 84:631–634
24. Azhar A, Lim C, Kelly E, O’Rourke K, Dudeney S, Hurson B, Quinlan W (2008) Cost induced by hip fractures. Ir Med J 101:213–215
25. Mateus M, Cruz C, Alves de Matos A, Branco J (2002) Hospital care costs of osteoporotic hip fractures - comparative study with other prevalent diseases. Osteoporos Int 13 (Suppl 1):S75
26. International Bank for Reconstruction and Development/The World Bank (2008) 2005 International Comparison Program, Tables of final results.
27. Bielik J, Jureček L, Hroncová D (2010) Epidemiologické a ekonomické aspekty osteoporózy. Farmakoekonomika a lieková politika 6:25–28
28. Brecht JG, Kruse HP, Mohrke W, Oestreich A, Huppertz E (2004) Health-economic comparison of three recommended drugs for the treatment of osteoporosis. Int J Clin Pharmacol Res 24:1–10
29. Kanis JA, Oden A, Johnell O, Jonsson B, De Laet C, Dawson A (2001) The burden of osteoporotic fractures: a method for setting intervention thresholds. Osteoporos Int 12:417–427
30. Melton LJ, III, Gabriel SE, Crowson CS, Tosteson AN, Johnell O, Kanis JA (2003) Cost-equivalence of different osteoporotic fractures. Osteoporos Int 14:383–388
31. Brecht JG, Kruse HP, Felsenberg D, Mohrke W, Oestreich A, Huppertz E (2003) Pharmacoeconomic analysis of osteoporosis treatment with risedronate. Int J Clin Pharmacol Res 23:93–105
32. Eurostat (2011) Statistics database. Data retrieved November, 2011. http://epp.eurostat.ec.europa.eu,
33. Stadsledningskontoret (2003) Stockholms stads budgetavräkning.
34. Jonsson B, Christiansen C, Johnell O, Hedbrandt J, Karlsson G (1996) Cost-effectiveness of fracture prevention in established osteoporosis. Scand J Rheumatol Suppl 103:30–38
35. Zethraeus N, Strom O, Borgstrom F (2006) What is the risk of institutionalization after hip fracture? Osteoporos Int 17 (Suppl 1):57–58
36. National Board of Health and Welfare (2006) Care and sevices to elderly persons 2005, The National Board of Health and Welfare, Stockholm, Sweden
37. Scottish Hip Fracture Audit (2009) The patient journey post hip fracture: What constitutes rehabilitation? - A report from the Scottish hip fracture audit
38. Seniorenheim (2011) Austria Nursing Home Cost. Accessed November 2012. www.seniorenheim.at
39. Latvia Ministry (2011) Latvijas Republikas - Labklajibas Ministrija. www.lm.gov.lv/index.php
40. Autier P, Haentjens P, Bentin J, Baillon JM, Grivegnee AR, Closon MC, Boonen S (2000) Costs induced by hip fractures: a prospective controlled study in Belgium. Belgian Hip Fracture Study Group. Osteoporos Int 11:373–380
41. Republic of Lithuania - Ministry of Health (2011) Kauno Territorial Health Insurance Fund. www.sam.lt/index.php?3474664842
42. MIA-2004 LTD,Home For Elderly People (2011) Personal communication, Alexandrovska and Vlad - Jordanka Vladimirova ET - average of three Bulgarian nursing homes (750, 650, and 550 lev/month).
43. Meerding WJ, Mulder S, van Beeck EF (2006) Incidence and costs of injuries in The Netherlands. Eur J Public Health 16:272–278
44. Kronborg C, Vass M, Lauridsen J, Avlund K (2006) Cost effectiveness of preventive home visits to the elderly: economic evaluation alongside randomized controlled study. Eur J Health Econ 7:238–246
45. Schulz SE (2011) Alten- und Pflegeheim Wiblingen. Senioren Centrum. Domicil. www.pflegeheim-haus-am-see.de, www.aphwtelebus.de, www.hausstiftstrasse.de, www.domicil-seniorenresidenzen.de.
46. Hujanen T, Kapiainen S, Tuominen U, Pekurinen M (2008) Terveydenhuollon yksikkökustannukset Suomessa vuonna 2006.
47. Kobelt G, Berg J, Lindgren P, Izquierdo G, Sanchez-Solino O, Perez-Miranda J, Casado MA (2006) Costs and quality of life of multiple sclerosis in Spain. Eur J Health Econ 7 Suppl 2:S65–S74
48. Garaiacu A (2011) Personal communication-National Health Insurance House.
49. Seniorville Nursing Home (2011) www.seniorville.sk
50. Health Insurance Institute of Slovenia (ZZZS) (2011) www.zzzs.si and Maja Tomšic, personal communication
51. Freyler P, Hungarian National Health Insurance Fund OEP (2011) Personal communication.
52. IMS Health (2010) IMS data on pharmaceutical sales 2010.
53. International Osteoporosis Foundation (IOF) (2011) Osteoporosis in the European Union in 2008: Ten years of progress and ongoing challenges. IOF, Nyon
54. The International Osteoporosis Foundation (IOF) (2011) Eastern European & Central Asian Regional Audit-Individual Country Reports. www.iofbonehealth.org/publications/eastern-european-central-asian-audit-2010.html;
55. NÖ Gebeitskrankenkasse (2011) Zusatzvereinbarung Honorarordning 2009. Accessed June 2011, www.noegkk.at
56. Hauptverband und Österreichischen (2011) Hauptverband und Österreichischen, Accessed July 2011. www.hauptverband.at/portal27/portal/hvbportal/emed/
57. INAMI-RIZIV Institut national d’assurance maladie-invalidité (2011) Accessed June 2011. http://www.inami.fgov.be/insurer/fr/rate/pdf/last/doctors/rx20110601fr.pdf
58. Vatkova J (2011) National Health Insurance Fund in Bulgaria. Personal communication
59. Ministry of Health Bulgaria (2011) http://www.mh.government.bg/Articles.aspx?lang=bg-BG&pageid=383&categoryid=3999. Accessed June 2011
60. Ministry of Health, Cyprus (2011) www.moh.gov.cy. Accessed June 2011
61. SÚKL State Institute for Drug Control in Czech Republic (2011) Accessed in June 2011. www.sukl.eu/
62. The Danish Ministry of Health (2000) Takstsystem 2011 ISBN 978-87-7601304-2:
63. Danish Medicines Agency (2011) Accessed July 2011. http://www.medicinpriser.dk
64. Estonian Health Insurance Fund (2011) Available at Riigi Teataja. www.riigiteataja.ee/akt/121062011024#para121062011017
65. Estonian Medicine Information (Raviminfo) (2011) Accessed August 2012. http://www.raviminfo.ee/otsing.php
66. The Social Insurance Institution of Finland (2011) Accessed July. http://kela.fi/
67. Saraux A, Brun-Strang C, Mimaud V, Vigneron AM, Lafuma A (2007) Epidemiology, impact, management, and cost of Paget’s disease of bone in France. Joint Bone Spine 74:90–95
