Combined vertebral fracture assessment and bone mineral density measurement: a new standard in the diagnosis of osteoporosis in academic populations

Vertebral Fracture Analysis enables the detection of vertebral fractures in the same session as bone mineral density testing. Using this method in 2,424 patients, we found unknown vertebral fractures in approximately one out of each six patients with significant impact on management. The presence of osteoporotic vertebral fractures (VF) is an important risk factor for all future fractures independent of BMD. Yet, determination of the VF status has not become standard practice. Vertebral Fracture Assessment (VFA) is a new feature available on modern densitometers. In this study we aimed to determine the prevalence of VF using VFA in all patients referred for BMD testing in a university medical center and to evaluate its added clinical value. Prospective diagnostic evaluation study in 2,500 consecutive patients referred for BMD. Patients underwent VFA in supine position after BMD testing. Questionnaires were used to assess perceived added value of VFA. In 2,424 patients (1,573 women), results were evaluable. In 541 patients (22%), VFA detected a prevalent VF that was unknown in 69%. In women, the prevalence was 20% versus 27% found in men (p <0.0001). The prevalence of VF was 14% in patients with normal BMD (97/678), increased to 21% (229/1,100) in osteopenia and to 26% in those with osteoporosis (215/646) by WHO criteria. After excluding mild fractures VF prevalence was 13% (322/2,424). In 468 of 942 questionnaires (50% response rate), 27% of the referring physicians reported VFA results to impact on patient management. VFA is a patient friendly new tool with a high diagnostic yield, as it detected unknown VF in one out of each six patients, with significant impact on management. We believe these findings justify considering VFA in all new patients referred for osteoporosis assessment in similar populations

Impact of generic alendronate cost on the cost-effectiveness of osteoporosis screening and treatment

Introduction: Since alendronate became available in generic form in the Unites States in 2008, its price has been decreasing. The objective of this study was to investigate the impact of alendronate cost on the cost-effectiveness of osteoporosis screening and treatment in postmenopausal women. Methods: Microsimulation cost-effectiveness model of osteoporosis screening and treatment for U.S. women age 65 and older. We assumed screening initiation at age 65 with central dual-energy x-ray absorptiometry (DXA), and alendronate treatment for individuals with osteoporosis; with a comparator of "no screening" and treatment only after fracture occurrence. We evaluated annual alendronate costs of $20 through$800; outcome measures included fractures; nursing home admission; medication adverse events; death; costs; quality-adjusted life-years (QALYs); and incremental cost-effectiveness ratios (ICERs) in 2010 U.S. dollars per QALY gained. A lifetime time horizon was used, and direct costs were included. Base-case and sensitivity analyses were performed. Results: Base-case analysis results showed that at annual alendronate costs of $200 or less, osteoporosis screening followed by treatment was cost-saving, resulting in lower total costs than no screening as well as more QALYs (10.6 additional quality-adjusted life-days). When assuming alendronate costs of$400 through $800, screening and treatment resulted in greater lifetime costs than no screening but was highly cost-effective, with ICERs ranging from$714 per QALY gained through $13,902 per QALY gained. Probabilistic sensitivity analyses revealed that the cost-effectiveness of osteoporosis screening followed by alendronate treatment was robust to joint input parameter estimate variation at a willingness-to-pay threshold of$50,000/QALY at all alendronate costs evaluated. Conclusions: Osteoporosis screening followed by alendronate treatment is effective and highly cost-effective for postmenopausal women across a range of alendronate costs, and may be cost-saving at annual alendronate costs of $200 or less. © 2012 Nayak et al

Distribution, size, shape, growth potential and extent of abdominal aortic calcified deposits predict mortality in postmenopausal women

Background: Aortic calcification is a major risk factor for death from cardiovascular disease. We investigated the relationship between mortality and the composite markers of number, size, morphology and distribution of calcified plaques in the lumbar aorta.Methods: 308 postmenopausal women aged 48-76 were followed for 8.3 ± 0.3 years, with deaths related to cardiovascular disease, cancer, or other causes being recorded. From lumbar X-rays at baseline the number (NCD), size, morphology and distribution of aortic calcification lesions were scored and combined into one Morphological Atherosclerotic Calcification Distribution (MACD) index. The hazard ratio for mortality was calculated for the MACD and for three other commonly used predictors: the EU SCORE card, the Framingham Coronary Heart Disease Risk Score (Framingham score), and the gold standard Aortic Calcification Severity score (AC24) developed from the Framingham Heart Study cohorts.Results: All four scoring systems showed increasing age, smoking, and raised triglyceride levels were the main predictors of mortality after adjustment for all other metabolic and physical parameters. The SCORE card and the Framingham score resulted in a mortality hazard ratio increase per standard deviation (HR/SD) of 1.8 (1.51-2.13) and 2.6 (1.87-3.71), respectively. Of the morphological x-ray based measures, NCD revealed a HR/SD >2 adjusted for SCORE/Framingham. The MACD index scoring the distribution, size, morphology and number of lesions revealed the best predictive power for identification of patients at risk of mortality, with a hazard ratio of 15.6 (p < 0.001) for the 10% at greatest risk of death.Conclusions: This study shows that it is not just the extent of aortic calcification that predicts risk of mortality, but also the distribution, shape and size of calcified lesions. The MACD index may provide a more sensitive predictor of mortality from aortic calcification than the commonly used AC24 and SCORE/Framingham point card systems

