Evidence from a Multidimensional Health Assessment Questionnaire (MDHAQ) of the Value of a Biopsychosocial Model to Complement a Traditional Biomedical Model in Care of Patients with Rheumatoid Arthritis

Theodore Pincus; Jacquelin R Chua; Kathryn A Gibson

doi:10.4078/jrd.2016.23.4.212

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Pincus, Chua, and Gibson: Evidence from a Multidimensional Health Assessment Questionnaire (MDHAQ) of the Value of a Biopsychosocial Model to Complement a Traditional Biomedical Model in Care of Patients with Rheumatoid Arthritis

Review Article

J Rheum Dis 2016;23(4):212-233.

Published online: 31 October 2016

DOI: https://doi.org/10.4078/jrd.2016.23.4.212

Evidence from a Multidimensional Health Assessment Questionnaire (MDHAQ) of the Value of a Biopsychosocial Model to Complement a Traditional Biomedical Model in Care of Patients with Rheumatoid Arthritis

Theodore Pincus¹, Jacquelin R Chua¹, Kathryn A Gibson²

¹Division of Rheumatology, Department of Internal Medicine, Rush University Medical Center, Chicago, IL, USA

²Rheumatology Department, Liverpool Hospital, University of New South Wales, and Ingham Research Institute, Liverpool, NSW, Australia

Corresponding to: Theodore Pincus, Division of Rheumatology, Department of Internal Medicine, Rush University Medical Center, 1611 West Harrison Street, Suite 510, Chicago, IL 60612, USA. E-mail: tedpincus@gmail.com

Received 27 May 2016 Revised 25 August 2016 Accepted 25 August 2016

This is a Free Access article, which permits unrestricted non-commerical use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Patient self-report questionnaires such as a multidimensional health assessment questionnaire (MDHAQ) have advanced knowledge concerning prognosis, care, course and outcomes of rheumatoid arthritis (RA). The MDHAQ may overcome some limitations of a “biomedical model,” the dominant paradigm of contemporary medical services, including limitations of laboratory tests, radiographs, joint counts, and clinical trials, to predict and depict the long-term course and outcomes of RA. A complementary “biopsychosocial model” captures components of a patient medical history on patient questionnaires as quantitative, standard, “scientific” scores for physical function, pain, fatigue, and other problems, rather than as “subjective” narrative descriptions. A rationale for a biopsychosocial model in RA includes the importance of a patient history in diagnosis and management compared to biomarkers in many chronic diseases such as hypertension and diabetes. Some important observations which support a biopsychosocial model in RA based on patient questionnaires include that MDHAQ physical function scores are far more significant than radiographs or laboratory tests to predict severe RA outcomes such as work disability and premature death; patient self-report measures are more efficient than tender joint counts and laboratory tests to distinguish active from control treatments in RA clinical trials involving biological agents; and MDHAQ scores are more likely than laboratory tests to be abnormal at presentation and to document incomplete responses to methotrexate at initiation of biological agents. Patient questionnaires can save time for doctors and patients, and improve doctor-patient communication. A standardized database of MDHAQ scores consecutive patients over long periods might be considered by all rheumatologists in routine clinical care.

REFERENCES

1. Engel GL. The need for a new medical model: a challenge for biomedicine. Science. 1977; 196:129–36.

2. Weed LL. Medical records that guide and teach. N Engl J Med. 1968; 278:652–7.

3. Pincus T, Callahan LF. Reassessment of twelve traditional paradigms concerning the diagnosis, prevalence, morbidity and mortality of rheumatoid arthritis. Scand J Rheumatol Suppl. 1989; 79:67–96.

4. Callahan LF, Pincus T. Education, self-care, and outcomes of rheumatic diseases: further challenges to the “biomedical model” paradigm. Arthritis Care Res. 1997; 10:283–8.

5. McCollum L, Pincus T. A biopsychosocial model to complement a biomedical model: patient questionnaire data and socioeconomic status usually are more significant than laboratory tests and imaging studies in prognosis of rheumatoid arthritis. Rheum Dis Clin North Am. 2009; 35:699–712.

6. Pincus T, Castrejón I. MDHAQ/RAPID3 scores: quantitative patient history data in a standardized “scientific” format for optimal assessment of patient status and quality of care in rheumatic diseases. Bull NYU Hosp Jt Dis. 2011; 69:201–14.

7. Pincus T, Castrejón I. An evidence-based medical visit for patients with rheumatoid arthritis based on standard, quantitative scientific data from a patient MDHAQ and physician report. Bull NYU Hosp Jt Dis. 2012; 70:73–94.

8. Pincus T, Yazici Y, Castrejón I. Pragmatic and scientific advantages of MDHAQ/ RAPID3 completion by all patients at all visits in routine clinical care. Bull NYU Hosp Jt Dis. 2012; 70(Suppl 1):30–6.

9. Pincus T, Castrejón I. Are patient self-report questionnaires as “scientific” as biomarkers in “treat-to-target” and prognosis in rheumatoid arthritis? Curr Pharm Des. 2015; 21:241–56.

10. Pincus T, Sokka T, Kautiainen H. Patients seen for standard rheumatoid arthritis care have significantly better articular, radiographic, laboratory, and functional status in 2000 than in 1985. Arthritis Rheum. 2005; 52:1009–19.

11. Lichtenstein MJ, Pincus T. How useful are combinations of blood tests in “rheumatic panels” in diagnosis of rheumatic diseases? J Gen Intern Med. 1988; 3:435–42.

12. Pincus T. A pragmatic approach to cost-effective use of laboratory tests and imaging procedures in patients with musculoskeletal symptoms. Prim Care. 1993; 20:795–814.

