Treat-to-target for Osteoporosis: Is Now the Time? E. Michael Lewiecki, Steven R. Cummings, and Felicia Cosman

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1 SPECIAL Position FEATURE Statement Treat-to-target for Osteoporosis: Is Now the Time? E. Michael Lewiecki, Steven R. Cummings, and Felicia Cosman New Mexico Clinical Research & Osteoporosis Center (E.M.L.), Albuquerque, New Mexico 87106; San Francisco Coordinating Center (S.R.C.), California Pacific Medical Center Research Institute and the Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California 94115; Regional Bone Center (F.C.), Helen Hayes Hospital, West Haverstraw, New York 10993; and Department of Medicine (F.C.), Columbia University College of Physicians and Surgeons, New York, New York Objectives: Current clinical practice guidelines identify patients at high risk for fracture who are likely to benefit from pharmacological therapy and suggest ways to monitor for effectiveness of therapy. However, there is no clear guidance on when fracture risk has been reduced to an acceptably low level. As a consequence, some patients at low risk for fracture may be treated for longer than necessary, whereas others at high risk for fracture may have treatment stopped when they might benefit from continuation of the same treatment or a change to a more potent therapeutic agent. The objective of this statement is to describe the potential clinical utility of developing a treat-to-target strategy for the management of patients with osteoporosis. Participants: We recommend that a task force of clinicians, clinical investigators, and other stakeholders in the care of osteoporosis explore the options, review the evidence, and identify additional areas for investigation to establish osteoporosis treatment targets. Evidence: Data from large, prospective, randomized, placebo-controlled registration trials for currently available osteoporosis therapies should be analyzed for commonalities of correlations between easily measured endpoints and fracture risk. Consensus Process: Osteoporosis experts, professional organizations, and patient care advocates should be involved in the process of developing consensus on easily measurable osteoporosis treatment targets that are supported by the best available evidence and likely to be accepted by clinicians and patients in the care of osteoporosis. Conclusions: A treat-to-target strategy for osteoporosis offers the potential of improving osteoporosis care by reducing the burden of osteoporotic fractures and limiting adverse effects of therapy. (J Clin Endocrinol Metab 98: , 2013) Many chronic diseases have well-defined treatment targets to assist physicians in disease management. This strategy is sometimes called treat-to-target or treat-to-goal. Risk-based treatment guidelines typically set a value for a biomarker that identifies individuals at high risk who require pharmacological treatment in addition to universally accepted nonpharmacological measures, then set a target for that biomarker that is associated with a reduced level of risk. A biomarker is a measurement that is an indicator of a physiological process, pathological process, or pharmacological response to an intervention (1). In the treatment of hypertension (blood pressure 140/90 mm Hg), for example, the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure has recommended a target blood pressure of 140/90 mm Hg to reduce the risk of cardiovascular disease, with a lower target of 130/80 mm Hg when diabetes or renal disease is also present (2, 3). The Coordinating Committee of the National Cholesterol Education Program recommends a target low-den- ISSN Print X ISSN Online Printed in U.S.A. Copyright 2013 by The Endocrine Society Received October 20, Accepted December 11, First Published Online January 21, 2013 Abbreviations: BMD, bone mineral density; BTM, bone turnover marker; DXA, dual-energy x-ray absorptiometry; LDL-C, low-density lipoprotein cholesterol; LSC, least significant change. 946 jcem.endojournals.org J Clin Endocrinol Metab, March 2013, 98(3): doi: /jc

2 doi: /jc jcem.endojournals.org 947 sity lipoprotein cholesterol (LDL-C) of 160 mg/dl in patients at low risk for coronary heart disease (0 1 risk factors), 130 mg/dl for moderate-risk patients (2 or more risk factors with 10-y risk 10%) and moderately high-risk patients (2 or more risk factors with 10-y risk 10 20%), and 100 mg/dl for high-risk patients (10-y risk 20%) (4); there is an optional goal of 70 mg/dl for moderately high and high-risk patients based on the findings of subsequent clinical trials with statin therapy (5). The American Diabetes Association recommends variable target hemoglobin A1C levels to reduce the risk of micro- and macrovascular complications in patients treated for diabetes, depending on individual patient factors: A1C 8% for patients with a history of severe hypoglycemia, limited life expectancy, advanced microvascular or macrovascular complications, and