The application of health technology assessment in osteoporosis

Best Practice & Research Clinical Endocrinology & Metabolism xxx (2014) 1–16

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The application of health technology assessmentin osteoporosis

John A. Kanis, MD, Professor Emeritus a,*,Mickaël Hiligsmann, PhD, Assistant Professor b,1

aCentre for Metabolic Bone Diseases, University of Sheffield Medical School,Beech Hill Road, Sheffield S10 2RX, UKbDepartment of Health Services Research, School for Public Health and Primary Care (CAPHRI),Maastricht University, P.O. Box 616, 6200MD Maastricht, The Netherlands

Keywords:burden of diseasecost-effectivenesseconomic evaluationhealth technology assessmentosteoporosistreatment

* Corresponding author. Tel.: þ44 114 285 1109;E-mail addresses: [email protected] (J.A

1 Tel.: þ31 43 38 82 219; Fax: þ31 43 38 84 162

http://dx.doi.org/10.1016/j.beem.2014.04.0011521-690X/� 2014 Elsevier Ltd. All rights reserved

Please cite this article in press as: Kanassessment in osteoporosis, Best Practice &dx.doi.org/10.1016/j.beem.2014.04.001

Because of the high costs to patients, health care payers and tosociety, it is important to allocate healthcare resources appropri-ately and efficiently. Health technology assessment aims to eval-uate the clinical, economic, social, and ethical implications of adisease, and its prevention and treatment to guide nationalhealthcare policies (e.g. clinical and research investment, reim-bursement decisions). In this chapter, we review the various as-pects of health technology assessment in osteoporosis, includingepidemiology and burden of disease, and assessment of the cost-effectiveness of the treatment of osteoporosis and the preventionof fracture. Health technology assessment indicates an immenseburden of osteoporotic fractures for patients and society that is setto increase as the number of elderly people increases. Preventionand treatment of osteoporosis have been shown to be a cost-effective way of allocating scarce healthcare resources.

� 2014 Elsevier Ltd. All rights reserved.

Introduction

Osteoporosis is a major cause of fracture worldwide, most notably of the hip, spine, and forearm.Because of the high costs to patients, health care payers and to society, it is becoming increasinglyimportant to allocate healthcare resources appropriately and efficiently. Health technology assessment

Fax: þ44 114 285 1813.. Kanis), [email protected] (M. Hiligsmann)..

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is JA, Hiligsmann M, The application of health technologyResearch Clinical Endocrinology & Metabolism (2014), http://

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J.A. Kanis, M. Hiligsmann / Best Practice & Research Clinical Endocrinology & Metabolism xxx (2014) 1–162

(HTA) aims to evaluate the clinical, economic, social, and ethical implications of a disease and itsprevention and treatment to guide national healthcare policies (e.g. clinical and research investment,reimbursement decisions) [1]. The principal aim of HTA is to form a bridge between scientific experts inclinical practice and decision-makers in healthcare, in order to make the most appropriate use ofavailable resources. The ultimate target is the optimization of public health initiatives.

Scope of health technology assessment

According to the International Network of Agencies for Health Technology Assessment [2], HTA isthe systematic evaluation of “the medical, social, ethical and economic implications of development,diffusion, and use of health technology”. Its purpose is to support healthcare decisions and informpolicy-making through objective information at the local, national, or international levels. The aim ofHTA is to improve the quality of care by promoting an appropriate and rational use of healthcaretechnologies [3] and by facilitating the introduction and dissemination of new technologies.

HTA covers not only drugs, medical equipment, and devices, but also prevention, diagnostic, andtreatment procedures. HTA is conducted by interdisciplinary groups that use explicit analyticalframeworks [2]. The field of research was developed in the 1970 and 1980s in the USA and Europe, andhas spread to the rest of the world over the last two decades [4]. HTA government agencies are nowavailable in many countries. They have been established to provide advice to governments and toaddress the containment of healthcare costs and the assessment of the impact of new technologies [5].The organization of HTA and its influence on the public policy-making process can vary markedlybetween countries [6]. In addition, many research institutions are concernedwith HTA [7], for example,the National Health Service Centre for Reviews and Dissemination in the UK. In March 2014, the In-ternational Network of Agencies for HTA comprised 57 members from 32 countries.

HTA is increasingly used by regulatory agencies to authorize a drug, device or technology for marketor for reimbursement. HTA can also be used to support decision-making by clinicians and patients. Itmay also be used by other bodies, for example, by associations of health professionals, hospitals for theacquisition of new technologies, and by companies to aid product development and marketing de-cisions [2]. The application of HTA in osteoporosis is covered below, except where covered elsewhere inthis volume (i.e. the efficacy of interventions).

