The management of osteoporosis is changing—for the better. Perhaps the most progressive recent step has been the assessment of fracture risk using clinical risk factors through tools such as the Fracture Risk Assessment Tool (FRAX).1 In addition to traditional intervention thresholds, such as those for osteoporosis defined by the WHO T-score or prior fracture, many guidelines now include recommendations for dual-energy X-ray absorptiometry (DXA) assessment or treatment for subgroups of patients identified to be at certain levels of fracture risk.2–6 In this regard, osteoporosis management is starting to follow risk-based strategies that have already been adopted in other disease areas, particularly in cardiovascular disease. In this issue's Perspective article, Cummings and colleagues7 suggest that osteoporosis management should also embrace an additional strategy, that of goal-directed therapy. Although there is certainly merit in consideration and discussion of this proposal, the authors recognize that there are many challenges to be overcome. We would strongly argue that these challenges cannot be easily dismissed or glossed over in the desire to move forward—but we welcome the future discussions, debates, and most importantly, the research that will determine whether osteoporosis lends itself to goal-directed therapy.

The major limitation in developing a goal-directed approach in osteoporosis is the choice of the parameter to define the goal. Cummings and colleagues7 imply that bone turnover markers (BTMs), bone mineral density (BMD), or fracture risk might be suitable parameters, but there remain many uncertainties and there is an ongoing debate about the optimal marker(s) of response in osteoporosis.8–14 Goal-directed therapy can only be considered when we are confident that we can accurately and consistently detect a therapeutic response and can demonstrate a strong correlation between that response and an improvement in clinical outcome. Such requirements are met in the fields of hypertension, hypercholesterolemia, diabetes, and critical care, in which treatment can be titrated to the desired level of effect. For example, in the treatment of hypercholesterolemia there is a strong relationship between the reduction in total cholesterol (TC) or low-density lipoprotein (LDL)-cholesterol (LDL-C) and mortality rates; in one meta-analysis, for every 1-mmol/L decrease in TC or LDL-C, there was a 24.5% or 28% reduction in coronary heart disease (CHD)-related mortality, respectively.15 Can we say the same about markers of response in osteoporosis?

In the Perspective, a proposal is made that the goal could be a certain risk of fracture or level of BMD. It is certainly not unreasonable, given the availability of tools that calculate fracture risk, to consider a reduction to below a given threshold of risk as a goal for therapy. But how do we achieve this? The Perspective quite rightly draws attention to a number of unknowns about the interpretation of changes in risk factors during therapy. Other considerations are worth highlighting: a number of clinical risk factors can remain stable (eg, prior fracture status) or only progress in the direction of increased risk (eg, age, incident fracture in a fracture-naïve patient). Others can move in the direction of lower risk, eg, stopping smoking or decreasing alcohol intake, though it is uncertain whether the expected risk reduction is actually achieved because there are no prospective studies to provide direct evidence of this. If such risk factors remain unchanged during therapy, then the only parameter in the risk models that can really show treatment-induced changes is BMD. So why not just propose a goal for BMD? As stated earlier, the role of BMD in monitoring therapeutic response remains controversial.16 In part, this reflects limitations in our ability to detect small within-person changes in BMD relative to the inherent measurement error. It also appears that the relationship between an increase in BMD and reduction in fracture risk in the setting of therapeutic response does not parallel the gradient of risk for BMD to predict fractures in untreated individuals. Many studies have shown that the relationship between change in BMD and fracture risk reduction is relatively weak for the most commonly prescribed osteoporosis therapies and underestimates the fracture reduction.17–20 This might change, as stated in the Perspective, with the use of more recent antiresorptives, for which the relationship appears somewhat stronger,21, 22 but it remains unclear that those achieving a threshold value of BMD do better than those who fail to do so. How can we handle this discrepancy between BMD change and reduction in fracture risk? One possibility would be to add in a variable for treatment in the risk calculator that carries with it an assumed reduction in fracture risk, perhaps derived from meta-analyses. Ideally, this could be agent-specific in terms of onset or offset of action, and would accommodate interactions with other parameters (eg, baseline fracture probability or BMD). But this is an assumption and is not the same as goal-directed therapy, which implies the demonstration of achievement of a measured goal within the individual. Indeed, one could argue that the strongest contender for goal-directed therapy in osteoporosis is the use of the parameter that receives least attention in the Perspective, namely BTMs. If an antihypertensive is prescribed, the clinician wants to see a reduction in blood pressure toward the target; if an antiresorptive is given, a reduction in bone resorption (or indirectly, bone formation) should be the target—the drug should do “what it says on the tin.” A similar line of argument could be made for anabolic therapy with an increase in markers of bone formation. Any change in BMD is actually secondary to these effects, but the correlation is not particularly strong; therefore, a change in BMD may not accurately reflect the actual cellular effect of therapy. There remains, however, a need to standardize these biochemical measurements before they are ready for routine clinical practice, let alone for setting a treatment target, and the Perspective from Cummings and colleagues7 might hasten such efforts.23, 24

The “goal” of goal-directed therapy is a laudable one, but the long list of limitations raised in the Perspective needs to be at the forefront of our thoughts. We have learned that acceptance of a simple BMD threshold, such as a T-score of –2.5, is fraught with complexities and flaws. The greatest misinterpretation, arguably, of a BMD goal is that patients may not derive benefit once the T-score has risen above the mystical value of –2.5 so that treatment could be discontinued, and that those failing to reach this threshold have received suboptimal therapy. Such analyses bear more scrutiny. In conclusion, the discussion of goal-directed therapy in osteoporosis is to be welcomed. There is, however, a much more fundamental question to be addressed related to monitoring of response to therapy. We need to make decisions about the optimal way to define and measure response before we can even start to consider the setting of goals or thresholds. The debate and discussion is to be welcomed.


  1. Top of page
  2. Disclosures
  3. References
  4. Supporting Information

The authors state that they have no conflicts of interest.


  1. Top of page
  2. Disclosures
  3. References
  4. Supporting Information
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  • 2
    Grossman JM, Gordon R, Ranganath VK, Deal C, Caplan L, Chen W, Curtis JR, Furst DE, McMahon M, Patkar NM, Volkmann E, Saag KG. American College of Rheumatology 2010 recommendations for the prevention and treatment of glucocorticoid-induced osteoporosis. Arthritis Care Res (Hoboken). 2010 Nov; 62(11):15151526.
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    Papaioannou A, Morin S, Cheung AM, Atkinson S, Brown JP, Feldman S, Hanley DA, Hodsman A, Jamal SA, Kaiser SM, Kvern B, Siminoski K, Leslie WD. Scientific Advisory Council of Osteoporosis Canada. 2010 clinical practice guidelines for the diagnosis and management of osteoporosis in Canada: summary. CMAJ. 2010 Nov 23; 182(17):18641873.
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  2. Disclosures
  3. References
  4. Supporting Information

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