ARAMIS: Arthritis, Rheumatism and Aging Medical Information Systems---Research Page

Musculoskeletal disability is the most prevalent of the major health problems of our aging population. Rheumatoid arthritis and osteoarthritis, compared with other chronic diseases, appear to make the greatest contribution to subsequent disability among the elderly. Rheumatoid arthritis and osteoarthritis and other musculoskeletal diseases pose special problems for analysis. Disease outcomes evolve over years, even decades, and randomized studies of short-term efficacy of single medical or surgical treatments cannot address the questions of long-term outcomes. For their study, therefore, longitudinal, prospective, primary data sets and multidisciplinary investigation are required to evaluate quality of life, resource use, costs, work force disability, morbidity and mortality, and other diverse outcomes.

Over the past 27 years, ARAMIS has assembled the long-term data sets, the underlying foundation, outcome assessment techniques, the large numbers of patients, the multi-disciplinary research teatm, and the institutional collaborations necessary to study these outcomes.

Three major models underlie the current ARAMIS research projects:

1. Rheumatoid Arthritis

There are numerous factors potentially leading to poor outcomes in rheumatoid arthritis. Patient factors, exemplified by genetic haplotypes, plus an external event or perturbation of unknown kind, lead to the disease condition termed rheumatoid arthritis. The intensity of inflammation in and around the joints and the duration of this inflammation together form a product of joint damage which leads to poor outcomes of pain, disability, and premature mortality. Specific medicines such as disease-modifying anti-rheumatic drugs and prednisone are employed to reduce the intensity of the inflammation and may or may not be successful in this regard. The duration of inflammation is influenced by the degree to which the suppression of inflammation strategy is consistently followed and upon the sequences of treatment which optimally provide suppression. The ability to follow the strategy is influenced by the side effects of the therapies and can directly lead to poor outcomes as well. Following joint destruction, total knee replacement, total hip replacement, and other procedures may be employed appropriately and effectively, or not.

Outcome also is conditioned upon sex, race, age and other patient characteristics which influence the intensity and duration of inflammation. Self-management activities, including exercise, other lifestyle factors, and development and maintenance of personal self-efficacy contribute to improved outcomes or, when not employed appropriately, to poor outcomes, either directly or through associated comorbid diseases (heart attacks, chronic obstructive pulmonary disease, stroke, others) which themselves result in part from risk factors under personal control.

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2. Osteoarthritis

Musculoskeletal disability and osteoarthritis increase with increasing age. ARAMIS studies recognize the inconstant correlation between clinical osteoarthritis as assessed radiologically and clinical outcomes of pain and disability as experienced by the patient. There are thus two main sequences which may end in poor outcomes. The first is traditional, in which patient characteristics, biological factors and risk factors such as obesity and injuries accelerate the rate of degeneration of articular cartilage. Over time, this process results in clinical osteoarthritis. The progress of the clinical osteoarthritis might be affected positively or negatively by effects of the treatment upon cartilage and by the side effects of therapy which might allow or not allow consistent application of a regimen. Side effects can also contribute directly to poor outcomes. Reconstruction of failed joints as in total knee replacement or total hip replacement may be appropriately employed or not.

In addition, patient characteristics and a larger set of risk factors including a sedentary life, obesity, injuries, and other lifestyle factors including psychological factors, determine the rate of musculoskeletal aging or atrophy. The musculoskeletal aging process is related to time, but also includes a significant element of disuse atrophy. Soft tissue injuries and impairments add to progression of this syndrome. As this process progresses, there may be failure of self-management approaches including exercise, weight control, maintenance of personal self-efficacy, smoking and other lifestyle factors, and such self-management failure may operate directly to accelerate musculoskeletal aging/atrophy or may act through causation of heart attack, stroke, obstructive pulmonary disease, or other comorbid conditions which add to a poor outcome experience.

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3. The Therapeutic Segment and the Concept of Cumulative Outcomes

Outcome assessment in the rheumatic diseases has traditionally used endpoints at a single point in time as the primary dependent variable and has analyzed treatment effects after fixed treatment durations, such as one year. The ultimate clinical goal, however, is to improve an outcome (e.g. disability) over the entire course of the illness. And, treatment courses do not conveniently least for a fixed period of time. A typical therapeutic segment has a period of waning response which ultimately results in a treatment change. Treatment of a RA patient over 25 years is conveniently thought of as a series of 5 to 15 therapeutic segments involving DMARD deployment alone or in combination. The segment begins with a DMARD treatment change. It may be characterized rather concisely as having duration, an area-under-the-curve for each dependent variable (e.g., disability) consisting of the area of improvement minus the area of progression, an initial value, a final value, and the average disability improvement/worsening per year of the segment.

Cumulative disability under the curve may be expressed in absolute terms or relative to the baseline represented by the initial disability level. Therapeutic segments of course are different for different individuals, and the descriptive variables have distributions and statistical characteristics. "Modifiers" exist which predict different segment characteristics for a population or for an individual, such as age, prior segment, number in sequence, prior responses, prior toxicities, initial disability, and others. The concept of therapeutic segments breaks RA treatment down to discrete chunks, and then enables modeling of optional treatment over an entire disease course to take place.