68. Vidal-pro (L’information de référence sur le médicament) (2004).
69. Lordick F, Ehlken B, Ihbe-Heffinger A, Berger K, Krobot KJ, Pellissier J, Davies G, Deuson R (2007) Health outcomes and cost-effectiveness of aprepitant in outpatients receiving antiemetic prophylaxis for highly emetogenic chemotherapy in Germany. Eur J Cancer 43:299–307
70. Rote Liste (2011) www.rote-liste.de
71. IKA Social Insurance Instiute G (2011) Accessed July 2012. http://www.ika.gr/
72. Hellenic Association of Pharmaceutical Companies (2011) SFEE. Accessed July 2011. www.sfee.gr
73. Hungarian National Health Insurance Fund (OEP) (2011) Communication with Petra Freyler. www.oep.hu
74. Database CED (2011) Accessed June 2012. www.cedd.oep.hu
75. Irish Osteoporosis Society (2011) Personal communication Michele O’Brien, August 2011 and www.irishosteoporosis.ie
76. Gillespie P, O’Shea E, Murphy AW, Byrne MC, Byrne M, Smith SM, Cupples ME (2010) The cost-effectiveness of the SPHERE intervention for the secondary prevention of coronary heart disease. Int J Technol Assess Health Care 26:263–271
77. Capri S, Perlini S (2005) Cost-effectiveness in Italy of preventive treatment with ramipril in patients at high risk of cardiovascular events. Curr Med Res Opin 21:913–921
78. Agenzia Italiana del Farmco (2011) www.agenziafarmaco.it
79. Health Payment Center in Latvia (VNC) (2011) communication with Toms Noviks August, 2011. http://www.vnc.gov.lv/
80. Health RoL-Mo (2011) Lithuanian National Health Insurance Fund under the Ministry of Health. www.vlk.lt
81. Caisse Nationale de Santé Luxembourg (2011) www.cns.lu
82. Ministry for Health (2011) Elderly and Community Care, Malta. Mater Dei Hospital price. www.sahha.gov.mt,
83. Malta Competition and Consumer Affairs Authority (2011) www.msa.org.mt and personal communication with Gianpiero Fava
84. The Dutch Healthcare Authority (NZa) (2011) Accessed August 2012. www.nza.nl
85. Health Care Insurance Board’s medicine price list (2011) Accessed August. www.medicijnkosten.nl
86. Dal NR, Piskorz P, Vives R, Guilera M, Sazonov K, V, Badia X (2007) Healthcare utilisation and costs associated with adding montelukast to current therapy in patients with mild to moderate asthma and co-morbid allergic rhinitis: PRAACTICAL study. Pharmacoeconomics 25:665–676
87. Portal da Saudé Portugal (2011) Accessed in July 2012. www.portaldasaude.pt
88. Secretaria-Geral Ministério da Saudé Portugal (2011) Communication with Lina Freitas. http://www.sg.min-saude.pt/
89. National Authority of Medicines and Health Products Portugal (2011) Accessed July 2012. http://www.infarmed.pt/
90. Casa de Asagurari de Sanatate a Municipiului Bucuresti (2011) Accessed August, 2011. http://www.casmb.ro/
91. Casa National de Asigurari de Sanatate (2011) Accessed August, 2011. http://www.cnas.ro/medicamente/lista-medicamentelor-2011
92. Portal Farma (2011) www.portalfarma.com
93. FASS (2009) www.fass.se
94. Curtis L (2008) Unit Costs of Health and Social Care, Personal Social Services Research Unit, University of Kent, www.pssru.ac.uk/project-pages/unit-costs/2010/index.php. Accessed Dec 2010
95. British National Formulary (2011) http://www.bnf.org/bnf/
96. Kobelt G (2002) Health Economics: An introduction to economic evaluation. Office of Health Economics, London
97. Szende A, Oppe M, Devlin N EQ-5D Value Sets: Inventory, Comparative Review and User Guide. In Springer (ed) Series: EuroQol Group Monographs, Vol 2
98. WHO (2003) The burden of musculoskeletal conditions at the start of the new millennium.
99. Borgstrom F, Lekander I, Strom O, et al. (2013) The International Costs and Utilities Related to Fractures Study (ICUROS) - Quality of Life During the First 4 Months After Fracture. Osteoporos Int 24: 811–23
100. Peasgood T, Herrmann K, Kanis JA, Brazier JE (2009) An updated systematic review of Health State Utility Values for osteoporosis related conditions. Osteoporos Int 20:853–868
101. Borgstrom F, Johnell O, Kanis JA, Oden A, Sykes D, Jonsson B (2004) Cost effectiveness of raloxifene in the treatment of osteoporosis in Sweden: an economic evaluation based on the MORE study. Pharmacoeconomics 22:1153–1165
102. Kanis JA, Oden A, Johnell O, De Laet C, Jonsson B (2004) Excess mortality after hospitalisation for vertebral fracture. Osteoporos Int 15:108–112
103. Parker MJ, Anand JK (1991) What is the true mortality of hip fractures? Public Health 105:443–446
104. OTosteson AN, Gottlieb DJ, Radley DC, Fisher ES, Melton LJ, III (2007) Excess mortality following hip fracture: the role of underlying health status. Osteoporos Int 18:1463–1472
105. Gauthier A, Kanis JA, Jiang Y, Martin M, Compston JE, Borgstrom F, Cooper C, McCloskey EV (2011) Epidemiological burden of postmenopausal osteoporosis in the UK from 2010 to 2021: estimations from a disease model. Arch Osteoporos 6:179–188
106. Hirth RA, Chernew ME, Miller E, Fendrick AM, Weissert WG (2000) Willingness to pay for a quality-adjusted life year: in search of a standard. Med Decis Making 20:332–342
107. WHO Commission on Macroeconomic Health (2001) Macroeconomics and Health: investing in health for economic development. Report of the Commission on Macroeconomics and Health.
108. Murray C, Lopez A (1996) Global and regional descriptive epidemiology of disability. Incidence, prevalence, health expectancies and years lived with disability. In Murray C, Lopez A (eds) The global burden of disease: a comprehensive assessment of mortality and disability from diseases, injuries and risk factors in 1990 and projected to 2020. Cambridge University Press, Cambridge, pp 201–246
109. Eichler HG, Kong SX, Gerth WC, Mavros P, Jonsson B (2004) Use of cost-effectiveness analysis in health-care resource allocation decision-making: how are cost-effectiveness thresholds expected to emerge? Value Health 7:518–528
110. Zethraeus N, Borgstrom F, Strom O, Kanis JA, Jonsson B (2007) Cost-effectiveness of the treatment and prevention of osteoporosis—a review of the literature and a reference model. Osteoporos Int 18:9–23
111. Kanis JA, Adams J, Borgstrom F, Cooper C, Jonsson B, Preedy D, Selby P, Compston J (2008) The cost-effectiveness of alendronate in the management of osteoporosis. Bone 42:4–15
112. Borgstrom F, Jonsson B, Strom O, Kanis JA (2006) An economic evaluation of strontium ranelate in the treatment of osteoporosis in a Swedish setting: Based on the results of the SOTI and TROPOS trials. Osteoporos Int 17:1781–1793
113. Gustavsson A, Svensson M, Jacobi F, et al. (2011) Cost of disorders of the brain in Europe 2010. Eur Neuropsychopharmacol 21:718–779
114. Leal J, Luengo-Fernandez R, Gray A, Petersen S, Rayner M (2006) Economic burden of cardiovascular diseases in the enlarged European Union. Eur Heart J 27:1610–1619
115. Pugliatti M, Beghi E, Forsgren L, Ekman M, Sobocki P (2007) Estimating the cost of epilepsy in Europe: a review with economic modeling. Epilepsia 48:2224–2233
116. Wancata J, Musalek M, Alexandrowicz R, Krautgartner M (2003) Number of dementia sufferers in Europe between the years 2000 and 2050. Eur Psychiatry 18:306–313
117. National Institutes of Health (2011) NIH Estimates of Funding for Various Research, Condition and Disease Categories.
