Diagnosis and Monitoring
Evidence Report/Technology Assessment: Number 28
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Under its Evidence-based Practice Program, the Agency for Healthcare Research and Quality (AHRQ) is
developing scientific information for other agencies and organizations on which to base clinical guidelines,
performance measures, and other quality improvement tools. Contractor institutions review all relevant
scientific literature on assigned clinical care topics and produce evidence reports and technology
assessments, conduct research on methodologies and the effectiveness of their implementation, and
participate in technical assistance activities.
Overview / Reporting the Evidence / Methodology / Findings / Future Research / Availability of Full Report
At an international consensus development conference, osteoporosis was defined as "a systemic skeletal disease characterized by low bone mass and microarchitectural deterioration of bone tissue, leading to enhanced bone fragility and a consequent increase in fracture risk." In 1994, a World Health Organization (WHO) working group proposed that, in epidemiologic studies, osteoporosis could be determined when bone density at the hip, spine, or forearm is 2.5 standard deviations or more below the mean for healthy, young, adult women (a value defined as the T-score), or when a history of a fracture is present in the absence of trauma. The group also proposed that osteopenia be determined when the bone density was 1.0 to 2.5 standard deviations below the mean for young, healthy women.
According to the National Health and Nutrition Examination Survey (NHANES III), an estimated 14 million American women over age 50 years are affected by low bone density at the hip, and 5 million more have bone density that measures 2.5 standard deviations or more below the mean at the hip. The prevalence of osteoporosis in Mexican-American women is similar to that in white women, while rates in black women are approximately half that of the first two groups. The prevalence of osteoporosis increases with age for all sites, and by the WHO definition up to 70 percent of women over age 80 years have osteoporosis.
Furthermore, age is an important factor in the relationship between bone density and the absolute risk of fracture. An increase in age of 13 years increases the risk of hip fracture by the same amount as a decrease in bone density of one standard deviation. Older women have a much higher fracture rate than younger women who have the same bone density, because of increasing risk from other factors, such as a change in bone quality and the tendency to fall.
Women with osteoporosis are more likely to experience fractures. Demographic trends for hip fracture parallel those for osteoporosis. Hip-fracture incidence in white women rises from 50 per 100,000 at age 50 years to 237 per 100,000 at age 65 years. White women are generally two to three times more likely than nonwhite women to suffer a hip fracture. Hip fractures are associated with high rates of mortality and loss of independence. Wrist fracture incidence tends to increase at earlier ages than does that of hip fractures.
Vertebral fractures have also been associated with significant morbidity. Sixteen percent of postmenopausal women have osteoporosis of the lumbar spine; furthermore, five percent of 50-year-old white women and 25 percent of 80-year-old women have had at least one vertebral fracture. Vertebral fractures can cause severe pain and are associated with more than five million days of restricted activity in those age 45 years or older.
The disease burden of osteoporosis extends beyond consequences of low bone density and fractures. For example, the act of screening, diagnosis, and subsequent treatment can also affect the quality of life. Fear of fracture itself can reduce the quality of life in women who have been diagnosed as having osteoporosis.
In 1995, the total direct medical expenditure in the United States for the treatment of osteoporotic fractures in adults older than 45 years was estimated at $13.8 billion. The majority of this total ($8.6 billion) was spent for inpatient care. Hip fracture alone accounted for $8.7 billion (63 percent) of osteoporosis-related costs, while fractures at sites other than the hip accounted for approximately 37 percent of the total expenditure (about $5.1 billion). In addition to these costs is the cost of lost productivity for women with fractures, or for their family or other caregivers. As the median age of the U.S. population increases, the costs associated with osteoporotic fractures are also likely to increase.
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Reporting the Evidence
This evidence report describes the effectiveness of various strategies for diagnosing and monitoring postmenopausal women with osteoporosis, as represented by six topic areas:
- Risk Factors. What is the role of clinical risk factors, in conjunction with bone measurement tests, in identifying high-risk women and guiding initial treatment decisions?
- Bone Measurement Tests. What are the advantages and disadvantages of various bone measurement tests at different anatomic sites for identifying women at high risk of fracture?
- Monitoring. Are bone measurement tests effective for monitoring response to treatment and for guiding decisions about changes in management?
- Markers. What is the role of markers of bone turnover for identifying women at risk of bone loss, guiding initial treatment decisions, or monitoring response to therapy?