13. Pincus T, Sokka T. Laboratory tests to assess patients with rheumatoid arthritis: advantages and limitations. Rheum Dis Clin North Am. 2009; 35:731–4.

14. Pincus T, Sokka T. Complexities in the quantitative assessment of patients with rheumatic diseases in clinical trials and clinical care. Clin Exp Rheumatol. 2005; 23(5 Suppl 39):S1–9.

15. Pincus T. Advantages and limitations of quantitative measures to assess rheumatoid arthritis: joint counts, radiographs, laboratory tests, and patient questionnaires. Bull NYU Hosp Jt Dis. 2006; 64:32–9.

16. Yazici Y, Sokka T, Pincus T. Radiographic measures to assess patients with rheumatoid arthritis: advantages and limitations. Rheum Dis Clin North Am. 2009; 35:723–9.

17. Fuchs HA, Brooks RH, Callahan LF, Pincus T. A simplified twenty-eight-joint quantitative articular index in rheumatoid arthritis. Arthritis Rheum. 1989; 32:531–7.

18. Sokka T, Pincus T. Quantitative joint assessment in rheumatoid arthritis. Clin Exp Rheumatol. 2005; 23(5 Suppl 39):S58–62.

19. Feinstein AR. An additional basic science for clinical medicine: II. The limitations of randomized trials. Ann Intern Med. 1983; 99:544–50.

20. Freireich EJ. The randomized clinical trial as an obstacle to clinical research. Varco RL, Delaney JP, editors. Controversy in surgery. Philadelphia: WB Saunders;1983. p. 5–12.

21. Ioannidis JP, Trikalinos TA. An exploratory test for an excess of significant findings. Clin Trials. 2007; 4:245–53.

22. Kaptchuk TJ. The double-blind, randomized, placebo-controlled trial: gold standard or golden calf? J Clin Epidemiol. 2001; 54:541–9.

23. Pincus T, Sokka T. Clinical trials in rheumatic diseases: designs and limitations. Rheum Dis Clin North Am. 2004; 30:701–24.

24. Pincus T, Stein CM. What is the best source of useful data on the treatment of rheumatoid arthritis: clinical trials, clinical observations, or clinical protocols? J Rheumatol. 1995; 22:1611–7.

25. Nishimura K, Sugiyama D, Kogata Y, Tsuji G, Nakazawa T, Kawano S, et al. Meta-analysis: diagnostic accuracy of anti-cyclic citrullinated peptide antibody and rheumatoid factor for rheumatoid arthritis. Ann Intern Med. 2007; 146:797–808.

26. Castrejón I, McCollum L, Tanriover MD, Pincus T. Importance of patient history and physical examination in rheumatoid arthritis compared to other chronic diseases: results of a physician survey. Arthritis Care Res (Hoboken). 2012; 64:1250–5.

27. 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; 36:1596–9.

28. Wolfe F, Michaud K. The clinical and research significance of the erythrocyte sedimentation rate. J Rheumatol. 1994; 21:1227–37.

29. Smedstad LM, Moum T, Guillemin F, Kvien TK, Finch MB, Suurmeijer TP, et al. Correlates of functional disability in early rheumatoid arthritis: a cross-sectional study of 706 patients in four European countries. Br J Rheumatol. 1996; 35:746–51.

30. 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; 36:1387–90.

31. Pincus T, Gibson KA, Shmerling RH. An evidence-based approach to laboratory tests in usual care of patients with rheumatoid arthritis. Clin Exp Rheumatol. 2014; 32(5 Suppl 85):S–23-8.

32. Olsen NJ, Callahan LF, Brooks RH, Nance EP, Kaye JJ, Stastny P, et al. Associations of HLA-DR4 with rheumatoid factor and radiographic severity in rheumatoid arthritis. Am J Med. 1988; 84:257–64.

33. Yelin E, Meenan R, Nevitt M, Epstein W. Work disability in rheumatoid arthritis: effects of disease, social, and work factors. Ann Intern Med. 1980; 93:551–6.

34. Pincus T, Callahan LF, Sale WG, Brooks AL, Payne LE, Vaughn WK. Severe functional declines, work disability, and increased mortality in seventy-five rheumatoid arthritis patients studied over nine years. Arthritis Rheum. 1984; 27:864–72.

35. Callahan LF, Bloch DA, Pincus T. Identification of work disability in rheumatoid arthritis: physical, radiographic and laboratory variables do not add explanatory power to demographic and functional variables. J Clin Epidemiol. 1992; 45:127–38.

36. Wolfe F, Hawley DJ. The longterm outcomes of rheumatoid arthritis: Work disability: a prospective 18 year study of 823 patients. J Rheumatol. 1998; 25:2108–17.

37. Puolakka K, Kautiainen H, Möttönen T, Hannonen P, Hakala M, Korpela M, et al. Predictors of productivity loss in early rheumatoid arthritis: a 5 year follow up study. Ann Rheum Dis. 2005; 64:130–3.

38. Wolfe F, Mitchell DM, Sibley JT, Fries JF, Bloch DA, Williams CA, et al. The mortality of rheumatoid arthritis. Arthritis Rheum. 1994; 37:481–94.

39. Aletaha D, Landewe R, Karonitsch T, Bathon J, Boers M, Bombardier C, et al. Reporting disease activity in clinical trials of patients with rheumatoid arthritis: EULAR/ACR collaborative recommendations. Arthritis Rheum. 2008; 59:1371–7.

40. Lubeck DP, Spitz PW, Fries JF, Wolfe F, Mitchell DM, Roth SH. A multicenter study of annual health service utilization and costs in rheumatoid arthritis. Arthritis Rheum. 1986; 29:488–93.

41. Michaud K, Messer J, Choi HK, Wolfe F. Direct medical costs and their predictors in patients with rheumatoid arthritis: a three-year study of 7,527 patients. Arthritis Rheum. 2003; 48:2750–62.

