Because Dr. Yelin is Editor of Arthritis Care & Research, review of this article was handled by the Editor of Arthritis & Rheumatism.
Systemic Lupus Erythematosus
Osteoporosis screening, prevention, and treatment in systemic lupus erythematosus: application of the systemic lupus erythematosus quality indicators
Article first published online: 23 FEB 2010
Copyright © 2010 by the American College of Rheumatology
Arthritis Care & Research
Volume 62, Issue 7, pages 993–1001, July 2010
How to Cite
Schmajuk, G., Yelin, E., Chakravarty, E., Nelson, L. M., Panopolis, P. and Yazdany, J. (2010), Osteoporosis screening, prevention, and treatment in systemic lupus erythematosus: application of the systemic lupus erythematosus quality indicators. Arthritis Care Res, 62: 993–1001. doi: 10.1002/acr.20150
- Issue published online: 29 JUN 2010
- Article first published online: 23 FEB 2010
- Manuscript Accepted: 9 FEB 2010
- Manuscript Received: 6 NOV 2009
- American College of Rheumatology/Research and Education Foundation Physician-Scientist Development Award
- National Center for Research Resources. Grant Number: 5-M01-RR-00079
- Rosalind Russell Medical Research Center for Arthritis, NIH. Grant Number: R01-AR-44804
- State of California Lupus Fund
- Arthritis Foundation
- Agency for Healthcare Research and Quality
- National Institute of Arthritis and Musculoskeletal and Skin Diseases. Grant Numbers: 1-R01-HS-013893, P60-AR-053308
Osteoporosis and fragility fractures are associated with significant morbidity for patients with systemic lupus erythematosus (SLE). New quality indicators (QIs) for SLE advise bone mineral density testing, calcium and vitamin D use, and antiresorptive or anabolic treatment for specific subgroups of patients receiving high-dose steroids.
Subjects were participants in the University of California, San Francisco Lupus Outcomes Study, an ongoing longitudinal study of patients with physician-confirmed SLE, in 2007–2008. Patients responded to an annual telephone survey and were queried regarding demographic, clinical, and other health care–related variables. Multiple logistic regression was used to predict receipt of care per the QIs described above.
One hundred twenty-seven patients met the criteria for the formal definitions of the denominators for QI I (screening) and QI II (calcium and vitamin D); 91 met the formal criteria for QI III (treatment). The proportions of patients receiving care consistent with the QIs were 74%, 58%, and 56% for QIs I, II, and III, respectively. In a sensitivity analysis of all steroid users (n = 427 for QI I and II and n = 224 for QI III), rates were slightly lower. Predictors of receiving care varied by QI and by denominator; however, female sex, older age, white race, and longer disease duration were associated with higher-quality care.
Bone health–related care in this community-based cohort of SLE patients is suboptimal. Quality improvement efforts should address osteoporosis prevention and care among all SLE patients, especially those receiving high-dose, prolonged steroids.
In the past 50 years, systemic lupus erythematosus (SLE)–related mortality has improved significantly. Lupus patients are living longer and experiencing increased morbidity from complications related to chronic inflammation and long-term medication use, including coronary artery disease, malignancies, and osteoporotic fractures (1–3).
Although estimates for the prevalence of osteopenia and osteoporosis in SLE have varied, some of the largest studies indicate that the burden of osteoporosis may be more than 20% (4, 5). Individuals with SLE are at particular risk for osteoporosis compared with age-matched controls because of high disease activity, vitamin D deficiency due to sun avoidance, early menopause from use of cytotoxic agents, and glucocorticoid use (6–8). The minimum dose of glucocorticoids that poses an increased risk of osteoporosis is debated because many studies have found glucocorticoid use in SLE to be associated with low bone mineral density (BMD) (9–15), whereas others have not confirmed this association after adjusting for disease damage and duration (16, 17). Some studies suggest that patients with SLE may have a baseline increased risk of low bone density that is independent of glucocorticoid use or disease duration (18, 19).
