The authors are now sufficiently senior to recall the early 1970s, at which time rheumatologists were considered elite members of the medical community in their zealous search for evidence in clinical care. Rheumatology fellows were using terms such as “sensitivity,” “specificity,” “true negatives” and “false positives” more than trainees in other fields. This emphasis may have resulted from an important difference in rheumatic diseases versus many other diseases – the absence of a single “gold standard” measure for diagnosis, prognosis, management and assessment of outcomes in each individual patient with a given diagnosis. Trainees in cardiology, endocrinology, nephrology and other fields had a lesser interest in complexities of clinical measures as they often had a definitive “gold standard,” such as sustained elevated blood pressure in hypertension, sustained elevated glucose in diabetes mellitus, or a definitive biopsy in lymphoma, to guide clinical care.

The discovery in 1948 of rheumatoid factor [1] and the LE cell phenomenon [2] gave hope that a single gold standard biomarker would be available similarly for diagnosis, prognosis, management and assessment of outcomes in rheumatoid arthritis (RA) or systemic lupus erythematosus (SLE), the two most common inflammatory rheumatic diseases. However, despite extensive clinical research, that hope has not been met. Rheumatoid factor was described as present in 70 % of patients seen with RA in the initial report of Rose, Ragan et al. [1], virtually identical to 69 % in a recent meta-analysis [3]. Furthermore, rheumatoid factor is found in about 5–10 % of people in the general population [3], including patients with chronic infections and no apparent disease at all. Antibodies to citrullinated proteins (anti-CCP or ACPA) show increased specificity for RA, as they are seen in fewer than 5 % of individuals in the normal population; however, these antibodies are found in only 67 % of RA patients [3], quite comparable to rheumatoid factor.

Further biomarkers have been sought in RA based on the erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP). As with rheumatoid factor and ACPA, these measures are abnormal in the majority of patients. However, at this time, at least 40 % of patients do not show elevated values [4], although this proportion has declined from about 80 % in the early 80s to approximately 55 % in recent years [5], as RA patient clinical status has been improving [6]. The absence of a gold standard laboratory biomarker such as serum glucose, cholesterol, creatinine, hemoglobin or hemoglobin A1c, therefore, distinguishes rheumatic diseases from many chronic diseases for clinical trials, other clinical research and routine clinical care.

In the absence of “gold standard” laboratory tests or other quantitative biomarkers such as blood pressure or bone densitometry scores, pooled indices are required to assess quantitatively clinical status and responses to therapy in individual patients with a rheumatic diagnosis. The most successful pooled indices are seen in RA, based on a core data set of 7 measures: 3 recorded by a physician from a physical examination, i.e., tender joint count, swollen joint count, and physician global estimate of status; 3 based on a patient self-report questionnaire – physical function, pain, and patient global estimate of status; and only 1 laboratory test, ESR or CRP [7]. Patients who may have many swollen joints and low pain levels, or a reciprocal pattern, are assessed according to an identical quantitative index. The core data set has been used for more than 2 decades and may be regarded as one of the major advances in rheumatology, prerequisite for the better status of patients at this time compared with previous decades [6].

The most prominent traditional index for RA has been the disease activity score (DAS) [8] and DAS28 [9], based on 4 measures: tender joint count, swollen joint count, ESR or CRP, and patient global estimate of status. The limitations of the DAS28 include a need for a laboratory test [ESR or CRP], which often is not available at the time of the visit, and is normal in up to 40 % of patients [4], and complex calculations, although easily accomplished at an excellent website. These limitations are overcome by the clinical disease activity index (CDAI) [10], which is simply a total of 4 measures: 28 tender joint count, 28 swollen joint count, and physician and patient global estimates 10 cm visual analog scales (VAS), total 0–76. An index of only the 3 patient self-report measures, known as routine assessment of patient index data (RAPID3), includes three 0–10 scales for physical function, pain and patient estimate of global status, total 0–30 [11]. Levels have been established for high, moderate, low activity or severity of each index [12]; an index of only patient measures is not as specific to assess disease activity, since it might be sensitive to joint damage and chronic pain, but the other indices also are affected, though less so [13].