42. Wolfe F, Zwillich SH. The long-term outcomes of rheumatoid arthritis: a 23-year prospective, longitudinal study of total joint replacement and its predictors in 1,600 patients with rheumatoid arthritis. Arthritis Rheum. 1998; 41:1072–82.

43. Pincus T, Callahan LF. What is the natural history of rheumatoid arthritis? Rheum Dis Clin North Am. 1993; 19:123–51.

44. Smolen JS, Aletaha D, Bijlsma JW, Breedveld FC, Boumpas D, Burmester G, et al. Treating rheumatoid arthritis to target: recommendations of an international task force. Ann Rheum Dis. 2010; 69:631–7.

45. van der Heijde DM, van't Hof MA, van Riel PL, Theunisse LA, Lubberts EW, van Leeuwen MA, et al. Judging disease activity in clinical practice in rheumatoid arthritis: first step in the development of a disease activity score. Ann Rheum Dis. 1990; 49:916–20.

46. Prevoo ML, van't Hof MA, Kuper HH, van Leeuwen MA, van de Putte LB, van Riel PL. Modified disease activity scores that include twenty-eight-joint counts. Development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum. 1995; 38:44–8.

47. Aletaha D, Smolen J. The Simplified Disease Activity Index (SDAI) and the Clinical Disease Activity Index (CDAI): a review of their usefulness and validity in rheumatoid arthritis. Clin Exp Rheumatol. 2005; 23(5 Suppl 39):S100–8.

48. Felson DT, Smolen JS, Wells G, Zhang B, van Tuyl LH, Funovits J, et al. American College of Rheumatology/ European League Against Rheumatism provisional definition of remission in rheumatoid arthritis for clinical trials. Arthritis Rheum. 2011; 63:573–86.

49. Felson DT, Anderson JJ, Boers M, Bombardier C, Furst D, Goldsmith C, et al. American College of Rheumatology. Preliminary definition of improvement in rheumatoid arthritis. Arthritis Rheum. 1995; 38:727–35.

50. Pincus T, Yazici Y, Sokka T. Quantitative measures of rheumatic diseases for clinical research versus standard clinical care: differences, advantages and limitations. Best Pract Res Clin Rheumatol. 2007; 21:601–28.

51. Klinkhoff AV, Bellamy N, Bombardier C, Carette S, Chalmers A, Esdaile JM, et al. An experiment in reducing interobserver variability of the examination for joint tenderness. J Rheumatol. 1988; 15:492–4.

52. Uhlig T, Kvien TK, Pincus T. Test-retest reliability of disease activity core set measures and indices in rheumatoid arthritis. Ann Rheum Dis. 2009; 68:972–5.

53. Tugwell P, Wells G, Strand V, Maetzel A, Bombardier C, Crawford B, 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. Leflunomide Rheumatoid Arthritis Investigators Group. Arthritis Rheum. 2000; 43:506–14.

54. 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 (Oxford). 2004; 43:704–11.

55. Pincus T, Richardson B, Strand V, Bergman MJ. Relative efficiencies of the 7 rheumatoid arthritis Core Data Set measures to distinguish active from control treatments in 9 comparisons from clinical trials of 5 agents. Clin Exp Rheumatol. 2014; 32(5 Suppl 85):S–47-54.

56. Scott DL, Grindulis KA, Struthers GR, Coulton BL, Popert AJ, Bacon PA. Progression of radiological changes in rheumatoid arthritis. Ann Rheum Dis. 1984; 43:8–17.

57. Østergaard M, Pedersen SJ, Døhn UM. Imaging in rheumatoid arthritis– status and recent advances for magnetic resonance imaging, ultrasonography, computed tomography and conventional radiography. Best Pract Res Clin Rheumatol. 2008; 22:1019–44.

58. Pincus T, Swearingen CJ, Luta G, Sokka T. Efficacy of prednisone 1-4 mg/day in patients with rheumatoid arthritis: a randomised, double-blind, placebo controlled withdrawal clinical trial. Ann Rheum Dis. 2009; 68:1715–20.

59. Anderson J, Caplan L, Yazdany J, Robbins ML, Neogi T, Michaud K, et al. Rheumatoid arthritis disease activity measures: American College of Rheumatology recommendations for use in clinical practice. Arthritis Care Res (Hoboken). 2012; 64:640–7.

60. Pincus T, Swearingen CJ, Bergman MJ, Colglazier CL, Kaell AT, Kunath AM, et al. RAPID3 (Routine Assessment of Patient Index Data) on an MDHAQ (Multidimensional Health Assessment Questionnaire): agreement with DAS28 (Disease Activity Score) and CDAI (Clinical Disease Activity Index) activity categories, scored in five versus more than ninety seconds. Arthritis Care Res (Hoboken). 2010; 62:181–9.

61. Sackett DL, Rosenberg WM, Gray JA, Haynes RB, Richardson WS. Evidence based medicine: what it is and what it isn't. BMJ. 1996; 312:71–2.

62. Williams HJ, Ward JR, Reading JC, Brooks RH, Clegg DO, Skosey JL, et al. Comparison of auranofin, methotrexate, and the combination of both in the treatment of rheumatoid arthritis. A controlled clinical trial. Arthritis Rheum. 1992; 35:259–69.

63. Felson DT, Anderson JJ, Meenan RF. The comparative efficacy and toxicity of second-line drugs in rheumatoid arthritis. Results of two metaanalyses. Arthritis Rheum. 1990; 33:1449–61.

64. Pincus T, Marcum SB, Callahan LF. Longterm drug therapy for rheumatoid arthritis in seven rheumatology private practices: II. Second line drugs and prednisone. J Rheumatol. 1992; 19:1885–94.