Burden of osteoporosis

The burden of osteoporosis in terms of epidemiology can be quantified in several ways. Examplesinclude the prevalence of osteoporosis as defined by bone mineral density (BMD), the incidence offracture, lifetime or 10 year probability of fracture, prevalence of prior fracture, cost of fractures andquality adjusted life years (QALYs) lost.

The burden of osteoporosis in the European Union (EU) has been extensively reviewed recently [8–10] and is summarised in Table 1. Using theWorld Health Organization (WHO) criteria for the diagnosisof osteoporosis, 22millionwomen and 5.5millionmen aged 50 years or morewere estimated to have aBMD T-score of less than�2.5 SD at the femoral neck (Table 1). The prevalence of osteoporosis was 6.6%inmen over the age of 50 years and 22.1% inwomen over the age of 50 years, giving a prevalence of 5.5%in the general population.

Several risk indicators for fracture have been studied at a pan-European level. A prior fracture is awell recognised risk factor for a further fracture, and the number of men and women in the EU with aprior fragility fracture has been estimated at 22.5 million [8]. The number of individuals at high risk canalso be assessed from FRAX, a country-specific tool to assess the 10-year probability of a major oste-oporotic fracture (http://www.shef.ac.uk/FRAX/) [11]. High risk individuals have been characterised asthose with a fracture probability equal to or greater than in awomanwith a prior fragility fracture. Thislevel of risk is adopted in several countries as an intervention threshold (e.g. [12]) and in Europeanguidelines [13,14]. In 2010, there were 2.85 million men and 18.44 million women whose fractureprobability lay at or above this threshold risk [8].

The number of new fractures in 2010 in the EU was estimated at 3.5 million, comprising approxi-mately 620,000 hip fractures, 520,000 vertebral fractures, 560,000 forearm fractures and 1,800,000

Please cite this article in press as: Kanis JA, Hiligsmann M, The application of health technologyassessment in osteoporosis, Best Practice & Research Clinical Endocrinology &Metabolism (2014), http://dx.doi.org/10.1016/j.beem.2014.04.001

http://www.shef.ac.uk/FRAX/

Table 1Key indicators of the burden of osteoporosis for 2010 in 27 countries of the European Union [8,9].

Epidemiological

Population at risk (men and women aged 50 years or more) 183,397,000Men and women with osteoporosis 27,519,790Prevalence of osteoporosis (% total EU population) 5.5Men and women with a prior hip or spine fracture 6,758,040Men and women with a prior fragility fracture 22,526,800Men and women at high fracture risk based on FRAXa 21,291,000New fragility fractures in 2010 3,492,058Deaths causally related to fracture in 2010 42,808QALYs lost due to death or disability in 2010 1,165087Cost-related (2010)Direct cost of fractures occurring in 2010 (V 000,000) 24,633Direct cost in 2010 of fractures occurring before 2010 (V000,000) 10,718Cost of medical intervention (V 000,000) 2051Total direct cost in 2010 (V 000,000) 37,402Direct cost/capita in 2010 (V) 75Cost of deaths and QALYs lost in 2010 (V 000,000)b 57,243

a 10-year probability of a major fracture that is equal to or exceeds that of a woman with a prior fragilityfracture.

b Value of a QALY set at 2 � gross domestic product.

J.A. Kanis, M. Hiligsmann / Best Practice & Research Clinical Endocrinology & Metabolism xxx (2014) 1–16 3

other fractures (i.e. fractures of the pelvis, rib, humerus, tibia [in women], fibula, clavicle, scapula,sternum and other femoral fractures) [8]. Thus, hip, vertebral, forearm and “other fractures” accountedfor 18%, 15%, 16% and 51% of all fractures respectively. Two thirds of all incident fractures occurred inwomen.

The direct costs of osteoporosis (or more accurately the cost of fractures that arise) in Europe wereestimated at V 37 billion [8]. This comprises the cost of the fractures that occurred in 2010 (V24.6billion in the EU), the ongoing cost in 2010 incurred by fractures that occurred before 2010 (V10.7billion), and the cost of intervention (V2.1 billion). It is of interest that the intervention costs (DXA, GPvisits and drugs) only contribute 6% of the total cost. In Table 1, the total cost is also computed per headof the population and averages V75 for each man, woman and child in the EU (the osteoporosis tax).