Developed through a process that combined systematic literature reviews with formal expert consensus processes, the first set of quality indicators (QIs) for SLE was published in 2009 (20). As opposed to clinical guidelines, which define optimal health care practices in the context of complex clinical decision making, QIs specify a minimally acceptable standard of care for a specific patient population (21). Three of the 20 published QIs addressed bone health–related care and set a glucocorticoid dosage of 7.5 mg of prednisone daily for at least 3 months as the threshold above which patients should be advised to take calcium and vitamin D and to obtain screening for osteoporosis with a BMD test. As expected, guidelines regarding osteoporosis care (not specific to SLE patients) set a higher bar for screening and prevention: the American College of Rheumatology (ACR; 2001) suggests that patients receiving more than 5 mg of prednisone daily for 3 months be screened for osteoporosis and given calcium and vitamin D prophylaxis (22). Guidelines from the National Osteoporosis Foundation (1999) go further by suggesting that patients receiving 5 mg of prednisone daily for an unspecified length of time or patients with any chronic condition associated with low bone mass should receive calcium and vitamin D and screening for osteoporosis (23).
The objective of this study was to evaluate the quality of osteoporosis screening, prevention, and treatment in a community-based cohort of patients with physician-confirmed SLE. We applied the measures developed in the SLE QI project to examine the proportion of patients who met criteria for each osteoporosis-related QI.
PATIENTS AND METHODS
The University of California, San Francisco (UCSF) Lupus Outcomes Study (LOS) is an ongoing longitudinal survey of patients with confirmed SLE recruited between 2002 and 2009. Patients were originally recruited from academic rheumatology offices (22%), community rheumatology offices (11%), and other community-based sources (66%), such as SLE support groups, the Internet, and media advertisements. Two-thirds of the participants were residents of California, whereas the remainder lived in 40 other US states. Patients were required to carry a diagnosis of SLE provided by a physician. SLE diagnoses for all of the LOS participants were additionally confirmed by a formal chart review to document ACR criteria for SLE (24).
Questions regarding osteoporosis care and prevention were introduced into the LOS in 2007–2008, during the sixth wave of interviews. Seven hundred seventy-nine individuals were interviewed as part of wave 6. Thirty-seven (4.8%) of these patients were excluded because of incomplete data for the outcomes or main predictors, leaving 742 patients eligible for this analysis.
Data were collected via an annual, structured, 1-hour–long telephone survey conducted by trained interviewers. The survey included validated items covering the following domains: demographics and socioeconomic status, SLE symptoms and disease status, disability, general health and social functioning, employment, psychological and cognitive status, health care utilization, medications, and health insurance coverage.
The UCSF and Stanford University Committees on Human Research approved the study protocol. All of the participants provided informed consent prior to the interviews.
Socioeconomic and demographic characteristics included age, sex, self-reported race/ethnicity (white, Hispanic, African American, Asian, other/multiple), education level (high school or less, some college or vocational school, college graduate), and income (annual household income at or below 125% of the federal poverty threshold in the year prior to the interview).
The insurance section of the questionnaire, derived from the Medical Expenditures Panel Survey, included items regarding the type of health plan (health maintenance organization versus fee-for-service) and source of coverage, if any (employment based, individually purchased plan, Medicare, or Medicaid) (25).
SLE-specific variables included disease duration and disease activity, captured using the Systemic Lupus Activity Questionnaire, a validated self-report measure of SLE activity (range 0–44) (26, 27). Patients were also queried regarding their physical functioning (using the Medical Outcomes Study Short Form 36) and menopause status (28). Presence of nontraumatic (fragility) fracture was determined by asking a series of questions (“Has a doctor told you that you broke or fractured a bone or had a spinal compression fracture?” If yes, “Which bone did you break?” If the reply included a spine or hip fracture, “Was it from a traumatic injury such as from playing a sport or a car accident?”). Self-reported diagnoses of osteoporosis were based on the following question: “Do you have or are you being treated for osteoporosis or thinning bones?”
Health care utilization.
The health care utilization section of the questionnaire asked participants about their medical care over the prior 12 months. It included an enumeration of all health care practitioner visits by specialty, including hospitalizations. The participants were asked directly about who serves as their “main SLE doctor” (rheumatologist, nephrologist, internist, general practice, other, or none).