65. Yazici Y, Sokka T, Kautiainen H, Swearingen C, Kulman I, Pincus T. Long term safety of methotrexate in routine clinical care: discontinuation is unusual and rarely the result of laboratory abnormalities. Ann Rheum Dis. 2005; 64:207–11.

66. Donahue KE, Gartlehner G, Jonas DE, Lux LJ, Thieda P, Jonas BL, et al. Systematic review: comparative effectiveness and harms of disease-modifying medications for rheumatoid arthritis. Ann Intern Med. 2008; 148:124–34.

67. Sokka T, Kautiainen H, Toloza S, Mäkinen H, Verstappen SM, Lund Hetland M, et al. QUEST-RA: quantitative clinical assessment of patients with rheumatoid arthritis seen in standard rheumatology care in 15 countries. Ann Rheum Dis. 2007; 66:1491–6.

68. Sokka T, Pincus T. Most patients receiving routine care for rheumatoid arthritis in 2001 did not meet inclusion criteria for most recent clinical trials or american college of rheumatology criteria for remission. J Rheumatol. 2003; 30:1138–46.

69. Sokka T, Pincus T. Eligibility of patients in routine care for major clinical trials of anti-tumor necrosis factor alpha agents in rheumatoid arthritis. Arthritis Rheum. 2003; 48:313–8.

70. Ruberman W, Weinblatt E, Goldberg JD, Chaudhary BS. Psychosocial influences on mortality after myocardial infarction. N Engl J Med. 1984; 311:552–9.

71. Pincus T. Limitations of traditional randomized controlled clinical trials in rheumatology. Yazici H, Yazici Y, Lesaffre E, editors. Understanding evidence based rheumatology – a guide to interpreting criteria, drugs, trials, registries, and ethics. New York: Springer International Publishing Switzerland;2014. p. 179–207.

72. Howick J. The philosophy of evidence-based medicine. Chichester, Wiley-Blackwell;. 2011.

73. Hampton JR, Harrison MJ, Mitchell JR, Prichard JS, Seymour C. Relative contributions of history-taking, physical examination, and laboratory investigation to diagnosis and management of medical outpatients. Br Med J. 1975; 2:486–9.

74. Sandler G. The importance of the history in the medical clinic and the cost of unnecessary tests. Am Heart J. 1980; 100:928–31.

75. Peterson MC, Holbrook JH, Von Hales D, Smith NL, Staker LV. Contributions of the history, physical examination, and laboratory investigation in making medical diagnoses. West J Med. 1992; 156:163–5.

76. Pryor DB, Shaw L, McCants CB, Lee KL, Mark DB, Harrell FE Jr, et al. Value of the history and physical in identifying patients at increased risk for coronary artery disease. Ann Intern Med. 1993; 118:81–90.

77. Fries JF, Spitz P, Kraines RG, Holman HR. Measurement of patient outcome in arthritis. Arthritis Rheum. 1980; 23:137–45.

78. Pincus T, Swearingen C, Wolfe F. Toward a multidimensional Health Assessment Questionnaire (MDHAQ): assessment of advanced activities of daily living and psychological status in the patient-friendly health assessment questionnaire format. Arthritis Rheum. 1999; 42:2220–30.

79. Pincus T, Sokka T, Kautiainen H. Further development of a physical function scale on a MDHAQ [corrected] for standard care of patients with rheumatic diseases. J Rheumatol. 2005; 32:1432–9.

80. Boers M, Tugwell P, Felson DT, van Riel PL, Kirwan JR, Edmonds JP, et al. World Health Organization and International League of Associations for Rheumatology core endpoints for symptom modifying antirheumatic drugs in rheumatoid arthritis clinical trials. J Rheumatol Suppl. 1994; 41:86–9.

81. Pincus T, Bergman M, Sokka T, Roth J, Swearingen C, Yazici Y. Visual analog scales in formats other than a 10 centimeter horizontal line to assess pain and other clinical data. J Rheumatol. 2008; 35:1550–8.

82. Pincus T, Bergman MJ, Yazici Y, Hines P, Raghupathi K, Maclean R. 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; 47:345–9.

83. Pincus T, Swearingen CJ, Bergman M, Yazici Y. RAPID3 (Routine Assessment of Patient Index Data 3), a rheumatoid arthritis index without formal joint counts for routine care: proposed severity categories compared to disease activity score and clinical disease activity index categories. J Rheumatol. 2008; 35:2136–47.

84. Pincus T, Hines P, Bergman MJ, Yazici Y, Rosenblatt LC, MacLean R. Proposed severity and response criteria for Routine Assessment of Patient Index Data (RAPID3): results for categories of disease activity and response criteria in abatacept clinical trials. J Rheumatol. 2011; 38:2565–71.

85. Pincus T. Can RAPID3, an index without formal joint counts or laboratory tests, serve to guide rheumatologists in tight control of rheumatoid arthritis in usual clinical care? Bull NYU Hosp Jt Dis. 2009; 67:254–66.

86. DeWalt DA, Reed GW, Pincus T. Further clues to recognition of patients with fibromyalgia from a simple 2-page patient multidimensional health assessment questionnaire (MDHAQ). Clin Exp Rheumatol. 2004; 22:453–61.

87. Pincus T, Hassett AL, Callahan LF. Clues on the MDHAQ to identify patients with fibromyalgia and similar chronic pain conditions. Rheum Dis Clin North Am. 2009; 35:865–9.

88. Kirwan JR, Minnock P, Adebajo A, Bresnihan B, Choy E, de Wit M, et al. Patient perspective: fatigue as a recommended patient centered outcome measure in rheumatoid arthritis. J Rheumatol. 2007; 34:1174–7.