- Secondary Causes. What diagnostic or laboratory tests are appropriate for evaluating patients with osteoporosis, as determined by bone measurement tests or documented vertebral fractures?
- Cost. Assuming consistent treatment approaches, what are the costs and cost-effectiveness of various diagnostic strategies for identifying women with osteoporosis?
These topic areas do not include the effectiveness of dietary, lifestyle, hormonal, and medical interventions for primary prevention or treatment of osteoporosis.
This report is confined to diagnostic and monitoring strategies as they apply to individual women, and does not include issues regarding mass screening in the general population. Also, while most of the literature addressing these topic areas is aimed at an audience of clinical researchers who specialize in osteoporosis, we have attempted to assess the research findings from the perspectives of clinicians and patients. However, it is not the purpose of this report to propose practice recommendations.
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With input from local and national experts, we developed analytic frameworks and key questions in each of the six topic areas. Relevant studies were identified from multiple searches of MEDLINE (for the years 1966 to 2000) and HealthSTAR (for the years 1975 to 2000), from the reference lists of systematic review articles, and from national experts. All searches were limited to publications in the English language. The authors excluded articles if they did not provide sufficient information to determine the methods for selecting subjects and for analyzing data.
Out of 10,174 citations retrieved for all topics combined, the authors selected as possibly relevant 530 articles about risk factors, 123 about bone measurement tests, 23 about bone density monitoring, 277 about biochemical markers, and 53 about costs. An additional 242 studies were retrieved after reviewing reference lists of studies and by suggestion of the expert panel or leading researchers in the field. The search yielded no papers with data for the secondary causes topic, but this topic was addressed by reviewing published guidelines and by a supplemental analysis of physician practice patterns for the evaluation of secondary causes of osteoporosis.
For articles that were included, the authors applied criteria proposed by the U.S. Preventive Services Task Force to rate the quality of individual studies. A second supplemental analysis investigated the cost-effectiveness of various diagnostic strategies.
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Relevant articles were reviewed. The findings about the clinical risk factors that predict bone density, bone loss, and fractures included:
- Factors that are consistently associated with increased risks of low bone density and fractures in postmenopausal women include increasing age, white race, low weight or weight loss, nonuse of estrogen replacement, history of previous fracture, family history of fracture, history of falls, and low scores on one or more measures of physical activity or function.
- Other factors are less consistent predictors across studies, but also have statistically significant associations with low bone density and fractures. These include smoking, alcohol use, caffeine use, low calcium and vitamin D intake, and use of certain drugs.
- Predictors of low bone density are similar to those for fracture, except for those factors related to physical function and falls.
- Some clinical risk factors, especially those related to physical function and falls, are as powerful as bone density in the prediction of hip fracture.
- Women with multiple risk factors and low bone density have an especially high risk of hip fracture.
- Most of the strongest risk factors are consistently related to outcomes, regardless of the racial and ethnic population, although there are few studies of nonwhite women.
A second set of findings about risk factors concerned the accuracy of the sets of clinical questions (typically called instruments, tools, or profiles) used in assessing the risk factors that identify women at risk of fracture. These included:
- In contrast to the extensive research about determining clinical risk factors for osteoporosis and fractures, there are fewer studies available that evaluate how to use these risk factors to identify individual women at risk for fracture.
- Instruments designed to assess risk of low bone density or fractures generally have low to moderate sensitivity and specificity. Those that perform well when originally tested either have performed less well in other populations or have not yet been widely tested. Some instruments, especially those developed in large community populations and containing variables known to be strong predictors, may ultimately be applicable to the clinical setting once they are tested there.
A third set of findings, exploring whether risk factors are useful in treatment decisions, included:
- The authors did not identify any studies that examined whether treatment decisions based on clinical risk factors lead to better or worse health outcomes than those based on bone measurement tests or a combination of bone tests and risk factors.
Bone Measurement Tests
The major findings related to the capacity of different bone measurement tests to predict fractures included:
- Among different bone measurement test values obtained at various anatomical sites, bone density measured at the femoral neck by dual energy x-ray absorptiometry (DXA) is the best predictor of hip fracture and is comparable to forearm measurements for predicting fracture at other sites.
- Recent prospective studies have evaluated quantitative ultrasound (QUS) measurements at the heel. For both this test and DXA, a result in the osteoporotic range is associated with an increased short-term probability of hip fracture. Individuals who have low scores by one of these tests, but not the other, have a higher risk of fracture than those who have higher scores by both tests, and a lower risk of fracture than those whose results on both tests are low.
