The effects of physician specialty and patient comorbidities on the use and discontinuation of coxibs.код для вставкиСкачать
Arthritis & Rheumatism (Arthritis Care & Research) Vol. 49, No. 3, June 15, 2003, pp 293–299 DOI 10.1002/art.11117 © 2003, American College of Rheumatology ORIGINAL ARTICLE The Effects of Physician Specialty and Patient Comorbidities on the Use and Discontinuation of Coxibs FAUSTO G. PATINO,1 JEROAN ALLISON,2 JASON OLIVIERI,1 AMY MUDANO,1 LUCIA JUAREZ,3 SHARINA PERSON,2 TED R. MIKULS,4 LARRY MORELAND,1 STACEY H. KOVAC,3 AND KENNETH G. SAAG2 Objective. To examine the effects of physician specialty and comorbidities on cyclooxygenase 2–selective nonsteroidal antiinflammatory drugs (NSAIDs; coxibs) utilization. Methods. Medical records of 452 patients from a regional managed care organization with >3 consecutive NSAID prescriptions from June 1998 to April 2001 were abstracted. Multivariable adjusted associations between coxib initiation and discontinuation and patient and provider characteristics were examined. Results. A total of 1,142 NSAID prescriptions were written over 9,398 total patient-months of followup. Compared with patients seeing family or general practitioners, patients seeing rheumatologists (odds ratio [OR] 3.4, 95% confidence interval [95% CI] 2.1–5.7) and internists (OR 2.3, 95% CI 1.5–3.6) were significantly more likely to receive a coxib, as well as patients with a history of osteoarthritis (OR 2.6, 95% CI 1.7–3.8), gastrointestinal disease (OR 2.3, 95% CI 1.2– 4.5), and congestive heart failure (OR 4.1, 95% CI 1.0 –16.4). Although specialists were more likely than generalists to prescribe coxibs, only family or general practitioners were significantly more likely to selectively use coxibs among their patients with a history of gastrointestinal disease. Fifty-four percent of NSAID prescriptions were discontinued, and coxibs were significantly less likely to be discontinued than were traditional NSAIDs (OR 0.6, 95% CI 0.5– 0.8). Conclusion. Our findings suggest significantly greater, but perhaps less selective use of coxibs among specialists, even after accounting for important covariates. The initiation and discontinuation of coxibs was influenced by physician specialty and by patient risk factors. KEY WORDS. Nonsteroidal antiinflammatory drugs; Coxibs; Practice pattern variation. Nonsteroidal antiinflammatory drugs (NSAIDs) are among the most frequently prescribed medication class worldwide (1– 8). Despite their popularity, patient safety remains a significant concern of chronic NSAID use (3,9 – 19). It is unknown, however, whether factors leading to significant variation in safe physician practices observed for other musculoskeletal therapies (5,20 –22) may also influence use of the newer, potentially safer cyclooxygenase 2 (COX-2)–selective NSAIDs (or coxibs). To identify associations with coxib use, we linked administrative, pharmacy, and medical record review data for a sample of chronic NSAID users who were enrollees in a regional managed health care organization. We hypothesized that risk factors for NSAID toxicity such as older age Supported in part by grants from the NIH (P60-AR-2061423) and the Agency for Healthcare Research and Quality (U18-HS-10389). 1 Fausto G. Patino, MD, DrPH, Jason Olivieri, MPH, Amy Mudano, MPH, Larry Moreland, MD: Center for Education and Research on Therapeutics of Musculoskeletal Disorders, University of Alabama at Birmingham; 2Jeroan Allison, MD, MSc, Sharina Person, PhD, Kenneth G. Saag, MD, MSc: Center for Education and Research on Therapeutics of Musculoskeletal Disorders, Center for Outcomes and Effectiveness Research and Education, University of Alabama at Birmingham; 3Lucia Juarez, MA, Stacey H. Kovac, PhD: Center for Outcomes and Effectiveness Research and Education, University of Alabama at Birmingham; 4Ted R. Mikuls, MD, MSPH: University of Nebraska, Omaha. Dr. Saag has served as a paid consultant and has received honoraria from Merck & Co. Address correspondence to Kenneth G. Saag, MD, MSc, Associate Professor and Director, Center for Education and Research on Therapeutics of Musculoskeletal Disorders, University