Are patient questionnaire scores as "scientific" as laboratory tests for rheumatology clinical care?
Patients with diabetes are now monitored with the goal of "tight control" of abnormal laboratory tests, often primarily through self-management, sometimes with high-technology pumps, with substantially improved outcomes. (9) An approach similar to diabetes has been applied to a strategy of "tight control" of other chronic diseases, including hypertension and hyperlipidemia, resulting in important advances in care and outcomes.
The model of diabetes has appeared attractive to apply the scientific method to diagnosis and management of rheumatoid arthritis (RA). Arthritis also was recognized in ancient cultures, although, rather than RA, it may likely have been gout, ankylosing spondylitis, or osteoarthritis. (10) RA was described by Garrod in 1890. (11) Rheumatoid factor was described, in 1940, by Waaler in Norway (12) and, in 1948, by Rose, Ragan, and colleagues in the United States. (13) This discovery led to establishment of an "autoimmune" basis of RA, with extensive characterization of immunologic abnormalities and inflammation over the second half of the 20th century. The discovery of prednisone, in 1949, led to an award of a Nobel Prize to Hench and coworkers in 1950. (14,15) Major advances in therapy of RA have been seen in recent decades, with aggressive therapies and tight control aiming for remission, (16,17) methotrexate as a superior disease-modifying antirheumatic drug (DMARD), (18) and biological agents targeting cytokines such as tumor necrosis factor alpha (TNF[alpha]). (19) Further laboratory research remains the best hope to understand the pathogenesis of RA and to develop new therapies for all rheumatic diseases, analogous to major advances for infectious diseases, anemia, renal failure, diabetes, and many others.
At the same time, the clinical application of rheumatoid factor and the more recently discovered anti-cyclic citrullinated peptide (anti-CCP) antibodies, in 1998, (20,21) as well as acute-phase reactants, erythrocyte sedimentation rate (ESR), and serum level of C-reactive protein (CRP), (22,23) has not been analogous to glucose or hemoglobin A1c in clinical care. All four tests are abnormal in the majority of patients with RA. However, rheumatoid factor and anti-CCP are negative in at least 30% of patients. (24) ESR and CRP are normal in 40% of patients seen over the last 2 decades. (25-28) Thus, rheumatology laboratory tests differ from "gold standard" tests, as they are not informative for diagnosis and management in all patients with a given disease, although they are essential to further understanding of pathogenesis and development of therapies.
Recognition that no laboratory test (or any other single measure) could provide a "gold standard" for all patients with RA led rheumatologists in the late 1980s to develop pooled indices (29) to assess patient status, based on a Core Data Set (30) of seven measures: three from a physician or other health professional--swollen joint count, tender joint count, and physical global estimate of status; three from a patient--physical function, pain, and patient global estimate of status; and one laboratory test of an acute-phase reactant, either ESR or CRP.
Inclusion of patient self-report information, in addition to laboratory tests and joint counts, to assess and monitor patients with RA presents a major paradigm shift from the "biomedical model," (31) the dominant paradigm of 20th century medicine. This model suggests that information from a patient history is "subjective" and nonquantitative, in contrast to scientific "objective" data from laboratory tests, imaging, and other high-technology sources. Patient information has been regarded primarily, if not entirely, as "clues" to identify appropriate objective "scientific" high technology laboratory and imaging tests for diagnosis and treatment. However, the RA Core Data Set regards patient questionnaires as standardized, quantitative "scientific" data for medical care.
Patient questionnaire scores as "scientific" data, according to the scientific method, are based on the science of psychometrics, developed by social scientists over the 20th century. Psychometric approaches use standardized methodology to collect quantitative patient self-report data at baseline and for comparison from one visit to the next, just as laboratory tests. Indeed, standards of measurement accuracy, validity, reliability (reproducibility), and precision applied to patient questionnaires generally are considerably more stringent than those applied to laboratory tests, possibly, in part, due to the "subjective" source of the data.
A major milestone in development of patient questionnaires for rheumatology was publication of the health assessment questionnaire (HAQ) (32) and the Arthritis Impact Measurement Scales (AIMS) (33) in the same issue of Arthritis & Rheumatism in 1980. Shortly thereafter, a few (but not many) rheumatologists, including the author (34) and Frederick Wolfe, (35) adopted these questionnaires for usual clinical care. The HAQ was more easily completed by patients in usual care settings, although the AIMS had superior psychometric properties. (36) The author developed a modified version of the HAQ (MHAQ) with eight rather than 20 activities, to allow additional information within a two-page format, reported in 1983. (34)
Patient questionnaires have been viewed by the rheumatology community (and continue to be viewed by many rheumatologists) as a poor surrogate for traditional "objective" laboratory tests, formal joint counts, a radiograph, etc. In 1984, it was reported that patient questionnaire scores indicating poor functional status predicted survival of less than 50% of RA patients over the next 5 years (Fig. 1A),37 which had not been reported previously (or since) for baseline radiographic scores or laboratory tests (Fig. 1B indicated significantly higher survival according to more years of formal education, which is discussed in detail elsewhere).38 Indeed, survival of patients with RA who had poor functional status over 5 years (Fig. 1A) was comparable to stage IV Hodgkin's disease at that time at Stanford University (Fig. 1C),38 and three-vessel coronary artery disease at the Cleveland Clinic (Fig. 1D).39 This information suggested that patient questionnaire scores were not a poor surrogate for traditional measures, and, in fact, were as "scientific" as any data for the clinical prognosis of RA. Patient questionnaire scores, which had been used in the author's clinic, then were transformed from a somewhat optional to a mandatory component of all visits in the author's clinical care.