89. Sokka T, Pincus T. Poor physical function, pain and limited exercise: risk factors for premature mortality in the range of smoking or hypertension, identified on a simple patient self-report questionnaire for usual care. BMJ Open. 2011; 1:e000070.

90. Pincus T, Bergman MJ, Yazici Y. RAPID3-an index of physical function, pain, and global status as “vital signs” to improve care for people with chronic rheumatic diseases. Bull NYU Hosp Jt Dis. 2009; 67:211–25.

91. Hess EV, Fries JF, Klinenberg JR. A uniform database for rheumatic diseases. Arthritis Rheum. 1979; 22:1029–33.

92. Tugwell P, Boers M. Developing consensus on preliminary core efficacy endpoints for rheumatoid arthritis clinical trials. OMERACT Committee. J Rheumatol. 1993; 20:555–6.

93. Moses LE. The series of consecutive cases as a device for assessing outcomes of intervention. N Engl J Med. 1984; 311:705–10.

94. Yazici Y, Erkan D. Eligibility of rheumatoid arthritis patients seen in clinical practice for rheumatoid arthritis clinical trials: comment on the article by Sokka and Pincus. Arthritis Rheum. 2003; 48:3611. author reply 3613-5.

95. Ideker T, Galitski T, Hood L. A new approach to decoding life: systems biology. Annu Rev Genomics Hum Genet. 2001; 2:343–72.

96. Hood L, Flores M. A personal view on systems medicine and the emergence of proactive P4 medicine: predictive, preventive, personalized and participatory. N Biotechnol. 2012; 29:613–24.

97. Leigh JP, Fries JF. Mortality predictors among 263 patients with rheumatoid arthritis. J Rheumatol. 1991; 18:1307–12.

98. Wolfe F, Kleinheksel SM, Cathey MA, Hawley DJ, Spitz PW, Fries JF. The clinical value of the Stanford Health Assessment Questionnaire Functional Disability Index in patients with rheumatoid arthritis. J Rheumatol. 1988; 15:1480–8.

99. Söderlin MK, Nieminen P, Hakala M. Functional status predicts mortality in a community based rheumatoid arthritis population. J Rheumatol. 1998; 25:1895–9.

100. Sokka T, Abelson B, Pincus T. Mortality in rheumatoid arthritis: 2008 update. Clin Exp Rheumatol. 2008; 26(5 Suppl 51):S35–61.

101. Pincus T, Callahan LF. Formal education as a marker for increased mortality and morbidity in rheumatoid arthritis. J Chronic Dis. 1985; 38:973–84.

102. Pincus T, Callahan LF. Taking mortality in rheumatoid arthritis seriously–predictive markers, socioeconomic status and comorbidity. J Rheumatol. 1986; 13:841–5.

103. Callahan LF, Pincus T. Formal education level as a significant marker of clinical status in rheumatoid arthritis. Arthritis Rheum. 1988; 31:1346–57.

104. Callahan LF, Smith WJ, Pincus T. Self-report questionnaires in five rheumatic diseases: comparisons of health status constructs and associations with formal education level. Arthritis Care Res. 1989; 2:122–31.

105. Kim HS, Jung UH, Lee H, Kim SK, Lee H, Choe JY, et al. Effect of formal education level on measurement of rheumatoid arthritis disease activity. J Rheum Dis. 2015; 22:231–7.

106. Pincus T, Amara I, Segurado OG, Bergman M, Koch GG. 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; 35:201–5.

107. Pincus T, Furer V, Keystone E, Yazici Y, Bergman MJ, Luijtens K. RAPID3 (Routine Assessment of Patient Index Data 3) severity categories and response criteria: Similar results to DAS28 (Disease Activity Score) and CDAI (Clinical Disease Activity Index) in the RAPID 1 (Rheumatoid Arthritis Prevention of Structural Damage) clinical trial of certolizumab pegol. Arthritis Care Res (Hoboken). 2011; 63:1142–9.

108. Pincus T, Strand V, Koch G, Amara I, Crawford B, Wolfe F, et al. An index of the three core data set patient questionnaire measures distinguishes efficacy of active treatment from that of 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; 48:625–30.

109. Pincus T, Chung C, Segurado OG, Amara I, Koch GG. An index of patient 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.

110. Hart LE, Tugwell P, Buchanan WW, Norman GR, Grace EM, Southwell D. Grading of tenderness as a source of interrater error in the Ritchie articular index. J Rheumatol. 1985; 12:716–7.

111. Lewis PA, O'Sullivan MM, Rumfeld WR, Coles EC, Jessop JD. Significant changes in Ritchie scores. Br J Rheumatol. 1988; 27:32–6.

112. Scott DL, Choy EH, Greeves A, Isenberg D, Kassinor D, Rankin E, et al. Standardising joint assessment in rheumatoid arthritis. Clin Rheumatol. 1996; 15:579–82.

113. Pincus T, Castrejón I. Are patient self-report questionnaires as “scientific” as biomarkers in “treat-to-target” and prognosis in rheumatoid arthritis? Curr Pharm Des. 2015; 21:241–56.

114. Pincus T. RAPID3, an index of only 3 patient self-report core data set measures, but not ESR, recognizes incomplete responses to methotrexate in usual care of patients with rheumatoid arthritis. Bull Hosp Jt Dis. 2013; 71:117–20.

115. Castrejón I, Dougados M, Combe B, Guillemin F, Fautrel B, Pincus T. Can remission in rheumatoid arthritis be assessed without laboratory tests or a formal joint count? possible remission criteria based on a self-report RAPID3 score and careful joint examination in the ESPOIR cohort. J Rheumatol. 2013; 40:386–93.