extensive comorbid conditions and for those with long-standing diabetes in whom the general goal of A1C 7% is difficult to attain; A1C 7% for many nonpregnant adults; and a more aggressive target of A1C 6.5% for selected patients, such as those with short duration of diabetes, long life expectancy, and no significant cardiovascular disease (6). Once the target for blood pressure, LDL-C, or A1C has been reached, the same treatment is usually continued unless an adverse effect is recognized or a superior treatment becomes available. When the underlying disease becomes less severe, as might occur with changes in diet, weight, or physical fitness, the dose or type of medication may require adjustment. Excessive treatment of hypertension and diabetes mellitus results in recognizable symptoms or signs (ie, hypotension and hypoglycemia, respectively) that require immediate medical attention. The intent of establishing treatment targets is to simplify and facilitate disease management decisions, thereby resulting in reduction in organ damage and improved clinical outcomes. There is good evidence that achieving treatment targets for hypertension (7), hypercholesterolemia (8), and diabetes mellitus type 1 (9) and type 2 (10) reduces the risk of cardiovascular events. Clinical practice guidelines that include treatment targets have been widely accepted and influential in clinical practice. Application of the treat-to-target principle has been so successful with these asymptomatic diseases that a similar paradigm has been adopted for rheumatoid arthritis, using a composite index of disease activity in 28 joints (DAS28) as one of the treatment targets (11). The treat-to-target paradigm has not been accepted by all. For example, treatment targets for LDL-C have been vigorously challenged by those who believe that the medical evidence is insufficient to support the targets, suggesting that individualized care may improve outcomes while reducing harms and costs (12). The theme of individualizing care through wise use of guidelines has been echoed by others (13). Individualized guidelines for the care of hypertension have been proposed, using risk calculators for myocardial infarction and stroke to rank people in decreasing order of expected benefit and then applying thresholds to the ranked list to achieve desired objectives (14). Some medications to reduce the risk of cardiovascular disease have no treatment target; as an example, aspirin has been recommended for all patients with coronary artery disease unless contraindicated, without a biomarker to assess success or failure of therapy (3). For osteoporosis, a common chronic condition that reduces bone strength and increases the risk of fractures, no treatment targets have been established, and the effects of overtreatment, if it occurs, are not easily recognized. Although the goal of pharmacological treatment of osteoporosis is to reduce fracture risk, there is no way to directly measure bone strength or fracture risk in an individual patient. Current clinical practice guidelines, such as those of the US National Osteoporosis Foundation (NOF) (15), offer helpful recommendations on selecting patients for starting treatment but do not provide a target that would inform the clinician and the patient when treatment has been successful. Since treat-to-target guidelines have aided clinicians in the management of a variety of chronic diseases, a similar strategy for osteoporosis might enhance efforts to reduce the risk of osteoporotic fractures. Osteoporosis Treatment Challenges Despite the availability of therapeutic agents proven to reduce fracture risk, osteoporosis remains a disease that is underdiagnosed and undertreated (16, 17). Adherence to therapy, when started, is often poor (18). Although there are well-established guidelines for selecting patients for bone mineral density (BMD) testing, assessing fracture risk, and initiating therapy to reduce fracture risk, the management of patients receiving therapy is less clear. Physicians who treat osteoporosis may have difficulty determining whether treatment is effective or not. As a consequence, patient management decisions are sometimes inappropriate (eg, a change in treatment when none is needed), expensive (eg, unnecessary laboratory tests, a change to a more expensive drug or unproven combination therapy), or even harmful (eg, a treatment change to a drug with greater risk of adverse effects or discontinuation of an effective drug in a patient with high fracture risk) (19). There are concerns regarding potential adverse effects of long-term therapy, particularly atypical femur fractures and osteonecrosis of the jaw, despite evidence that the