Subjects were asked about the use of medications since the previous survey, including medications used for common comorbid conditions, glucocorticoids (oral and intravenous), and disease-modifying antirheumatic drugs. We created a measure of pill burden by summing the number of medications each patient reported taking (range 0–15); this sum excluded calcium or vitamin D use or medications taken for the treatment of osteoporosis.
The primary outcome of interest was receipt of care as described in each of the 3 osteoporosis QIs. This was determined by calculating the proportion of patients eligible for the measure (denominator) who met the criteria for care consistent with that measure (numerator). Numerators and denominators for each of the QIs are outlined in Table 1.
|QI I (screening)||QI II (calcium/vitamin D)||QI III (treatment)|
|Numerator||Patients who have received a bone mineral density test within 12 months prior to or 6 months following initiation of glucocorticoid therapy or who are receiving antiresorptive or anabolic therapy*||Patients who are taking calcium and vitamin D or have their recommendation documented in the medical record||Patients who are being treated with antiresorptive or anabolic therapy|
|Formal||Patients taking at least 7.5 mg of prednisone per day for at least 3 months||Patients taking at least 7.5 mg of prednisone per day for at least 3 months||Patients taking at least 7.5 mg of prednisone per day for at least 1 month, and either have a central T score of less than or equal to −2.5 or have a history of fragility fracture†|
|All steroid||Patients taking any dose of steroid for any period of time within the prior 12 months||Patients taking any dose of steroid for any period of time within the prior 12 months||Patients taking any dose of steroid for any period of time within the prior 12 months with either a central T score of less than or equal to −2.5 or have a history of fragility fracture†|
In order to define the stability of the QIs to changes in the denominator, we measured the receipt of the QIs in 2 non–mutually exclusive groups of patients. First, we assessed the QIs as they were written, using the formal denominators listed in Table 1 (formal denominator). Second, we examined patients taking glucocorticoids at any dose for any period of time (QI I [screening] and QI II [calcium and vitamin D]) or among patients taking glucocorticoids at any dose for any period of time who also had a history of osteoporosis or fragility fracture (QI III [treatment]; all steroid denominator).
Outcomes and eligibility (i.e., numerators and denominators) were determined based on questions posed during the survey, including direct questions about BMD testing, calcium, vitamin D, and antiresorptive and anabolic use. Qualifying antiresorptive/anabolic agents included alendronate, risedronate, ibandronate, etidronate, pamidronate, zoledronic acid, calcitonin nasal spray, raloxifene, and teriparatide.
Because questions about BMD testing were posed in all waves of the LOS, we were able to determine whether patients had received BMD testing at any time within the past 24 months. We chose a 24-month window because 1) the QIs do not provide a specific timeframe for BMD testing and 2) the majority of insurance companies, including Medicare, cover the cost of BMD testing for qualifying patients at least once every 24 months (29).
We calculated the percentage of patients who received the individual outcomes of BMD testing, calcium, vitamin D, and antiresorptive or anabolic agents. We determined the proportions of patients in each denominator (formal and all steroid) who received care consistent with each QI. We used bivariate analyses and multiple logistic regression to assess the association between baseline characteristics and the QI outcomes. Variables in the multivariate models were determined a priori based on prior studies of osteoporosis care, and included age, ethnicity, income, education, health insurance, disease duration, disease activity, daily pill burden, and the specialty of the main SLE physician (30, 31). All of the covariates were tested to ensure noncolinearity. In the models for the formal denominator, some of the covariate categories were collapsed because of the small number of events. SAS, version 9.2 (SAS Institute), was used for all of the analyses.