The prevalence of vertebral fracture amongst patients presenting with non-vertebral fractures

INTRODUCTION: Despite vertebral fracture being a significant risk factor for further fracture, vertebral fractures are often unrecognised. A study was therefore conducted to determine the proportion of patients presenting with a non-vertebral fracture who also have an unrecognised vertebral fracture. METHODS: Prospective study of patients presenting with a non-vertebral fracture in South Glasgow who underwent DXA evaluation with vertebral morphometry (MXA) from DV5/6 to LV4/5. Vertebral deformities (consistent with fracture) were identified by direct visualisation using the Genant semi-quantitative grading scale. RESULTS: Data were available for 337 patients presenting with low trauma non-vertebral fracture; 261 were female. Of all patients, 10.4% were aged 50–64 years, 53.2% were aged 65–74 years and 36.2% were aged 75 years or over. According to WHO definitions, 35.0% of patients had normal lumbar spine BMD (T-score −1 or above), 37.4% were osteopenic (T-score −1.1 to −2.4) and 27.6% osteoporotic (T-score −2.5 or lower). Humerus (n=103, 31%), radius–ulna (n=90, 27%) and hand/foot (n=53, 16%) were the most common fractures. For 72% of patients (n=241) the presenting fracture was the first low trauma fracture to come to clinical attention. The overall prevalence of vertebral deformity established by MXA was 25% (n=83); 45% (n=37) of patients with vertebral deformity had deformities of more than one vertebra. Of the patients with vertebral deformity and readable scans for grading, 72.5% (58/80) had deformities of grade 2 or 3. Patients presenting with hip fracture, or spine T-score ≤−2.5, or low BMI, or with more than one prior non-vertebral fracture were all significantly more likely to have evidence of a prevalent vertebral deformity (p<0.05). However, 19.8% of patients with an osteopenic T-score had a vertebral deformity (48% of which were multiple), and 16.1% of patients with a normal T-score had a vertebral deformity (26.3% of which were multiple). Following non-vertebral fracture, some guidelines suggest that anti-resorptive therapy should be reserved for patients with DXA-proven osteoporosis. However, patients who have one or more prior vertebral fractures (prevalent at the time of their non-vertebral fracture) would also become candidates for anti-resorptive therapy—which would have not been the case had their vertebral fracture status not been known. Overall in this study, 8.9% of patients are likely to have had a change in management by virtue of their underlying vertebral deformity status. In other words, 11 patients who present with a non-vertebral fracture would need to undergo vertebral morphometry in order to identify one patient who ought to be managed differently. CONCLUSIONS: Our results support the recommendation to perform vertebral morphometry in patients who are referred for DXA after experiencing a non-vertebral fracture. Treatment decisions will then better reflect any given patient’s future absolute fracture risk. The 'Number Needed to Screen' if vertebral morphometry is used in this way would be seven to identify one patient with vertebral deformity, and 14 to identify one patient with two or more vertebral deformities. Although carrying out MXA will increase radiation exposure for the patient, this increased exposure is significantly less than would be obtained if X-rays of the dorso-lumbar spine were obtained

Using clinical risk factors and bone mineral density to determine who among patients undergoing bone densitometry should have vertebral fracture assessment

Vertebral fracture assessment (VFA) is a new method for imaging thoracolumbar spine on bone densitometer. Among patients referred for bone densitometry, the selection of patients for VFA testing can be optimized using an index derived from clinical risk factors and bone density measurement. VFA, a method for imaging thoracolumbar spine on bone densitometer, was developed because vertebral fractures, although common and predictive of future fractures, are often not clinically diagnosed. The study objective was to develop a strategy for selecting patients for VFA. A convenience sample from a university hospital bone densitometry center included 892 subjects (795 women) referred for bone mineral density (BMD) testing. We used questionnaires to capture clinical risk factors and dual-energy X-ray absorptiometry to obtain BMD and VFA. Prevalence of vertebral fractures was 18% in women and 31% in men (p = 0.003 for gender difference). In women, age, height loss, glucocorticoid use, history of vertebral and other fractures, and BMD T-score were significantly and independently associated with vertebral fractures. A multivariate model which included above predictors had an area under the receiver operating curve of 0.85 with 95% confidence interval (CI) of 0.81 to 0.89. A risk factor index was derived from the above multivariate model. Using a level of 2 as a cut-off yielded 93% sensitivity (95% CI 87, 96) and 48% specificity (95% CI 69, 83). Assuming a 15% prevalence of vertebral fractures, this cut-off value had a 24% positive and 97% negative predictive value and required VFA scanning of three women at a cost of $60 (assuming a$20 cost/VFA scan) to detect one with vertebral fracture(s). Selecting patients for VFA can be optimized using an index derived from BMD measurement and easily obtained clinical risk factors

