OBJECTIVES: To conduct a structured review of the recent osteoporosis cost-effectiveness modeling literature and provide an overview of their methodologies and approaches. METHODS: A detailed systematic review was performed of the following literature databases: MEDLINE, MEDLINE In-Process, EMBASE, Cochrane, HEED, NHSEED, EconLit, and googlescholar. Using pre-selected inclusion/exclusion criteria relevant studies published since January 2005 were identified. Relevant information from each identified study was extracted according to a predefined grid and essential features of each osteoporosis cost-effectiveness model were recorded. RESULTS: Forty-eight relevant and recently published osteoporosis cost-effectiveness models were identified. Model structures were cohort Markov (56%) and individualized microsimulations (44%). Most models (35) used a lifetime timeframe (i.e., death or ≥ age 100). The primary interventions investigated were bisphosphonates (79%), raloxefine (15%), and hormone replacement therapy (10%). In 98% of the models hip fracture was a specific outcome, 94% contained vertebral fractures, and 77% contained wrist/forearm fractures. Eleven models incorporate at least one extraskeletal effect on cost and survival (including breast cancer, coronary heart disease, venous thromboembolism, stroke, and colorectal cancer). Thirty-two (32) of the 48 publications (67%) assume 100% compliance or do not directly mention/model compliance. The majority of the models take the approach that there was discontinuation and non-compliance in the clinical trials, and that the treatment efficacy rates sourced from the clinical trials are underestimated due to the use of an intention-to-treat paradigm. CONCLUSIONS: The current state of osteoporosis modeling favors a non-cohort Markov approach, with individualized, i.e., microsimulation  methodology being increasingly utilized as extraskeletal effects are incorporated. Treatment compliance and extraskeletal effects are extremely important in modeling real-world scenarios, yet they are not incorporated into the majority of the published models. Modeled treatment effectiveness should be properly imputed to account for the intention-to-treat impact of RCT-reported values as well as the reduced benefits of treatment noncompliance.