This type of analysis does not take into account the societal costs that arise from premature deathand disability. The quality adjusted life years (QALY) estimator is a useful outcome measurementbecause it captures the benefits from a reduction inmortality and from a reduction inmorbidity [15]. Inthis scheme, perfect health is assigned a value of 1 and death a value of 0. Thus a 50% disability for oneyear is given a value of 0.5 (e.g. after a hip fracture). Two years of such disability will thus result in theloss of 1 QALY. This is equivalent to the QALY lost by one year of premature death. Knowing theepidemiology of fracture, the health status (quality of life) of the population, the total QALYs lost can becalculated. The QALY status at one year following fracture is shown in Fig. 1.

In the EU, QALYs lost due to death or disability from osteoporotic fractures in 2010 were 1,165,087(Table 1). The next step is to value the QALY inmonetary terms. The starting point is to askwhat are you(or society) prepared to pay to prevent the loss of 1 QALY, usually termed the willingness to pay (WTP).The UK currently uses a WTP of £20,000 to £30,000 per QALY gained [17]. In other words, the UK isprepared to spend £20–30,000 for each QALY gained in the health care sector. Conversely a QALY lostcarries a value of the same amount in the UK. As an aside, the government will spend considerablymore in other sectors, for example in road or rail safety.

The valuation of health in the UK is not appropriate for all countries. It has been suggested WTPshould be set as a function of gross domestic product (GDP) to allow for variations in ability to paybetween countries. The WHO Commission on Macroeconomics and Health has suggested that oneaverted disability adjusted life year (DALY) can be valued at three times GDP per capita [18]. Thiscriterion has been used in health economics studies where interventions were judged to be very cost-effective with a cost per healthy life year gained of 1 � GDP per capita or less, and as cost-effectivewhen 3 � GDP per capita or less [19]. Whereas DALYs and QALYs are conceptually similar, they arebased on different methodologies and are therefore not directly comparable [20]. However, a

Please cite this article in press as: Kanis JA, Hiligsmann M, The application of health technologyassessment in osteoporosis, Best Practice & Research Clinical Endocrinology & Metabolism (2014), http://dx.doi.org/10.1016/j.beem.2014.04.001

Fig. 1. The comparative heath state values in patients before and one year after fracture [[16], with kind permission from SpringerScience and Business Media].


comparison of available estimates for different disease areas for the two outcome measures does notsuggest a substantial difference in practical terms. Consequently, several set the value of a QALY at2 � GDP per capita when assessing direct health care costs [8,21–23]. When QALYs are valued in thisway, this adds anotherV57.2 billion to the EU bill (Table 1) with a total cost of V94.6 billion per year. Inthis perspective the intervention costs are trivial (about 2% of the total cost).

The cost of osteoporosis by fracture type is shown in Fig. 2. Whereas hip fractures account for about17% of fractures in Europe, they account for the majority of costs.

Burden of disease across countries

These summary statistics from the EU hide a great deal of heterogeneity between countries [8,10].Heterogeneity arises because of differences in population size (e.g. Germany vs. Sweden), the incidence

Fig. 2. The number and cost of osteoporosis related fractures in the European Union (excluding value of QALYs lost costs and ofpharmacological intervention) by fracture site [8].



of fractures (e.g. Sweden vs. Spain), and differences in the cost of fractures and in the proportion of thehealth care budget devoted to osteoporosis. The age adjusted hip fracture incidence varies 3-fold in theEU (Fig. 3) and, on a worldwide basis, by more than 10-fold [10,24]. Reasons for the large variation infracture risk between countries are speculative, but, ecological studies have shown a weak but sig-nificant relationship between hip fracture risk and latitude and socio-economic prosperity [25]. Inaddition to fracture incidence, there is heterogeneity in mortality between countries. Both fracture riskand the death risk affect the probability of fracturewhich also varies markedly [24]. For example, at theage of 50 years, the remaining lifetime probability of hip fracture in men and women from Sweden is10.9% and 25.1%, respectively whereas in Poland the respective probabilities are 4.0% and 9.7% [10].Thus hip fracture probability is higher in men from Sweden than in women from Poland.

The delivery of health care for osteoporosis across Europe is not proportionate to the burden ofdisease and these inequalities have been formalised in a scorecard for osteoporosis [10].

Future planning of the burden of osteoporosis

Secular changes in life expectancy and birth rate are likely to change the number of elderly in-dividuals in different countries and thereby increase the need for resource allocation for diseasesassociated with ageing. In Europe the number of women aged 75 years or more will increase over aperiod of 15 years in all countries but varies by country ranging fromþ7% in Latvia to increases of over50% in Ireland and Cyprus. The increase is double or triple in the developing countries [26]. UnitedNations (UN) population projections over 15 years are relatively robust in that all men and women in2025 aged 50 years or more had already attained adulthood in 2010.