We analyzed data from 742 subjects from wave 6 of the LOS. Of these, 127 met the eligibility criteria for the formal denominator for QIs I (screening) and II (calcium and vitamin D), and 91 met the eligibility criteria for the formal denominator for QI III (treatment). Four hundred twenty-seven subjects met the criteria for the all steroid denominator for QIs I (screening) and II (calcium and vitamin D), and 224 met the criteria for the all steroid denominator for QI III (treatment). Baseline characteristics of the individuals meeting the eligibility criteria for each denominator are listed in Table 2.
|All patients (n = 742)||Formal, QI I/II (n = 127)†||Formal, QI III (n = 91)‡||All steroid, QI I/II (n = 427)§||All steroid, QI III (n = 224)¶|
|Women||682 (91.9)||119 (93.7)||88 (96.7)||393 (92.0)||210 (93.8)|
|Age, mean ± SD years||50.6 ± 12.6||46.0 ± 11.5||50.2 ± 11.4||49.6 ± 12.6||52.2 ± 11.8|
|White||449 (60.5)||63 (49.6)||54 (59.3)||235 (55.0)||138 (61.6)|
|Hispanic||72 (9.7)||16 (12.6)||9 (9.9)||43 (10.1)||15 (6.7)|
|African American||66 (8.9)||17 (13.4)||9 (9.9)||50 (11.7)||21 (9.4)|
|Asian||75 (10.1)||16 (12.6)||7 (7.7)||48 (11.2)||21 (9.4)|
|Other/multiple||80 (10.8)||15 (11.8)||12 (13.2)||51 (11.9)||29 (12.9)|
|High school or less||113 (15.2)||19 (15.0)||14 (15.4)||60 (14.0)||35 (15.6)|
|Vocational/trade/some college||325 (43.8)||69 (54.3)||49 (53.8)||197 (46.1)||103 (46.0)|
|College or beyond||304 (41.0)||39 (30.7)||28 (30.8)||170 (39.8)||86 (38.4)|
|Below poverty||86 (11.6)||22 (17.3)||12 (13.2)||65 (15.2)||37 (16.5)|
|Employer based||409 (55.1)||66 (52.0)||45 (49.4)||227 (53.2)||109 (48.7)|
|Medicare||207 (27.9)||38 (29.9)||34 (37.4)||129 (30.2)||84 (37.5)|
|Medicaid||42 (5.7)||8 (6.3)||4 (4.4)||27 (6.3)||11 (4.9)|
|Other insurance||71 (9.6)||12 (9.4)||7 (7.7)||37 (8.7)||18 (8.0)|
|No insurance||13 (1.8)||3 (2.4)||1 (1.1)||7 (1.6)||2 (0.9)|
|Disease duration, mean ± SD years||16.8 ± 8.6||15.6 ± 8.1||18.1 ± 7.6||17.2 ± 8.4||18.7 ± 8.0|
|SLAQ score, mean ± SD||11.7 ± 7.8||13.6 ± 7.7||14.5 ± 8.0||13.0 ± 8.1||13.9 ± 8.3|
|History of osteoporosis or fracture||327 (44.1)||78 (61.4)||91 (100.0)||224 (52.5)||224 (100.0)|
|Postmenopausal||373 (50.3)||60 (47.2)||56 (61.5)||215 (50.7)||137 (61.2)|
|SF-36 physical function score, mean ± SD||59.2 ± 29.8||49.5 ± 28.2||46.2 ± 27.6||54.3 ± 29.5||50.2 ± 28.3|
|Main SLE physician|
|Rheumatologist||554 (74.7)||111 (87.4)||80 (87.9)||338 (79.2)||176 (78.6)|
|Nephrologist||35 (4.7)||10 (7.9)||6 (6.6)||27 (6.3)||12 (5.3)|
|Internist||62 (8.4)||5 (3.9)||3 (3.3)||26 (6.1)||17 (7.6)|
|General practice||45 (6.1)||0 (0)||0 (0)||14 (3.3)||8 (3.6)|
|Other||13 (1.8)||1 (0.8)||1 (1.1)||6 (1.4)||3 (1.3)|
|None||33 (4.4)||0 (0)||1 (1.1)||16 (3.8)||8 (3.6)|
|Health care use within the past 12 months|
|No. of daily medications, mean ± SD#||3.3 ± 1.9||4.3 ± 1.6||4.6 ± 1.7||4.2 ± 1.7||4.3 ± 1.8|
|Disease-modifying agent use||512 (69.0)||111 (87.4)||78 (85.7)||344 (80.6)||181 (80.8)|