118. Cooper C, Cole ZA, Holroyd CR, Earl SC, Harvey NC, Dennison EM, Melton LJ, Cummings SR, Kanis JA (2011) Secular trends in the incidence of hip and other osteoporotic fractures. Osteoporos Int 22:1277–1288
119. Palvanen M, Kannus P, Niemi S, Parkkari J (2010) Secular trends in distal humeral fractures of elderly women: nationwide statistics in Finland between 1970 and 2007. Bone 46:1355–1358
120. Balasegaram S, Majeed A, Fitz-Clarence H (2001) Trends in hospital admissions for fractures of the hip and femur in England, 1989–1990 to 1997–1998. J Public Health Med 23:11–17
121. Icks A, Haastert B, Wildner M, Becker C, Meyer G (2008) Trend of hip fracture incidence in Germany 1995–2004: a population-based study. Osteoporos Int 19:1139–1145
122. Boereboom FT, de Groot RR, Raymakers JA, Duursma SA (1991) The incidence of hip fractures in The Netherlands. Neth J Med 38:51–58
123. Pentek M, Horvath C, Boncz I, Falusi Z, Toth E, Sebestyen A, Majer I, Brodszky V, Gulacsi L (2008) Epidemiology of osteoporosis related fractures in Hungary from the nationwide health insurance database, 1999–2003. Osteoporos Int 19:243–249
124. Dimai HP, Svedbom A, Fahrleitner-Pammer A, Pieber T, Resch H, Zwettler E, Chandran M, Borgstrom F (2010) Reversal in the secular trend of hip fracture incidences in Austria. Wien Klin Wochenschr 122:380–381
125. Hernandez JL, Olmos JM, Alonso MA, Gonzalez-Fernandez CR, Martinez J, Pajaron M, Llorca J, Gonzalez-Macias J (2006) Trend in hip fracture epidemiology over a 14-year period in a Spanish population. Osteoporos Int 17:464–470
126. Becker C, Cameron ID, Klenk J, Lindemann U, Heinrich S, Konig HH, Rapp K (2011) Reduction of femoral fractures in long-term care facilities: the Bavarian fracture prevention study. PLoS One 6:e24311
127. Mahon P, Harvey N, Crozier S, Inskip H, Robinson S, Arden N, Swaminathan R, Cooper C, Godfrey K (2010) Low maternal vitamin D status and fetal bone development: cohort study. J Bone Miner Res 25:14–19
128. Javaid MK, Cooper C (2002) Prenatal and childhood influences on osteoporosis. Best Pract Res Clin Endocrinol Metab 16:349–367
129. United Nations Department of Economic and Social Affairs-Population Division (2011) World Population Prospects test. Data retrieved in November, 2011. http://esa.un.org/unpd/wpp/unpp/p2k0data.asp
5. Uptake of osteoporosis treatments
This chapter describes current and recent uptake of osteoporosis treatments in the European Union. Since data on the number of patients treated are not readily available in most European countries, international sales data (on volume in mg and value (€)) on drugs used for treatment of osteoporosis from IMS Health was used as a proxy. Sales data from 2001 to 2011 were analysed.
The drugs included in the analysis are alendronate, denosumab, etidronate, ibandronate, parathyroid hormone (PTH) 1–84, raloxifene, risedronate, strontium ranelate, teriparatide and zoledronic acid. Four of these drugs received marketing authorisation before 2001. The latest drug to come to market was denosumab in 2010.
The results are presented as sales and defined daily dosages (DDDs) per 100 of the total population. The number and proportion of the population above 50 years that was treated was also estimated and expressed in relation to the estimated number of patients considered eligible for treatment.
The key messages of this chapter are:
Alendronate is the most commonly prescribed agent, accounting for approximately a quarter of the total value of sales. In terms of DDDs, alendronate represents almost half of all DDDs used to treat osteoporosis in the European Union.
The treatment uptake of osteoporosis drugs has increased considerably during the study time, however, recently a slight decrease has been observed.
The volume in terms of value of sales has decreased more than the volume in terms of DDDs in the two most recent years, mostly due to the decreasing price of generic bisphosphonates.
Uptake of individual treatments differs between regions in Europe. In general, Southern Europe shows a higher uptake of osteoporosis drugs.
There is a large gap between the number of women who are treated compared to the proportion of the population that could be considered eligible for treatment based on their fracture risk.
5.1 Uptake of osteoporosis treatment
This section discusses the extent and type of osteoporotic drugs used in the respective countries of the European Union. In order to analyse the uptake of treatments in different countries, data on the number of patients currently treated, treatment type and treatment compliance in each country are required. Unfortunately, in most countries, individual patient data are not readily available and there are only a few European nations (e.g., the Nordic countries and the Netherlands) that hold sufficiently large databases to allow a detailed analysis on filled prescription at an individual level. In the absence of country- and patient-specific data on filled prescriptions, we utilised international sales data in order to compare treatment uptake and osteoporosis medication sales between countries and over time. A similar, but more extensive, data analysis has been performed for EU5 + Sweden report in a previous report . The analyses were conducted using international sales of osteoporosis drugs from IMS Health to estimate the use of osteoporosis treatment in the EU27 in value (€) and volume (DDD).
5.2 Data and methods
IMS Health data are currently the only source of comparative data on sales of pharmaceuticals at an international level. However, the data have a number of shortcomings. It is unlikely that 100 % of sales are captured in any country, but it is difficult to define the magnitude of underestimation. For some countries, it is known that part or all of hospital sales are omitted and that certain wholesalers or other channels of distribution are not included. Similarly, it is possible that sales are overestimated in some countries as a consequence of the sample of pharmacies and hospitals that provide data. Since IMS Health attempts to correct for under- and over-estimation, and in the absence of any additional information, we have refrained from any overall adjustment of the available sales figures.
Another difficulty may arise from parallel trade. Although drugs launched in the last two decades generally have a rather narrow price band across Europe, price control mechanisms, adaptation to distribution channels and currency fluctuations have created a price difference that give incentives for parallel trade. IMS Health adjusts the data for parallel trade but it is difficult to estimate the accuracy of these corrections. Also, not all countries have adjustments for parallel trade. The countries included in this report for which adjustments have been made are: Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Italy, the Netherlands, Poland, Spain, Sweden and the UK.
The number of patients treated is an important component in the analysis of treatment uptake. The IMS Health sales data allow the estimation of how many treatment years the sales volume can cover. However, not all patients are completely adherent to therapy, and such an approach would consequently result in an underestimation of the actual number of patients that have started a treatment since some patients only are treated for a part of the year. This has further implications for clinical outcome, and also means that the treatment effect is lower than that reported from clinical trials where persistence and compliance is high. To correct for suboptimal adherence, an adjustment factor was estimated from data from the Swedish Prescribed Drug Register (see below). The adjustment factor was employed irrespective of country because similar data were not readily available for any other country. The data from IMS Health were available as monthly number of defined daily doses (as defined by WHO, http://www.whocc.no/atc_ddd_index [DDDs]) sold per country, and the following steps were included in the estimations:
For comparisons of uptake between countries, the number of DDDs in each year was expressed as DDDs/100 of the population aged 50 years or above residing in the respective country . This analysis does not take into account that more women than men are treated, potentially overestimating treatment uptake in countries with a relatively high proportion of women over 50 years of age and vice versa. However, the proportion of women and men eligible for treatment that could be treated is assessed in a separate analysis.
