***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: PURPOSE To assess the ability of the Spanish version of the WHO fracture risk assessment tool ( FRAX ® ) to predict the observed incident fractures in the ECOSAP Study cohort . METHODS 5201 women , aged 65 or older , were enrolled in a three-year , prospect i ve study by a non-r and omized sampling of consecutive cases in 58 primary care centers in Spain . Participants completed an osteoporosis and fracture risk question naire and attended follow-up visits every 6 months . All radiologically or surgically confirmed low-trauma , non-spinal fractures were collected . The individual 10-year absolute risks of hip and major osteoporotic fractures were calculated with the FRAX ® algorithms for Spain without the inclusion of the bone mineral density ( BMD ) measurements . Calibration was evaluated by comparing the three-year estimated ( E ) fractures predicted with FRAX ® with the number of observed ( O ) fractures , and their discriminative ability for the probability of new fractures with the area under the receiving operating characteristic ( ROC ) curves . RESULTS Fifty ( 0.96 % ) women sustained an incident hip fracture , and 201 ( 3.81 % ) women presented with major osteoporotic fractures ( hip , forearm or humerus ) . The E/O ratios for hip and major osteoporotic fractures were 1.10 and 0.66 respectively . Clinical vertebral fractures were not collected ; therefore , the E/O ratio for major fractures should be expected to be lower . The difference between E and O cases reached statistical significance ( χ(2 ) , p<0.001 ) . Areas under the ROC curves were 0.640 and 0.615 for hip and major osteoporotic fractures respectively . CONCLUSIONS The Spanish FRAX ® underestimates the risk for major osteoporotic fractures . The estimated risk for hip fractures was similar to the observed fractures ; however the algorithm had only modest discriminative ability . These results should be interpreted in the context of the relatively low number of observed fractures , especially at the hip Objective To evaluate the performance of the QFractureScores for predicting the 10 year risk of osteoporotic and hip fractures in an independent UK cohort of patients from general practice records . Design Prospect i ve cohort study . Setting 364 UK general practice s contributing to The Health Improvement Network ( THIN ) data base . Participants 2.2 million adults registered with a general practice between 27 June 1994 and 30 June 2008 , aged 30 - 85 ( 13 million person years ) , with 25 208 osteoporotic fractures and 12 188 hip fractures . Main outcome measures First ( incident ) diagnosis of osteoporotic fracture ( vertebra , distal radius , or hip ) and incident hip fracture recorded in general practice records . Results Results from this independent and external validation of QFractureScores indicated good performance data for both osteoporotic and hip fracture end points . Discrimination and calibration statistics were comparable to those reported in the internal validation of QFractureScores . The hip fracture score had better performance data for both women and men . It explained 63 % of the variation in women and 60 % of the variation in men , with areas under the receiver operating characteristic curve of 0.89 and 0.86 , respectively . The risk score for osteoporotic fracture explained 49 % of the variation in women and 38 % of the variation in men , with corresponding areas under the receiver operating characteristic curve of 0.82 and 0.74 . QFractureScores were well calibrated , with predicted risks closely matching those across all 10ths of risk and for all age groups . Conclusion QFractureScores are useful tools for predicting the 10 year risk of osteoporotic and hip fractures in patients in the United Kingdom We performed a Monte Carlo study to evaluate the effect of the number of events per variable ( EPV ) analyzed in logistic regression analysis . The simulations were based on data from a cardiac trial of 673 patients in which 252 deaths occurred and seven variables were cogent predictors of mortality ; the number of events per predictive variable was ( 252/7 =) 36 for the full sample . For the simulations , at values of EPV = 2 , 5 , 10 , 15 , 20 , and 25 , we r and omly generated 500 sample s of the 673 patients , chosen with replacement , according to a logistic model derived from the full sample . Simulation results for the regression coefficients for each variable in each group of 500 sample s were compared for bias , precision , and significance testing against the results of the model fitted to the original sample . For EPV values of 10 or greater , no major problems occurred . For EPV values less than 10 , however , the regression coefficients were biased in both positive and negative directions ; the large sample variance estimates from the logistic model both overestimated and underestimated the sample variance of the regression coefficients ; the 90 % confidence limits about the estimated values did not have proper coverage ; the Wald statistic was conservative under the null hypothesis ; and paradoxical associations ( significance in the wrong direction ) were increased . Although other factors ( such as the total number of events , or sample size ) may influence the validity of the logistic model , our findings indicate that low EPV can lead to major problems Introduction In 2008 , the UK National Osteoporosis Guideline Group ( NOGG ) produced a guideline on the prevention and treatment of osteoporosis , with an up date in 2013 . This paper presents a major up date of the guideline , the scope of which is to review the assessment and management of osteoporosis and the prevention of fragility fractures in postmenopausal women and men age 50 years or over . Methods Where available , systematic review s , meta-analyses and r and omised controlled trials were used to provide the evidence base . Conclusions and recommendations were systematic ally grade d according to the strength of the available evidence . Results Review of the evidence and recommendations are provided for the diagnosis of osteoporosis , fracture-risk assessment , lifestyle measures and pharmacological interventions , duration and monitoring of bisphosphonate therapy , glucocorticoid-induced osteoporosis , osteoporosis in men , postfracture care and intervention thresholds . Conclusion The guideline , which has received accreditation from the National Institute of Health and Care Excellence ( NICE ) , provides a comprehensive overview of the assessment and management of osteoporosis for all healthcare professionals who are involved in its management Objectives To vali date the performance of a set of risk prediction algorithms developed using the Q Research data base , in an independent sample from general practice s contributing to the Clinical Research Data Link ( CPRD ) . Setting Prospect