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Objective Different regulatory actions for anti-osteoporotic medication (AOM) were taken during the last years, including marketing of new drugs, safety warnings, or restrictions on the indications. We aimed to characterise the secular trends of AOM use in Spain from 2001 to 2013. Methods A cohort study using the Spanish Database for Pharmacoepidemiological Research in Primary Care (BIFAP), was performed. BIFAP includes anonym records for 4 million patients. Participants entered the study when aged ≥ 50 years in 2001–2013 and after 1 year of data available, and were followed to an AOM prescription (including alendronate, other bisphosphonates, SERM (selective estrogen receptor modulators), strontium ranelate, teriparatide or denosumab), death, lost or the end of December 2013. Prevalence (%) and incidence rate (IR/1000 person-years (py)) of AOM users were computed by years and sex. Results Out of 1.5 million participants, 135,410 received AOM treatment during 2001–2013. Prevalence was 6.1% (women) and 1.1% (men), that increased from 2001 (2.0%) to 2009 (7.6%) to decrease thereafter. Out of them, 95,057 were incident. The IR was 24.90 (women) and 2.77 (men), that increased from 2001 (21.25 and 1.96) to 2007 (35.84 and 3.64), and decreased to 12.48 and 1.81 (2013). IRs were highest for bisphosphonates along the years (ranging 3.70–14.73 and 0.57–1.75 in women and men respectively), followed by SERM up to 2005 (6.51–9.02 and 0.06–0.07), and strontium ranelate from 2006 (4.66 and 0.45) to 2012 (2.05 and 0.26). IR for teriparatide increased from marketing in 2004 (0.10–1.01 and 0.02–0.29), as was denosumab from marketing in 2011 (0.03–2.64 and 0.09–0.15). Conclusions Population-based estimates of AOM use in Spain peaked in 2007–2009 and decreased thereafter, irrespective of age and sex. New treatments were ten times higher in women than men. Bisphosphonates were the most frequently prescribed class, followed by SERM in women before 2006, strontium otherwise till 2012, and denosumab in women or teriparatide in men in 2013. Changes in the osteoporosis criteria, fracture risk assessment strategies, and regulatory actions for AOM around the time, may explain that trend. [ABSTRACT FROM AUTHOR]

We aimed to develop and validate a fracture risk algorithm for the automatic identification of subjects at high risk of imminent and long-term fracture risk. A cohort of subjects aged 50–85, between 2007 and 2017, was extracted from the Catalan information system for the development of research in primary care database (SIDIAP). Participants were followed until the earliest of death, transfer out, fracture, or 12/31/2017. Potential risk factors were obtained based on the existing literature. Cox regression was used to model 1 and 5-year risk of hip and major fracture. The original cohort was randomly split in 80:20 for development and internal validation purposes respectively. External validation was explored in a cohort extracted from the Spanish database for pharmaco-epidemiological research in primary care. A total of 1.76 million people were included from SIDIAP (50.7 % women with mean age of 65.4 years). Hip and major fracture incidence rates were 3.57 [95%CI 3.53 to 3.60] and 11.61 [95%CI 11.54 to 11.68] per 1000 person-years, respectively. The derived model included 19 risk factors. Internal validity showed good results on calibration and discrimination. The 1-year C-statistic for hip and major fracture were 0.851 (95%CI 0.853 to 0.864), and 0.717 (95%CI 0.742 to 0.749) respectively. The 5-year C-statistic for hip and major fracture were 0.849 (95%CI 0.847 to 0.852) and 0.724 (95%CI 0.721 to 0.727) respectively. External validation showed good performance for hip and major fracture risk prediction. We have developed and validated a clinical prediction tool for 1- and 5-year hip and major osteoporotic fracture risks using electronic primary care data. The proposed algorithm can be automatically estimated at the population level using the available primary care records. Future work is needed on the cost-effectiveness of its use for population-based screening and targeted prevention of osteoporotic fractures. • A prediction model for hip and major fracture imminent risk and long-term risk is presented. • The algorithm can be estimated at population level using available primary care records for identification of subjects at high risk of fracture. • The tool was externally validated and has good external calibration and discrimination. [ABSTRACT FROM AUTHOR]