|No. of rheumatologist visits, mean ± SD||3.2 ± 3.4||5.3 ± 4.6||5.0 ± 3.5||4.1 ± 3.9||3.8 ± 3.3|
|Hospitalized at least once||142 (19.2)||39 (31.0)||31 (34.1)||106 (24.9)||61 (27.2)|
|Individual outcomes used in quality indicator numerators|
|BMD testing within 24 months||378 (50.9)||77 (60.6)||63 (69.2)||251 (58.8)||161 (71.9)|
|Calcium use within 12 months||464 (62.5)||92 (72.4)||70 (76.9)||293 (68.6)||170 (75.9)|
|Vitamin D use within 12 months||410 (55.3)||79 (62.2)||62 (68.1)||263 (61.6)||153 (68.3)|
|Antiresorptive or anabolic use within 12 months||202 (27.2)||52 (40.9)||51 (56.0)||152 (35.6)||122 (54.5)|
Figure 1 shows the proportion of eligible patients receiving care consistent with each of the QIs for the 2 denominators of interest (formal and all steroid) (Table 1). The proportion of patients receiving the care described in the QIs ranged from 54% to 74% and was slightly higher in the formal group compared with the all steroid group. Of note, when we assessed QI III (treatment) among men and postmenopausal women only, the proportions of patients receiving care per the QI were essentially unchanged, at 57% for the formal denominator (n = 56) and 54% in the all steroid denominator (n = 137).
In the bivariate analyses (unadjusted) of the formal denominator patients, receipt of QI I (screening) was predicted by age, white race, and disease duration (Table 3). The multivariate (adjusted) model showed only older age as predicting QI I (screening) receipt (per 10 years odds ratio [OR] 1.9, 95% confidence interval [95% CI] 1.2–3.1). Multivariate analysis for QI II (calcium and vitamin D) in the formal denominator showed a significant predictor of white race (OR 4.3, 95% CI 1.9–9.6). The multivariate model for QI III (treatment) did not reveal any significant predictors.
|QI I (screening)†||QI II (calcium and vitamin D)†||QI III (treatment)‡|
|Univariate OR (95% CI)||Adjusted OR (95% CI)§||Univariate OR (95% CI)||Adjusted OR (95% CI)§||Univariate OR (95% CI)||Adjusted OR (95% CI)§|
|Women (referent: men)||0.9 (0.2–4.9)||1.0 (0.1–7.6)||0.8 (0.2–3.6)||1.0 (0.2–6.7)||0.6 (0.1–7.2)||0.9 (0.1–11.7)|
|Age, per 10 years||2.1 (1.4–3.1)¶||1.9 (1.2–3.1)¶||1.4 (1.0–1.9)||1.5 (1.0–2.3)||1.1 (0.8–1.6)||1.0 (0.6–1.6)|
|White (referent: nonwhite)||3.0 (1.3–6.9)¶||1.8 (0.7–4.7)||4.7 (2.2–10.0)¶||4.3 (1.9–9.6)¶||1.4 (0.6–3.2)||1.3 (0.5–3.2)|
|High school or less||Referent||Referent||Referent||Referent||Referent||Referent|
|Some college or beyond||1.8 (0.7–5.2)||1.5 (0.4–6.0)||1.3 (0.5–3.5)||1.3 (0.4–4.5)||0.9 (0.3–3.0)||0.8 (0.2–2.9)|
|Income below the poverty line (referent: above the poverty line)||0.3 (0.1–0.9)||0.3 (0.1–1.3)||0.5 (0.2–1.3)||0.6 (0.2–2.1)||0.7 (0.2–2.5)||0.7 (0.2–3.1)|
|Other insurance/none||0.7 (0.3–1.6)||0.6 (0.2–1.8)||0.9 (0.5–1.9)||0.6 (0.2–2.1)||1.0 (0.4–2.4)||1.0 (0.4–2.9)|