An assessment of existing models for individualized breast cancer risk estimation in a screening program in Spain

Background: The aim of this study was to evaluate the calibration and discriminatory power of three predictive models of breast cancer risk. Methods: We included 13,760 women who were first-time participants in the Sabadell-Cerdanyola Breast Cancer Screening Program, in Catalonia, Spain. Projections of risk were obtained at three and five years for invasive cancer using the Gail, Chen and Barlow models. Incidence and mortality data were obtained from the Catalan registries. The calibration and discrimination of the models were assessed using the Hosmer-Lemeshow C statistic, the area under the receiver operating characteristic curve (AUC) and the Harrell’s C statistic. Results: The Gail and Chen models showed good calibration while the Barlow model overestimated the number of cases: the ratio between estimated and observed values at 5 years ranged from 0.86 to 1.55 for the first two models and from 1.82 to 3.44 for the Barlow model. The 5-year projection for the Chen and Barlow models had the highest discrimination, with an AUC around 0.58. The Harrell’s C statistic showed very similar values in the 5-year projection for each of the models. Although they passed the calibration test, the Gail and Chen models overestimated the number of cases in some breast density categories. Conclusions: These models cannot be used as a measure of individual risk in early detection programs to customize screening strategies. The inclusion of longitudinal measures of breast density or other risk factors in joint models of survival and longitudinal data may be a step towards personalized early detection of BC.This study was funded by grant PS09/01340 and The Spanish Network on Chronic Diseases REDISSEC (RD12/0001/0007) from the Health Research Fund (Fondo de Investigación Sanitaria) of the Spanish Ministry of Health

Mammographic density and risk of breast cancer according to tumor characteristics and mode of detection: a Spanish population-based case-control study

It is not clear whether high mammographic density (MD) is equally associated with all subtypes of breast cancer (BC). We investigated the association between MD and subsequent BC, considering invasiveness, means of detection, pathologic subtype, and the time elapsed since mammographic exploration and BC diagnosis. METHODS: BC cases occurring in the population of women who attended screening from 1997 through 2004 in Navarre, a Spanish region with a fully consolidated screening program, were identified via record linkage with the Navarre Cancer Registry (n = 1,172). Information was extracted from the records of their first attendance at screening in that period. For each case, we randomly selected four controls, matched by screening round, year of birth, and place of residence. Cases were classified according to invasiveness (ductal carcinoma in situ (DCIS) versus invasive tumors), pathologic subtype (considering hormonal receptors and HER2), and type of diagnosis (screen-detected versus interval cases). MD was evaluated by a single, experienced radiologist by using a semiquantitative scale. Data on BC risk factors were obtained by the screening program in the corresponding round. The association between MD and tumor subtype was assessed by using conditional logistic regression. RESULTS: MD was clearly associated with subsequent BC. The odds ratio (OR) for the highest MD category (MD >75%) compared with the reference category (MD <10%) was similar for DCIS (OR = 3.47; 95% CI = 1.46 to 8.27) and invasive tumors (OR = 2.95; 95% CI = 2.01 to 4.35). The excess risk was particularly high for interval cases (OR = 7.72; 95% CI = 4.02 to 14.81) in comparison with screened detected tumors (OR = 2.17; 95% CI = 1.40 to 3.36). Sensitivity analyses excluding interval cases diagnosed in the first year after MD assessment or immediately after an early recall to screening yielded similar results. No differences were seen regarding pathologic subtypes. The excess risk associated with MD persisted for at least 7 to 8 years after mammographic exploration. CONCLUSIONS: Our results confirm that MD is an important risk factor for all types of breast cancer. High breast density strongly increases the risk of developing an interval tumor, and this excess risk is not completely explained by a possible masking effect.This work was supported by research grants from Eli Lilly and Company (EV1 1082/08); and the Spanish Federation of Breast Cancer Patients (Federación Española de Cáncer de Mama) (FECMA 485 EPY 1170-10).S

Modelling the Cost Effectiveness of Interventions for Osteoporosis: Issues to Consider

Expenditure on treating osteoporotic fractures and on preventative intervention is considerable and is likely to rise in forthcoming years due to the association between fracture risk and age. With funders such as the National Institute for Health and Care Excellence and the Pharmaceutical Benefits Advisory Committee explicitly considering cost-effectiveness analyses within the process of producing guidance, it is imperative that economic models are as robust as possible. This article details issues that need to be considered specifically related to health technology assessments of interventions for osteoporosis, and highlights limitations within the current evidence base. A likely direction of impact on cost effectiveness of addressing the key issues has been included alongside a tentative categorization of the level of these impacts. It is likely that cost-effectiveness ratios presented in previous models that did not address the identified issues were favourable to interventions