Since age is an important risk factor for fractures and the elderly population is projected to increasein the majority of countries, the burden of fracture is also likely to increase. Projections for Europeindicate that the number of osteoporotic fractures will increase by 28% from 3.5 million in 2010 to 4.5million in 2025 (Fig. 4). The direct cost will increase by 25% but varies by country. The total costincluding values of QALYs lost (valued at 2 � GDP per capita) in the EU27 will rise from V99 billion in2010 to V121 billion in 2025, corresponding to an increase of 22% [8].

These projections do not take account of secular trends, i.e. changes in the age and sex specificincidence of fracture that have risen in some countries, remain stable in others and decreased in a few[27]. Such trends have an important impact [28] and can be built into economic assessment.

Fig. 3. Annual incidence of hip fracture in women from countries of the EU age-standardized to the world population for 2010 [[10],with kind permission from Springer Science and Business Media].


Fig. 4. The percentage increase in the number of fragility fractures between 2010 and 2025 in the EU and its member states [[10],with kind permission from Springer Science and Business Media].


Notwithstanding, the relatively short-term increases in the elderly can inform healthcare policymakers on the future need for orthopaedic beds, orthopaedic surgeons and aftercare following fracture.This is an urgent matter in that it takes many years to open hospital beds and train orthopaedicsurgeons.

Economic evaluation of interventions

Over the past 15 years, new treatments have become available to prevent and treat osteoporosis.Systematic review of the clinical efficacy, effectiveness, and side effect profiles of these drugs is acrucial part in HTA. Good-quality systematic reviews of the evidence base for the efficacy and safety ofthese drugs are available [14,29–31]. The efficacy of specific interventions is also reviewed elsewhere inthis volume (JY Reginster) and will not be discussed further here. Coincident with the development ofeffective interventions, economic evaluation is as important a branch of HTA.

Where resources within the health-care sector are scarce, it is important to conduct health eco-nomic evaluations of treatment opportunities in order to determine priorities and thereby optimizehealth benefits for society. A component of the assessment may be the budget impact of a newtechnology using the approach described for the burden of disease, but the major focus is on cost-effectiveness. Many countries currently require economic evaluation as part of the reimbursementprocess for drugs. Indeed, cost-effectiveness is currently considered as the fourth hurdle in drugdevelopment, behind quality, safety, and efficacy [32]. Although the most common application ofeconomic evaluation is drug pricing and reimbursement [33], the implementation and viability of anyother health intervention (such as screening or information campaigns) also depends on their evalu-ation and their relative cost-effectiveness.

Methods of economic evaluation

The specific goal of the economic assessment of intervention is to compare two (or more) differentstrategies. One such strategy is to compare the consequences of treatment of a new agent with notreatment. With the increasing development of new drugs, there is a corresponding focus on thecomparison of a new drug against the old. This is not without problems in the context of osteoporosis.A major problem is that there are very few comparator studies that evaluate fractures as the primary



outcome. Hence the efficacy of each agent is taken from meta-analyses of RCTs versus placebo. Thebaseline characteristics, including fracture risk vary widely between studies and there is good reason tosuppose that responsiveness to an intervention differs according to the type of patient enrolled. Ex-amples are provided in the Fracture Intervention Trials (FIT) with alendronate [34,35] and the hipfracture studies with risedronate [36] where the relative risk reductions in active treatment armsvaried within strata of the same agent.

The fourmain types of economic evaluation all approach costs in the sameway, but differ in thewaythey approach outcomes [37]:

� Cost-minimization analysis is used where the consequences of two or more interventions arebroadly equivalent, and so the difference between them is limited to a cost comparison. Thisapproach is only meaningful for agents with similar efficacies or side effects, which is difficult toapply to a heterogeneous class like the osteoporosis drugs [[38] Kanis 2011].

� Cost-benefit analysis measures both costs and benefits in monetary terms. This approach aims todemonstrate that a program will yield to a net welfare gain, and ranks interventions according tothe net benefit they provide. The practical difficulties of measurement and valuing health benefitshave limited the use of this type of analysis in healthcare [39].

� Cost-effectiveness analysis (CEA) compares costs and outcomes expressed in a single dimension,such as fracture saved, BMD gained, or life-years gained. This poses problems in the context ofosteoporosis since the saving of a fracture has a different significance in the case of a forearmfracture than for a hip fracture. In addition, it is not possible to compare the cost-effectivenessacross disease areas for example, to compare the cost-effectiveness of a statin in cardiovasculardisease with a bisphosphonate in osteoporosis.

