• Jun 21, 2019 | Webinar

    ASBMR Webinar: Anabolics and Combination Therapy

    Benjamin Z. Leder, M.D., Massachusetts General Hospital Harvard Medical School, USA

    Osteoporosis medications can be classified as either antiresorptive or anabolic based on their mechanism of action. The most commonly used antiresorptive agents include the nitrogen-containing bisphosphonates and the receptor activator of NFκB (RANK)- ligand inhibitor, denosumab. The currently available anabolic drugs, teriparatide and abaloparatide, both act through binding to the PTH/PTHrP receptor, and are generally reserved for patients with more significant disease. In contrast to other chronic diseases such as hypertension or diabetes, osteoporosis therapy has generally been limited to the sequential administration of a standard dose of a single medication. More recently, however, the efficacy of several combined anabolic/antiresorptive approaches to osteoporosis have been evaluated in clinical trials. Moreover, as osteoporosis treatment options continue to expand, and clinical guidelines have begun to include the concept of limiting treatment courses to several years, defining the optimal use of multiple agents in sequence has also become an area of increasing interest. In this webinar, Dr. Leder will review the relative efficacy of the various approaches to combination osteoporosis therapy as well as the comparative skeletal effects of the various sequential approaches evaluated to date.

    Educational Objectives: 

    • Describe the relative skeletal effects and clinical efficacy of the various approaches to combined anabolic/antiresorptive osteoporosis therapy investigated to date
    • Explain the potential mechanisms that underlie the specific efficacy of combined PTH-analog and RANKL-inhibition therapy
    • Recognize the relative efficacy of the various sequential approaches in osteoporosis therapy as well as the optimal way to consolidate bone mineral density gains achieved with combination, anabolic, or RANKL-inhibition therapy

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