Almost all osteoporosis drugs are prescribed to patients aged 50 years or older (97.2 % based on Swedish prescription data). Therefore, it was assumed that only patients 50 years or older were given osteoporosis treatments.
Population coverage is the proportion of the population at or above the age of 50 years in each country that could theoretically be covered by a full year of treatment based on the sales volume. It can be estimated by dividing the DDDs per 100 of the total population by 365 (alternatively 366 days in a leap year).
Based on an analysis of filled prescriptions from the Swedish Prescribed Drug Register between 2006 and 2009, it was estimated that the total volume of the prescription could cover 73 % of the total observed time (i.e., the sum of the days from treatment start to end of the year) for all patients that were prescribed an osteoporosis treatment during this period. This estimate was not found to vary with age. This factor was used to approximate the number of patients being treated during a year for all countries.
Additionally, to differentiate between men and women, it was assumed that 87 % of the sales were directed to women and 13 % to men. This assumption was made based on Swedish prescription data.
No data were available for Cyprus or Malta and these two countries were therefore excluded from all analyses of treatment uptake and population coverage.
5.3 Pharmacological treatment
There are a number of pharmacological options available in the European Union for the treatment of osteoporosis. Table 60 shows the year of introduction in Europe (EMA marketing authorisation) for the agents indicated for osteoporosis. The bisphosphonates were the first group of drugs to be approved, followed by the SERM raloxifene in 1998. In the 2000s, additional bisphosphonates as well as novel groups of drugs have become available. The patent of alendronate expired and generic versions of the drug became available in Europe in 2006. Also risedronate has been available in generic formulations since 2010.
The introduction of generic versions has, as expected, driven prices downwards, albeit by a different extent in different countries. The annual prices of generic alendronate and other medications indicated for osteoporosis are shown in Table 61. The prices differ markedly between the countries, e.g., the yearly price of generic alendronate ranges from €4 in the Netherlands to €327 in Cyprus, and generic risedronate from €19 in Belgium to €514 in Ireland.
5.4 Market shares
Data on estimated population-adjusted total sales and market shares, presented as sales of DDDs and in Euros, are shown in Figs. 33 and 34 for the time period 2001 through 2011 (and related to the size of the population). In terms of value, sales increased rapidly from 2001 to 2005; grew at a slower pace until 2008 and thereafter decreased. Over the entire period, the value of sales in the EU27 increased from approximately €344/100 persons aged 50 or above in 2001 to €883 in 2011. In terms of volume (DDDs per 100 person-years aged 50 or above) sales increased almost linearly until 2010 decreased slightly in 2011. The discrepancy between the development of sales in terms of value and volume was predominately driven by the decreased price of generic alendronate. DDDs per 100 person-years and value of sales for each drug and country are presented in the compendium of country specific summaries published concurrently with this report.
Fig. 33 Estimated market shares in EU27 2001–2011 (sales in Euros/100 persons aged 50 years or above)
Fig. 34 Estimated market shares in EU27 2001–2011 (DDDs/100 persons aged 50 years or above)
Estimated sales per product in 2010 measured both as DDDs and in Euros along with market shares are shown in Table 62. A comparison of market shares measured as sales and volume shows a substantially higher market share in terms of volume than in sales for alendronate, reflecting the low price of generic alendronate. Conversely, the effect of high price is seen with PTH and teriparatide, which have higher market shares in sales than in volume.
The estimated value of sales per region of the European Union (Northern, Western, Eastern and Southern Europe) for osteoporotic drugs is shown in Figs. 35 to 38. In Northern and Eastern Europe, sales per 100 persons aged 50 years or above were generally lower than the average for EU27, whilst the opposite was observed for countries from Western and Southern Europe.
Fig. 35 Estimated annual sales in Northern Europe 2001–2011 (€/100persons aged 50 years or above)
Fig. 36 Estimated annual sales in Western Europe 2001–2011 (€/100persons aged 50 years or above).
Fig. 37 Estimated annual sales in Eastern Europe 2001–2011 (€/100 persons aged 50 years or above)
Fig. 38 Estimated annual sales in Southern Europe 2001–2011 (€/100 persons aged 50 years or above).
The average cost per DDD by region is presented in Figs. 39 to 42. Across all regions, the average cost per DDD remained stable from 2001 to 2005 and subsequently decreased year on year until 2011. If inflation during these years is taken into account, the decrease would be even more marked.
The largest and smallest intra-region variation was observed in Eastern and Southern Europe, respectively. In Western Europe, cost per DDD was comparatively homogenous in 2001 but variation increased thereafter. A similar pattern, albeit less marked, was observed in Northern Europe. Much of the variation seen in the cost per DDD can be explained by the market penetration of generic alendronate. The most notable decrease in cost per DDD was observed in the UK (€1.64 in 2001 to €0.24 in 2011).
Fig. 39 Cost (€) per DDD in Northern Europe: average for all drugs
Fig. 40 Cost (€) per DDD in Western Europe: average for all drugs
Fig. 41 Cost (€) per DDD in Eastern Europe: average for all drugs
Fig. 42 Cost (€) per DDD in Southern Europe: average for all drugs
5.5 Population coverage
The population coverage estimations are calculated, as described in the Data and Methods section, using the DDDs sold per year adjusted by the proportion of the population over 50 years that could be treated. This estimate is subsequently adjusted for suboptimal compliance. For the European Union in total, there seems to be an increase up until 2008, followed by a subsequent plateau or even a decrease in population coverage. The uptake differs among the regions of the European Union, as is shown in Figs. 43 to 46. Generally, uptake is lower than the average for EU27 in Northern and Eastern Europe (exceptions being Ireland and to some extent Hungary), whilst Western Europe shows slightly higher population coverage. There is no country in Southern Europe that has a lower coverage than the EU27 average from 2010. In 2010, the proportion of persons, aged 50 years or more, potentially treated (assuming treatment for 73 % of the year) ranged from approximately 0.5 % in Bulgaria to 9.3 % in Spain.
Fig. 43 Estimated proportion (%) of the population 50 years or older treated in Northern Europe
Fig. 44 Estimated proportion (%) of the population 50 years or older treated in Western Europe
Fig. 45 Estimated proportion (%) of the population 50 years or older treated in Eastern Europe
Fig. 46 Estimated proportion (%) of the population 50 years or older treated in Southern Europe
5.6 Uptake of individual treatments
The uptake, measured by DDDs per 100 of the population aged 50 years or more stratified by country, is shown in the figures below. The countries are grouped into four regions as discussed above.
The general trend in the EU27 of the uptake of alendronate was an increase from 2001 to approximately 2008, followed by a plateau. A slight decrease was noted in 2011. This is in sharp contrast to statins, for example simvastatin, where after patent expiration the sales in volume more than doubled. In the UK, treatments for hypercholesterolaemia and osteoporosis have been available for a similar time period; simvastatin was introduced in 1989 and etidronate in 1992. Simvastatin and alendronate were the most prescribed products in their drug class prior to the introduction of cheap generic equivalents in 2003 and 2005, respectively. In 2007 there was, however, a 5-fold difference between peak annual drug spend on statins and osteoporosis drugs indicating significantly different levels of clinical activity in these two chronic diseases . There may be several reasons for the observed development. One is that there are fewer incentives to market the product or that better alternatives are available. This seems unlikely given the continued dominance of alendronate in the market and the contraction of the general market. A possible factor may be that persistence has reduced over time, and there is some evidence that generic formulations are associated with a greater frequency of adverse effects and poorer persistence than proprietary formulations . The factor that is likely to have affected the market, particularly the bisphosphonates, is the wide publicity given to rare side effects so that many doctors and patients are more frightened of the side effects than they are of the disease.