of Alabama at Birmingham, Birmingham, AL 35294-3408. E-mail: firstname.lastname@example.org. Submitted for publication March 30, 2002; accepted in revised form August 14, 2002 INTRODUCTION 293 294 and comorbidity would be positively associated with increased coxib prescriptions, and that rheumatologists would be more likely than family or general practitioners to prescribe coxibs. In addition, we explored the reasons for discontinuation of NSAIDs. METHODS Data sources and data collection. After approval by the University of Alabama at Birmingham Institutional Review Board, we identified NSAID users from a sample of participants from a large, regional managed health care organization. National Drug Codes were used to identify all NSAID prescriptions from pharmacy claims. Study patients were restricted to chronic NSAID users, defined as persons receiving at least 3 consecutive nonaspirin NSAID prescriptions over any time interval from June 1998 to December 1999. To assess provider factors associated with practice pattern variation, NSAID users were stratified based on the specialty of their prescribing physician. We focused on providers who were more likely to care for chronic NSAID users (family or general practitioners, internists, and rheumatologists) and deliberately oversampled rheumatologists to address our hypotheses about the role of provider factors. From a total of 2,334 eligible patients using NSAIDs, 680 patients (29%) and their corresponding 136 providers (5 patients per provider) were randomly selected. Pharmacy claims data were initially used to identify subjects. Sociodemographic factors, type of insurance coverage, as well as physician specialty and number of covered patients using NSAIDs, were collected from administrative claims and provider databases. Patients were categorized into 2 groups according to the presence or absence of a drug benefit associated with their insurance plan. All subsequent analyses were based on data derived from medical record review. Medical record abstraction process. Medical record review included all chart documentation between June 1998 and April 2001. Trained nurse abstractors used a customized version of the MedQuest software (developed by Fu et al under contract from the Health Care Financing Administration) for chart abstraction. Medical record abstractors achieved 97% interrater reliability. Medical history, physical examination signs, and comorbidities (when recorded in the chart), with special attention to those that might predispose to NSAID use and discontinuation, were collected. Particular attention was devoted to NSAID use and medications that might adversely interact with NSAIDs or were markers for NSAID renal toxicity (diuretics, angiotensin-converting enzyme inhibitors) or were indicative of a predilection to NSAID gastrointestinal (GI) toxicity (corticosteroids, cytoprotective drugs, H2 blockers, and proton pump antagonists). NSAID use during the study period was defined as traditional (nonselective) NSAIDs only, or coxibs ever (including users of coxibs only and users of both types of medications). Intervals of use represented each uninterrupted Patino et al use of any NSAID during the followup period. One NSAID could have more than one interval if the patient used the drug intermittently. Cumulative use of NSAIDs represented the sum of NSAID interval periods, subtracting the overlap periods (when a patient was taking more than one NSAID). Information on NSAID use was restricted to prescription medication. Over-the-counter medications, such as nonprescription NSAIDs and acetaminophen, were not considered in this study. Statistical analysis. Chi-square and one-way analysis of variance or Student’s t-tests were used to describe categorical and continuous demographic, clinical, and NSAID utilization variables, respectively. To determine predictors of NSAID use and discontinuation, we performed multivariable logistic regression analysis using the model-building techniques described by Hosmer and Lemeshow (23). Generalized estimating equations (24) were used to adjust for artificial inflation of statistical significance resulting from patients