� Cost-utility analysis (CUA) is considered as a specific case of CEA where the outcome measure isexpressed in QALYs. As noted above, the QALY integrates the benefits from a reduction in mortalityand from a reduction in morbidity [15]. In addition, this approach allows comparison acrossdifferent health programs and diseases by using a generic unit of measure. For this reason, cost-utility is the most widely applied type of economic assessment.

There are different categories of costs that may or may not be included in an economic evaluation. Itis essential to specify and justify the perspective in which the analysis is undertaken. The most com-mon perspectives used are those of healthcare payers and society. The societal perspective is thebroadest, including direct and indirect medical costs, and is theoretically preferred [37]. However, mostlocal health care agencies recommend the use of a healthcare payer perspective.

Incremental cost-effectiveness assessment

The results of a CEA or CUA are usually expressed in terms of the incremental cost-effectivenessratio (ICER), which is defined as the difference in terms of costs between two interventions dividedby their difference in effectiveness. An ICER represents the additional cost of an intervention pereffectiveness unit (for example, life year saved or QALY gained) versus the comparator.

Thus, the incremental cost-effectiveness ratio (ICER) is:

ICER ¼ DCDE

¼ cost A� cost Beffectiveness A� effectiveness B

The results can be presented graphically on the cost-effectiveness plane (Fig. 5), where the differ-ence in effectiveness between intervention A and comparator B is represented on the horizontal axis,and the difference in cost on the vertical axis [40]. If A is located in quadrants II or IV, the choice isstraightforward: in quadrant II, intervention A is more effective and less costly than comparator B, andsaid to be dominant; in quadrant IV, intervention A is less effective and more costly than B, and shouldbe rejected. In quadrants I and III, there is no obvious decision; intervention A is either more effectiveand more costly than comparator B (quadrant I), or less effective and less costly (quadrant III). The


Fig. 5. Cost-effectiveness plane. The difference in QALYs gained between intervention A and comparator B is represented on thehorizontal axis, and the difference in cost on the vertical axis. The slope of the line between intervention A and comparator B is theincremental cost-effectiveness ratio (ICER). The dashed line represents the WTP threshold. See text for further explanation.


choicewill depend on themaximum amount the decision-maker is willing to pay (or willing to accept -WTA) for a unit of effect (for example, a fracture prevented or a QALY). The slope of the line betweenintervention A and comparator B is the ICER. As shown in Fig. 5, if intervention A falls below the WTPthreshold, then it is deemed cost-effective.

Willingness to pay

In order to draw conclusions about the intervention’s cost-effectiveness, a comparison of the ICER istherefore requiredwith a cost-effectiveness threshold, abovewhich the interventionwould be deemednot cost-effective (because the additional cost for an additional unit of effect is too high) and belowwhich it would be deemed cost-effective. As noted above, the UK uses a threshold of £20,000 to£30,000 per QALY gained. In the example in Fig. 5, treatment A is more costly but more effective thantreatment B but falls below the WTP threshold and deemed cost effective.

Models

Decision-analytic models have become a necessary feature for estimating the economic value ofhealth interventions. This is especially true in osteoporosis since the prevention of an osteoporoticfracture (in particular of the hip or vertebrae) has long-term consequences on costs and outcomes thatmay not be captured by trial data. Healthcare modelling involves the application of mathematicaltechniques to summarize available information about healthcare processes and their implications [41],usually with computer software. A model aims to represent the complexity of the process in a simpleand comprehensible form [42]. Modelling is useful to extrapolate beyond clinical trials, to combinemultiple sources of evidence, to incorporate epidemiological, clinical, and economic data, and thereforeto answer more relevant policy questions. In addition, modelling is also appropriate at the early stagesof the development of a new technology to inform research priorities bymodelling prior to initiation ofclinical trials.

Economic evaluations conducted in the field of osteoporosis are usually based on so-called Markovstate-transition models [15]. Markov models are particularly appropriate when a decision problem



involves a continuous risk over time, when the timing of events is important, and when events mayhappenmore than once [43], which is the case for osteoporosis. In a Markovmodel, a cohort of patientsis followed over time along mutually exclusive health states (such as “healthy”, fracture states, anddeath). At the end of a cycle, patients can move to another health state according to transition prob-abilities. Values (typically cost and utilities) are assigned to each state and expected values are thenobtained by summing costs and utilities across health states, weighted by the proportion of the numberof patients in each state, and then summing across cycles. To assess Markov models, either cohort orindividual simulation can be carried out. A microsimulation model follows one individual at a timethroughout the model. Due to the probabilistic structure of the model, there will be random variationin individual outcomes (called first-order uncertainty), which can be reduced by simulating a largenumber of patients. The major advantage of microsimulation is that a full patient history is recorded,which increases the reliability of the results and is currently largely compatible with the existing stateof the art, evidence-based literature [44]. The weakness of such models is that they require moresophisticated and detailed data than cohort-based models without necessarily improving accuracy.This was argued as a rationale for remaining with cohort modelling approaches in osteoporosis [15].