[FIGURE 1 OMITTED]
A prospective study, initiated in 1985, indicated that the MHAQ and multidimensional HAQ (MDHAQ), derived from the HAQ, predicted 5-year mortality at higher levels of significance than laboratory tests, radiographs, or joint counts in the same patients. (40) Analysis of survival according to whether rheumatoid factor was present or absent indicates essentially no difference between the two groups (Fig. 2). By contrast, significant differences in survival were seen according to physical function; all patients with a normal physical function score of 0 (on a scale of 0-3) survived the 5-year period, while survival was only 65% among patients with the poorest physical function scores (Fig. 2).
All clinical measures at baseline, in 1985, except pain scores, indicated poorer status in patients who died prior to 1990, compared to survivors in 1990 (Table 2). (40) However, higher levels of significance were seen for patient questionnaire scores and measures of functional status, compared to laboratory tests and radiographic scores (Table 2). (40) Cox proportional hazard models indicated that the three significant independent variables which were prognostic of mortality were age, comorbidities, and functional status according to an MHAQ (Table 3). Thus, the functional status questionnaire score was significant, while joint counts, laboratory tests, and radiographic scores were not significant in multivariable analysis of clinical predictors of mortality.
Similar results have been reported in 16 additional studies (total of 18) in a descriptive analysis of all reports concerning prediction of mortality in patients with RA over periods of 5 years or longer (Fig. 3). (41) Physical function was significant in 17 of 18 studies, 14 (72%) in multivariate analyses and three (22%) in univariate analyses only, compared to comorbidities in 65% and 30% of 23 studies, rheumatoid factor in 45% and 21% of 29 studies, extra-articular disease in 44% and 39% of 18 studies, ESR in 37% and 32% of 19 studies, socioeconomic status in 31% and 46% of 13 studies, formal joint count in 22% and 28% of 18 studies, and a hand radiograph in 11% and 50% of 18 studies. (41) An elevated score for physical function might be viewed as a marker of a dysregulation, comparable to elevated blood pressure, glucose, or cholesterol. Control of dysregulation prevents damage to organs such as blood vessels, kidneys, and joints, leading to improved outcomes including survival.
[FIGURE 2 OMITTED]
Over the last 25 years, extensive evidence has emerged which indicates that patient self-report questionnaires provide quantitative data of comparable "scientific" value to laboratory tests or joint counts in clinical care, as described in several previous essays (42-50) and as summarized briefly below:
1. Patient questionnaire scores distinguish active from control treatment in clinical trials as efficiently as formal joint counts and laboratory tests
The relative efficiencies of the three patient-reported outcome measures in the Core Data Set--physical function, pain, and global estimate--to distinguish active from control group treatment responses are as great as laboratory tests or a swollen or tender joint count, in clinical trials involving leflunomide, methotrexate, adalimumab, and abatacept. (51-54) An index of these three measures, RAPID3, distinguishes active from control treatment as effectively as DAS (28) or ACR 20/50/70% criteria in clinical trials of these agents, (55-58) and is correlated significantly with DAS and CDAI in clinical trials and usual clinical care. (59,60)
2. Patient questionnaire scores are more reproducible than formal swollen and tender joint counts, and can be used by any physician
A careful joint examination clearly is required for diagnosis, and a formal tender and swollen joint count is the most specific indicator of change in RA status. However, joint counts are poorly reproducible in formal studies, (61-65) and are less sensitive in detecting inflammatory activity than magnetic resonance imaging (MRI) or ultrasound. (66) Even when optimally reliable, differences between observers have led to a requirement that the joint count be performed by the same observer from one visit to the next. Therefore, quantitative data concerning patient status cannot be collected reliably by other observers or general physicians, a serious limitation of the joint count for "scientific" patient care.
3. Patient questionnaire scores are more likely to reflect an abnormal state than laboratory tests
Patient questionnaire scores have been found abnormal in 80% to 90% of patients with RA or in all patients seen in a rheumatic disease clinic. (67) By contrast, rheumatoid factor is positive in 71% and anti-CCP in 69% of patients with RA, (24) while approximately 60% have abnormal ESR or CRP. (25,27) Therefore, patient questionnaire scores are more frequently abnormal than laboratory tests, although, as noted above, a tender or swollen joint count is the most sensitive measure in RA.