3 948 Lewiecki et al Treat-to-target for Osteoporosis J Clin Endocrinol Metab, March 2013, 98(3): benefits of therapy far outweigh the risks in appropriately selected patients (20). The concept of a bisphosphonate drug holiday has emerged as a way to minimize occurrences of atypical femur fractures and osteonecrosis of the jaw while still benefiting from fracture risk reduction due to persistence of antiresorptive effect from bisphosphonate retained in the skeleton (21). Different approaches to determining the optimal duration of bisphosphonate therapy have been recommended by osteoporosis experts (22 24). The prolonged antiresorptive effect after discontinuation of bisphosphonates is not encountered with other therapeutic agents and represents a unique challenge, and a potential benefit, for clinicians managing osteoporosis. Perhaps,ifosteoporosistreatmenttargetscouldbeidentified, physicians and patients might have a better understanding of when treatment has been effective (ie, reduction of fracture risk to an acceptable level), not so effective (ie, no reduction of fracture risk), or harmful (ie, adverse effect of treatment). This, in turn, hasthepotentialtooptimizethebalanceofbenefitandrisk with treatment and provide the greatest opportunity to reduce the burden of osteoporotic fractures. Monitoring Osteoporosis Therapy Evidenced-based clinical practice guidelines, such as those of the NOF (15), the American Association of Clinical Table 1. Potential Indicators of Suboptimal Response to Osteoporosis Therapy Indicator No change in BMD Decrease in BMD BMD initially increases but then remains stable Failure of BTM to change as expected (decrease with antiresorptive therapy, increase with osteoanabolic therapy) Failure to achieve an acceptable level of fracture probability Fracture Endocrinologists (25), and the North American Menopause Society (26), identify patients for BMD testing; provide recommendations for starting pharmacological therapy based on T-score, spine imaging for detection of vertebral fractures, and fracture risk assessment using algorithms such as FRAX; and suggest methods for monitoring the effects of therapy. Patients are typically monitored measuring BMD and/or a bone turnover marker (BTM) (27). Stability or improvement in BMD, a significant change of BTM (decrease with an antiresorptive agent, increase with an osteoanabolic agent), and the absence of a low trauma fracture are consistent with a favorable response to therapy (Table 1). A suboptimal response to therapy has been described as a statistically significant decrease in BMD (ie, a decrease that is equal to or greater than the least significant change [LSC], the smallest change in BMD that is statistically significant, calculated according to standard procedures) (28), failure of a BTM to respond as expected, or possibly 1 or more fragility fractures (29, 30), suggesting the need to reevaluate the patient and consider a change in therapy. However, many clinical uncertainties remain. For example, when BMD is stable but remains in the osteoporosis range after 3 to 5 years of bisphosphonate therapy (ie, fracture risk presumably remains high), should treatment be Comments This is sometimes perceived as a treatment failure, although clinical trials have shown that stability of BMD on therapy is associated with a reduction in fracture risk. A statistically significant BMD decrease is cause for concern and should trigger evaluation for contributing factors. Possible causes include poor adherence to therapy, malabsorption, and taking medications or developing a disease or condition with harmful skeletal effects. This is a typical response to treatment with bisphosphonates. When the BMD plateaus at a low level, it is not known whether a change in therapy that results in further increase in BMD provides additional antifracture benefit. Although BTMs may have a role in monitoring therapy, their use in clinical practice is confounded by factors that include assay variability and uncertainty on which BTM is best for each drug. BTM changes occur sooner than BMD changes. BTMs are not covered by some major health insurance companies in the United States. The goal of therapy is to reduce fracture risk. There is some evidence that FRAX generates a similar risk of major osteoporotic fracture in patients receiving prescriptions for oral antiresorptives. Other indices may be developed that are based on data from treated patients, taking into account changes on treatment. A fracture on therapy is an undesirable event that identifies the patient as being at higher risk for future fracture than previously recognized. When serial BMD tests or BTMs are used to assess response to therapy, the measurements must be technically valid and performed at a highquality facility. Precision assessment and calculation of the LSC is needed to distinguish measurement errors from changes that are likely to be clinically meaningful. If a fracture risk assessment tool such a FRAX is used, it must be validated in treated patients. Evidence of response to therapy is not necessarily the same as achieving a treatment target because a patient who is responding well may still have a risk of fracture that is higher than desirable.