Sensitivity analysis

Models are only as good as their ability to represent real world. In order for the results and con-clusions of economic evaluation to be reliable and valid, it is crucial that the model and the data bothtranslate the reality of the disease as accurately as possible. Guidelines have been developed to increasethe quality and reliability of modelling [45]. These include the characterization of uncertainty usingappropriate statistical approaches. There could be a substantial amount of uncertainty in the modelvariables (and assumptions) and this should be explored using univariate and probabilistic sensitivityanalyses. Univariate sensitivity analyses assess the impact of single parameters on the results (whichcould be represented as a tornado diagram), whilst probabilistic sensitivity analyses examine the effectof the joint uncertainty surrounding the model variables. Cost-effectiveness acceptability curves(CEAC) can then be constructed and show the probability that the intervention is cost-effectivecompared with the alternative, for a range of decision-maker’s willingness to pay. An example ofthis is shown in Fig. 6. CEAC has been widely adopted to represent uncertainty in cost-effectivenessanalyses [46].

Fig. 6. Example of cost-effectiveness acceptability curves showing the probability of an osteoporosis treatment (alendronate) beingcost-effective compared with no treatment in women aged 70 years with prevalent vertebral fractures and/or osteoporosis as afunction of the decision maker’s willingness to pay per one QALY gained [47]. The shaded area shows the threshold range of cost-effectiveness accepted in the UK.



Cost-utility in osteoporosis

The number of published economic evaluations in osteoporosis has markedly increased over therecent years [15,48–57]. They have mainly concerned treatment [15,58,59] and screening strategies[15,49,60].

The osteoporosis market is today dominated by bisphosphonates, particularly alendronate, whichhave become the mainstay first-line choice given its proven efficacy and low price. Bisphosphonatesare generally found to be cost-effective in women with osteoporosis, regardless of whether theperspective is societal or not and if the modelling horizon is lifetime or shorter [15].

A pan-European study from 2004 estimated the cost-effectiveness of branded alendronate in ninecountries [61]. In this study alendronate was shown to be cost-saving compared with no treatment inwomen aged 70 years with osteoporosis (with and without previous vertebral fracture) from the Nordiccountries (Norway, Sweden, and Denmark). The cost-effectiveness of alendronate compared to no treat-ment was also within acceptable ranges in Belgium, France, Germany, Italy, Spain and the UK. However,with the rapid decline in the price of the generic alendronate, analyses based on a branded drug price havebecomeobsolete andwould requireanupdate. Forexample, in theabovementionedstudy theannualpriceof alendronate varied between V444/year (UK) to V651/year (Denmark). The current drug price foralendronate is less than V300/year in all countries and even as low as V12/year in the UK. Revisiting theanalysis using these prices would markedly improve the cost-effectiveness of generic alendronate. In amore recent study from2008[47], the cost-effectivenessof alendronate comparedwithnotreatmentusingagenericprice intheUKwasassessedbyusing theFRAXalgorithmfor fracture riskestimation.Alendronatewas in this analysis priced at £95/year and could be considered cost-effective in most age and risk groups(Table 2).

The cost-effectiveness of a range of treatments has also been evaluated inwomenwith a BMD valuemeeting or exceeding the threshold of osteoporosis. As seen in Table 3, the cost-effectiveness ofalendronate compared with no treatment was better than for the alternatives. This is mainly driven bythe drug price rather than because of differences in efficacy between treatments. Thus, the studysupports the view that alendronate should be considered as a first line intervention, at least in a UKsetting. Nevertheless, cost-effective scenarios were found for treatments other than alendronate,providing credible alternative options for patients unable to take alendronate. Similar conclusions have

Table 2Cost-effectiveness of alendronate (cost (£000)/QALY gained) in UK womenwith clinical risk factors according to age and T-scorefor femoral neck BMD [47].