4. Treatment with placebo is more likely to result in improvement in joint counts, compared Patient questionnaire scores
Among the seven ACR Core Data Set measures, patients who receive placebo or control treatment in clinical trials generally show improvement in swollen and tender joint counts, but are much less likely to show improvement in patient questionnaire measures and laboratory tests. (51,52,68,69)
5. Patient questionnaire scores are correlated significantly with traditional joint counts, radiographs, and laboratory tests
Significant correlations of patient questionnaire scores with joint counts, laboratory tests, and radiographic scores were documented in the 1980s,43 albeit with different levels and with recognition of two categories of measures (Fig. 4). The first category includes traditional "objective" measures: radiographs, joint deformities, and laboratory tests, including histocompatibility type, which are correlated at higher levels with one another than with patient questionnaire scores or tender joint counts. (70) The second category includes patient questionnaire scores and tender joint counts, which are correlated at higher levels with one another than with radiographic or laboratory measures. (43) Laboratory and radiographic measures clearly are more important in pathogenesis and more specific to RA. However, patient self-report measures are far more significant in clinical prognosis than radiographs or laboratory measures, as noted below, and, therefore, are of comparable "scientific" value in clinical care.
[FIGURE 4 OMITTED]
6. Patient questionnaire scores for physical function are far more prognostic for severe long-term RA outcomes, including work disability and mortality, than radiographic or laboratory data
All studies that include a patient questionnaire indicate that a baseline questionnaire measure of physical function is far more significant than a radiograph or laboratory test in the prognosis of severe long-term outcomes of RA, including work disability, costs, joint replacement surgery, and death (all except radiographic damage). (71)
7. An MDHAQ/RAPID3 score is informative in patients with all rheumatic diseases
Most patients with any rheumatic disease experience problems in physical function, pain, or global status, quantified by MDHAQ/RAPID3 scores, as well as morning stiffness and fatigue, as assessed on the MDHAQ. (72) MDHAQ is informative in patients with all rheumatic diseases. (73)
8. RAPID3 can be calculated in fewer than 10 seconds, compared to 90 seconds for a swollen and tender joint count and 2 minutes for a CDAI or DAS28
As noted, a RAPID3 score can be calculated in fewer than 10 seconds. (74) By contrast, performance of a swollen and tender 28-joint count requires about 90 seconds. Calculation of a DAS28 or CDAI requires at least 2 minutes (including the joint counts), even when all the data are readily available. (74) The advantage of specificity is limited by limitations of feasibility in usual care.
9. Treatment guided by quantitative data results in better patient status than usual nonquantitative clinical care
Six clinical trials have now documented that guidance using quantitative data results in better patient status than usual care without such guidance: the Finnish Rheumatoid Arthritis Combination Therapy (FIN-RACo) trial (75,76); Tight Control for Rheumatoid Arthritis (TICORA) trial (77); Behandel Strategien (BeSt) or "treatment strategies" trial (78,79); Computer Assisted Management in Early Rheumatoid Arthritis (CAMERA) study (80); the Ciclosporine, Methotrexate, Steroid in Rheumatoid Arthritis (CIMESTRA) trial (81,82); and the TICORA2 trial. (83) All six trials used the DAS28 to generate quantitative data. DAS28 is not available at many visits in usual clinical care, and RAPID3 is correlated significantly with DAS28. Therefore, a RAPID3 score could be appropriate for usual clinical care, although prospective studies are needed to confirm this hypothesis.
Laboratory tests are the most technologically advanced measures, and joint counts are the most specific measures for RA. However, patient self-report questionnaire scores detect treatment effects at similar levels, are more significant in prognosis, and considerably more feasible and cost-effective than laboratory tests or joint counts. A patient questionnaire may be regarded as a quantitative patient history, equally "scientific" to monitor patient status as laboratory tests and joint counts.
A patient questionnaire does not replace a further patient history, joint counts, or laboratory tests. RAPID3 scores, based on self-report patient questionnaire scores, provide informative quantitative data for patient status from one visit to the next. If quantitative data are recorded, an opportunity for documentation and more rational monitoring is gained, along with enhanced efficiency of patient care. If no data are recorded, this opportunity is lost and can never be replaced.
It has been suggested that "80% of the data in 100% of the patients may be preferable to 100% of the data in 5% of the patients" (or fewer) who might be included in clinical research. (46) Therefore, a less comprehensive measure, which is feasible and applicable in usual clinical care, appears preferable to no quantitative measure at all. However, a RAPID3 score may provide more than "80%," and indeed may be as informative as a DAS or CDAI for patient assessment, reflecting patient and physician goals of treatment as accurately as the number of swollen and tender joints. All rheumatologists would find it valuable to ask all patients at all visits to complete a MDHAQ and for a staff member or themselves to score a RAPID3 in 5 seconds in usual care.