4 doi: /jc jcem.endojournals.org 949 stopped, continued, or changed? If treatment is stopped, when, if ever, should it be restarted, and if treatment is changed, what other drug(s) should be used? If BMD is greatly improved with treatment and fracture risk is no longer unacceptably high, should treatment be stopped, and for how long? Similar questions could be asked with regard to BTMs. When a low trauma fracture occurs on therapy, when does it represent a failure of treatment and when is it simply a fracture that occurred despite effective treatment (recognizing that treatments reduce fracture rates by about 50%, but do not eliminate fractures)? Current clinical practice guidelines do not provide a treatment target (eg, BMD, T-score, BTM value, or level of fracture risk) to determine when treatment has been effective (ie, satisfactory reduction in fracture risk). The lack of an osteoporosis treatment target, combined with widespread misperceptions of the balance of expected benefit and potential risks of treatment, may be contributing to the osteoporosis treatment gap, the difference between the number of patients who would benefit from treatment and the number that actually receive it (31). Establishment of an osteoporosis treatment target requires supporting medical evidence and consensus of the osteoporosis scientific community. The potential benefit for patient care is improved clinical outcomes through more effective use of limited healthcare resources. The prevailing paradigm of treating patients at high risk for fracture in order to reduce fracture risk (32, 33) suggests that treatment should be changed when fracture risk reduction is not achieved. Similarly, when treatment has greatly reduced fracture risk, perhaps treatment may be discontinued, at least temporarily, particularly when the drug has a prolonged effect after discontinuation. Another paradigm in the management of skeletal health involves the prevention of osteoporosis in order to avoid irreversible degradation of bone microarchitecture, with a goal of reducing fracture risk over a time scale beyond 10 years. The prevention strategy usually involves nonpharmacological therapy but does not exclude the use of pharmacological agents, especially those that are inexpensive and associated with very low risk. Regardless of the time horizon for achieving treatment goals, it is arguably helpful for physicians to have a well-defined target(s) that serves as a marker for treatment effect. Potential Measurements for Osteoporosis Treatment Targets The ideal measurement for an osteoporosis treatment target is one that is evidence-based, simple, widely available, inexpensive, achievable with therapy, associated with a reduction in fracture risk, understandable for physicians and patients, and applicable for men and women of all ethnicities worldwide. When treatment is started, the target should be clear to the patient, as with other chronic asymptomatic diseases. It could be a single treatment target for all patients or a choice of targets that vary according to patient factors such as age, baseline BMD, T-score, or level of fracture risk. It is highly unlikely that any measurement can satisfy all of these criteria, and it may not be possible to achieve consensus on any treatment target(s). However, if an acceptable treatment target could be found, it might serve to advance the care of osteoporosis and reduce the treatment gap. Several potential treatment targets are listed in Table 2 and described below. Bone mineral density The most intuitive treatment target is a measurement that is the same as is used for diagnosis, such as a target blood pressure value for a patient whose hypertension is diagnosed by measuring blood pressure. Because osteoporosis is diagnosed according to BMD expressed as a T-score, using criteria established by the World Health Organization (WHO) (34), this strategy would suggest a T-score as a treatment target. A T-score target might be absolute (eg, T-score 2.0), relative (eg, improved by 10% or 1.0 T-score units compared to pretreatment), categorical (eg, a change in WHO diagnostic classification from osteoporosis to osteopenia or normal), or some combination of these. There is evidence from clinical trials with bisphosphonates supporting the utility of T-scores at the hip in deciding whether to continue or withhold (at least temporarily) therapy after treatment for 3 to 5 years. In the Fracture Intervention Trial (FIT) Long Term Extension (FLEX) Trial, continuing alendronate for 10 years instead of stopping after 5 years was associated with a reduction in the risk of nonvertebral fractures for women without prevalent vertebral fractures whose femoral neck T-scores were 2.5 or less after 5 years of therapy, whereas nonvertebral fracture risk was not reduced in those continuing alendronate for 10 years when the femoral neck T-scores were 2.0 after 5 years of therapy (35). For women with a prevalent vertebral fracture, there was a protective effect of continuing alendronate treatment for clinical vertebral fractures that did not differ across levels of femoral neck T-scores (35, 36). In the Health Outcomes and Reduced Incidence with Zoledronic acid Once Yearly-Pivotal Fracture Trial (HORIZON-PFT) Extension Study, a femoral neck or total hip T-score 2.5 after 3 annual doses of zoledronic acid was predictive of increased risk of new morphometric and nonvertebral fractures in women subsequently randomized to stop treatment (37), suggesting that this hip T-score target could be used to determine

