1 Department of Social and Preventive Medicine, University at Buffalo, Buffalo, NY.
2 Department of Gynecology/Obstetrics, University at Buffalo, Buffalo, NY.
3 Department of Mathematics, University of North Carolina at Charlotte, Charlotte, NC.
Received for publication December 9, 2003; accepted for publication March 24, 2004.
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
bone density; densitometry; diagnosis; drug therapy; mass screening; osteoporosis, postmenopause; risk factors
Abbreviations: Abbreviations: CI, confidence interval; DXA, dual-energy x-ray absorptiometry; OR, odds ratio.
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Detection of osteoporosis is possible at treatable stages of the disease, and early detection and treatment have been shown to decrease associated morbidity and mortality (3). Dual-energy x-ray absorptiometry (DXA) is currently considered the "gold standard" for measuring bone mineral density and predicting fracture risk (4). Fracture risk is also affected by other factors, such as poor bone quality and a propensity to fall, but bone density is the single best predictor of fracture risk. The US Food and Drug Administration has approved several treatments for the prevention and/or treatment of osteoporosis, including bisphosphonates (alendronate and risedronate), calcitonin, hormone therapy (estrogen alone or in combination with progestin), raloxifene, and teriparatide (5).
Inadequate diagnosis and treatment of osteoporosis are a problem (6, 7). Previous studies have shown that providers recommend and women accept drug treatment more often when screening results show an increased risk of fracture (812). These studies have focused on the outcomes of a screening test ordered by a physician. Some degree of awareness of the disease and potential interest in treatment are implied when a physician orders a test. The factors associated with treatment following screening in an at-risk population not specifically referred by a physician have not been well documented.
This studys objectives were to determine the prevalence of osteoporosis in a previously unscreened group of postmenopausal women and, for women newly determined to have osteoporosis at screening, to assess factors associated with drug treatment initiation.
![]() |
MATERIALS AND METHODS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Participants completed several questionnaires that included items on known risk factors for osteoporosis and periodontal disease. Bone densities of the spine, hip, forearm, and total body were measured by DXA (Hologic QDR-4500A; Hologic, Inc., Waltham, Massachusetts), and an oral health examination was completed. Participants were mailed a copy of their DXA results with a summary cover sheet, which included the World Health Organization definitions and values of T-scores for four measured sites (anteroposterior spine, lateral spine, femoral neck, and total forearm).
The impact of this DXA screening on study participants was assessed by using a follow-up questionnaire. Participants were asked whether they discussed the DXA results with their health care provider, whether their provider recommended various treatments, whether they initiated any treatment, whether they were complying with treatment, and whether they personally decided to make any changes not recommended by their provider. Participants were mailed the questionnaires at least 1 year after they participated in the study (DXA screening) to allow ample time to discuss their DXA findings with their health care provider. A postage-paid envelope was included to return the completed questionnaires. Questionnaires not returned from the initial mailing were followed up with a second mailing, postcard reminders, and telephone follow-up.
This study was approved by the Health Sciences Internal Review Board of the University at Buffalo. Informed consent was obtained for both the Womens Health Initiative study and the Osteoporosis and Oral Bone Loss Study.
Data collected from the follow-up questionnaire were combined with existing data from participants records of the Womens Health Initiative Observational Study and the Osteoporosis and Oral Bone Loss Study to form the analytical data set. Since this study aimed to assess the impact of osteoporosis screening in a group of postmenopausal women unaware of their bone density status, participants who reported a previous diagnosis of osteoporosis, previous bone density testing, or ever taking a bone drug other than hormone therapy were excluded from the analyses. Descriptive statistics were computed for demographics and other variables and for outcomes of screening and discussion of results with a health care provider.