being nested within physicians. Due to their clinical relevance, all multivariable analyses were adjusted for age and sex. For other variables, a bivariate P value ⱕ0.25 was required to enter the models. Data management, reduction, and analyses were conducted in Microsoft Access (Microsoft Corporation, Redmond, WA), SAS (SAS Institute, Cary, NC) and SPSS (SPSS, Chicago, IL). RESULTS We received a total of 452 records (66% record response rate) from 103 physicians (43 internists, 44 general and family practitioners, 16 rheumatologists) (76% physician response rate). There were no significant differences in sex and age between patients whose records were reviewed and those whose records were not provided. A total of 1,142 NSAID prescriptions were written over 9,398 total patient-months of followup. Coxibs accounted for 435 (38%) of all NSAID prescriptions. Characteristics of the 452 NSAID users, stratified by type of NSAID used, are shown in Table 1. Compared with traditional NSAID users, coxib users were older, more likely to have history of GI disease and osteoarthritis (OA), and trended toward a higher prevalence of comorbidities and connective tissue diseases. Use of other prescription analgesics showed no association with use of coxibs. Patients using coxibs had a significantly longer cumulative drug use as well as a longer followup during the study period. Coxib ever users had more intervals of use than did traditional NSAID only users (2.9 versus 1.9; P ⬍ 0.001) (data not shown). There was no significant difference in the use of coxibs based on the type of drug benefit coverage; if anything, those with limited or no drug benefit trended toward more frequent coxib use. Patients seen by internists were older than patients seen by family or general practitioners and rheumatologists (see Table 2). Those seen by rheumatologists were less likely to have a history of diabetes or hypertension or to use antihypertensive medications. Patients seen by an internist or rheumatologist were Use and Discontinuation of Coxibs 295 Table 1. Characteristics of patients receiving traditional nonsteroidal antiinflammatory drugs versus coxibs* Characteristic Age, mean ⫾ SD, years Number of concomitant drugs, mean ⫾ SD Cumulative duration of NSAID use, mean ⫾ SD months Number of observation months, mean ⫾ SD Number of physician visits per 12 observation months, mean ⫾ SD Sex, women Conditions associated with NSAID toxicity Congestive heart failure Diabetes Gastrointestinal disease Hypertension Renal diseases Arthritis type Osteoarthritis Rheumatoid arthritis Lupus or connective tissue disease type unknown Possible concomitant medications associated with NSAID toxicity Angiotensin-converting enzyme inhibitors Diuretics Other antihypertensives Corticosteroids Warfarin Other analgesics Any of the above concomitant medications Traditional NSAIDs only users (n ⴝ 157) Coxib ever users (n ⴝ 295) 59.8 ⫾ 11.4 12.3 ⫾ 7.0 10.4 ⫾ 9.4 19.6 ⫾ 8.9 6.4 ⫾ 7.2 94 (59.9) 62.8 ⫾ 11.4† 14.5 ⫾ 8.9† 12.7 ⫾ 8.5† 21.4 ⫾ 7.4† 5.9 ⫾ 3.5 194 (65.8) 2 (1.3) 28 (17.8) 12 (7.6) 89 (56.7) 4 (2.5) 11 (3.7) 50 (16.9) 46 (15.6)‡ 145 (49.2) 11 (3.7) 86 (54.8) 14 (8.9) 41 (26.1) 216 (73.2)§ 30 (10.2) 99 (33.6) 40 (25.5) 41 (26.1) 69 (43.9) 37 (23.6) 3 (1.9) 64 (40.8) 124 (79.0) 78 (26.4) 98 (33.2) 113 (38.3) 58 (19.7) 6 (2.0) 125 (42.4) 236 (80.0) * Except where indicated otherwise, values are the number (%). Coxib ever users were patients who received at least one prescription for rofecoxib or celecoxib. Gastrointestinal disease includes peptic ulcer, gastritis, or gastrointestinal bleeding. NSAID ⫽ nonsteroidal antiinflammatory drug. † P ⬍ 0.01. ‡ P ⬍ 0.05. § P ⬍ 0.001. more likely to initiate coxibs referent to those seen by a family or general practitioner (P ⬍ 0.001). This pattern persisted among patients with a history of GI disease (Figure 1A) or hypertension (Figure 1B). Among patients with either a history of GI disease or potential NSAID gastrointestinal risk factors (age ⱖ65 years, concomitant use of oral corticosteroids), those seen by an internist or rheumatologist were significantly more likely to receive coxibs than Table 2. Characteristics