Derivation and validation of updated QFracture algorithm to predict risk of osteoporotic fracture in primary care in the United Kingdom: prospective open cohort study

Objective To develop and validate an updated version of the QFracture algorithm for estimating the risk of a patient sustaining an osteoporotic fracture or hip fracture in a primary care population. Design Prospective open cohort study using routinely collected data from 420 general practices in the United Kingdom to develop updated QFracture scores and 207 practices to validate scores. Cox's proportional hazards model was used in the derivation cohort to derive risk equations using several explanatory variables. We calculated measures of calibration and discrimination using the validation cohort. Participants 3 142 673 patients in derivation cohort and 1 583 373 in validation cohort, aged 30-100 years, who contributed 23 608 337 and 11 732 106 person years of observation, respectively. We identified 59 772 incident diagnoses of osteoporotic fracture in the derivation cohort and 28 685 in the validation cohort. Outcomes Incident diagnosis of osteoporotic fracture (vertebral, distal radius, proximal humerus, or hip) and incident hip fracture recorded in general practice records or linked cause of death records. Results We found significant independent associations with overall fracture risk in women for age, body mass index, ethnic origin, alcohol intake, smoking status, chronic obstructive pulmonary disease or asthma, any cancer, cardiovascular disease, dementia, diagnosis or treatment for epilepsy, history of falls, chronic liver disease, Parkinson's disease, rheumatoid arthritis or systemic lupus erythematosus, chronic renal disease, type 1 diabetes, type 2 diabetes, previous fracture, endocrine disorders, gastrointestinal malabsorption, any antidepressants, corticosteroids, unopposed hormone replacement therapy, and parental history of osteoporosis. Risk factors for hip fracture in women were similar except for gastrointestinal malabsorption and parental history of hip fracture. Risk factors for men were largely the same as those for women but also included care home residence. The updated hip fracture algorithm explained 71.7% (95% confidence interval 71.1% to 72.3%) of the variation in women and 70.4% (69.3% to 71.5%) in men. D statistic values for hip fracture were high for women (3.26, 3.21 to 3.31) and men 3.15, 3.06 to 3.24), and higher than for osteoporotic fracture. Values for the area under the receiver operating characteristics curves for hip fracture were 0.89 for women and 0.88 for men, compared with 0.79 and 0.71 for osteoporotic fracture, respectively. The updated algorithms performed better than the 2009 algorithms. Conclusions Two QFracture algorithms were updated to predict risk of osteoporotic and hip fracture in primary care populations to include ethnic origin, all classes of antidepressants, chronic obstructive pulmonary disease, epilepsy, dementia, Parkinson's disease, cancer, systemic lupus erythematosus, chronic renal disease, type 1 diabetes, previous fragility fracture, and care home residence. These updated algorithms showed improved performance compared with previous QFracture algorithms reported in 2009.