|Disease duration, per 10 years||2.4 (1.3–4.4)¶||1.7 (0.8–3.5)||0.9 (0.6–1.4)||0.6 (0.3–1.1)||1.2 (0.7–2.1)||1.3 (0.7–2.4)|
|SLAQ score||1.0 (1.0–1.1)||1.0 (0.9–1.1)||1.0 (1.0–1.0)||1.0 (0.9–1.0)||1.0 (0.9–1.0)||1.0 (0.9–1.1)|
|No. of daily medications||1.1 (0.9–1.4)||1.0 (0.7–1.4)||1.1 (0.9–1.4)||1.1 (0.8–1.4)||1.1 (0.9–1.4)||1.1 (0.9–1.4)|
|Rheumatologist as SLE physician (referent: nonrheumatologist)||1.3 (0.4–4.2)||1.4 (0.4–5.2)||1.5 (0.5–4.2)||1.1 (0.3–3.7)||2.5 (0.7–9.2)||2.6 (0.6–10.3)|
The sensitivity analysis using the all steroid denominator revealed slightly different predictors of receiving care as per the QIs. Multivariate (adjusted) analysis showed female sex (OR 2.8, 95% CI 1.3–5.9), older age (per 10 years OR 1.3, 95% CI 1.1–1.6), longer disease duration (per 10 years OR 1.5, 95% CI 1.1–2.1), and rheumatologist subspecialty care (OR 1.8, 95% CI 1.1–3.1) to be significant predictors for the receipt of QI I (screening) (Table 4). Female sex predicted the receipt of QI II (calcium and vitamin D; OR 2.6, 95% CI 1.2–5.5). Having a rheumatologist as the main SLE physician predicted receipt of QI III (treatment; OR 2.3, 95% CI 1.3–4.6).
|QI I (screening)†||QI II (calcium and vitamin D)†||QI III (treatment)‡|
|Univariate OR (95% CI)||Adjusted OR (95% CI)§||Univariate OR (95% CI)||Adjusted OR (95% CI)§||Univariate OR (95% CI)||Adjusted OR (95% CI)§|
|Women (referent: men)||2.7 (1.3–5.4)¶||2.8 (1.3–5.9)¶||2.2 (1.1–4.6)¶||2.6 (1.2–5.5)¶||1.6 (0.5–4.9)||1.9 (0.6–5.9)|
|Age, per 10 years||1.4 (1.2–1.6)¶||1.3 (1.1–1.6)¶||1.2 (1.0–1.4)||1.2 (1.0–1.4)||1.0 (0.8–1.2)||1.0 (0.8–1.3)|
|White (referent: nonwhite)||1.3 (0.9–2.0)||1.1 (0.7–1.7)||1.7 (1.1–2.5)¶||1.5 (1.0–2.3)||1.2 (0.7–2.0)||1.2 (0.7–2.2)|
|High school or less||Referent||Referent||Referent||Referent||Referent||Referent|
|Vocational/trade/some college||1.3 (0.7–2.5)||1.3 (0.7–2.6)||1.0 (0.6–1.8)||1.0 (0.5–1.8)||0.7 (0.3–1.6)||0.8 (0.4–1.8)|
|College or beyond||0.9 (0.5–1.7)||0.9 (0.5–1.9)||1.6 (0.9–2.9)||1.5 (0.8–3.0)||1.1 (0.5–2.4)||1.2 (0.5–2.8)|
|Income below the poverty line (referent: above the poverty line)||1.0 (0.5–1.7)||1.3 (0.6–2.7)||0.7 (0.4–1.1)||0.8 (0.4–1.5)||0.9 (0.4–1.7)||1.1 (0.4–2.6)|
|Medicare||1.1 (0.7–1.7)||0.7 (0.4–1.3)||1.0 (0.6–1.5)||0.9 (0.6–1.5)||1.1 (0.6–2.0)||1.2 (0.6–2.4)|
|Medicaid||0.7 (0.3–1.5)||0.6 (0.2–1.6)||0.9 (0.4–2.0)||1.6 (0.6–4.0)||1.6 (0.4–5.8)||2.3 (0.5–10.4)|
|Other insurance/none||1.0 (0.5–2.0)||1.0 (0.5–2.0)||0.7 (0.4–1.4)||0.7 (0.4–1.4)||1.4 (0.5–3.6)||1.4 (0.5–3.9)|
|Disease duration, per 10 years||1.7 (1.3–2.2)¶||1.5 (1.1–2.1)¶||1.2 (1.0–1.5)||1.1 (0.8–1.4)||1.1 (0.8–1.5)||1.1 (0.7–1.5)|
|SLAQ score||1.0 (1.0–1.0)||1.0 (1.0–1.0)||1.0 (1.0–1.0)||1.0 (1.0–1.0)||1.0 (1.0–1.0)||1.0 (0.9–1.0)|
|No. of daily medications||1.1 (1.0–1.3)||1.1 (1.0–1.2)||1.1 (1.0–1.2)||1.1 (1.0–1.2)||1.2 (1.0–1.4)||1.2 (1.0–1.4)|
|Rheumatologist as SLE physician (referent: nonrheumatologist)||1.6 (1.0–2.5)||1.8 (1.1–3.1)¶||1.5 (0.9–2.4)||1.6 (1.0–2.6)||2.2 (1.1–4.1)¶||2.3 (1.3–4.6)¶|