Univariate logistic regression models were developed to establish factors associated with drug treatment initiation that were further analyzed in multivariate models. Factors assessed included age (years), T-score (lowest of the femoral neck, lateral spine, anteroposterior spine, and total forearm T-scores), body mass index (kilograms per meter squared), race (American Indian/Alaskan Native, Asian/Pacific Islander, Black/African American, Hispanic/Latino, or White), hormone therapy use (never, former, or current), frequency of routine medical care (yearly or less or more often than yearly), fracture history after 40 years of age (yes or no), family history of fracture (yes or no), smoking (ever or never), education (high school or less, college attendance/graduation, or graduate school attendance/graduation), current employment (yes or no), income (<$50,000 or $50,000), visit date with health care provider (19971998 or after 1998), gender of provider (male or female), length of relationship with provider (years), and specialty of provider (gynecologist or other). The "other" category for specialty of provider included mainly primary care physicians and internists but also a small number of nurse practitioners, physicians assistants, rheumatologists, endocrinologists, and orthopedists. The multivariate logistic regression modeling attempted to use all factors associated (p < 0.10) with the outcome in univariate models. Stepwise logistic regression, with entry criteria of p < 0.10 and removal criteria of p > 0.05, was used to establish the final multivariate predictive model. The Statistical Package for the Social Sciences (SPSS), version 10.0 for Windows (SPSS, Inc., Chicago, Illinois), was utilized for all analyses.
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
|
|
|
|
Similarly, because some providers may have been aware of the National Osteoporosis Foundation guidelines for treatment of osteoporosis, the logistic regression analyses were repeated by restricting them to participants who had a T-score of 2.0 or less. According to National Osteoporosis Foundation guidelines, these participants should be considered for treatment (15). A total of 500 (52.9 percent) participants had T-scores of 2.0 or less, and 357 (71.4 percent) of those women discussed the results with their provider. The logistic regression findings for treatment initiation again did not differ appreciably (data not presented). Finally, the analysis was repeated by restricting it to Caucasian participants only, and our findings did not change (data not presented).
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Of those women determined at screening to be osteoporotic, 27 percent did not discuss their DXA results with a health care provider. This rate of follow-up is lower than that determined in a previous study by Rubin and Cummings (8), which included a very high percentage of women who received a referral from their physician for screening. This difference in follow-up is likely attributable to the difference in study design; our study involved community-like screening without referral from a physician. Community-based screening tests are effective only if they influence clinical decisions, and an important consideration should be a mechanism to ensure that women discuss screening results with their provider.
It is an important public health finding that even within this group of healthy, well-educated, and self-selected women, a large percentage were previously unaware of their bone density status and were newly diagnosed with osteoporosis. Over half of those women determined as having osteoporosis who consulted their health care provider after screening initiated treatment, a notable percentage initiating treatment for a disease that may not have been detected without the study DXA screening. However, almost half of the osteoporotic women did not initiate treatment. Decisions regarding initiation of treatment after diagnosis are multifactorial and may be influenced by risk factors for osteoporosis and related fracture other than low bone density. Physician recommendation and patient acceptance of treatment are also important in decision making and may be influenced by the perceived effectiveness of osteoporosis drug treatments or side effects, costs, expected uptake of treatment, or agreement with treatment recommendations.
A unique attribute of our study is that we evaluated associations between treatment initiation and characteristics (i.e., gender and specialty) of health care providers. While no significant association was found for gender of the provider, women were over three times as likely to initiate treatment if they consulted a gynecologist compared with other provider specialties. This finding suggests that gynecologists may be more likely to discuss treatment of osteoporosis. Note that the analysis did not account for treatment recommendations of providers that were not initiated by the participant, which may have resulted in underestimation of the response of all specialties of providers to their patients DXA results indicating osteoporosis.
It was an interesting finding that, even within a group of women whose T-scores were less than 2.5, women whose scores were lower were more likely to initiate treatment. This finding is consistent with the literature showing that lower T-score, in general, is associated with treatment initiation (812). It has been estimated that fracture risk approximately doubles with each standard deviation decrement in bone density compared with optimal mean bone density (18). Therefore, treatment would be expected to increase with worsening T-score and increased fracture risk.