5 950 Lewiecki et al Treat-to-target for Osteoporosis J Clin Endocrinol Metab, March 2013, 98(3): Table 2. Considerations for Osteoporosis Treatment Targets Measurement Parameter Pros Cons BMD/T-score Absolute value DXA is widely available and currently used to monitor therapy. T-scores are used for diagnostic classification and to determine when treatment is indicated. Physicians and patients are already generally familiar with T-scores. Change in value Osteoporosis therapy is often monitored by quantitative comparison of BMD. An increase in BMD is associated with reduction in fracture risk. BTM Absolute value A target level below or above the mean value for a healthy reference population might be used for antiresorptive and anabolic therapy, respectively. Change in value Looking for a significant change from the baseline value might avoid difficulties in assessing effect of therapy when the baseline value is extremely high or low. Fracture risk Absolute value FRAX is often used to select patients for initiation of therapy. Change in value Using a change in fracture risk as a target would account for differences among patients in the initial level of risk. whether prolonged extension of the dosing interval is reasonable. There are potential problems with the use of T-score as a treatment target. Although there is a correlation between BMD improvement with treatment and fracture risk reduction, there is disagreement on the magnitude of that relationship (38, 39). The relationship between BMD response to therapy and reduction in fracture has varied in different analyses and may be different with different drugs. Some analyses have shown a reduction in fracture risk with bisphosphonate therapy with no change or a loss in BMD (40, 41), probably due to effects on bone remodeling that are not captured by BMD testing. There is evidence that vertebral fracture risk is reduced in women treated with teriparatide despite a decrease in femoral neck BMD, although lumbar spine BMD increased in the same patients (42). With zoledronic acid (43) and denosumab (44), a strong correlation between BMD increase and fracture risk reduction has been reported. Another confounding factor in many patients is the development of BMD is one of many risk factors for fracture. Other risk factors, particularly age and previous fragility fracture, are also important predictors of fracture risk. BMD values vary with different instruments and at different skeletal sites. An absolute target may not account for improvement when the baseline fracture risk is very high. No change in BMD with therapy is also associated with reduction in fracture risk. There is debate on the magnitude of BMD change and reduction of fracture risk with therapy. A change in the reference database is a confounding factor in comparing T-scores. An absolute value target may not recognize improvement from an extreme baseline level. It is not clear which BTM is best for which drug. Assay variability. Timing of specimen collection. Assessing the significance of a change in value requires knowledge of the LSC, which may vary for each BTM. FRAX is an algorithm that is still not familiar to many physicians and patients. FRAX requires extra effort to use and fully understand. FRAX does not account for all risk factors for fracture. FRAX value may not change, or even worsen with age, when an effective drug stabilizes but does not increase BMD. There may be benefit in having several target levels for a measurement, with the most appropriate one selected according to factors that include baseline fracture risk, age, or type of drug therapy. Achievement of a treatment target implies that fracture risk has been reduced to an acceptable level, recognizing that no treatment can ever eliminate the risk of fracture. More data are needed to validate treatment targets. The use of treatment targets is not likely to be widespread unless endorsed by experts and included in clinical practice guidelines. structural abnormalities, such as degenerative arthritis, that may increase BMD, particularly in the spine, without imparting an increase in bone strength. In a patient with a very low baseline T-score, it may not be possible, at least with currently available treatments, to raise the T-score to a level that is classified as osteopenia or normal. For all these reasons, a T-score treatment target, while attractive because of its intuitive nature and simplicity, has potential limitations that must be overcome. Because the T-score may change when the reference database for calculating the T-score changes, the International Society for Clinical Densitometry recommends that BMD (g/cm 2 ), not T-scores, be used for performing quantitative comparisons (28). Dual-energy x-ray absorptiometry (DXA)-generated BMD (in g/cm 2 ), rather than T-score, might also be considered as a treatment target, as either an absolute value (in g/cm 2 ) or a change in value (percentage increase) compared with pretreatment. This is attractive because BMD is currently the most common measurement used to monitor therapy, and monitoring

6 doi: /jc jcem.endojournals.org 951 BMD is included in many treatment guidelines (15, 25, 26). Quantitative BMD comparison requires high-quality DXA testing, performance of precision assessment, and calculation of the LSC (28). However, BMD is subject to many of the limitations noted with T-scores, and with either, it would have to be decided which skeletal site(s) would be preferred. With these biomarkers and others, the target may need to be different for different drugs. Bone turnover markers BTMs, while not used to diagnose osteoporosis, are modulated by all drugs used to treat osteoporosis, although weak antiresorptive agents, such as salmon calcitonin and raloxifene, may not decrease BTMs more than the LSC. Evidence-based clinical practice guidelines have included BTMs as a method for monitoring the effects of therapy (15, 45). A decrease in BTMs with antiresorptive agents (eg, bisphosphonates) and an increase in BTMs with an anabolic agent (eg, teriparatide) are associated with a subsequent increase in BMD (46, 47). Measurement of BTMs is potentially useful in assessing the offset of effect after discontinuation of therapy and may provide insight on restarting therapy after a drug holiday (48). The limitations of using BTMs as a treatment target include assay variability and lack of clarity regarding the optimal choice of BTM, which may differ for different drugs. The