The three countries with the highest uptake of alendronate in 2010 were Hungary, Ireland and the UK with approximately 1.68, 1.17 and 1.14 million DDDs per 100 persons aged 50 years or above, respectively. The three countries with the lowest uptake in 2010 were Bulgaria, Lithuania and Slovakia (42, 74 and 75 DDDs per 100 persons aged 50 years or above, respectively). The difference between the country with the highest and the lowest uptake was thus 40-fold. However, it should be noted that sales from Hungary, for example, are not adjusted for parallel trade, which consequently could be a reason for the high numbers estimated for this country.
In Northern Europe, Baltic countries were below the average for the EU27 (Fig. 47) whereas Denmark, Ireland and the UK were above the average. Finland showed a three-fold increase in uptake between 2001 and 2006, followed by a decrease over the next 5 years, resulting in a below average uptake in 2011. The highest increase in uptake was observed in Denmark.
In Western Europe, except for Germany, most countries showed an above average uptake for most of the period (Fig. 48). Uptake in all countries decreased in recent years, so that in 2010, Germany, France and Luxemburg had a below average uptake in 2011.
In Eastern Europe, all countries except Hungary had lower uptake than the EU27 average (Fig. 49). The converse was noted for Southern Europe where all countries showed higher uptake than the EU27 average (Fig. 50). Slovenia and Portugal showed a marked decrease in the last few years.
Fig. 47 Uptake of alendronate in Northern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 48 Uptake of alendronate in Western Europe (DDDs per 100 persons aged 50 years or above)
Fig. 49 Uptake of alendronate in Eastern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 50 Uptake of alendronate in Southern Europe (DDDs/100 persons aged 50 years or above)
The latest drug to be introduced for treatment of osteoporosis was denosumab—a monoclonal antibody. It was introduced in 2010, and approved in nine EU countries the same year. In 2011, denosumab was sold in all countries except France, Greece and Portugal. The highest uptake in 2010 was observed in Denmark and Germany with uptakes of 8.4 and 6.4 DDD per 100 persons aged 50 years or above, respectively, and in 2011 in Slovakia (160 DDDs per 100 persons aged 50 years or above) (Fig. 51).
Fig. 51 Uptake of denosumab in 2010 (DDDs per 100 persons aged 50 years or above)
In 2011, etidronate was marketed in 11 EU countries. Overall, the uptake decreased markedly from 76 DDDs in 2001 per 100 persons aged 50 years or above to 3 DDDs per 100 persons aged 50 years or above in 2011. The phenomenon likely reflects the availability of new bisphosphonates with more robust evidence for efficacy. Sweden had the highest uptake of the countries in Northern Europe, whilst there was no uptake in Lithuania (Fig. 52). Of the countries in Western Europe, France followed the aggregated estimates for EU27, while there was higher uptake in Germany and the Netherlands and lower uptake than average in the other countries (Fig. 53). In Eastern Europe, etidronate was not marketed after 2005 (Fig. 54). Also in Southern Europe the uptake was low (Fig. 55). This decrease in uptake for etidronate may reflect the superior evidence that alendronate and other pharmacological therapies reduce fracture rates more than etidronate.
Fig. 52 Uptake of etidronate in Northern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 53 Uptake of etidronate in Western Europe (DDDs per 100 persons aged 50 years or above)
Fig. 54 Uptake of etidronate in Eastern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 55 Uptake of etidronate in Southern Europe (DDDs per 100 persons aged 50 years or above)
Since the first approval of ibandronate for treatment of osteoporosis in 2005, the uptake increased in all countries (except for Sweden where ibandronate is not available for the treatment of osteoporosis) (Figs. 56–59). The highest uptake in 2010 was seen in Spain, Greece and Slovenia (438, 426, and 407 DDDs per 100 persons aged 50 years or above, respectively). Apart from Sweden, Austria (2.2 DDDs per 100 persons aged 50 years or above), Hungary (15.1 DDDs per 100 persons aged 50 years or above) and Germany (30.6 DDDs per 100 persons aged 50 years or above) show the lowest uptake in 2010. When estimating the uptake of ibandronate, only prescriptions for osteoporosis and not cancer related treatment were considered.
Fig. 56 Uptake of ibandronate in Northern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 57 Uptake of ibandronate in Western Europe (DDDs per 100 persons aged 50 years or above)
Fig. 58 Uptake of ibandronate in Eastern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 59 Uptake of ibandronate in Southern Europe (DDDs per 100 persons aged 50 years or above)
5.6.5 PTH (1–84)
The first sales of PTH were registered in 2006. PTH (1–84) is the recombinant full-length PTH protein (amino acids 1–84), in contrast to teriparatide, which comprises the first 34 amino acids of PTH. In 2011, PTH was sold in 16 out of 27 countries in the European Union. In 2010, the highest uptake was observed in Greece, followed by Denmark and Slovakia (11.2, 4.8. and 4.4 DDDs/100 persons aged 50 years or above, respectively) (Figs. 60–63).
Fig. 60 Uptake of PTH in Northern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 61 Uptake of PTH in Western Europe (DDDs per 100 persons aged 50 years or above)
Fig. 62 Uptake of PTH in Eastern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 63 Uptake of PTH in Southern Europe (DDDs per 100 persons aged 50 years or above)
In the European Union, the uptake of raloxifene increased from 2001 to 2005 and then decreased continuously. Raloxifene has been shown to increase the risk of venous thromboembolic events when compared to controls. On the other hand, beneficial effects on the risk of breast cancer were seen . The uptake of raloxifene was highest in Spain throughout the time period studied, followed by France and Portugal (232, 202, and 167 DDDs per 100 persons aged 50 years or above, respectively, in 2010). Latvia and Estonia had virtually no uptake of this drug. By region, the uptake was highest in Southern Europe and lowest in Northern and Eastern Europe (Figs. 64 to 67).
Fig. 64 Uptake of raloxifene in Northern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 65 Uptake of raloxifene in Western Europe (DDDs per 100 persons aged 50 years or above)
Fig. 66 Uptake of raloxifene in Eastern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 67 Uptake of raloxifene in Southern Europe (DDDs per 100 persons aged 50 years or above)
The uptake of risedronate increased rapidly between 2001 and 2006 but has not changed substantially between 2006 and 2010 when studied at the level of the European Union, although a slight downward trend is evident in later years (Figs. 68–71). In individual countries, uptake is seen both to increase (e.g., in Slovakia, Spain and Greece) and decrease substantially (e.g., in Austria, Germany and Portugal) over the last 5 years. The highest uptake in 2010 was seen in Spain (715 DDDs per 100 persons aged 50 years or above), Slovakia (606 DDDs per 100 persons aged 50 years or above) and Greece (603 DDDs per 100 persons aged 50 years or above) whilst the lowest was seen in Poland (9.7 DDDs per 100 persons aged 50 years or above), Bulgaria (18.9 DDDs per 100 persons aged 50 years or above) and Denmark (21 DDDs per 100 persons aged 50 years or above).