of patients receiving traditional nonsteroidal antiinflammatory drugs and coxibs by prescribing physician specialty* Physician specialty Characteristic Age, mean ⫾ SD, years Comorbid conditions Diabetes Gastrointestinal disease Hypertension Congestive heart failure Any of above comorbid conditions Possible concomitant medications Angiotensin-converting enzyme inhibitors Corticosteroids Diuretics Other antihypertensives Any of above concomitant medications Family or general practitioner (n ⴝ 184 patients) Internist (n ⴝ 194 patients) Rheumatologist (n ⴝ 74 patients) 57.8 ⫾ 12.5 69.9 ⫾ 9.4 60.8 ⫾ 10.0† 33 (17.9) 24 (13.0) 101 (54.9) 5 (2.7) 11 (60.3) 43 (22.2) 25 (12.9) 122 (62.9) 8 (4.1) 137 (70.6) 2 (2.7)‡ 9 (12.2) 11 (14.9)† 0 (0.0) 20 (27.0)† 51 (27.7) 20 (10.9) 57 (31.0) 68 (37.0) 110 (59.8) 56 (28.9) 52 (26.8) 67 (34.5) 93 (47.9) 145 (74.7) 11 (14.9) 23 (31.1)† 15 (20.3) 21 (28.4)‡ 44 (59.5)‡ * Except where indicated otherwise, values are the number (%). Gastrointestinal disease includes peptic ulcer, gastritis, or gastrointestinal bleeding. † P ⬍ 0.001, by one-way analysis of variance or chi-square trend test. ‡ P ⬍ 0.01, by one-way analysis of variance or chi-square trend test. 296 Patino et al Figure 2. Proportion of patients discontinuing nonsteroidal antiinflammatory drugs (NSAIDs), stratified by prescribing physician specialty. * ⫽ P ⫽ 0.05, comparisons between all physician specialties. coxib use within each physician specialty, family and general practitioners but not internists or rheumatologists were more likely to selectively prescribe coxibs rather than traditional NSAIDs to their patients with a history of GI disease (odds ratio [OR] 2.6, 95% confidence interval [95% CI] 1.0 – 6.5) (Figure 1A). Only rheumatologists, however, trended toward a preference for coxib selection over traditional NSAIDs for their patients with hypertension (Figure 1B). In Table 3, after multivariable adjustment for potential confounders, a history of OA, GI disease, or congestive heart failure remained significantly and positively associated with initiation of coxibs. Even after adjustment for these potential confounders, being seen by an internist or rheumatologist was still a significant predictor of coxib use. Figure 2 shows discontinuation of NSAIDs according to prescribing physician specialty. Patients seen by family or general practitioner were less likely to discontinue at least one NSAID drug compared with patients seen by internists Figure 1. Proportion of patients with gastrointestinal (GI) disease (A) or hypertension (B) receiving coxibs, stratified by prescribing physician specialty. GI disease includes peptic ulcer, gastritis, or GI bleeding. † ⫽ P ⫽ 0.04, comparison within family or general practitioners only. ‡ ⫽ P ⫽ 0.001, comparisons between all physician specialties. were those seen by a generalist (P ⫽ 0.03 and P ⫽ 0.003, respectively) (data not shown). When comparing the use of nonselective NSAID versus Table 3. Patient and provider characteristics associated with ever use of a coxib Variable Age, years 18–49 50–64 65⫹ Sex (referent to men) Osteoarthritis Rheumatoid arthritis, systemic lupus erythematosus, or other connective tissue disease Comorbid conditions Gastrointestinal disease† Hypertension Congestive heart failure Cancer Provider type General or family practitioner Internist Rheumatologist Insurance drug coverage Unadjusted odds ratio 95% confidence interval Adjusted odds ratio* 95% confidence interval 1.0 1.6 2.1 1.3 2.3 1.5 Referent 0.9–2.9 1.1–3.9 0.9–1.9 1.5–3.4 1.0–2.2 1.0 1.1 1.0 1.3 2.6 1.5 Referent 0.6–2.1 0.5–2.3 0.9–1.9 1.7–3.8 1.0–2.4 2.2 0.7 3.0 2.5 1.1–4.4 0.5–1.1 0.7–13.7 0.9–6.6 2.3 0.7 4.1 2.7 1.2–4.5 0.4–1.1 1.0–16.4 0.9–8.2 1.0 2.4 4.0 1.2 Referent 1.6–3.7 2.1–7.7 1.0–1.4 1.0 2.3 3.4 1.0 Referent 1.5–3.6 2.1–5.7 0.5–2.0 * Includes age, sex, and variables with univariate P ⬍ 0.25 (osteoarthritis, comorbidities, provider type, insurance drug coverage). † Gastrointestinal disease includes peptic ulcer, gastritis, or gastrointestinal bleeding. c statistic ⫽ 0.72 (47); Hosmer and Lemeshow goodness of fit statistic P ⫽ 0.47 (48). Use and Discontinuation of Coxibs 