Using Risk Factors and Quantitative Ultrasound to Identify Postmenopausal Caucasian Women at Risk of Osteoporosis

Abstract

There is a need to prescreen large numbers of individuals for osteoporosis due to current demands on clinical resources. Some previous attempts to predict individuals at risk have used simple indices based on patient information, or Quantitative Ultrasound (QUS) and have shown good sensitivity but also demonstrated low specificity, which means that many individuals with good bone mineral density were also selected. The aim of this study was to determine if a tool based on a combination of risk factors and QUS measurements could also be made to provide improved specificity. A risk factors measurement questionnaire was created and completed for a sample of Caucasian postmenopausal women (n = 235) who had undergone Dual-energy X-ray absorptiometry scanning. QUS measurements were also taken at various skeletal sites. Assessment tools were generated using stepwise regression to predict osteoporosis, evaluated by receiver operating characteristic curves, and assessed using area under the curve values. Specificity values were determined at a sensitivity of 0.90 to establish the comparative utility of each assessment tool. Using only a risk factors model the specificities were 0.28 at the lumbar spine, 0.45 for the femoral neck and 0.68 for the total hip. In a risk factors + QUS data model the specificities measured were 0.44 for the lumbar spine, 0.78 for the femoral neck, and 0.84 for the total hip. These novel assessment tools can identify those with low bone mineral density at a number of skeletal sites and help towards avoiding many unnecessary investigations in the future.

Introduction

The skeletal condition osteoporosis is characterized in cancellous bone by a reduction in the apparent density and structural integrity of the bone and a thinning of the trabeculae within the 3D network. These effects result in the reduced mechanical integrity of the tissue and the low trauma fractures, which are characteristic of the condition. The selection of individuals with low Bone Mineral Density (BMD) is important as it enables the early application of treatments that can lower the risk of fracture. The determination of BMD by Dual-Energy X-ray Absorptiometry (DXA) is widely accepted as the standard method for the assessment of axial skeletal density and it is the T-scores determined on the basis of a BMD measurement on which the World Health Organization and the International Society for Clinical Densitometry base the definition of Osteoporosis. The problem arises, that the densitometry equipment is expensive and requires a skilled radiographer if high-quality results are to be obtained. As a result, densitometry services are frequently hospital based, expensive to run and, due to the increasing number of people at risk and age of the population, running beyond capacity. Indeed, a report carried out by the National Osteoporosis Society suggested that an additional 126 axial DXA scanners are required to cope with the current and future needs of the National Health Service (NHS) (1).

The potential to have a method of screening large groups of individuals so that selection and prioritization can occur is an attractive proposition. This will enable earlier detection and diagnosis of those individuals most at risk of osteoporosis. Many groups have attempted to produce simple assessment tools based on easily attainable patient information 2, 3, 4, 5, 6, 7. These tools were generated to predict those at the highest risk of osteoporosis for immediate priority treatment and those at low risk could perhaps be reassessed at a later date. The use of Quantitative Ultrasound (QUS) has been shown to have a moderate-to-good ability to predict osteoporosis in postmenopausal women, depending on the technique and the site of investigation 8, 9, 10, 11.

The idea of combining risk factors and QUS measurements to predict osteoporosis has been less extensively explored. The study by Richy et al (12) demonstrated that a combined tool using both QUS at the proximal phalanx and a risk factor based assessment, could improve the diagnostic ability over and above that which was obtainable by the use of the individual methods separately. Pongchaiyakul et al (13) compared how a score based on age and weight, QUS at the calcaneus and a combination of both these techniques for predicting osteoporosis at the femoral neck. They found that for a Thai population the combination model had a significantly higher Area Under the Curve (AUC).

The down side of these screening methods is that they focus primarily on the correct selection of those most at risk of osteoporosis. This has led to promising predictive abilities, but at the expense of specificity, which is the ability to correctly select those individuals not at risk of osteoporosis. As a result the numbers of individuals being selected as needing a densitometry investigation when it is not a priority remains high.

The aim of this study was to analyze risk factors associated with osteoporosis and a variety of QUS measurements, at various skeletal sites, to determine if a combination of these could be used to discriminate between patients with osteoporosis and those with BMD within the normal range, maintaining high levels of sensitivity but also achieving good specificity.