Dr. Pincus has received consultant fees and lecture fees from Bristol-Myers Squibb. He has received consultant fees from and served on a Scientific Advisory Board for UCB, Inc. He has received research support from Centocor, Inc.
(1.) Peirce CS. The fixation of belief. Popular Science Monthly. 1877;12:1-15.
(2.) Dobson M. Nature of the urine in diabetes. Medical Observations and Inquiries. 1776;5:298-310.
(3.) Steinke J, Thorn GW. Diabetes mellitus. In: Wintrobe MM, Thorn GW, Adams RD, et al. (eds): Harrison's Principles of Internal Medicine (6th ed). New York: McGraw-Hill Book Co., 1970, pp. 523-539.
(4.) Banting FG, Best CH, Collip JB, et al. Pancreatic extracts in the treatment of diabetes mellitus: preliminary report. Can Med Assoc J. 1922;12(3):141-6.
(5.) Banting FG, Best CH. The internal secretion of the pancreas. J Lab Clin Med. 1922;7:251-66.
(6.) Huisman TH, Martis EA, Dozy A. Chromatography of hemoglobin types on carboxymethylcellulose. J Lab Clin Med. 1958;52(2):312-27.
(7.) Rahbar S, Blumenfeld O, Ranney HM. Studies of an unusual hemoglobin in patients with diabetes mellitus. Biochem Biophys Res Commun. 1969;36(5):838-43.
(8.) Koenig RJ, Peterson CM, Jones RL, et al. Correlation of glucose regulation and hemoglobin AIc in diabetes mellitus. N Engl J Med. 1976;295(8):417-20.
(9.) The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. The Diabetes Control and Complications Trial Research Group. N Engl J Med. 1993;329(14):977-86.
(10.) Rothschild BM. Diffuse idiopathic skeletal hyperostosis as reflected in the paleontologic record: dinosaurs and early mammals. Semin Arthritis Rheum. 1987;17:119-25.
(11.) Garrod AE. A Treatise on Rheumatism and Rheumatoid Arthritis. London: Charles Griffin & Co. Ltd., 1890.
(12.) Waaler E. On the occurrence of a factor in human serum activating the specific agglutination of sheep blood corpuscles. Acta Path Microbiol Scand. 1940;17:172-8.
(13.) Rose HM, Ragan C, Pearce E, Lipman MO. Differential agglutination of normal and sensitized sheep erythrocytes by sera of patients with rheumatoid arthritis. Proc Soc Exp Biol Med. 1948;68:1-6.
(14.) Hench PS, Kendall EC, Slocumb CH, Polley HF. The effect of a hormone of the adrenal cortex (17-hydroxy-11-dehydrocorticosterone; compound E) and of the pituitary adrenocorticotropic hormone on rheumatoid arthritis. Proc Staff Meet Mayo Clin. 1949;24:181.
(15.) Hench PS. The potential reversibility of rheumatoid arthritis: heberden oration, Heberden Society of London, 15 October 1948. Mayo Clin Proc. 1949;24:167-78.
(16.) Emery P, Salmon M. Early rheumatoid arthritis: time to aim for remission? Ann Rheum Dis. 1995;54:944-7.
(17.) Weinblatt ME. Rheumatoid arthritis: treat now, not later! (Editorial). Ann Intern Med. 1996;124:773-4.
(18.) Sokka T, Pincus T. Ascendancy of weekly low-dose methotrex ate in usual care of rheumatoid arthritis from 1980 to 2004 at two sites in Finland and the United States. Rheumatology (Oxford). 2008;47(10):1543-7.
(19.) Olsen NJ, Stein CM. New drugs for rheumatoid arthritis. N Engl J Med. 2004;350:2167-79.
(20.) Schellekens GA, de Jong BAW, van den Hoogen FHJ, et al. Citrulline is an essential constituent of antigenic determinants recognized by rheumatoid arthritis-specific autoantibodies. J Clin Invest. 1998;101:273-81.
(21.) Riedemann JP, Munoz S, Kavanaugh A. The use of second generation anti-CCP antibody (anti-CCP2) testing in rheumatoid arthritis--a systematic review. Clin Exp Rheumatol. 2005;23:S69-76.
(22.) Lipsky PE. Rheumatoid arthritis. In: Fauci AS, Langford CA (eds). Harrison's Rheumatology. New York: McGraw-Hill, 2006, pp. 85-104.
(23.) Chatham WW, Blackburn WD, Jr. Laboratory findings in rheumatoid arthritis. In: Koopman WJ, Moreland LW (eds). Arthritis and Allied Conditions: A Textbook of Rheumatology (15th ed). Philadelphia, PA: Lippincott, Williams & Wilkins, 2005, pp. 1207-1221.
(24.) Nishimura K, Sugiyama D, Kogata Y, et al. Meta-analysis: diagnostic accuracy of anti-cyclic citrullinated peptide antibody and rheumatoid factor for rheumatoid arthritis. Ann Intern Med. 2007;146(11):797-808.