116. Castrejón I, Bergman MJ, Pincus T. MDHAQ/RAPID3 to recognize improvement over 2 months in usual care of patients with osteoarthritis, systemic lupus erythematosus, spondyloarthropathy, and gout, as well as rheumatoid arthritis. J Clin Rheumatol. 2013; 19:169–74.

117. Askanase AD, Castrejón I, Pincus T. Quantitative data for care of patients with systemic lupus erythematosus in usual clinical settings: a patient Multidimensional Health Assessment Questionnaire and physician estimate of noninflammatory symptoms. J Rheumatol. 2011; 38:1309–16.

118. Danve A, Reddy A, Vakil-Gilani K, Garg N, Dinno A, Deodhar A. Routine Assessment of Patient Index Data 3 score (RAPID3) correlates well with Bath Ankylosing Spondylitis Disease Activity index (BASDAI) in the assessment of disease activity and monitoring progression of axial spondyloarthritis. Clin Rheumatol. 2015; 34:117–24.

119. Cinar M, Yilmaz S, Cinar FI, Koca SS, Erdem H, Pay S, et al. A patient-reported outcome measures-based composite index (RAPID3) for the assessment of disease activity in ankylosing spondylitis. Rheumatol Int. 2015; 35:1575–80.

120. Michelsen B, Fiane R, Diamantopoulos AP, Soldal DM, Hansen IJ, Sokka T, et al. A comparison of disease burden in rheumatoid arthritis, psoriatic arthritis and axial spondyloarthritis. PLoS One. 2015; 10:e0123582.

121. Park SH, Choe JY, Kim SK, Lee H, Castrejón I, Pincus T. Routine Assessment of Patient Index Data (RAPID3) and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) scores yield similar information in 85 Korean patients with ankylosing spondylitis seen in usual clinical care. J Clin Rheumatol. 2015; 21:300–4.

122. Annapureddy N, Elsallabi O, Baker J, Sreih AG. Patient-reported outcomes in ANCA-associated vasculitis. A comparison between Birmingham Vasculitis Activity Score and routine assessment of patient index data 3. Clin Rheumatol. 2016; 35:395–400.

123. 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; 35:819–27.

Figure 1.

Standard composite treatment effect (in standard units). Meta-analysis of 66 clinical trials reported in 1990 concerning the efficacy of DMARDs in the treatment of RA [91]. This meta-analysis included 117 treatment groups: 11 for anti-malarial drugs (e.g., hydroxychloroquine), 23 for auranofin, 29 for injectable gold, 7 for methotrexate, 19 for d-penicill-amine, 6 for sulfasalazine, and 22 for placebo. All drugs have greater efficacy than placebo in the management of RA, determined according to a composite of grip strength (a measure of effectiveness of grip), TJC, and ESR, adjusted for disease duration, trial length, initial tender joint count, and blinding. In these analyses, no significant differences were seen between sulfasalazine, d-penicillamine, methotrexate, and injectable gold (From Felson et al. The comparative efficacy and toxicity of second-line drugs in rheumatoid arthritis. Results of two metaanalyses. Arthritis Rheum 1990;33:1449-61; with per-mission) [63]. DMARDs: disease-modifying anti-rheumatic drugs, RA: rheumatoid arthritis, TJC: tender joint count, AUR: auranofin, AntiM: antimalarial drug, AZA: azathioprine, MTX: methotrexate, DPen: d-penicillamine, SSZ: sulfasalazine, ESR: erythrocyte sedimentation rate.

Figure 2.

(A) Estimated continuation of all 1,083 courses of second line therapies in 532 patients with rheumatoid arthritis over 60 months. Differences between methotrexate and all other drugs, as well as between oral gold (auranofin) and all other drugs, are statistically significant (p＜0.001), while differences among other drugs are not significant. (B) Estimated continuation of 477 courses of the initial second line therapy used in the same 532 patients over 12 months. Differences between methotrexate versus oral gold (auranofin) are not statistically significant, and are considerably less apparent than in (A), in which estimated continuation was studied for all courses over 60 months (Pincus et al. Longterm drug therapy for rheumatoid arthritis in seven rheumatology private practices: II. Second line drugs and prednisone. J Rheumatol 1992;19:1885-94) [64].

Figure 3.

The multidimensional health assessment questionnaire (MDHAQ). (From Pincus et al. RAPID3 (Routine Assessment of Patient Index Data 3), a rheumatoid arthritis index without formal joint counts for routine care: proposed severity categories compared to disease activity score and clinical disease activity index categories. J Rheumatol 2008;35:2136-47) [83].

Figure 4.

Time to score various rheumatoid arthritis indices in seconds, including 28 joint count, health assessment questionnaire-disability index (HAQ-DI), disease activity score 28 (DAS28), clinical disease activity index (CDAI), routine assessment of patient index data (RAPID3) scores 0∼10, RAPID3 scored 0∼30 (Pincus et al. RAPID3 (Routine Assessment of Patient Index Data) on an MDHAQ (Multidimensional Health Assessment Questionnaire): agreement with DAS28 (Disease Activity Score) and CDAI (Clinical Disease Activity Index) activity categories, scored in five versus more than ninety seconds. Arthritis Care Res (Hoboken) 2010;62:181-9) [60].

Figure 5.

Nine to ten year survival according to quantitative markers in three chronic diseases, rheumatoid arthritis, Hodgkin's disease, coronary artery disease. Adapted from Figure 1 in the article of Pincus and Callahan (J Rheumatol 1986;13:841-5) [102].

Figure 6.

Significance of 8 variables as predictors of mortality, in a review of 84 reports concerning mortality in rheumatoid arthritis, 53 cohorts presented predictors of mortality. For each variable, n=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 not significant (white). ESR: erythrocyte sedimentation rate. Adapted from Figure 2 in the article of Sokka et al. (Clin Exp Rheumatol 2008;26(5 Suppl 51):S35-61) [100].