This study examined the screening, prophylaxis, and treatment of osteoporosis in a large, community-based cohort of patients with physician-confirmed SLE. Regardless of whether we used lenient or strict definitions to delineate the patient populations eligible for relevant processes of care, the proportion of patients receiving these interventions was similar. Screening for osteoporosis with a BMD test occurred more frequently (69–74%) than calcium and vitamin D use (56–58%) or antiresorptive or anabolic use (54–56%), even when the QI III (treatment) analysis was restricted to men and postmenopausal women (54–57%). We conclude that osteoporosis screening, prophylaxis, and treatment for SLE patients is suboptimal.
Our results show slightly higher proportions of patients receiving bone health–related care compared with prior estimates. Lee et al surveyed US women with SLE seen in an academic rheumatology practice. In that study of 204 women, 50% reported calcium use and approximately 45% reported vitamin D use; 62% were postmenopausal and 50% were currently receiving glucocorticoids (32). In our sample with a comparable fraction of postmenopausal women and patients receiving glucocorticoids, 62% of patients reported calcium use and 55% reported vitamin D use. Almehed et al studied 163 women with SLE in Sweden, again with similar fractions of postmenopausal patients and steroid users: 53% of these patients reported taking calcium and vitamin D (4). Only 35% of patients with documented osteoporosis were taking bisphosphonates. In our sample, 47% of patients with documented osteoporosis were taking antiresorptive or anabolic agents. Pineau et al examined a clinical database to show that 40% of female SLE patients from the University of Toronto Lupus Clinic received a BMD test over a 5-year period (33). Our sample showed that 51% of patients reported receiving a BMD test within 2 years. Self-reported use of dual x-ray absorptiometry (DXA) scans has been shown to have a very high positive predictive value when compared with medical chart review (34). One possible explanation for these discrepancies is that over time, awareness of osteoporosis has increased, and patients and their physicians are taking more care to perform screening, prevention, and treatment. Alternately, these differences may be a result of dissimilarities in health care system factors or the demographics of the populations studied.
We found that the major predictors of receipt of care varied by QI and by denominator. Important factors predicting higher-quality care included female sex, older age, white race, and longer disease duration, although these were not predictive for the receipt of all of the QIs. Notably, in the model that examined the formal denominator, the only predictive factors were older age (QI I [screening] only) and white race (QI II [calcium and vitamin D] only).