(25.) Wolfe F, Michaud K. The clinical and research significance of the erythrocyte sedimentation rate. J Rheumatol. 1994;21:1227-37.
(26.) Wolfe F. Comparative usefulness of C-reactive protein and erythrocyte sedimentation rate in patients with rheumatoid arthritis. J Rheumatol. 1997;24:1477-85.
(27.) Sokka T, Pincus T. Erythrocyte sedimentation rate, C-reactive protein, or rheumatoid factor are normal at presentation in 35%-45% of patients with rheumatoid arthritis seen between 1980 and 2004: analyses from Finland and the United States. J Rheumatol. 2009;36(7):1387-90.
(28.) Abelson B, Sokka T, Pincus T. Declines in erythrocyte sedimentation rates in patients with rheumatoid arthritis over the second half of the 20th century. J Rheumatol. 2009;36(8):1596-9.
(29.) Goldsmith CH, Smythe HA, Helewa A. Interpretation and power of pooled index. J Rheumatol. 1993;20:575-8.
(30.) Felson DT, Anderson JJ, Boers M, et al. The American College of Rheumatology preliminary core set of disease activity measures for rheumatoid arthritis clinical trials. Arthritis Rheum. 1993;36:729-40.
(31.) Engel GL. The need for a new medical model: a challenge for biomedicine. Science. 1977;196:129-36.
(32.) Fries JF, Spitz P, Kraines RG, Holman HR. Measurement of patient outcome in arthritis. Arthritis Rheum. 1980;23:137-45.
(33.) Meenan RF, Gertman PM, Mason JH. Measuring health status in arthritis: the arthritis impact measurement scales. Arthritis Rheum. 1980;23:146-52.
(34.) Pincus T, Summey JA, Soraci SA Jr, et al. Assessment of patient satisfaction in activities of daily living using a modified Stanford health assessment questionnaire. Arthritis Rheum. 1983;26:1346-53.
(35.) Wolfe F. A brief health status instrument: CLINHAQ. (Abstract). Arthritis Rheum. 1989;32:S99.
(36.) Pincus T, Swearingen CJ. The HAQ compared with the MDHAQ: "keep it simple, stupid" (KISS), with feasibility and clinical value as primary criteria for patient questionnaires in usual clinical care. Rheum Dis Clin North Am. 2009;35(4):787-98, ix.
(37.) Pincus T, Callahan LF, Sale WG, et al. Severe functional declines, work disability, and increased mortality in seventy-five rheumatoid arthritis patients studied over nine years. Arthritis Rheum. 1984;27:864-72.
(38.) Kaplan HS. Survival as related to treatment. In: Kaplan HS (ed). Hodgkin's Disease. Cambridge: Harvard University Press, 1972, pp. 360-388.
(39.) Proudfit WL, Bruschke AVG, Sones FM Jr. Natural history of obstructive coronary artery disease: ten-year study of 601 nonsurgical cases. Prog Cardiovasc Dis. 1978;21:53-78.
(40.) Callahan LF, Pincus T, Huston JW, III, et al. Measures of activity and damage in rheumatoid arthritis: depiction of changes and prediction of mortality over five years. Arthritis Care Res. 1997;10:381-94.
(41.) Sokka T, Abelson B, Pincus T. Mortality in rheumatoid arthritis: 2008 update. Clin Exp Rheumatol. 2008;26(5 Suppl 51):S35-61.
(42.) Pincus T, Callahan LF, Vaughn WK. Questionnaire, walking time and button test measures of functional capacity as predictive markers for mortality in rheumatoid arthritis. J Rheumatol. 1987;14:240-51.
(43.) Pincus T, Callahan LF, Brooks RH, et al. Self-report questionnaire scores in rheumatoid arthritis compared with traditional physical, radiographic, and laboratory measures. Ann Intern Med. 1989;110:259-66.
(44.) Pincus T, Brooks RH, Callahan LF. Prediction of long-term mortality in patients with rheumatoid arthritis according to simple questionnaire and joint count measures. Ann Intern Med. 1994;120:26-34.
(45.) Pincus T, Keysor J, Sokka T, et al. Patient questionnaires and formal education level as prospective predictors of mortality over 10 years in 97% of 1416 patients with rheumatoid arthritis from 15 United States private practices. J Rheumatol. 2004;31:229-34.
(46.) Pincus T, Wolfe F. Patient questionnaires for clinical research and improved standard patient care: is it better to have 80% of the information in 100% of patients or 100% of the information in 5% of patients? J Rheumatol. 2005;32:575-7.
(47.) Pincus T. The DAS is the most specific measure, but a patient questionnaire is the most informative measure to assess rheumatoid arthritis. J Rheumatol. 2006;33:834-7.
(48.) Pincus T. Patient questionnaires and formal education as more significant prognostic markers than radiographs or laboratory tests for rheumatoid arthritis mortality--limitations of a biomedical model to predict long-term outcomes. Bull NYU Hosp Jt Dis. 2007;65(Suppl 1):S29-36.