Higher level of education and greater income were positively associated with initiation of drug treatment after bone density screening. More-educated women are perhaps more likely to initiate discussions with their health care provider and to have a better understanding of the risks of low bone density. Higher education and income may also be a proxy measure for an increased likelihood of having medical insurance, although only 1 percent of participants in this study did not have medical insurance. No information was available on prescription coverage. A previous study found no association with education (8); however, that study also included an overall highly educated group of women. Our study sample had more variation in educational level. Women who reported seeking routine medical care more often than yearly were twice as likely as women who reported less frequent medical care to initiate treatment for osteoporosis. These women are perhaps more health oriented in general and may have more opportunity to discuss their results with their health care provider. Women were surveyed at least 1 year after DXA screening, and the majority reported seeking routine medical care at least yearly. As such, most participants should have had the opportunity to discuss their results with their provider at one of their routine visits.
The results showing that higher educational level, greater income, and more frequent routine medical care are associated with treatment initiation indicate that the same groups of women who are more likely to utilize the health care system are more likely to discuss results with a health care provider and to initiate treatment after osteoporosis screening. Since screening in a community setting is valuable in reaching at-risk groups who may not otherwise use the health care system, this finding supports continuing challenges in emphasizing both screening and preventive health care for older women. However, this study included a group of women who chose to participate in a health-oriented research study, which may limit generalizability. Women in the general population undergoing osteoporosis screening may be less likely than women in our study to initiate treatment after a diagnosis of osteoporosis.
Although hormone therapy use was not found to predict treatment initiation, women who were already receiving hormone therapy could be considered to be appropriately treated for osteoporosis, which may have influenced our findings. However, restricting analyses to women not on hormone therapy did not appreciably change our findings. Similarly, race was not found to be a predictor of treatment initiation, but the number of non-White subjects was extremely small. Restriction of analyses to only White subjects did not change our findings. In addition, repeated analyses excluding lateral spine T-scores when determining osteoporotic status and changing the definition of osteoporosis to a T-score of 2.0 or less (National Osteoporosis Foundation treatment guidelines) did not change our findings.
This study has a number of strengths, including its similarity to a general population screening. Previous studies have evaluated screening outcomes for women individually referred for screening by their physician (8, 9, 11, 12). Women in our study did not undergo screening because of their individual risk of osteoporosis or physician referral. A further strength of this study was our assessment of treatment initiation at a time when several treatment options had just been approved by the Food and Drug Administration. Prior to 1996, treatment options for osteoporosis were limited largely to hormone therapy. Note that data collection was completed prior to publication of findings of adverse effects of certain types of hormone therapy in the Womens Health Initiative clinical trial (19).
Although all races were included in this study, about 98 percent of participants were Caucasian, limiting the generalizability of this study to Caucasian postmenopausal women. Another important consideration is that this analysis did not assess decisions about managing osteoporosis other than prescription drug treatments. Initiation of nonprescription therapies (e.g., calcium and vitamin D) and lifestyle changes (e.g., increased exercise and smoking cessation) were not assessed here but are important in understanding the full influence of screening on change. This is an area for future research.
In conclusion, this study showed that many postmenopausal women at risk of osteoporosis remain undiagnosed and untreated. Over one third of those screened had previously undiagnosed osteoporosis. Of those women, less than half subsequently initiated treatment. Women who had lower T-scores, higher educational levels, and greater income and who visited their provider more regularly were more likely to be treated. Additionally, women consulting a gynecologist were more likely to initiate treatment. More effort is needed to increase screening of appropriate persons at risk of osteoporosis and eventual fracture. Additional education on the importance of treatment for women whose bone density is low to prevent fractures should be emphasized to both women and their health care providers. Ultimately, treatment initiation is based on an individualized decision-making process between a woman and her health care provider. Further understanding of the factors that influence decisions to screen for and treat osteoporosis in appropriate persons may be useful in developing strategies to reduce fracture in those at risk.
![]() |
ACKNOWLEDGMENTS |
---|
![]() |
NOTES |
---|
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|