i ve open cohort study using practice s contributing to the CPRD data base and practice s contributing to the Q Research data base . Participants The CPRD validation cohort consisted of 3.3 million patients , aged 25–99 years registered at 357 general practice s between 1 Jan 1998 and 31 July 2012 . The validation statistics for Q Research were obtained from the original published papers which used a one-third sample of practice s separate to those used to derive the score . A cohort from Q Research was used to compare incidence rates and baseline characteristics and consisted of 6.8 million patients from 753 practice s registered between 1 Jan 1998 and until 31 July 2013 . Outcome measures Incident events relating to seven different risk prediction scores : QRISK2 ( cardiovascular disease ) ; QStroke ( ischaemic stroke ) ; QDiabetes ( type 2 diabetes ) ; QFracture ( osteoporotic fracture and hip fracture ) ; QKidney ( moderate and severe kidney failure ) ; QThrombosis ( venous thromboembolism ) ; QBleed ( intracranial bleed and upper gastrointestinal haemorrhage ) . Measures of discrimination and calibration were calculated . Results Overall , the baseline characteristics of the CPRD and Q Research cohorts were similar though Q Research had higher recording levels for ethnicity and family history . The validation statistics for each of the risk prediction scores were very similar in the CPRD cohort compared with the published results from Q Research validation cohorts . For example , in women , the QDiabetes algorithm explained 50 % of the variation within CPRD compared with 51 % on Q Research and the receiver operator curve value was 0.85 on both data bases . The scores were well calibrated in CPRD . Conclusions Each of the algorithms performed practically as well in the external independent CPRD validation cohorts as they had in the original published Q Research validation cohorts Background : Fractures have largely been assessed by their impact on quality of life or health care costs . We conducted this study to evaluate the relation between fractures and mortality . Methods : A total of 7753 r and omly selected people ( 2187 men and 5566 women ) aged 50 years and older from across Canada participated in a 5-year observational cohort study  . Incident fractures were identified on the basis of vali date d self-report and were classified by type ( vertebral , pelvic , forearm or wrist , rib , hip and “ other ” ) . We subdivided fracture groups by the year in which the fracture occurred during follow-up ; those occurring in the fourth and fifth years were grouped together . We examined the relation between the time of the incident fracture and death . Results : Compared with participants who had no fracture during follow-up , those who had a vertebral fracture in the second year were at increased risk of death ( adjusted hazard ratio [ HR ] 2.7 , 95 % confidence interval [ CI ] 1.1–6.6 ) ; also at risk were those who had a hip fracture during the first year ( adjusted HR 3.2 , 95 % CI 1.4–7.4 ) . Among women , the risk of death was increased for those with a vertebral fracture during the first year ( adjusted HR 3.7 , 95 % CI 1.1–12.8 ) or the second year of follow-up ( adjusted HR 3.2 , 95 % CI 1.2–8.1 ) . The risk of death was also increased among women with hip fracture during the first year of follow-up ( adjusted HR 3.0 , 95 % CI 1.0–8.7 ) . Interpretation : Vertebral and hip fractures are associated with an increased risk of death . Interventions that reduce the incidence of these fractures need to be implemented to improve survival A representation and interpretation of the area under a receiver operating characteristic ( ROC ) curve obtained by the " rating " method , or by mathematical predictions based on patient characteristics , is presented . It is shown that in such a setting the area represents the probability that a r and omly chosen diseased subject is ( correctly ) rated or ranked with greater suspicion than a r and omly chosen non-diseased subject . Moreover , this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic . These two relationships are exploited to ( a ) provide rapid closed-form expressions for the approximate magnitude of the sampling variability , i.e. , st and ard error that one uses to accompany the area under a smoothed ROC curve , ( b ) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area , and ( c ) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques Summary We evaluated the Women ’s Health Initiative ( WHI ) hip fracture risk score in 15,648 postmenopausal Danish nurses . The algorithm was well calibrated for Denmark . However , the sensitivity was poor at common decision making thresholds . Obtaining sensitivity better than 80 % led to a low specificity of 61.4 % . Introduction A new score based on data from the WHI has been design ed to predict 5-year risk of hip fracture in postmenopausal women . The performance of the algorithm has not been vali date d in population s with different lifestyle characteristics and ethnicity . The aim of this study was to test the clinical performance of the algorithm in a large Danish cohort of postmenopausal Caucasian women against hip fracture . Methods The Danish Nurse Cohort is a prospect i ve risk factor and hormone therapy ( HT ) study established in 1993 . Participants in the present analysis were 15,648 postmenopausal nurses . The calibration and diagnostic performance of the WHI algorithm was evaluated using fracture events captured in the Danish National Hospital Registry . Results During 5 years of follow-up , 122 participants suffered a hip fracture ( 1.8/1,000 person years ) . The WHI algorithm predicted that 107 hip fractures would occur , indicating an underestimation of the number of fractures by 12 % . To obtain sensitivity better than 80 % , the cut-off value for 5-year risk was set to 0.5 % , which was accompanied by a low positive predictive value of 1.9 % and a low specificity of 61.4 % . The algorithm predicted too many fractures in HT-users ( 12 observed , 22 expected ) and too few in non HT-users ( 107 observed , 81 expected ) . Conclusions While the WHI algorithm was well calibrated on the Danish population , the clinical utility of the WHI algorithm in Danish postmenopausal women was limited by poor sensitivity at common decision-making thresholds and suboptimal in non-HT-users BACKGROUND Mortality increases after hip fractures  in women and more so in men . Little is known , however , about mortality after other fractures . We investigated the mortality associated with all fracture types in elderly women and men . METHODS We did a 5-year prospect i ve cohort study  in the semi-urban city of Dubbo , Australia , of all residents aged 60 years and older (  
    Output:
    
Conclusions QFracture , FRAX with BMD , and Garvan with BMD have the highest discriminative performance for predicting fracture .