Fig. 68 Uptake of risedronate (DDDs per 100 persons aged 50 years or above) in Northern Europe
Fig. 69 Uptake of risedronate (DDDs per 100 persons aged 50 years or above) in Western Europe
Fig. 70 Uptake of risedronate (DDDs (per 100 persons aged 50 years or above) in Eastern Europe
Fig. 71 Uptake of risedronate (DDDs (per 100 persons aged 50 years or above) in Southern Europe
5.6.8 Strontium ranelate
Strontium ranelate showed a progressive increase in uptake in the European Union since its introduction on the market in 2004. This was also the case for most individual countries (exceptions being Latvia, Lithuania and Poland). The uptake by region is shown in Figs. 72 to 75. Although there was a continuous increase, most countries showed modest absolute uptake of strontium ranelate. Portugal had the highest increase and level of uptake (263 DDDs per 100 persons aged 50 or above in 2010). In Northern, Eastern and Western Europe, all countries but three had an uptake below the average European uptake. In Southern Europe on the other hand, all countries had an uptake above the European average.
Fig. 72 Uptake of strontium ranelate in Northern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 73 Uptake of strontium ranelate in Western Europe (DDDs per 100 persons aged 50 years or above)
Fig. 74 Uptake of strontium ranelate in Eastern Europe (DDDs (per 100 persons aged 50 years or above)
Fig. 75 Uptake of strontium ranelate in Southern Europe (DDDs per 100 persons aged 50 years or above)
Teriparatide is the more commonly used of the two PTH peptides available for treatment of osteoporosis (i.e., teriparatide and PTH). It is sold in all countries of the European Union except in Bulgaria. Even though there has been a steady increase in uptake of teriparatide since its introduction on the market in 2003, the absolute numbers remain low. Up until 2011, sales were highest in Greece (peaking at 54 DDDs per 100 persons aged 50 or above in 2009). In 2011, sales were highest in Spain, estimated at 41 DDDs per 100, persons aged 50 years or above, in 2010. The uptake per region is shown in Figs. 76 to 79. Compared to other regions, Eastern Europe had a low uptake of teriparatide.
Fig. 76 Uptake of teriparatide in Northern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 77 Uptake of teriparatide in Western Europe (DDDs per 100 persons aged 50 years or above)
Fig. 78 Uptake of teriparatide in Eastern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 79 Uptake of teriparatide in Southern Europe (DDDs per 100 persons aged 50 years or above)
5.6.10 Zoledronic acid
The uptake of zoledronic acid increased steeply since its approval for osteoporosis in 2005. Note that cancer-related use of zoledronic acid was not included in this analysis. Figures 80 to 83 show uptake of zoledronic acid in Northern, Western, Eastern and Southern Europe, respectively. The pattern of uptake was different with zoledronic acid compared to most other drugs, with highest uptake in Western and Eastern Europe and lowest in Northern and Southern Europe. The individual country with the highest uptake was Belgium, followed by Slovakia (196 and 156 DDDs per 100 persons aged 50 years or above in 2010, respectively). Luxembourg and Estonia had very low uptakes of zoledronic acid.
Fig. 80 Uptake of zoledronic acid in Northern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 81 Uptake of zoledronic acid in Western Europe (DDDs per 100 persons aged 50 years or above)
Fig. 82 Uptake of zoledronic acid in Eastern Europe (DDDs per 100 persons aged 50 years or above)
Fig. 83 Uptake of zoledronic acid in Southern Europe (DDDs per 100 persons aged 50 years or above)
Overall, these data indicate a decrease in the population coverage in the last 2 years (i.e., the proportion of the population treated at or above the age of 50 years). Also the pattern of drugs prescribed has changed over the 11 years studied (2001–2011). The population coverage varies substantially between countries. Ireland is the country where the highest proportion of the population over 50 years is treated, followed by Spain and Greece. The high numbers observed for Ireland and Greece could be a result of parallel trade, since the data from IMS Health were not corrected for this factor in these countries. The lowest proportions treated were found in Bulgaria, Romania and the Baltic States. In Bulgaria, 0.5 % of the population above 50 years is treated. This can be compared to population coverage of almost 9 % in Ireland. The uptake of etidronate and raloxifene was observed to decrease over the study period, whereas the uptake of all other treatments was generally observed to increase. As expected, the increase was highest for drugs approved within the study period. In all years of analysis, the drug with the highest uptake was alendronate. As mentioned in the Data and methods section however, all analyses should be interpreted with caution since the original sales data are imperfect.
The most disturbing finding is the plateau and downward trend in the number of patients being treated. The phenomenon is most marked in the case of the bisphosphonates (Fig. 84). As noted above, many doctors and patients are more frightened of the rare but serious side effects than they are of the disease. The substantial difference in prescribing for hypercholesterolaemia and osteoporosis may also arise because of inconsistent approaches to health technology assessment. For example, the 2008 NICE Technology Appraisals [27, 28] on osteoporosis treatments in the UK restricted access to more costly second-line agents other than generic alendronate until BMD was lower, the patient older or they developed more clinical risk factors. This was not the case for second-line statin therapies described in the relevant guidance (NICE TA 94). This inconsistency of recommendations in the two disease areas is surprising given the volume and costs incurred by the prescribing of non-generic statins by the NHS in England compared to that for bone remodelling agents.
Fig. 84 Estimated sales (DDDs/100 population aged 50+ years) from 2001 to 2011
5.7 Patients eligible for treatments and treatment gap
To estimate the proportion of patients treated out of those eligible for treatment, it is necessary to define an intervention threshold. There are several approaches to estimate intervention thresholds; they have traditionally been estimated on the basis of T-score for BMD with little consideration of cost-effectiveness. This approach is still largely reflected in the guidance in several European countries.
Efforts have also been made to develop intervention thresholds in osteoporosis treatment based on cost-effectiveness. In Europe, several studies have described the hip fracture probability at or over which treatment becomes cost-effective [29–32].
The advent of FRAX (www.shef.ac.uk/FRAX) in 2008 provided a clinical tool for the calculation of fracture probability which can be applied to the development of intervention thresholds . Application of FRAX in clinical practice provides a tool for determination of the fracture probability at which to intervene. This can be done using two approaches: firstly to translate the current practice in the light of FRAX and justify the thresholds developed by cost-effectiveness analyses or secondly, to determine the fracture probability at which intervention becomes cost-effective. The second approach has been used in North America [34, 35] whereas the former has been favoured in Europe.
The UK guidance for the identification of individuals at high fracture risk developed by the NOGG is an example of the translation of former guidance provided by the Royal College of Physicians (RCP) [36, 37] into probability based assessment . The RCP guidance indicates that women with a prior fragility fracture may be considered for intervention without the necessity for a BMD test, and the management of women over the age of 50 years on this basis has been shown to be cost-effective . For this reason, the intervention threshold set by NOGG was at the 10-year fracture probability equivalent to women with a prior fragility fracture without knowledge of BMD . Thus, the intervention threshold can be likened to a fracture threshold expressed in terms of fracture probability. The same intervention threshold was applied to men, since the effectiveness of intervention in men is broadly similar to that in women for equivalent risk. This translational approach from existing treatment guidelines is characterised by an intervention threshold that increases progressively with age. The major reason for this is that the source guidelines took little or no account of age. Since age is an important independent factor for fracture risk, the fracture probability of an individual with a prior fracture is higher at the age of 70 years than at the age of 50 years. This age-dependent increase in the intervention threshold is not found when intervention thresholds are derived from health economic analyses alone .