297 Table 4. Reasons for discontinuation of traditional nonsteroidal antiinflammatory drugs and coxibs* Reason Traditional NSAIDs (n ⴝ 707 prescriptions) Coxibs (n ⴝ 435 prescriptions) 411 (58.1) 204 (46.9)† 72 (10.2) 66 (9.3) 41 (9.4) 27 (6.2) 42 (5.9) 3 (0.4) 21 (3.0) 24 (3.4) 4 (0.6) 21 (3.0) 8 (1.8)† 5 (1.1) 14 (3.2) 3 (0.7)† 9 (2.1)§ 6 (1.4) Drug discontinued, n ⫽ 615 Known reason for discontinuation, n ⫽ 273‡ Lack of efficacy Adverse event Type of adverse event Gastrointestinal Non-gastrointestinal Other or not mentioned Therapeutic course completed Too expensive Other factors * Values are the number (%). Gastrointestinal events include abdominal pain, gastrointestinal bleeding, or gastrointestinal complications. Non-gastrointestinal events include dyspnea, headache, dizziness, renal complications, and central nervous system complaints. NSAIDs ⫽ nonsteroidal antiinflammatory drugs. † P ⬍ 0.01. ‡ Explicit reason known for 44% of all NSAIDs discontinued. § P ⬍ 0.05. (OR 0.5, 95% CI 0.2– 0.9) and rheumatologists (OR 0.6, 95% CI 0.4 – 0.9). However, patients of rheumatologists were less likely to completely discontinue all of their NSAIDs compared with patients seen by internists (OR 0.4, 95% CI 0.2– 0.9) or family and general practitioners (OR 0.6, 95% CI 0.3–1.3). Patients who stopped at least one NSAID medication were more likely to have a history of GI disease (P ⫽ 0.004) and a history of OA (P ⫽ 0.045). Stopping all NSAIDs was not significantly associated with any of the patient characteristics examined (data not shown). Patients who had documented complaints of GI problems or whose medical record presented evidence of GI bleeding were more likely to stop at least one NSAID prescription (n ⫽ 57; 83%) than were patients for whom these complaints or medical findings were not documented (n ⫽ 260; 68%) (P ⫽ 0.014). A similar trend was observed for discontinuation of all NSAIDs (23% versus 18%) (data not shown). We next examined patterns and predictors of NSAID discontinuation at the individual prescription level (Table 4). Of all NSAID prescriptions written (n ⫽ 1,142), 615 (54%) were discontinued during followup after a mean ⫾ SD cumulative duration of 5.8 ⫾ 5.9 months per agent. Compared with traditional NSAIDs (411 prescriptions; 58%), coxibs (204 prescriptions; 47%) were significantly less likely to be discontinued (OR 0.6, 95% CI 0.5– 0.8). Of the 615 documented NSAIDs that were stopped, 273 (44%) had a documented reason for discontinuation. Among these, lack of efficacy was the most frequent reason (n ⫽ 113, 41%) followed by an adverse event (n ⫽ 93, 34%). GI complaints (abdominal pain, GI bleeding, or GI complications) were the most frequently documented medical problems considered to be an adverse event by the managing physicians (n ⫽ 50, 54%). There was no significant association between NSAID type (coxibs or traditional) and reporting of an adverse event as a reason for discontinuation. Compared with coxibs, traditional NSAIDs were sig- nificantly more likely to be discontinued because of a GI adverse event (OR 4.2, 95% CI 1.6 –10.9) or a history of GI disease (OR 1.7, 95% CI 1.1–2.6). In contrast, coxibs were more likely to be discontinued when the patient had a history of hypertension (OR 1.5, 95% CI 1.0 –2.1). Multivariable regression analyses exploring reasons for NSAID discontinuation showed that patients with a history of GI disease (OR 2.5, 95% CI 1.2–5.3) and those seeing an internist (OR 1.7, 95% CI 1.0 –2.7) or a rheumatologist (OR 3.1, 95% CI 1.7–5.6) (referent to those seeing a family or general practitioner) remained more likely to discontinue at least one NSAID (data not shown). DISCUSSION Despite the increasing worldwide use of coxibs (25,26), patterns and predictors of coxib use have not been previously studied at a population level. A plausible explanation for the greater use of coxibs by specialists in our study is that internists (and particularly rheumatologists) see referred patients who already have tried traditional NSAIDs and either experienced no benefit or experienced toxicity. It is also possible that these same patients are also more likely to be exposed to