Our findings regarding predictors of care are not surprising: postmenopausal women without SLE have an indication for BMD testing and osteoporosis prophylaxis (35). In addition, our results are consistent with previous studies: Pineau et al reported that SLE patients who were referred for BMD testing had a greater number of traditional risk factors for osteoporosis, higher SLE activity, renal involvement, increased damage, higher mean glucocorticoid dose, increased use of immunosuppressants, and presence of avascular necrosis (33). In studies of osteoporosis care in patients with rheumatoid arthritis (RA), predictors have been similar. Aizer et al assessed predictors of BMD testing among 2,717 patients with RA entering the Consortium of Rheumatology Researchers of North America database without a prior DXA scan: older age, female sex, history of fracture, and history of steroid use predicted BMD testing within 12 months of entering the study (36). Solomon et al evaluated osteoporosis care in 236 RA patients taking oral glucocorticoids: rates of BMD testing were low (23%), as were calcium and vitamin D use (42%) (31). Predictors of care included female sex, postmenopause status, and having no additional comorbidities. Although these studies did not find an association of racial/ethnic groups with quality care, studies of QIs for cardiovascular disease, stroke and transient ischemic attack, and diabetes mellitus have found such racial disparities (37, 38). The fact that we found few predictors of care may indicate that we were limited in our power to detect differences; however, it is important to note that receipt of the QIs was low overall.
Our results must be interpreted with several caveats. First, data for the LOS, including data used for definitions of the numerators and denominators for the QIs, were collected by self-report. There is support in the literature for the validity of self-report for fragility fractures and osteoporosis diagnoses, as well as for BMD testing and medication use, including calcium and vitamin D. The sensitivity and specificity of self-report for documented hip fracture has been found to be very high (39, 40). Agreement between self-report and medical record for the diagnosis of osteoporosis appears to be lower, but “false-positive” self-reported diagnoses of osteoporosis are rare (41). Self-reported use of DXA scans has a 93% positive predictive value for DXA documented in the medical record (32). The concordance of self-report for medication use (including calcium and vitamin D use) with medical record or administrative claims data is variable (42–44). However, several studies have shown substantial agreement between patient interview and medical records as sources of information regarding medication use and suggest that the impact of possible misclassification on models that predict medication use is minimal (45, 46). Overall, these studies show that the validity self-report for bone health–related care is reasonable, and therefore our results are likely reliable.
Second, few (n = 127) patients met the criteria for the formal QI denominators. We may have been underpowered to detect differences in rates of QI receipt among different subgroups of patients in this group. Third, QIs are process measures designed to be assessed on physicians or health care systems and are intended to account for patient refusal of a measure or contraindications to a drug. We do not have information on reasons for drug nonuse or contraindications (other than premenopause status) available in this study, so it is possible that some patients were intolerant or otherwise ineligible to take calcium, vitamin D, or antiresorptive/anabolic agents. In this case, we may be underestimating the proportion of patients receiving care consistent with the QIs.
Based on the low receipt of the 3 bone health–related SLE QIs, we have established that a gap exists between actual and minimally acceptable care. Quality improvement efforts should address osteoporosis prevention and treatment among all SLE patients, especially in those taking high-dose, prolonged steroids. Educational initiatives highlighting the SLE QIs to SLE patients and their providers will likely improve the rates of quality bone health–related care in these populations.
All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Schmajuk had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study conception and design. Schmajuk, Yelin, Nelson, Panopolis, Yazdany.
Acquisition of data. Schmajuk, Yelin, Yazdany.
Analysis and interpretation of data. Schmajuk, Yelin, Chakravarty, Nelson, Yazdany.
- 2European Working Party on Systemic Lupus Erythematosus. Morbidity and mortality in systemic lupus erythematosus during a 10-year period: a comparison of early and late manifestations in a cohort of 1,000 patients. Medicine (Baltimore) 2003; 82: 299–308., , , , , , et al, and the
- 22American College of Rheumatology. Recommendations for the prevention and treatment of glucocorticoid-induced osteoporosis: 2001 update. 2001. URL: http://www.rheumatology.org/practice/clinical/guidelines/osteo/osteoupdate.asp.
- 23National Osteoporosis Foundation. Clinician's guide to prevention and treatment of osteoporosis. 2008. URL: http://www.nof.org/professionals/pdfs/NOF_Clinicians_Guide%202008.pdf.
- 29National Osteoporosis Foundation. Frequently asked questions regarding bone density testing for Medicare beneficiaries. URL: http://www.nof.org/professionals/reimbursement/reimbursement_faqs.htm.
- 45Agreement between patient report and medical record review for medications used for rheumatoid arthritis: the accuracy of self-reported medication information in patient registries. Arthritis Rheum 2007; 57: 234–9., , , , , .