The NOGG guideline provides an opportunity to determine the burden of disease in terms of FRAX. In other words, to determine the number of individuals that have a 10-year fracture probability that is equivalent to or exceeds the fracture threshold (i.e., the age and country specific probability of fracture in a woman with a prior fragility fracture). The 10-year probability of a major osteoporotic fracture of women at the fracture threshold is provided for the countries of the European Union for different ages in Table 63. The fracture thresholds differ between countries due to the differences in fracture risk in the respective countries. For example, the fracture threshold at the age of 87 years ranged from a 10-year probability of 12 % (Bulgaria and Romania) to 46 % (Denmark). Note that FRAX models are not available for Bulgaria, Cyprus, Estonia, Latvia, Luxembourg and Slovenia. For these countries surrogate FRAX models were used (Romania, Malta, Lithuania, Lithuania, Belgium and Hungary, respectively). The surrogate countries were chosen on the likelihood that the fracture rate (and mortality) was similar to that of the index country.
The proportion of men and women who exceed the probability threshold for fracture can be computed by simulation based on the distribution of the risk-score among the cohorts used by WHO to develop FRAX and the epidemiology of fracture and death in each EU country. Tables 64 and 65 show the proportion of men and women with a probability of a major osteoporotic fracture exceeding that of a woman with a previous fracture and no other clinical risk factor, an average BMI and unknown BMD. This proportion, which in this report represents the proportion that could be eligible for treatment, varied between countries and by age and sex. The relative difference between countries was larger in men than in women. Greece and the UK appear to have the highest proportion of women falling above the fracture threshold, whilst the UK shows the lowest proportion of men. This variation across countries is caused by differences in fracture risk between women and men and differences in population prevalence of the risk factors used by FRAX.
Combined with UN data on population demography , the resulting number of persons with a fracture probability at or above the fracture threshold, and thus here regarded eligible for treatment, is shown for the countries of the European Union in Figs. 85 and 86.
Fig. 85 Number (in thousands) of men in each age group that have a 10-year probability for osteoporotic fracture above the probability threshold for fracture
Fig. 86 Number (in thousands) of women in each age group that have a 10-year probability for osteoporotic fracture above the probability threshold for fracture
5.8 Proportion of patients treated
Figures 87 and 88 show the number of men and women that could be treated for the year 2010 given sales in 2010 and adjusted for suboptimal adherence, compared to the remaining number of persons eligible for treatment according to risks described in the section above. The proportion of patients estimated to be eligible for treatment but not receiving treatment can be viewed as an approximation of the treatment gap. The treatment gap varies between countries, in accordance with different sales of anti-osteoporotic treatments as well as differences in fracture risk between countries. The highest treatment gap for women is noted for Bulgaria and the Baltic states, where less than 15 % of the population eligible for treatment receives an osteoporotic drug. The same countries, with the addition of Romania, also show the highest treatment gap for men.
Fig. 87 Estimated number (in thousands) of men treated (blue) and patients eligible for treatment that are not treated (red) in 2010
Fig. 88 Estimated number (in thousands) of women treated (blue) and patients eligible for treatment that are not treated (red) in 2010
All of the countries in the European Union have higher estimates for women that should be treated than the estimates of patients actually treated. The lowest treatment gap is seen for Spain, where sales are high and fracture risks relatively low, with approximately 75 % of the women eligible for treatment potentially treated. Other countries with low treatment gaps are Ireland and Hungary. More detailed data for men and women are shown in Table 66 and Table 67, respectively.
For men, the data indicate that the volume of sold osteoporosis drugs would be sufficient to cover treatment for more patients than the number that fall above the fracture threshold in Greece, Luxembourg and the UK. It should be noted, however, that the results from this analysis should be interpreted with some caution since it has been assumed that the distribution of drug use between genders observed in Sweden is valid for all countries. In addition, it is not known how well treatment is targeted to the high risk population. In total in the EU, 1.7 million men out of the 2.9 million men that exceed the risk level are not treated. Corresponding numbers for women are 10.6 million out of 18.4 million women exceeding the fracture threshold.
These analyses suggest that there is wide inter-country variation in the treatment penetration of women with higher risk for osteoporotic fractures. Large treatment gaps are identified in countries with populations of both high and low risks of fracture. The strength of the information based on IMS Health data is that information is available for nearly all EU member states. However, the pattern of use cannot be ascertained, so that it is not possible to determine whether treatment is targeted appropriately to high risk individuals. There are several indicators that suggest that the targeting of treatment is heterogeneous in the EU. Good evidence comes from the Global Longitudinal Study of Osteoporosis in Women (GLOW) which is a general practice based observational cohort study in women aged 55 years or more conducted in 10 countries, including several EU countries . In the EU, there was heterogeneity of treatment uptake between countries with the lowest proportion of women aged 55 years or more treated in the Netherlands (7 %) and the highest in Spain (23 %) (Fig. 89). Although treatment uptake was higher in women at very high risk (a prior hip or spine fracture), a minority (45 %) was receiving treatment in these countries. Again, there was heterogeneity in treatment uptake with a range from 36 % in the Netherlands to 57 % in Italy. Moreover, some low risk women were targeted in all countries.
Fig. 89 Proportion of women, included in the GLOW study, receiving treatment in six EU member states according to category of risk. All women refer to women aged 55 years or more (n = 24,249). Low risk comprises women aged less than 75 years with a T-score for BMD in the range of osteopenia, no prior fracture, no maternal hip fracture or osteoporosis (n = 1166). High risk refers to women reported to have a BMD measurement in the range of osteoporosis (n = 5258). Very high risk comprises women with a previous hip or spine fracture (n = 913) 
These data demonstrate that a large number of women at high risk of fractures are not receiving treatment, that a substantial number of women at low risk are prescribed treatment and that there are important differences in the uptake of treatment between countries.
The differences could not be explained by other clinical risk factors, and the regional difference in probability of treatment thus seems to have little correlation to existing evidence of best practice and cost-effectiveness.
Comparing data for Sweden from IMS Health and the Swedish Drug Register and Sales Data
To validate the data from IMS Health, a comparison of the data was made with data from the Swedish Prescribed Drug Register. Information on all filled prescriptions outside of the hospital setting are available from 2006 (available on the website of National Board of Health and Welfare [www.sos.se]). The database contains information on the number of patients filling a prescription, the number of prescriptions and the number of DDDs. Figure 90 shows the number of DDDs of alendronate sold as reported by the Swedish drug registry database and by IMS Health. These numbers correspond well with the data in this report, although IMS Health reports slightly higher numbers (2–3 %). Comparison of bisphosphonates used in cancer treatment is not as easily undertaken since only data from IMS Health discriminates the two indications.
Fig. 90 DDDs of alendronate sold in Sweden as reported by IMS Health and the Swedish Prescribed Drug Register
The sales of teriparatide, on the other hand, show a greater discrepancy between the numbers from the Swedish Prescribed Drug Register and IMS Health, and the trend is reversed with IMS Health data being 14–17 % lower than the numbers from the Swedish Prescribed Drug Register (Fig. 91). The reasons for these differences, however small, are not evident, since neither the data from IMS Health nor the Swedish registry data claim to take hospital use into account.
Fig. 91 DDDs of teriparatide sold in Sweden as reported by IMS Health and the Swedish Prescribed Drug Register
Using Swedish data from the National Board of Health and Welfare, it appears that treatment variation could exist within countries as well as between countries, suggesting a lack of evidence based treatment for osteoporosis on the national level: Among the 21 county councils in Sweden, the number of women aged over 50 years per 1,000 who filled at least on prescription of medications used to treat osteoporosis (ATC code M05B) in 2011 ranged from 36 to 63 (Fig. 92) with an average of 48.