and/or influenced by directto-consumer advertising. Practice pattern variations among the therapies for musculoskeletal disorder are well documented (20,22,27–29). Variations in practice patterns and unequal levels of patient care may be partially attributable to inadequate dissemination of the latest knowledge. Specialists such as rheumatologists are quicker to adopt new treatments when choosing medications (22,27,30 –34). It should be noted that of all pharmaceutical products being marketed, rofecoxib had the largest recent advertising budget of any current pharmaceutical product (35). Accordingly, rheumatologists and internists are more fre- 298 quently exposed to pharmaceutical detailing of newer arthritis products than are family or general practitioners, and this may preferentially influence their prescribing behaviors. Comorbidity, especially GI disease and cardiac failure, appeared to be a factor favoring the selection of coxibs. This may be a reflection of physicians prescribing these medications to “sicker” patients. Our finding that generalists are more likely to selectively prescribe coxibs to their patients at higher risk for GI disease is important, because ⬎60% of patients with musculoskeletal disorders are treated primarily by generalists (36), and ⬎20% of all encounters with primary care providers are for musculoskeletal complaints (37,38). Generalists tend to be more conservative and often more cost-effective in their adoption of newer musculoskeletal therapies (30), which may influence their willingness to selectively prescribe coxibs to a patient with a history of GI disease. Compared with nonselective NSAIDs, coxibs were significantly less likely to be discontinued, suggesting that they may be better tolerated. During the first months of the study period, only traditional NSAIDs were prescribed, and it is possible that coxibs were too new to the drug market and had not been used for a long enough time to be as commonly discontinued. However, the duration of NSAID use did not significantly differ between the 2 classes of drugs in our study. GI problems have been consistently reported as the most frequently documented adverse event leading to discontinuation of an NSAID (39). As expected, a history of GI disease was the factor most associated with discontinuation of at least one NSAID. Although the numbers were small, nonselective NSAIDs had more discontinuations for GI reasons than did the coxibs. These findings support the premise that GI symptoms or adverse effects may be a major factor associated with switching between NSAIDs. Absence of more comprehensive data on discontinuation prohibits us from deeper exploration of these findings. This study did not addresses important questions on physicians’ prescribing behaviors, such as overprescription of NSAIDs or adherence to community standards of care. We did not define absolute standards against which to measure prescribing quality, because evidence on which to generate consensus remains incomplete. Because medical record review is constrained by the completeness and accuracy of the information recorded (40 – 42), our analysis may partially reflect quality of documentation rather than quality of care. In addition, medical charts do not provide accurate information on adherence to medical treatment or on the magnitude of use of over-the-counter medications (43– 46). However, our detailed record review protocol with stringent quality control and excellent interrater reliability increase confidence in our results. Another limitation in the present study is that we were not able to ascertain patient race/ethnicity, because the managed care organization did not routinely collect racial or ethnic information. Last, given the restriction of our sample to one geographic area, our results may not be generalizable to all groups of chronic NSAID users. Despite these potential limitations, the data for this study came from a large regional managed health care organiza- Patino et al tion, allowing linkage of data from medical records, pharmacy claims, and administrative files. In conclusion, we observed significantly greater use of coxibs among specialists, even after accounting for important case-mix covariates. We also determined that patient factors, such as GI disease, had an important impact on both initiation and discontinuation of traditional NSAIDs compared with coxibs. Further research is needed to relate these interesting NSAID use patterns with long-term patient safety. REFERENCES 1. Wolfe MM, Lichtenstein DR, Singh G. Gastrointestinal toxicity of nonsteroidal antiinflammatory drugs. N Engl J Med 1999;34024:1888 –99. 