T-score (SD)

Age 0 �1 �2 �3Prior fracture50 18.1 15.7 9.9 3.260 18.4 15.6 10.5 2.670 9.0 6.5 3.2 c.s.80 13.9 7.3 2.3 c.s.Family history50 16.3 14.7 11.1 5.960 15.7 14 10.4 5.970 9 6 1.8 c.s.80 5.1 c.s. c.s. c.s.Glucocorticoids50 23.3 19.5 13.3 4.660 22.3 19.0 12.6 3.170 10.6 7.5 2.9 c.s.80 15.0 6.4 c.s. c.s.Rheumatoid arthritis50 21.1 22.6 15.4 6.260 25.1 21.1 14.4 6.370 11.5 8.4 4.4 c.s.80 15.7 7.8 1.9 c.s.

c.s. ¼ cost-saving.


Table 3Cost-per QALY gained (£) of various drugs compared to no treatment in women aged 70 years in the UK [47].

T-score ¼ �2.5 SD No BMD

Intervention No prior fracture Prior fracture Prior fracture

Alendronate 3714 867 2119Etidronate 12,869 10,098 9093Ibandronate daily 20,956 14,617 14,694Ibandronate intermittent 31,154 21,587 21,745Raloxifene 11,184 10,379 10,808Raloxifene without breast cancer 34,011 23,544 23,755Risedronate 18,271 12,659 13,853Strontium ranelate 25,677 18,332 19,221Strontium ranelate, post hoc analysis 18,628 13,077 13,673


also been reached in separate studies for most second line treatments [15,50,52,54,58,62–67]. Thereare differences, however, in the spectrum of efficacy of these alternatives across different fracture sitesthat will determine their suitability in the clinical management of individuals.

When considering the body of published evidence, fracture preventionwith alendronate inwomen atelevated risk of fracture older than 50 years is cost-effective inmost western countries. Cost-effectivenessimproves further in patients with additional risk factors. Fracture risk at a given T-score is similar in menandwomen [11], the effectiveness of intervention inmen is broadly similar to that inwomen at equivalentrisk, and the cost anddisutilityof fractures is similar inmenandwomen [16,68]. For these reasons the cost-effectiveness of treating menwill broadly be the same as for women at a given absolute risk of fracture.

Cost-effectiveness analyses between active comparators have started to appear in the osteoporosisliterature, as is the case for denosumab, strontium ranelate and zoledronic acid [69,70]. Indirectcomparisons of efficacy between drugs are less robust because of different baseline characteristics ofthe populations studied and overlapping confidence intervals for the effect of treatment [71]. Suchanalyses should therefore be interpreted with great caution.

Other economic applications of HTA

Recently, models have been developed to assess the economic impact of poor adherence withosteoporosis medications and the economic value of improving adherence [53,72–76]. These studiessuggest that, depending on their costs and effects on outcomes, interventions to improve adherence(e.g. education programs) could be cost-effective.

With the development of probability-based assessment guidelines, a recent development has beenthe incorporation of FRAX into health economic models [23,63,77–83]. The incorporation of FRAXenables the estimation of risk based on a wide range of clinical risk factors and evaluation of treatmentefficacy in populations at differing levels of risk [79]. The cost-effectiveness of drug treatments cantherefore be estimated in various types of patients with different combinations of clinical risk factors.An example is shown in Fig. 7 which examines the relationship between fracture probabilities and thecost-effectiveness for all possible combinations of the FRAX clinical risk factors at BMD T-scores be-tween 0 and -3.5 SD in 0.5 SD steps (512 combinations) with a BMI set to 26 kg/m2 [84]. Thus, this is nota population simulation, but a display of all possible combinations.

The point estimates for the correlations shown in Fig. 7 permit an estimate of the mean fractureprobability for any willingness to pay (WTP). There was rather little difference in the threshold atdifferent ages with a mean value of 7.0% with a WTP of £20,000/QALY. At a WTP of £10,000 the meanprobability threshold rose to 11.7% and at aWTP of £30,000 was 3.6%. Thus, with aWTP of £20,000, anyrecommendations for intervention should ensure that individuals have a fracture probability thatexceeds 7%. Such an approach has been used to validate treatment guidelines from an economicperspective [83,84]. As can be seen from Fig. 8, treatment scenarios developed for postmenopausalwomen or men aged 50 years or more in the UK were cost-effective. Many country-dependent factorscould have an impact on intervention thresholds, including fracture cost, intervention cost, and will-ingness to pay [54]. Intervention thresholds should therefore be determined on a per-country basis.


Fig. 7. Correlation between the ten-year probability of a major fracture and cost-effectiveness at the age of 50 years in women (BMIset to 26 kg/m2) comparing no treatment with alendronate. Each point represents a particular combination of BMD and clinical riskfactors [[84], with kind permission from Springer Science and Business Media].