Fig. 92 Number of women per (1,000) aged 50 years or above prescribed medication to treat osteoporosis (M05B)
This variation in prescription rates among counties does not appear to be explained by differences in fracture risk given that there were no significant correlations (r = −0.3 p = 0.9) between prescription and hip fracture rates (ICD-10 code S72) (Fig. 93).
Fig. 93 Correlation of hip fracture and prescription rates on county level in women aged 50 years or above in Sweden 2011
1. Strom O, Borgstrom F, Kanis JA, Compston J, Cooper C, McCloskey EV, Jonsson B (2011) Osteoporosis: burden, health care provision and opportunities in the EU: a report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Arch Osteoporos 6:59–155
2. Eurostat (2011) Statistics database. Data retrieved in November, 2011. http://epp.eurostat.ec.europa.eu,
3. Hauptverband der Österreichischen Sozialversicherungsträger (2011) Accessed July 2011, www.hauptverband.at/portal27/portal/hvbportal/emed/.
4. INAMI-RIZIV Institut national d’assurance maladie-invalidité (2011) Accessed June. http://www.inami.fgov.be/insurer/fr/rate/pdf/last/doctors/rx20110601fr.pdf
5. Ministry of Health Bulgaria (2011) http://www.mh.government.bg/Articles.aspx?lang=bg-BG&pageid=383&categoryid=3999. Accessed June, 2011.
6. Ministry of Health Cyprus (2011) www.moh.gov.cy. Accessed June 2011.
7. SÚKL State Institute for Drug Control in Czech Republic (2011) www.sukl.eu/ Accessed June 2011
8. Danish Medicines Agency (2011) http://www.medicinpriser.dk Accessed July 2011.
9. Estonian Medicine Information (Raviminfo) (2011) http://www.raviminfo.ee/otsing.php Accessed August 2011
10. The Social Insurance Institution of Finland (2011) http://kela.fi/ Accessed July 2011
11. Vidal-pro (2004) L’information de référence sur le médicament (2004) www.vidalpro.net
12. Rote Liste (2011) www.rote-liste.de Accessed June 2011
13. Hellenic Association of Pharmaceutical Companies (2011) SFEE. Accessed July 2011. www.sfee.gr
14. Database CEDD (2011) www.cedd.oep.hu Accessed June 2011
15. Agenzia Italiana del Farmco (2011) www.agenziafarmaco.it
16. Caisse National de Santé du Luxembourg (2011) www.cns.lu
17. Malta Competition and Consumer Affairs Authority (2011) www.msa.org.mt and personal communication with Gianpiero Fava
18. Health Care Insurance Board’s medicine price list (2011) www.medicijnkosten.nl Accessed August 2011
19. National Authority of Medicines and Health Products Portugal (2011) http://www.infarmed.pt/ Accessed July 2012
20. Casa National de Asigurari de Sanatate (2011) http://www.cnas.ro/medicamente/lista-medicamentelor-2011 Accessed August, 2011
21. Portal Farma (2011) www.portalfarma.com
22. FASS (2009) www.fass.se Accessed June 2011
23. British National Formulary (2011) http://www.bnf.org/bnf/
24. Mitchell PJ, Bayly JR (2009) A comparative analysis of drug prescribing and costs for osteoporosis and hypercholesterolaemia in England for 1998–2007. J Bone Miner Res 24, Suppl 1, :
25. Kanis JA, Reginster JY, Kaufman JM, Ringe JD, Adachi JD, Hiligsmann M, Rizzoli R, Cooper C (2012) A reappraisal of generic bisphosphonates in osteoporosis. Osteoporos Int 23:213–221
26. Barrett-Connor E, Mosca L, Collins P, Geiger MJ, Grady D, Kornitzer M, McNabb MA, Wenger NK (2006) Effects of raloxifene on cardiovascular events and breast cancer in postmenopausal women. N Engl J Med 355:125–137
27. National Institute for Health and Clinical Excellence (NICE) (2010) Osteoporosis- primary prevention. Alendronate, etidronate, risedronate, raloxifene and strontium ranelate for the primary prevention of osteoporotic fragility fractures in postmenopausal women: guidance 29 October 2008. Technology appraisal TA 160. www.nice.org.uk/guidance/TA160
28. National Institute for Health and Clinical Excellence (NICE) (2011) Osteoporosis- secondary prevention including strontium ranelate: guidance 29 October 2008. Technology appraisal TA 161. www.nice.org.uk/guidance/TA161
29. Borgstrom F, Johnell O, Kanis JA, Jonsson B, Rehnberg C (2006) At what hip fracture risk is it cost-effective to treat? International intervention thresholds for the treatment of osteoporosis. Osteoporos Int 17:1459–1471
30. Kanis JA, Oden A, Johnell O, Jonsson B, De Laet C, Dawson A (2001) The burden of osteoporotic fractures: a method for setting intervention thresholds. Osteoporos Int 12:417–427
31. Kanis JA, Johnell O, Oden A, De Laet C, Oglesby A, Jonsson B (2002) Intervention thresholds for osteoporosis. Bone 31:26–31
32. Kanis JA, Johnell O, Oden A, Borgstrom F, Johansson H, De Laet C, Jonsson B (2005) Intervention thresholds for osteoporosis in men and women: a study based on data from Sweden. Osteoporos Int 16:6–14
33. Kanis JA, McCloskey EV, Johansson H, Oden A, Melton LJ, III, Khaltaev N (2008) A reference standard for the description of osteoporosis. Bone 42:467–475
34. NOF (2003) Physicians Guide to prevention and treatment of osteoporosis. National Osteoporosis Foundation. Washington, DC
35. Tosteson AN, Melton LJ, III, Dawson-Hughes B, Baim S, Favus MJ, Khosla S, Lindsay RL (2008) Cost-effective osteoporosis treatment thresholds: the United States perspective. Osteoporos Int 19:437–447
36. Compston J, Cooper A, Cooper C, Francis R, Kanis JA, Marsh D, McCloskey EV, Reid DM, Selby P, Wilkins M (2009) Guidelines for the diagnosis and management of osteoporosis in postmenopausal women and men from the age of 50 years in the UK. Maturitas 62:105–108
37. Kanis JA, McCloskey EV, Johansson H, Strom O, Borgstrom F, Oden A (2008) Case finding for the management of osteoporosis with FRAX—assessment and intervention thresholds for the UK. Osteoporos Int 19:1395–1408
38. Kanis JA, Adams J, Borgstrom F, Cooper C, Jonsson B, Preedy D, Selby P, Compston J (2008) The cost-effectiveness of alendronate in the management of osteoporosis. Bone 42:4–15
39. United Nations Department of Economic and Social Affairs - Population Division (2011) World Population Prospects test. Data retrieved in November, 2011. http://esa.un.org/unpd/wpp/unpp/p2k0data.asp
40. Diez-Perez A, Hooven FH, Adachi JD, et al. (2011) Regional differences in treatment for osteoporosis. The Global Longitudinal Study of Osteoporosis in Women (GLOW). Bone 49:493–498
41. Hooven FH, Adachi JD, Adami S, et al. (2009) The Global Longitudinal Study of Osteoporosis in Women (GLOW): rationale and study design. Osteoporos Int 20:1107–1116