2. Baum C, Kennedy DL, Forbes MB. Utilization of nonsteroidal antiinflammatory drugs. Arthritis Rheum 1985;28:686 –92. 3. Kaufman DW, Kelly JP, Rosenberg L, Anderson TE, Mitchell AA. Recent patterns of medication use in the ambulatory adult population of the United States: the Slone survey. JAMA 2002;287:337– 44. 4. Emery P. Considerations for nonsteroidal anti-inflammatory drug therapy: benefits. Scand J Rheumatol Suppl 1996;105: 5–9. 5. Hochberg MC, Altman RD, Brandt KD, Clark BM, Dieppe PA, Griffin MR, et al. Guidelines for the medical management of osteoarthritis. Part I. Osteoarthritis of the hip. American College of Rheumatology. Arthritis Rheum 1995;38:1535– 40. 6. Holt WS, Jr., Mazzuca SA. Prescribing behaviors of family physicians in the treatment of osteoarthritis. Fam Med 1992; 24:524 –7. 7. Ward MM, Fries JF. Trends in antirheumatic medication use among patients with rheumatoid arthritis, 1981-1996. J Rheumatol 1998;253:408 –16. 8. Berard A, Solomon DH, Avorn J. Patterns of drug use in rheumatoid arthritis. J Rheumatol 2000;27:1648 –55. 9. Saag KG, Cowdery JS. Nonsteroidal anti-inflammatory drugs: balancing benefits and risks. Spine 1994;19:1530 – 4. 10. Singh G: Recent considerations in nonsteroidal anti-inflammatory drug gastropathy. Am J Med 1998;105:31S–38S. 11. Page J, Henry D. Consumption of NSAIDs and the development of congestive heart failure in elderly patients: an underrecognized public health problem. Arch Intern Med 2000; 1606:777– 84. 12. Feenstra J, Heerdink ER, Grobbee DE, Stricker BH. Association of nonsteroidal anti-inflammatory drugs with first occurrence of heart failure and with relapsing heart failure: the Rotterdam Study. Arch Intern Med 2002;162:265–70. 13. Delzell E, Shapiro S. A review of epidemiologic studies of nonnarcotic analgesics and chronic renal failure. Medicine (Baltimore) 1998;77:102–21. 14. Saag KG, Rubenstein LM, Chrischilles EA, Wallace RB. Nonsteroidal antiinflammatory drugs and cognitive decline in the elderly. J Rheumatol 1995;22:2142–7. 15. Karplus TM, Saag KG. Nonsteroidal anti-inflammatory drugs and cognitive function: do they have a beneficial or deleterious effect? Drug Saf 1998;19:427–33. 16. Simon LS, Weaver AL, Graham DY, Kivitz AJ, Lipsky PE, Hubbard RC, et al. Anti-inflammatory and upper gastrointestinal effects of celecoxib in rheumatoid arthritis: a randomized controlled trial. JAMA 1999;282:1921– 8. 17. Morgan GJ, Poland M, DeLapp RE. Efficacy and safety of nabumetone versus diclofenac, naproxen, ibuprofen, and piroxicam in the elderly. Am J Med 1993;95:19S–27S. 18. Pope JE, Anderson JJ, Felson DT. A meta-analysis of the effects of nonsteroidal anti-inflammatory drugs on blood pressure. Arch Intern Med 1993;153:477– 84. 19. Johnson AG, Nguyen TV, Day RO. Do nonsteroidal anti-inflammatory drugs affect blood pressure? A meta-analysis. Ann Intern Med 1994;121:289 –300. Use and Discontinuation of Coxibs 20. Criswell LA, Redfearn WJ. Variation among rheumatologists in the use of prednisone and second-line agents for the treatment of rheumatoid arthritis. Arthritis Rheum 1994;37:476 – 80. 21. Criswell LA, Such CL, Yelin EH. Differences in the use of second-line agents and prednisone for treatment of rheumatoid arthritis by rheumatologists and non-rheumatologists. J Rheumatol 1997;24:2283–90. 22. Mazzuca SA, Brandt KD, Katz BP, Dittus RS, Freund DA, Lubitz R, et al. Comparison of general internists, family physicians, and rheumatologists managing patients with symptoms of osteoarthritis of the knee. Arthritis Care Res 1997;10: 289 –99. 23. Hosmer JDW, Lemeshow S. Applied Logistic Regression. New York: John Wiley; 1989. 