An Assessment Tool for Predicting Fracture Risk in Postmenopausal Women

178

114

The aim of this prospective study was (1) to identify significant and independent clinical risk factors (CRFs) for major osteoporotic (OP) fracture among peri-and early postmenopausal women, (2) to assess, in this population, the discriminatory capacity of FRAX and bone mineral density (BMD) for the identification of women at high risk of fracture, and (3) to assess whether adding risk factors to either FRAX or BMD would improve discriminatory capacity. The study population included 2651 peri-and early postmenopausal women [mean age (AE SD): 54 AE 4 years] with a mean follow-up period of 13.4 years (AE1.4 years). At baseline, a large set of CRFs was recorded, and vertebral BMD was measured (Lunar, DPX) in all women. Femoral neck BMD also was measured in 1399 women in addition to spine BMD. Women with current or past OP treatment for more than 3 months at baseline (n ¼ 454) were excluded from the analyses. Over the follow-up period, 415 women sustained a first low-energy fracture, including 145 major OP fractures (108 wrist, 44 spine, 20 proximal humerus, and 13 hip). In Cox multivariate regression models, only 3 CRFs were significant predictors of a major OP fracture independent of BMD and age: a personal history of fracture, three or more pregnancies, and current postmenopausal hormone therapy. In the subsample of women who had a hip BMD measurement and who were not receiving OP therapy (including hormone-replacement therapy) at baseline, mean FRAX value was 3.8% (AE2.4%). The overall discriminative value for fracture, as measured by the area under the Receiver Operating Characteristic (ROC) curve (AUC), was equal to 0.63 [95% confidence interval (CI) 0.56-0.69] and 0.66 (95% CI 0.60-0.73), respectively, for FRAX and hip BMD. Sensitivity of both tools was low (ie, around 50% for 30% of the women classified as the highest risk). Adding parity to the predictive model including FRAX or using a simple risk score based on the best predictive model in our population did not significantly improve the discriminatory capacity over BMD alone. Only a limited number of clinical risk factors were found associated with the risk of major OP fracture in peri-and early postmenopausal women. In this population, the FRAX tool, like other risk scores combining CRFs to either BMD or FRAX, had a poor sensitivity for fracture prediction and did not significantly improve the discriminatory value of hip BMD alone. ß

Section: Discussionmentioning

confidence: 95%

Fracture risk prediction using BMD and clinical risk factors in early postmenopausal women: Sensitivity of the WHO FRAX tool

Trémollières

Pouillès

Drewniak

et al. 2010

178

114

“…For this reason, there has been interest in the development of algorithms that express absolute risk, or the probability of fracture within a given time period. (4)(5)(6)(7) The World Health Organization (WHO) Collaborating Center for Metabolic Bone Diseases conducted several metaanalyses of data from large-scale prospective studies in various countries to identify and quantify the risk of fracture associated with several clinical factors (personal history of fracture (8,9) or parental history of fracture, (10) body mass index, (11) smoking, (12) and glucocorticoid treatment (13) ) independent from BMD and age. These extensive studies have contributed to the development of a standardized methodaimed at use in clinical practice-for expressing absolute fracture risk in men and women.…”

Section: Introductionmentioning

confidence: 99%

The FRAX tool in French women: How well does it describe the real incidence of fracture in the OFELY cohort

Sornay‐Rendu

Munoz

Delmas

et al. 2010

The FRAX tool estimates an individual's fracture probability over 10 years from clinical risk factors with or without bone mineral density (BMD) measurement. The aim of our study was to compare the predicted fracture probabilities and the observed incidence of fracture in French women during a 10-year follow-up. The probabilities of fracture at four major sites (hip, clinical spine, shoulder, or wrist) and at the hip were calculated with the FRAX tool in 867 women aged 40 years and over from the Os des Femmes de Lyon (OFELY) cohort. The incidence of fracture was observed over 10 years. Thus 82 women sustained 95 incident major osteoporotic (OP) fractures including 17 fractures at the hip. In women aged at least 65 years (n ¼ 229), the 10-year predicted probabilities of fracture with BMD were 13% for major OP fractures and 5% for hip fractures, contrasting with 3.6% and 0.5% in women younger than 65 years ( p < .0001). The predicted probabilities of both major OP and hip fractures were significantly higher in women with osteoporosis (n ¼ 77, 18% and 10%) and osteopenia (n¼ 390, 6% and 2%) compared with women with normal BMD (n ¼ 208, 3% and <1%; p < .0001. The predicted probabilities of fracture were two and five times higher in women who sustained an incident major OP fracture and a hip fracture compared with women who did not ( p < .0001). Nevertheless, among women aged at least 65 years with low BMD values (T-score -1; n ¼ 199), the 10-year predicted probability of major OP fracture with BMD was 48% lower than the observed incidence of fractures ( p < .01). A 10-year probability of major OP fracture higher than 12% identified more women with incident fractures than did BMD in the osteoporotic range ( p < .05). In French women from the OFELY cohort, the observed incidence of fragility fractures over 10 years increased with age following a pattern similar to the predicted probabilities given by the FRAX tool. However, in women aged at least 65 years with low BMD, the observed incidence of fractures was substantially higher than the predicted probability. ß

“…(2)(3)(4) In clinical practice, the physician now can assess the risk of hip fracture for an individual patient from several clinical factors, which include age, weight, fracture after age 50 years, parental hip fracture, smoking status, alcohol intake, glucocorticoid therapy, and secondary causes of osteoporosis, with or without areal bone mineral density (aBMD). (5,6) These variables can be pooled into the recent World Health Organization (WHO) FRAX tool (www.shef.ac.uk/FRAX/) or similar algorithms to calculate a 10-year fracture risk. (7,8) Guidelines for treatment have been published in the United States and Europe, (9)(10)(11) but targeting preventive interventions is still challenging.…”

Section: Introductionmentioning

confidence: 99%

In vivo discrimination of hip fracture with quantitative computed tomography: Results from the prospective European Femur Fracture Study (EFFECT)

Bousson

Adams

Engelke³

et al. 2010

In assessing osteoporotic fractures of the proximal femur, the main objective of this in vivo case-control study was to evaluate the performance of quantitative computed tomography (QCT) and a dedicated 3D image analysis tool [Medical Image Analysis Framework-Femur option (MIAF-Femur)] in differentiating hip fracture and non-hip fracture subjects. One-hundred and seven women were recruited in the study, 47 women (mean age 81.6 years) with low-energy hip fractures and 60 female non-hip fracture control subjects (mean age 73.4 years). Bone mineral density (BMD) and geometric variables of cortical and trabecular bone in the femoral head and neck, trochanteric, and intertrochanteric regions and proximal shaft were assessed using QCT and MIAF-Femur. Areal BMD (aBMD) was assessed using dual-energy X-ray absorptiometry (DXA) in 96 (37 hip fracture and 59 non-hip fracture subjects) of the 107 patients. Logistic regressions were computed to extract the best discriminates of hip fracture, and area under the receiver characteristic operating curve (AUC) was calculated. Three logistic models that discriminated the occurrence of hip fracture with QCT variables were obtained (AUC ¼ 0.84). All three models combined one densitometric variable-a trabecular BMD (measured in the femoral head or in the trochanteric region)-and one geometric variable-a cortical thickness value (measured in the femoral neck or proximal shaft). The best discriminant using DXA variables was obtained with total femur aBMD (AUC ¼ 0.80, p ¼ .003). Results highlight a synergistic contribution of trabecular and cortical components in hip fracture risk and the utility of assessing QCT BMD of the femoral head for improved understanding and possible insights into prevention of hip fractures. ß