In analyses of clinical trials, essentially any 3 or 4 core data set measures will give very similar results, as was shown in analyses to establish remission criteria for RA [14]. Some rheumatologists support use of the simplest measure, RAPID3, as the patient does 95 % of the work and measurement involves the same single observer – the patient – at all visits. At the same time, other rheumatologists, particularly outside the USA, feel uncomfortable with only patient measures and include a CDAI or a DAS28.

Indices exist for many other rheumatic diseases. In general, all include at least one measure from a physical examination and from patient self-report questionnaire, as well as a laboratory test. All are more complex than a “gold standard” measure. However, it also is possible that clinical decisions based on a gold standard measure may oversimplify what is needed for optimal patient care in chronic diseases. For example, functional status is as significant as ejection fraction to predict 3-year hospitalizations and deaths in congestive heart failure [15], CD4/CD8 ratios and other AIDS-specific measures to predict 3-year mortality in AIDS [16], and physiologic data and comorbidities to predict 1-year mortality in hospitalized elder patients [17]. Therefore, the importance of these measures may extend beyond rheumatology.

Some indices in rheumatology may be insensitive to clinical changes, which may account in part for some of the limitations in clinical trials. If an index includes, say, 10 measures, only 2 of which may change substantially and the others not at all, the index may indicate no change when an important clinical change has occurred in the 2 measures. Ironically, criteria for psychometric validation of indices based on statistical tools such as Cronbach’s alpha and convergent validity generally may reduce sensitivity to change. Such sensitivity often is greatest with simple 10 cm visual analog scales (VAS). Nonetheless, it is essential to have an index for diseases in which certain clinical manifestations may vary widely and be prominent in some patients and absent in others, as noted for joint swelling and pain for RA.

A survey was conducted in which 313 physicians, approximately half of whom were rheumatologists and half non-rheumatologists, estimated the relative importance of 5 elements of the clinical encounter – vital signs, patient history, physical examination, laboratory tests and ancillary studies (imaging, biopsy, endoscopy, etc.) – in clinical decisions in 8 chronic diseases: congestive heart failure (CHF), diabetes mellitus, hypercholesterolemia, hypertension, lymphoma, pulmonary fibrosis, rheumatoid arthritis, and ulcerative colitis. The response options were 1–100 % in 5 equally divided intervals [18].

As expected, vital signs were most prominent in hypertension; laboratory tests were most prominent for diabetes and hyperlipidemia; and ancillary studies were most prominent for lymphoma, pulmonary fibrosis, ulcerative colitis, and congestive heart failure (Figure 1) [18]. RA was the only one of the 8 chronic conditions in which a patient history and physical examination accounted for more than 50 % of the information required for diagnosis and management (the total could be higher than 100 % due to “ties”) [18]. These data provide evidence that the clinical encounter in rheumatology practice differs substantially from that in other subspecialties.

The results of this survey are reflected in the 7 items of the RA core data set, which includes 3 items from a patient questionnaire, 3 from a physical examination, and 1 laboratory test. A patient self-report questionnaire may be regarded as providing information for the patient history as quantitative data rather than narrative non-quantitative descriptions. A formal joint count may be regarded as providing information from the physical examination as quantitative data rather than narrative non-quantitative descriptions. The RA indices therefore reflect patient history and physical examination in contrast to gold standard biomarkers, which are most prominent in clinical decisions in many other chronic diseases.