- While other peripheral measures may approach QUS in predicting hip fracture, there are no recent prospective studies that directly compare prediction of hip fracture of these tests with DXA of the hip. Radiographic absorptiometry (RA) or quantitative microdensitometry (QMD) of the hand can predict the risk of nonspine fractures in general, many of which are in the forearm, but there are no recent data about the ability of hand measurement to predict hip fracture.
- Correlations between different bone measurement tests are generally too low to be accepted as evidence that one test will identify patients at similar risk to those identified by another test.
Major findings on identification of the factors related to bone testing that influence diagnosis included:
- The likelihood of being diagnosed with osteoporosis varies greatly, depending on the site and type of the bone measurement test, on the brand of densitometer, and on the relevance of the reference range to the local population.
- The likelihood of being diagnosed as having osteoporosis also depends on the number of sites tested. Testing in the forearm, hip, spine, or heel will generally identify different groups. A physician cannot say, based only on one of these tests, that the patient "does not have osteoporosis."
- The results of bone measurement tests are often inaccurately reported to patients.
Major findings related to how bone measurement test results affect patients' and physicians' decisions and actions included:
- One randomized trial suggests that women who undergo densitometry are more likely to start hormone replacement therapy than women who do not.
- In a randomized trial and a large, uncontrolled case series, women who had densitometry and were told they had osteoporosis were more likely to start or continue hormone replacement therapy than women who were told they had normal bone density.
- In one randomized trial, physicians found densitometry reports confusing and were not confident that their interpretations of T-scores were correct.
The major findings regarding whether bone measurement tests are effective for monitoring response to therapy and for guiding decisions about changes in management included:
- The weight of the evidence is currently against repeating bone density tests within the first year of treatment. There is insufficient evidence to determine whether repeating bone density tests 2 years after starting therapy is useful.
- There are also no studies about the effect of either monitoring responses to therapy using densitometry or the choice of test on the outcome of therapy.
Findings regarding whether biochemical markers can be used instead of bone measurement tests to identify women who have low bone density included:
- No single marker or cluster of markers accurately identified individuals who had osteoporosis, as determined by the results of densitometry. It is not surprising that agreement between the two tests was poor. Densitometry measures current bone status, whereas markers measure the process of bone turnover.
Major findings as to how well biochemical markers predict fracture included:
- No marker was associated with increased fracture risk consistently across all studies. One study provides evidence that using markers in conjunction with densitometry may increase predictability, but this result has not been otherwise confirmed.
In addition, major findings as to whether markers can help select patients for treatment included:
- Studies correlating marker results and bone loss indicated no clear trend. Furthermore, sensitivity and specificity of markers were too low to be useful for the purpose of selecting patients for treatment.
- Some studies found better test accuracy when a combination of two or more markers and/or other risk factors was used to predict bone loss.
Major findings regarding whether markers can predict a patients' response to therapy included:
- There is a small correlation between response to therapy as measured by densitometry and marker results, but no marker is accurate enough to reliably identify those individuals who will fail to respond to treatment.
Evaluation for Secondary Causes of Osteoporosis
Major findings from a literature review, assessment of published guidelines, and a secondary analysis regarding which diagnostic or laboratory tests are appropriate for evaluating patients with osteoporosis for secondary causes included:
- There is no evidence from controlled trials on which to base recommendations for a strategy of testing to determine secondary causes of osteoporosis.
- Some guidelines and experts support extensive testing to rule out major concomitant disease, while others suggest a limited testing strategy based on findings in the history and physical examination. Because the diagnosis of primary osteoporosis is often seen as a diagnosis of exclusion, the pattern of diagnostic testing may continue to be costly until the diagnostic yield is fully demonstrated.
- Assumptions about the probability of a secondary disease or disorder to explain the occurrence of osteoporosis vary by practice type and specialty.
- Thyroid stimulating hormone measurement, chemistry battery, and complete blood count were the most frequently ordered tests to rule out secondary causes of osteoporosis cited by respondents in our supplemental analysis. These were also the most frequently recommended tests in our review of expert guidelines.
The reports' findings regarding the costs and cost-effectiveness of diagnostic strategies for identifying women with osteoporosis included:
- Published economic assessments suggested that diagnosis and treatment of women at risk for osteoporosis would be more cost-effective by targeting treatment to those with the lowest bone measurement results. Inclusion of another assessment, such as a risk profile or additional bone measurement test, prior to DXA may improve the cost-effectiveness of diagnosis.