availability and affordability of BTMs may be problematic in some world regions. Fracture probability Fracture probability is now commonly used to select patients for treatment according to country-specific guidelines, and it is particularly useful in identifying patients with osteopenia who could benefit from therapy. It is important to recognize, however, that no registration trial for approved osteoporosis treatments has selected patients using FRAX, and there are mixed findings on post hoc analyses, with evidence for an association between a high baseline FRAX value and reduction in fracture risk with clodronate (49) and bazedoxifene (50), but not for raloxifene (51), strontium ranelate (52), and alendronate (53). On the contrary, there is robust evidence from registration trials that these drugs reduce fracture risk when baseline BMD is in the osteoporosis range or when there is at least 1 prevalent vertebral fracture, with the possible exception of salmon calcitonin (54). FRAX is a fracture risk algorithm in common usage worldwide, although others, such as the Garvan calculator (55) and the Canadian Association of Radiologists and Osteoporosis Canada calculator (56), are also available (57). Because fracture probability is the method for identifying many patients for treatment, and in some Medicare jurisdictions fracture probability has been recognized for diagnosing osteoporosis, it follows that fracture probability is a candidate treatment target. FRAX is derived from meta-analyses of data from 12 prospective population-based cohorts with almost men and women having more than 3300 osteoporotic fractures in over person-years of observation (32). The FRAX model is calibrated to a population of interest according to data on hip fracture incidence and mortality rates because hip fracture and mortality rates vary in different populations and mortality is a risk that competes with fractures. Cost-effective fracture risk intervention thresholds have been developed through consideration of factors that include fracture-related expenses, expected treatment costs, and societal willingness to pay for treatment to prevent fractures (15, 58, 59). Just as clinical practice guidelines for initiation of osteoporosis treatment are intended to direct limited healthcare resources to those most likely to benefit, so might targetdirected treatment enhance cost-effectiveness by better recognizing patients who should continue, change, or stop therapy. Because the FRAX algorithm was validated with data in patients who were largely untreated, it is generally used in clinical practice as an aid in determining whether untreated patients should be treated. However, it has been used by some in an invalidated fashion in treated patients, with the presumption that treatment results in a fracture risk that is probably less than the values generated by FRAX (60). FRAX has recently been studied in patients receiving pharmacological therapy for osteoporosis. In a large clinical cohort consisting of women age 50 years and older in Manitoba, Canada, FRAX probabilities were linked to pharmacy claims and fracture outcomes (61). It was found that FRAX performed similarly for the prediction of 10-year probability of major osteoporotic fractures and hip fractures in women who where untreated, currently treated, and previously treated. In the highest risk tertile of women highly adherent to bisphosphonate therapy for at least 5 years, the observed hip fracture risk was significantly less than predicted, although major osteoporotic fracture risk was similar to predicted. This could indicate that treatments, as used in that cohort, had little effect on fracture risk. The authors cautioned against the use of FRAX to monitor therapy and made no mention of FRAX as a potential treatment target. The use of a fracture risk algorithm as a treatment target should include factors such as patterns of BMD change (increased, decreased, or stable) during treatment and the predictive value of an incident fracture during treatment, as well as consider the most appropriate time horizon, which may be less than 10 years with the current FRAX model.

7 952 Lewiecki et al Treat-to-target for Osteoporosis J Clin Endocrinol Metab, March 2013, 98(3): Where Do We Go From Here? Development of a treat-to-target strategy is a potential means of improving osteoporosis care and reducing the burden of osteoporotic fractures. We recommend the formation of a task force, consisting of medical experts and representatives of physician and patient organizations, to explore the feasibility of establishing osteoporosis treatment targets. The methodology should include review of the best available medical evidence. Analysis of data already available in large randomized placebo-controlled trials with fractures as a primary endpoint may help to identify the best treatment targets, at least for the drug or drug class investigated. A consensus process with consideration of expert opinion will be needed to generate the task force recommendations. If treatment targets can be identified, they should be included in clinical practice guidelines and disseminated to healthcare providers. The impact of the recommendations on patient outcomes should subsequently be evaluated. As new treatments and new evidence become available, it is likely and desirable that the recommendations be revised. Treat-to-target for osteoporosis should not be overly prescriptive and should allow for individualization of treatment decisions. Acknowledgments Address all correspondence and requests for reprints to: E. Michael Lewiecki, MD, New Mexico Clinical Research & Osteoporosis Center, 300 Oak Street NE, Albuquerque, New Mexico mlewiecki@gmail.com. Disclosure Summary: E.M.L. has received consulting/advisory board fees from Eli Lilly, Novartis, Merck, Warner Chilcott, GSK, and Genentech; and grant/research support from Amgen, Merck, Eli Lilly, Novartis, Warner Chilcott, GSK, and Genentech. 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