A special need for the incorporation of FRAX into health economic models arises from studies thathave examined the interaction between FRAX-based probabilities with effectiveness. Two of these re-analyses of clinical trials data have shown greater efficacy against fracture in individuals at higher risktreated with clodronate or bazedoxifene [85,86] whereas others have shown benefit of strontiumranelate or raloxifene across a range of fracture probabilities (with greater absolute risk reductions inthose at higher risk) [82,87]. In a further pre-planned analysis of the FREEDOM trial, greater efficacyagainst fracture was shown in individuals at higher risk treated with denosumab [66]. The heatheconomic consequences can be illustrated when comparing the cost-effectiveness of the two selective

Fig. 8. Management chart for osteoporosis in the UK based on fracture probability. The darker shaded area in the left hand panelshows the limits of fracture probabilities for the assessment of BMD. The right hand panel gives the intervention threshold [[84],with kind permission from Springer Science and Business Media].



oestrogen receptor modulators, raloxifene and bazedoxifene. The overall effectiveness of these twoagents on vertebral fracture risk is rather comparable but the efficacy of bazedoxifene increases inwomen the higher the baseline fracture probability. In contrast the relative risk reduction with ral-oxifene is constant over the range of fracture probabilities studied. As a consequence, raloxifene hasbetter cost-effectiveness at low fracture probabilities whereas bazedoxifene has the better cost-effectiveness at high baseline fracture probabilities [77].

Summary and conclusions

An increasing number of economic studies have revealed a high economic burden of osteoporoticfractures, and this is expected to further increase in the future. This information will prove useful toestablish priorities between interventions/diseases and guide research priorities. Furthermore, eco-nomic analyses have suggested that recent advances in the prevention and treatment of osteoporosisincluding novel treatments, fracture risk assessment, and improved medication adherence are anappropriate and efficient way of allocating scarce healthcare resources. Such analyses may contributeto a more efficient healthcare system.

HTA is a rapidly evolving discipline. As more countries use HTA to inform healthcare decisions, theharmonization of HTA between jurisdictions has been discussed in order to avoid duplications of ef-forts [88]. Clinical data for new technologies usually applies across countries, but cost-effectiveness(and therefore appraisals of technologies for reimbursement) should be evaluated at a national levelbecause differences in the incidence of the disease, the availability of health resources, clinical practicepatterns, and relative prices may impact on cost-effectiveness [89]. The development of key principles[90] and good practices, as well as international collaborations between experts, could facilitate acommon process for the conduct of HTA for resource allocation decisions.

Despite the growth of HTA over the past decades, its overall impact on policymakingmay be limited[6]. The role of science is however to inform, not to dictate policy decisions. As recently argued thatscientific evidence alone is not sufficient basis for health policy and that other factors (such as dem-ocratic and human rights considerations) should be taken into consideration in health policy [91].

Practice points

� The societal burden of osteoporotic fractures is substantial and is expected to increase in the

future.

� The prevention and treatment of osteoporosis represents a cost-effective way of allocating

scarce healthcare resources.

� Cost-effectiveness studies in the field of osteoporosis should be country-specific.

� Medication adherence should be incorporated in cost-effectiveness analysis in osteoporosis.

� Analyses should be differentiating according to the individual fracture risk (using FRAX for

example).

Research agenda

� Data on the incidence of hip fracture are required for many countries.

� Data on the epidemiology of non-hip fractures are required for the majority of countries.

� Studies to assess the costs and outcomes impact of osteoporotic fractures are required (the

ICUROS study is in progress to provide this need).

� Effectiveness data from real-life studies are required to assess the real cost-effectiveness of

osteoporotic drugs.

� The effectiveness and cost-effectiveness of osteoporosis medications in male population

require further investigation.



Conflict of interest

JA Kanis has received consulting fees, advisory board fees, lecture fees, and/or grant support fromthe majority of companies concerned with skeletal metabolism.

M Hiligsmann has received research grants from Amgen, Novartis, Pfizer, Servier, SMB, andconsulting fees from Servier and SMB.

Acknowledgement

The text of this chapter is in part drawn from a review prepared by the Belgian Bone Club: 1Hiligsmann M, Kanis JA, Compston J, Cooper C, Flamion B, Bergmann P, Body JJ, Boonen S, Bruyere O,Devogelaer JY, Goemaere S, Kaufman JM, Rozenberg S, Reginster JY (2013) Health technology assess-ment in osteoporosis. Calcif Tissue Int. 93: 1-14. We thank the Belgian Bone Club and Springer Scienceand Business Media for permission to use extracts from this review.

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