- Using data from two large studies, the authors conducted cost-effectiveness analyses to estimate cost per hip fracture prevented. These analyses suggested that a sequential diagnostic approach may be more cost-effective than DXA alone. The sequential approach that the authors considered was QUS of the heel followed by DXA of the femoral neck only for those with low values of QUS/BUA. A range of QUS/BUA measures was used because there are no established cut points that separate high risk from normal risk. The authors used QUS as an example of a less expensive and more widely available diagnostic approach than DXA.
- Diagnosis with DXA of the femoral neck alone prevented more fractures, in most cases, but at a higher cost per hip fracture prevented, compared with the sequential approach.
- In sensitivity analyses, the authors considered the possibility that treatment efficacy could be 5-15 percent less following diagnosis using QUS than when using DXA. If this assumption were correct, the use of QUS alone would be less cost-effective than DXA at cut points of 75 dB/MHz or less.
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Much of the evidence for the diagnosis and monitoring strategies for osteoporosis comes from epidemiologic studies. To be more useful for clinicians and patients, future research should focus on the application of these data to the clinical setting and include a wider diversity of patient populations. Tools for assessing risk factors should be tested in prospective studies to determine if their use can correctly stratify women by risk factors, influence treatment decisions, and ultimately reduce fracture outcomes.
Clinical trials should be conducted to determine if identifying and reducing modifiable risk factors influences fracture outcomes. Addressing some of these modifiable risk factors, such as by supplementation with calcium and vitamin D, has already demonstrated effects on fracture risk after intervention. Examples of additional interventions to test include smoking cessation, correcting visual loss, and improving physical function.
Future research should examine the clinical utility of the WHO working group's criterion for diagnosing osteoporosis. Randomized, controlled trials of treatments for osteoporosis should be done to test the hypothesis that overall fracture risk, rather than bone measurement results alone, determines the likelihood that a patient will benefit from therapy. Trials should also address whether patients who are identified to have bone loss demonstrated by different techniques at different anatomical sites demonstrate a similar benefit to those identified solely by hip DXA measurements.
Additional research is needed to examine the quality of information provided to patients who undergo various bone measurement tests, as well as to identify other patient education and information needs.
Studies that use bone measurement tests for monitoring response to therapy could compare fracture outcomes in a group of patients who had tailored therapy based on test results versus a group in whom changes in therapy, if any, were guided by the history alone. A study could also record how often test results in patients on therapy led to a change in therapy or improved compliance, to establish the mechanism by which monitoring leads to improved fracture outcomes.
Prospective studies of biochemical markers should define, apply, and evaluate criteria for using marker results in clinical decisionmaking.
Determining the utility of screening for secondary disorders by use of common laboratory tests requires studies of the frequency of abnormal baseline laboratory test results in large cohorts or in treatment trials of osteoporosis. Clinical follow-up of these subjects would provide data on bone measurement test results or fracture outcomes.
Studies to formally account for the adverse quality-of-life impact of treatment and treatments side effects are needed to more accurately determine the balance of risks and benefits of the therapy options presented to patients.
Additional cost-effectiveness research could include identifying a scientifically appropriate cut point for QUS/BUA that can be used in a sequential diagnostic approach or for diagnosis with QUS alone. Performing additional cost-effectiveness analyses using data from other large, population-based cohorts with various cut points and conducting a more detailed, societal-perspective, cost-effectiveness analysis would address some of the deficiencies in the authors' analysis. If these findings can be demonstrated in one or two other populations, and in a more complete economic evaluation, a randomized, controlled trial of diagnostic approaches would be a useful next step.
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Availability of Full Report
The full evidence report from which this summary was derived was prepared for the Agency for Healthcare Research and Quality by the Oregon Health Sciences University Evidence-based Practice Center under contract No. 290-97-0018. Printed copies may be obtained free of charge from the AHRQ Publications Clearinghouse by calling 800-358-9295. Requestors should ask for Evidence Report/Technology Assessment No. 28, Osteoporosis in Postmenopausal Women: Diagnosis and Monitoring (AHRQ Publication No. 01-E032).
The Evidence Report is also online on the National Library of Medicine Bookshelf.
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AHRQ Publication Number 01-E031
Current as of February 2001