24. Diggle PJ, Liang KY, Zeger SL. Analysis of Longitudinal Data. New York: Oxford University Press; 1994. 25. IMS Health: IMS HEALTH Reports Cox-2 Drug Sales In US Surge 137% in Six Month Period. Westport (CT): IMS Health Inc; 2000. 26. IMS Health: Top products, July 2001. Westport (CT): IMS Health Inc; 2001. 27. Stross JK. Relationships between knowledge and experience in the use of disease-modifying antirheumatic agents: a study of primary care practitioners. JAMA 1989;262:2721–3. 28. Katz JN, Solomon DH, Bates DW. Differences between generalists and specialists. Arthritis Care Res 1997;10:161–2. 29. Saag KG, Doebbeling BN, Rohrer JE, Kolluri S, Mitchell TA, Wallace RB. Arthritis health service utilization among the elderly: the role of urban-rural residence and other utilization factors. Arthritis Care Res 1998;11:177– 85. 30. Donohoe MT. Comparing generalist and specialty care: discrepancies, deficiencies, and excesses. Arch Intern Med 1998; 158:1596 – 608. 31. Majumdar SR, Inui TS, Gurwitz JH, Gillman MW, McLaughlin TJ, Soumerai SB. Influence of physician specialty on adoption and relinquishment of calcium channel blockers and other treatments for myocardial infarction. J Gen Intern Med 2001; 16:351–9. 32. Turner BJ, Laine C. Differences between generalists and specialists: knowledge, realism, or primum non nocere? J Gen Intern Med 2001;16:422– 4. 33. Harrold LR, Field TS, Gurwitz JH. Knowledge, patterns of care, and outcomes of care for generalists and specialists. J Gen Intern Med 1999;14:499 –511. 34. Yelin EH, Such CL, Criswell LA, Epstein WV. Outcomes for persons with rheumatoid arthritis with a rheumatologist versus a non-rheumatologist as the main physician for this condition. Med Care 1998;36:513–22. 299 35. Rosenthal MB, Berndt ER, Donohue JM, Frank RG, Epstein AM. Promotion of prescription drugs to consumers. N Engl J Med 2002;346:498 –505. 36. Yelin E, Bernhard G, Pflugrad D. Access to medical care among persons with musculoskeletal conditions: a study using a random sample of households in San Mateo County, California. Arthritis Rheum 1995;38:1128 –33. 37. Spitzer WO, Harth M, Goldsmith CH, Norman GR, Dickie GL, Bass MJ, et al. The arthritic complaint in primary care: prevalence, related disability, and costs. J Rheumatol 1976;3:88 – 99. 38. Kahl LE. Musculoskeletal problems in the family practice setting: guidelines for curriculum design. J Rheumatol 1987; 14:811– 4. 39. Hawkey C, Laine L, Simon T, Beaulieu A, Maldonado-Cocco J, Acevedo E, et al. Comparison of the effect of rofecoxib (a cyclooxygenase 2 inhibitor), ibuprofen, and placebo on the gastroduodenal mucosa of patients with osteoarthritis: a randomized, double-blind, placebo-controlled trial. The Rofecoxib Osteoarthritis Endoscopy Multinational Study Group. Arthritis Rheum 2000;43:370 –7. 40. Shenfield GM, Robb T, Duguid M. Recording previous adverse drug reactions: a gap in the system. Br J Clin Pharmacol 2001;51:623– 6. 41. Hannan TJ. Detecting adverse drug reactions to improve patient outcomes. Int J Med Inf 1999;55:61– 4. 42. Allison JJ, Wall TC, Spettell CM, Calhoun J, Fargason CA Jr, Kobylinski RW, et al. The art and science of chart review. Jt Comm J Qual Improv 2000;26:115–36. 43. Gilchrist WJ, Lee YC, Tam HC, Macdonald JB, Williams BO. Prospective study of drug reporting by general practitioners for an elderly population referred to a geriatric service. Br Med J (Clin Res Ed) 1987;294:289 –90. 44. Jaski ME, Schwartzberg JG, Guttman RA, Noorani M. Medication review and documentation in physician office practice. Eff Clin Pract 2000;3:31– 4. 45. Beers MH, Munekata M, Storrie M. The accuracy of medication histories in the hospital medical records of elderly persons. J Am Geriatr Soc 1990;38:1183–7. 46. Lau HS, Florax C, Porsius AJ, De Boer A. The completeness of medication histories in hospital medical records of patients admitted to general internal medicine wards. Br J Clin Pharmacol 2000;49:597– 603. 47. Harrell FE, Jr., Lee KL, Califf RM, Pryor DB, Rosati RA. Regression modelling strategies for improved prognostic prediction. Stat Med 1984;3:143–52. 48. Lemeshow S, Hosmer DW Jr. A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 1982;115:92–106.