Figure 7.

Relative efficiencies of 7 rheumatoid arthritis Core Data Set measures to distinguish active from control treatments in 9 clinical trials, involving methotrexate, leflunomide, placebo, infliximab, adalimumab, and abatacept according to arithmetic and percentage changes. TJC: tender joint count, SJC: swollen joint count, DOCGL: physician global assessment, ESR: erythrocyte sedimentation rate, CRP: C-reactive protein, HAQ-FN: health assessment questionnaire-function, PATGL: patient global estimate of status, MTX: methotrexate, PBO: placebo, LEF: leflunomide, INF: infliximab, ADA: adalimumab, ABA: abatacept. Adapted from Figure 3 in the article of Pincus et al. (Clin Exp Rheumatol 2014;32 Suppl 85(5):S-47-54) [55].

Figure 8.

Spearman correlations of routine assessment of patient index data 3 (RAPID3) scores with (A, C) the disease activity score 28 (DAS28) and (B, D) clinical disease activity index (CDAI) in (A, B) the rheumatoid arthritis prevention of structural damage 1 (RAPID1) clinical trial of certolizumab pegol in 982 patients at 52 weeks and (C, D) in 285 patients with RA seen in usual clinical care. Adapted from (A, B) Figure 1 in the article of Pincus et al. (Arthritis Care Res (Hoboken) 2011;63:1142-9) [107] and (C, D) Figure 3 in the article of Pincus et al. (Bull NYU Hosp Jt Dis 2009;67:211-25) [90].

Figure 9.

Improvement in routine assessment of patient index data 3 (RAPID3) scores over 2 months in patients with 5 rheumatic diseases, rheumatoid arthritis (RA), osteoarthritis (OA), systemic lupus erythematosus (SLE), spondyloarthritis (SpA), gout. CI: confidence interval. Adapted from Figure 1 in the article of Castrejón et al. (J Clin Rheumatol 2013;19:169-74) [116].

Table 1.

Comparison of a “biomedical model” and a “biopsychosocial model” of disease

Variable	Biomedical model	Biopsychosocial model
Cause	Each disease has a single “cause”	Disease etiology is multifactorial: external pathogens, toxins, and internal host milieu, genes, behavior, social support
Diagnosis	Identified primarily through laboratory tests, radiographs, scans; information from patients of value primarily (or only) to suggest appropriate tests	A patient medical history provides 50%∼90% of the information needed to make many, perhaps most, diagnoses
Assessment of status and prognosis	Also established most accurately on the basis of information from high technology sources, rather than from a patient	Information provided by a patient often is the most valuable data to assess clinical status and establish a prognosis
Results of treatment	Involves only actions of health professionals, e.g., medications, surgery	Must involve patient, family, social structure
Role of health professionals and patients in general	Health and disease outcomes are determined primarily by decisions and actions of health	Health and outcomes of chronic diseases are determined as much by actions of individual
health and disease outcomes	professionals	patient as by health professionals

Table 2.

Some limitations of a biomedical model approach to rheumatoid arthritis

1) Some limitations of laboratory tests in RA
- a. Rheumatoid factor positive in 69% – negative in 31% of patients
- b. ACPA positive in 67% – negative in 33% of patients
- c. ESR and CRP normal in ＞40% of patients at presentation
- d. 5% of normal people have positive test for rheumatoid factor or ACPA – more people who do not have RA are positive than RA patients
- e. Laboratory tests not available at clinical visit in most settings
- f. Patient questionnaire physical function scores more significant in prognosis of work disability and mortality
2) Some limitations of radiographs in RA
- a. Not as sensitive as ultrasound, MRI
- b. Treatment should occur when normal – prior to damage
- c. Quantitative scoring not feasible in routine clinical care
- d. Patient questionnaire physical function scores more significant in prognosis of work disability and mortality
3) Some limitations of joint counts in RA
- a. Poorly reproducible – need for same observer at each visit, excluding other health professionals
- b. Similar or lower relative efficiencies than global and patient measures to document differences between active and control treatments in clinical trials
- c. Not as sensitive to detect inflammatory activity as ultrasound
- d. Most visits to a rheumatologist include a careful joint examination, but do not include a formal joint count
4) Limitations of clinical trials in RA (1) Pragmatic limitations
- a. Relatively short time frame in chronic diseases – too short to identify important clinical benefits or possible loss of efficacy over time
- b. Inclusion and exclusion criteria restrict eligibility to fewer than 10% of patients
- c. Statistical significance may not be clinically significant and vice versa
- d. Important variables affecting outcomes such as socioeconomic status usually ignored in reporting of clinical trial results
- e. Inflexible dosage schedules and restriction of concomitant medications
- f. Surrogate markers and indices may be suboptimal to detect changes in clinical status (2) Intrinsic limitations
- g. Design can greatly influence results – availability of a control group does not eliminate bias
- h. Data are reported in groups – ignore possible substantial variation in individual patients
- i. Risk/benefit of a therapy interpreted differently by different patients – all may be “correct”
- j. Loss of a “placebo effect” in a clinical trial

RA: rheumatoid arthritis, ACPA: anti-cyclic citrullinated peptide antibodies, ESR: erythrocyte sedimentation rate, CRP: C-reactive protein, MRI: magnetic resonance.

Table 3.