(49.) Pincus T, Sokka T. Quantitative clinical rheumatology: "keep it simple, stupid": MDHAQ function, pain, global, and RAPID3 quantitative scores to improve and document the quality of rheumatologic care. J Rheumatol. 2009;36(6):1099-100.
(50.) Pincus T, Bergman MJ, Maclean R, Yazici Y. Complex measures and indices for clinical research compared with simple patient questionnaires to assess function, pain, and global estimates as rheumatology "vital signs" for usual clinical care. Rheum Dis Clin North Am. 2009;35(4):779-86, ix.
(51.) Strand V, Tugwell P, Bombardier C, et al. Function and health-related quality of life: results from a randomized controlled trial of leflunomide versus methotrexate or placebo in patients with active rheumatoid arthritis. Arthritis Rheum. 1999;42:1870-8.
(52.) Tugwell P, Wells G, Strand V, et al. Clinical improvement as reflected in measures of function and health-related quality of life following treatment with leflunomide compared with methotrexate in patients with rheumatoid arthritis: sensitivity and relative efficiency to detect a treatment effect in a twelve-month, placebo-controlled trial. Arthritis Rheum. 2000;43(3):506-14.
(53.) Wells G, Li T, Maxwell L, et al. Responsiveness of patient reported outcomes including fatigue, sleep quality, activity limitation, and quality of life following treatment with abatacept for rheumatoid arthritis. Ann Rheum Dis. 2008;67(2):260-5.
(54.) Pincus T, Amara I, Segurado OG, et al. Relative efficiencies of physician/assessor global estimates and patient questionnaire measures are similar to or greater than joint counts to distinguish adalimumab from control treatments in rheumatoid arthritis clinical trials. J Rheumatol. 2008;35(2):201-5.
(55.) Pincus T, Strand V, Koch G, et al. An index of the three core data set patient questionnaire measures distinguishes efficacy of active treatment from placebo as effectively as the American College of Rheumatology 20% response criteria (ACR20) or the disease activity score (DAS) in a rheumatoid arthritis clinical trial. Arthritis Rheum. 2003;48(3):625-30.
(56.) Pincus T, Amara I, Koch GG. Continuous indices of Core Data Set measures in rheumatoid arthritis clinical trials: lower responses to placebo than seen with categorical responses with the American College of Rheumatology 20% criteria. Arthritis Rheum. 2005;52:6.
(57.) Pincus T, Chung C, Segurado OG, et al. An index of patient self-reported outcomes (PRO Index) discriminates effectively between active and control treatment in 4 clinical trials of adalimumab in rheumatoid arthritis. J Rheumatol. 2006;33:2146-52.
(58.) Pincus T, Bergman MJ, Yazici Y, et al. An index of only patient-reported outcome measures, routine assessment of patient index data 3 (RAPID3), in two abatacept clinical trials: similar results to disease activity score (DAS28) and other RAPID indices that include physician-reported measures. Rheumatology (Oxford). 2008;47(3):345-9.
(59.) Wolfe F, Michaud K, Pincus T. A composite disease activity scale for clinical practice, observational studies and clinical trials: the patient activity scale (PAS/PAS-II). J Rheumatol. 2005;32:2410-5.
(60.) Pincus T, Yazici Y, Bergman M, et al. A proposed continuous quality improvement approach to assessment and management of patients with rheumatoid arthritis without formal joint counts, based on quantitative Routine Assessment of Patient Index Data (RAPID) scores on a Multidimensional Health Assessment Questionnaire (MDHAQ). Best Pract Res Clin Rheumatol. 2007;21(4):789-804.
(61.) Hart LE, Tugwell P, Buchanan WW, et al. Grading of tenderness as a source of interrater error in the Ritchie articular index. J Rheumatol. 1985;12:716-7.
(62.) Lewis PA, O'Sullivan MM, Rumfeld WR, et al. Significant changes in Ritchie scores. Br J Rheumatol. 1988;27:32-6.
(63.) Klinkhoff AV, Bellamy N, Bombardier C, et al. An experiment in reducing interobserver variability of the examination for joint tenderness. J Rheumatol. 1988;15:492-4.
(64.) Thompson PW, Hart LE, Goldsmith CH, et al. Comparison of four articular indices for use in clinical trials in rheumatoid arthritis: patient, order and observer variation. J Rheumatol. 1991;18:661-5.
(65.) Scott DL, Choy EHS, Greeves A, et al. Standardising joint assessment in rheumatoid arthritis. Clin Rheumatol. 1996;15:579-82.
(66.) Wakefield RJ, Kong KO, Conaghan PG, et al. The role of ultrasonography and magnetic resonance imaging in early rheumatoid arthritis. Clin Exp Rheumatol. 2003;21:S42-9.