As noted above, when rheumatoid factor was discovered in 1948, it was initially thought that this autoantibody might be both causative and diagnostic, as with antinuclear antibodies in 1960 for SLE, HLA B27 in ankylosing spondylitis, and mutant gene associations in FMF and MEFV [19]. However, the information from the laboratory is relatively limited in rheumatic diseases, compared to lab tests in other subspecialties of internal medicine, such as hemoglobin A1c or serum glucose. Of course, laboratory markers are important in groups and as clues to pathogenesis and development of treatments. For example, the development of biological therapy for RA may be traced directly to identification of rheumatoid factor with subsequent recognition of cytokines.

Laboratory markers are not positive in 30–50 % of all patients with RA [20]. Furthermore, they are “abnormal” (false positive) in some individuals in the normal population who have other diseases or no disease whatsoever, unlike measures such as sustained hypertension or elevated glucose over time.

There is value in calculating the sensitivity and specificity and predictive value of different tests, for the probability of a certain disease being present in a patient. However, the individual patient who may not have any positive tests but has pathognomonic clinical features of a disease has a 100 % probability of having the disease, regardless of the test results. A test that is positive in only 70 % of patients has limited utility in daily practice, although most rheumatologists are not aware of this problem. It is sobering to remember that information from the laboratory in rheumatology is not pathognomic as in other diseases.

Structural changes are prominent in many rheumatic diseases, which might suggest an expectation that imaging would be most informative in diagnosis and management. Magnetic resonance imaging (MRI) and ultrasound certainly have improved sensitivity compared to plain radiographs. However, these new imaging modalities have not improved specificity. It is also worth remembering that the severe outcomes of RA such as work disability and premature death are predicted at far higher levels of significance by physical function on a patient questionnaire and by comorbidities than by hand radiographs [21].

Ironically, one possible limitation of studies to analyze radiographs as prognostic of severe outcomes may be that radiographic data are derived from the hand, whereas work disability and death are far more prominently influenced by large joints, particularly knees, but also hips and shoulders. For example, the initial series reported on mortality in RA indicated that 6 joints, 2 shoulders, 2 hips and 2 knees could predict mortality as effectively as all joints [22].

Furthermore, radiographic findings and clinical symptoms are often highly dissociated. For example, joint tenderness and radiographic findings have no correlation whatsoever [23]. Many people who may have 4+ osteoarthritis of the knee report no pain [24].

Rheumatic diseases may include biopsies in an effort to establish or feel more secure about a given diagnosis. However, many findings have little tissue specificity, such as the synovitis in RA which can be seen in many forms of inflammatory arthritis. While tissue specificity is seen in immune complexes in the kidneys or dermoepidermal junction in SLE, uric acid crystals in synovial fluid or tophi in gout, giant cells and in the vessel wall in giant cell arteritis and in Takayasu disease, lymphocyte infiltration in salivary gland biopsies in Sjogren’s syndrome, and bacilli in the intestinal wall in Whipple’s disease; it is difficult to further expand the scope of histopathology in rheumatic disease.

The major paradigm for advances in medical care over the last two centuries is a “biomedical model,” in which clinical observations are translated into quantitative high-technology data from laboratory tests and ancillary studies. Early examples include bacterial cultures and quantitative laboratory measures of organ function (e.g., liver, kidney function tests), which can be used to guide care as “gold standard’ measures for diagnosis, management, prognosis and assessment of outcomes in individual patients.

Over the last few decades there has been growing awareness that the traditional biomedical model, while spectacularly effective in acute disease and acute aspects of many chronic diseases, includes some significant limitations, particularly for chronic diseases. A classical statement was provided by George Engel, in a widely-read article in Science in 1978 [25]:

“I contend that all medicine is in crisis and, further, that medicine’s crisis derives from …adherence to a model of disease no longer adequate for its scientific tasks and social responsibilities…The biomedical model embraces both reductionism, the philosophic view that complex phenomena are ultimately derived from a single primary principle, and mind-body dualism, the doctrine that separates the mental from the somatic.”

We may contrast the classical biomedical model with a biopsychosocial model of disease, which appears relevant to rheumatic diseases as complementary to a biomedical model (Table 1).