A huge number of risk assessment tools have been developed. Far from all have been validated in external studies, more of them have absence of methodological and transparent evidence, and few are integrated in national guidelines. Therefore, we performed a systematic review to provide an overview of existing valid and reliable risk assessment tools for prediction of osteoporotic fractures. Additionally, we aimed to determine if the performance of each tool was sufficient for practical use, and last, to examine whether the complexity of the tools influenced their discriminative power. We searched PubMed, Embase, and Cochrane databases for papers and evaluated these with respect to methodological quality using the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) checklist. A total of 48 tools were identified; 20 had been externally validated, however, only six tools had been tested more than once in a population-based setting with acceptable methodological quality. None of the tools performed consistently better than the others and simple tools (i.e., the Osteoporosis Self-assessment

Compared to an office-based case-finding strategy, the two-step systematic screening strategy had no overall effect on fracture incidence. The two-step strategy seemed, however, to be beneficial in the group of women who were identified by FRAX as moderate- or high-risk patients and complied with DXA.

Nonresponse appears related to linguistic and/or educational limitations, to alienation generated by the questions' focus on disease and cultural assumptions, or mistrust regarding anonymity. Ethnic minorities seem particularly affected by such barriers. To increase survey participation, questions could be sensitized to reflect multicultural traditions, and the impact of sender and setting considered.

Comparison of FRAX® and simpler screening tools (OST, ORAI, OSIRIS, SCORE) in predicting fractures indicate that FRAX® did not perform better in fracture risk prediction compared with the simpler tools or even age alone in a screening scenario without bone mineral density assessment.

Some conditions are already known to be associated with an increased risk of osteoporotic fractures. Other conditions may also be significant indicators of increased risk. The aim of the current study was to identify conditions for inclusion in a fracture prediction model (fracture risk evaluation model [FREM]) for automated case finding of high-risk individuals of hip or major osteoporotic fractures (MOFs). We included the total population of Denmark aged 45+ years (N = 2,495,339). All hospital diagnoses from 1998 to 2012 were used as possible conditions; the primary outcome was MOFs during 2013. Our cohort was split randomly 50/50 into a development and a validation dataset for deriving and validating the predictive model. We applied backward selection on ICD-10 codes (International Classification of Diseases and Related Health Problems, 10th Revision) by logistic regression to develop an age-adjusted and sex-stratified model. The FREM for MOFs included 38 and 43 risk factors for women and men, respectively. Testing FREM for MOFs in the validation cohort showed good accuracy; it produced receiver-operating characteristic (ROC) curves with an area under the ROC curve (AUC) of 0.750 (95% CI, 0.741 to 0.795) and 0.752 (95% CI, 0.743 to 0.761) for women and men, respectively. The FREM for hip fractures included 32 risk factors for both genders and showed an even higher accuracy in the validation cohort as AUCs of 0.874 (95% CI, 0.869 to 0.879) and 0.851 (95% CI, 0.841 to 0.861) for women and men were found, respectively. We have developed and tested a prediction model (FREM) for identifying men and women at high risk of MOFs or hip fractures by using solely existing administrative data. The FREM could be employed either at the point of care integrated into electronic patient record systems to alert physicians or deployed centrally in a national case-finding strategy where patients at high fracture risk could be invited to a focused DXA program. © 2018 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research (ASBMR).