(67.) Pincus T, Swearingen CJ. Erythrocyte sedimentation rate (ESR) is the least likely of Core Data Set measures to identify an "abnormal state" in new patients with RA to monitor therapeutic responses, according to 3 definitions of "abnormal state." (Abstract #318). Arthritis Rheum. 2009;60(Suppl):S117.
(68.) Scott DL, Strand V. The effects of disease-modifying antirheumatic drugs on the Health Assessment Questionnaire score. Lessons from the leflunomide clinical trials database. Rheum. 2002;41:899-909.
(69.) Cohen SB, Strand V, Aguilar D, Ofman JJ. Patient- versus physician-reported outcomes in rheumatoid arthritis patients treated with recombinant interleukin-1 receptor antagonist (anakinra) therapy. Rheumatology. 2004;43(6):704-11.
(70.) Olsen NJ, Callahan LF, Brooks RH, et al. Associations of HLA-DR4 with rheumatoid factor and radiographic severity in rheumatoid arthritis. Am J Med. 1988;84:257-64.
(71.) Pincus T, Sokka T. Quantitative measures to assess patients with rheumatic diseases: 2006 update. Rheum Dis Clin North Am. 2006;32(Suppl 1):29-36.
(72.) Pincus T, Askanase AD, Swearingen CJ. A multi-dimensional health assessment questionnaire (MDHAQ) and routine assessment of patient index data (RAPID3) scores are informative in patients with all rheumatic diseases. Rheum Dis Clin North Am. 2009;35(4):819-27, x.
(73.) Pincus T, Sokka T. Can a Multi-Dimensional Health Assessment Questionnaire (MDHAQ) and Routine Assessment of Patient Index Data (RAPID) scores be informative in patients with all rheumatic diseases? Best Pract Res Clin Rheumatol. 2007;21(4):733-53.
(74.) Yazici Y, Bergman M, Pincus T. Time to score quantitative rheumatoid arthritis measures: 28-joint count, disease activity score, health assessment questionnaire (HAQ), multidimensional HAQ (MDHAQ), and routine assessment of patient index data (RAPID) scores. J Rheumatol. 2008;35:603-9.
(75.) Mottonen T, Hannonen P, Leirisalo-Repo M, et al. Comparison of combination therapy with single-drug therapy in early rheumatoid arthritis: a randomised trial. FIN-RACo trial group. Lancet. 1999;353:1568-73.
(76.) Puolakka K, Kautiainen H, Mottonen T, et al. Early suppression of disease activity is essential for maintenance of work capacity in patients with recent-onset rheumatoid arthritis: five-year experience from the FIN-RACo trial. Arthritis Rheum. 2005;52(1):36-41.
(77.) Grigor C, Capell H, Stirling A, et al. Effect of a treatment strategy of tight control for rheumatoid arthritis (the TICORA study): a single-blind randomised controlled trial. Lancet. 2004;364:263-9.
(78.) Goekoop-Ruiterman YPM, de Vries-Bouwstra JK, Allaart CF, et al. Clinical and radiographic outcomes of four different treatment strategies in patients with early rheumatoid arthritis (the BeSt study): a randomized, controlled trial. Arthritis Rheum. 2005;52:3381-90.
(79.) Goekoop-Ruiterman YPM, de Vries-Bouwstra JK, Allaart CF. et al. Comparison of treatment strategies in early rheumatoid arthritis: a randomized trial. Ann Intern Med. 2007;146(6):406-15.
(80.) Verstappen SMM, Jacobs JWG, van der Veen MJ, et al. Intensive treatment with methotrexate in early rheumatoid arthritis: aiming for remission. Computer Assisted Management in Early Rheumatoid Arthritis (CAMERA, an open-label strategy trial). Ann Rheum Dis. 2007;66(11):1443-9.
(81.) Hetland ML, Ejbjerg BJ, Horslev-Petersen K, et al. MRI bone oedema is the strongest predictor of subsequent radiographic progression in early rheumatoid arthritis. Results from a 2 year randomised controlled trial (CIMESTRA). Ann Rheum Dis. 2009;68:384-90.
(82.) Hetland ML, Stengaard-Pedersen K, Junker P, et al. Aggressive combination therapy with intra-articular glucocorticoid injections and conventional disease-modifying anti-rheumatic drugs in early rheumatoid arthritis: second-year clinical and radiographic results from the CIMESTRA study. Ann Rheum Dis. 2008;67:815-22.
(83.) Saunders SA, Capell HA, Stirling A, et al. Triple therapy in early active rheumatoid arthritis: a randomized, single-blind, controlled trial comparing step-up and parallel treatment strategies. Arthritis Rheum. 2008;58(5):1310-7.
Theodore Pincus, M.D., is Clinical Professor of Medicine, New York University School of Medicine, and within the Division of Rheumatology, Department of Medicine, NYU Hospital for Joint Diseases, NYU Langone Medical Center, New York, New York. Correspondence: Theodore Pincus, M.D., Division of Rheumatology, Suite 1608, NYU Hospital for Joint Diseases, 301 East 17th Street, New York, New York 10003; email@example.com.