Comparison of HAQ and MDHAQ

Variable	HAQ	MDHAQ
First report	1980	1999
Patient completion	5∼10 minutes	5∼10 minutes
Number of activities of daily living	20	10
Pain VAS	10 cm line	21 circles
Patient global VAS	10 cm line	21 circles
Fatigue	No	21 circles
Psychological variables: sleep, anxiety, depression	No	3-HAQ format
Review of systems	No	60 symptoms
Medical history	No	Yes
Demographic data	No	Yes
Social history	No	Yes
Scoring templates	No	Yes
MD scan (“eyeball”)	30 seconds	5 seconds
Time to score	41.8 seconds	4.5 seconds
Time to score index of 3 measures	Not available	9.5 seconds

HAQ: health assessment questionnaire, MDHAQ: multidimensional health assessment questionnaire, VAS: visual analog scales, MD scan: Time for physician to scan questionnaire.

Table 4.

Value of patient questionnaire data to overcome limitations of biomedical model approach in prognosis and monitoring of RA

1. Physical function scores on MDHAQ and other questionnaires are far more significant than radiographs or laboratory tests in the prognosis of severe outcomes in RA, including work disability, costs, joint replacement surgery and premature death [33-35]

2. Formal education level, a surrogate for patient actions in disease, are as significant in the prognosis of mortality and more significant than age or duration of disease in RA status [101-105]

3. Individual patient self-report measures of physical function, pain, and patient global estimate of status, and RAPID3, are as efficient as joint counts, laboratory tests to distinguish active from control treatments in clinical trials [54,55,106]

4. Patient questionnaire scores, including RAPID3, are correlated significantly with DAS28 and CDAI in clinical trials [82,107-109] and clinical care [60,83]

5. MDHAQ scores are more reproducible than formal joint counts by physicians [16,51,52,110-113]

6. Patient questionnaire scores are more likely to be abnormal at baseline [8] and to document incomplete response to methotrexate and initiation of biological agent in RA than laboratory tests [114]

7. Remission criteria based on RAPID3 are similar to ACR/EULAR Boolean and SDAI remission criteria [115]

8. RAPID3 is effective to document change in clinical status in all rheumatic diseases [116]

9. Continuation of courses of DMARDs is more accurately described by observational data from clinical care than by data from clinical trials [64]

10. A survey of rheumatologists and non-rheumatologists, indicated that a medical history is far more prominent in diagnosis and management decisions in RA than laboratory tests or ancillary studies, in contrast to other chronic diseases [26]

RA: rheumatoid arthritis, MDHAQ: multidimensional health assessment questionnaire, RAPID3: routine assessment of patient index data 3, DAS: disease activity score, CDAI: clinical disease activity index, ACR: American College of Rheumatology, EULAR: European League Against Rheumatism, SDAI: simplified disease activity index, DMARDs: disease-modifying anti-rheumatic drugs.

Table 5.

Correlations and test-retest reliability of rheumatoid arthritis measures and indices at two time points

Measure/Index	Spearman rho	Interclass correlation coefficient
TJC28	0.76	0.83
SJC28	0.74	0.78
Physician global	0.69	0.79
Patient global	0.80	0.78
Function	0.98	0.96
Pain	0.83	0.88
ESR	0.84	0.95
CRP	0.71	0.97
DAS28	0.85	0.85
SDAI	0.87	0.88
CDAI	0.89	0.89
RAPID3	0.88	0.90
RADAI	0.89	0.92

TJC: tender joint count, SJC: swollen joint count, ESR erythrocyte sedimentation rate, CRP: C-reactive protein, DAS disease activity score, SDAI: simplified disease activity index CDAI: clinical disease activity index, RAPID3: routine assessment of patient index data 3, RADAI: rheumatoid arthritis disease activity index.

From the article of Uhlig et al. Test-retest reliability of disease activity core set measures and indices in rheumatoid arthritis Ann Rheum Dis 2009;68:972-5 [52].

Table 6.

Median levels of all patients for ESR, 3 (0∼10) MDHAQ scores for physical function, pain and patient global estimate and composite RAPID3 scores at initiation of methotrexate 1996∼2001 and mean of 2.6 years later in: A. 30 incomplete responders initiating biologic agent, B. 63 “control” adequate responders continuing methotrexate

Variable	A. 30 incomplete responders		B. 63 adequate responders (“controls”)
Variable	MTX start	Biologic start	MTX start	Follow-up 6 2.6 years later (no biologic)
ESR (mm/hr)	28	18	24	16
MDHAQ-function (0∼10)	3.2	3.3	2.3	1.0
Pain (0∼10)	5.2	6.8	4.1	1.4
Patient global (0∼10)	5.5	5.5	4.2	0.9
RAPID3 (0∼30)	14.9	16.2	10.6	3.6

ESR: erythrocyte sedimentation rate, MDHAQ: multidimensional health assessment questionnaire, RAPID3: routine assessment of patient index data 3, MTX: methotrexate.

From the article of Pincus. RAPID3, an index of only 3 patient self-report core data set measures, but not ESR, recognizes incomplete responses to methotrexate in usual care of patients with rheumatoid arthritis. Bull Hosp Jt Dis 2013;71:117-20 [114].

Table 7.

Rheumatic diseases in which routine assessment of patient index data 3 (RAPID3) has been reported to be informative about patient status and/or change in status

Rheumatic disease	Reference
Systemic lupus	Askanase et al., 2011 [117]
erythematosus	Castrejon et al., 2013 [116]
Osteoarthritis	Castrejon et al., 2013 [116]
Ankylosing spondylitis	Castrejon et al., 2013 [116]
	Danve et al., 2015 [118]
	Cinar et al., 2015 [119]
	Michelsen et al., 2015 [120]
	Park et al., 2015 [121]
Psoriatic arthritis	Castrejon et al., 2013 [116]
Gout	Castrejon et al., 2013 [116]
Vasculitis	Annapureddy et al., 2015 [122]
Fibromyalgia	Callahan et al., 1989 [104]
	DeWalt et al., 2004 [86]
	Pincus et al., 2009 [123]
Other	Castrejon et al., 2013 [116]
	Pincus et al., 2009 [123]

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