Table 1 Similarities of History of Measurement in Diabetes Mellitus and Rheumatoid Arthritis Diabetes Mellitus Rheumatoid Arthritis Ancient observations Sweet taste of urine Description of inflammatory arthritis (Gout? Ankylosing spondylitis? Maybe not RA) Description of disease 1776--Dobson (2) 1890--Garrod (11) Initial measurement of Serum glucose: Rheumatoid factor: laboratory abnormality 1859--Bernard (3) 1940--Waaler (12) 1948--Rose et al. (13) More specific Hemoglobin A1c: Anti-CCP: laboratory abnormality 1958--Huisman et 1998--Schellekens et al. (6) al. (20) 1969--Rahbar et al., Elevated levels in diabetes (7) 1976--Koenig et al., Superior to glucose to monitor control (8) Consequences of Tight control Tight control measurements Table 2 Mean Baseline Values in 206 RA Patients According to Survival or Mortality Status 5 Years Later * Measures Alive Dead P Value Age (years) 55.1 65.5 < 0.001 ARA functional class 2.2 2.6 < 0.001 Number of comorbidities 1.1 2.1 < 0.001 Walking time 10.8 16.8 < 0.001 ESR 33.8 48.3 0.004 MHAQ physical function score 1.98 2.32 0.005 Learned helplessness 2.41 2.55 0.007 Patient global estimate of status 2.6 3.0 0.01 Number of extra-articular features 0.2 0.5 0.02 Duration of disease 9.1 12.7 0.03 Years of education 10.8 9.4 0.03 Joint count 12.8 15.9 0.04 Radiographic score 1.2 1.4 0.20 Rheumatoid factor titer 2.7 2.9 0.28 Pain 5.40 5.19 0.68 * Mean baseline values, in 1985, in 206 patients with RA, according to whether patients were alive or dead 5 years later in 1990. Note that all measures indicated poorer status in patients who would not survive the 5-year period, except pain scores, but higher levels of significance were seen for patient questionnaire scores and measures of functional status, compared to laboratory tests and radiographic data (From Callahan, et al. Arthritis Care Res. 1997;10:381-94.)40 ARA, American Rheumatism Association; ESR, erythrocyte sedimentation rate; MHAQ, modified health assessment questionnaire. Table 3 Cox Proportional Hazards Model Analyses of Survival Between 1985 and 1990 * Univariate RR (95% CL) ([dagger]) P Value Age 1.07 (1.04-1.11) < 0.001 Comorbidity 1.63 (1.32-2.00) < 0.001 MHAQ physical function score 2.00 (1.28-3.12) 0.003 Disease duration 1.04 (1.01-1.06) 0.02 Education 0.89 (0.82-0.97) 0.007 ESR 1.01 (1.00-1.02) 0.005 Joint count 1.02 (0.97-1.04) 0.10 Walking time 1.03 (1.01-1.06) 0.04 Radiograph 1.04 (0.86-2.27) 0.17 Stepwise Model RR (95% CL) * P Value Age 1.06 (1.03-1.10) < 0.001 Comorbidity 1.40 (1.11-1.77) 0.02 MHAQ physical function score 1.76 (1.40-2.78) 0.02 Disease duration -- -- Education -- -- ESR -- -- Joint count -- -- Walking time -- -- Radiograph -- -- * Baseline demographic, joint count, radiographic, laboratory, functional, questionnaire, and disease variables were entered into a model to analyze survival in 206 patients over the subsequent 5 years (From Callahan, et al. Arthritis Care Res. 1997;10:381-94.) (40) ([dagger]) 95% CL = 95% confidence limit. MHAQ, modified health assessment questionnaire; ESR, erythrocyte sedimentation rate. Figure 3 Significance of eight variables as predictors of mortality. In a review of 84 reports concerning mortality in RA, 53 cohorts presented predictors of mortality. (41) For each variable, "n" is the number of reports that included the variable, and bars indicate the percentage of those reports in which the variable was a significant predictor of mortality in multivariate analyses (black), in univariate analyses (dotted), or was not significant (white). Significant Significant Not in multivariate in univariate Significant analyses analyses Physical function (N=18) 72% 22% 6% Comorbidities (N=23) 65% 30% 4% Rheumatoid factor (N=29) 45% 21% 34% Extra-articular disease (N=18) 44% 39% 17% ESR (N=19) 37% 32% 32% Socio-economic status (N=13) 31% 46% 23% Joint count (N=18) 22% 46% 50% Hand-radio graph (N=18) 11% 50% 39% Note: Table made from bar graph.
|Printer friendly Cite/link Email Feedback|
|Publication:||Bulletin of the NYU Hospital for Joint Diseases|
|Date:||Apr 1, 2010|
|Previous Article:||Informed consent: practical considerations.|
|Next Article:||Progress toward the development of a new definition of remission in rheumatoid arthritis.|