Rheumatoid Arthritis (algorithm)

Rheumatoid Arthritis (algorithm)

Contact: Natasja van Schoor
External contacts: Hennie Raterman, Marieke ter Wee


Rheumatoid arthritis (RA) is a chronic inflammatory disease affecting approximately one percent of the general population. Studies in the aging RA patient are not very common, although studies report prevalences up to 3.5% in elderly RA patients.1
The manifestations extend beyond a symmetrical inflammation of small joints and accumulating evidence shows RA to be associated with osteoporosis and an increased risk of death, largely due to excess cardiovascular disease (CVD).2-4The identification of patients with rheumatoid arthritis in the LASA population will enable us to study whether RA elderly also suffer from a large scale comorbid burden.

Measurement instruments in LASA

RA patients are identified by using different algorithms for older people participating in LASA at time point C (1995/96). These algorithms use data of interviews with older people and information obtained from the general practitioner. In this way possible or definite RA patients can be identified out of the total group who participated in LASA at time point C. To get a more reliable diagnosis of RA, a rheumatologist together with two PhD students are verifying diagnoses in a sample of (approximately 500 elderly) by visiting the general practitioner. In this way the results obtained by the different algorithms can be compared and validated by the verified diagnosis. The final aim is to construct an algorithm with a good reliability. Patients are selected out of the still participating respondents, i.e. persons who were invited in the most recent wave of LASA (2011/2012). The final algorithm is expected early 2013.

Availability of information per wave


Rheumatoid arthritis (algorithm)


¹ More information about the LASA data collection waves is available here.

* C=under construction
2B=baseline second cohort;
3B=baseline third cohort;
MB=migrants: baseline first cohort

Future research topics

As mentioned above, the identification of RA patients will enable us in the future to answer research questions in a cross sectional and observational/longitudinal manner.
Possible research questions after identification of RA patients involve estimations of prevalences and incidences of cardiovascular disease, cardiovascular mortality and identification of (modifiable) predictors and risk factors for cardiovascular disease in RA elderly as compared to controls. Moreover, estimations of abnormal bone mineral density can be calculated and identification of risk factors for low mineral density or vertebral fractures in RA elderly compared to controls.


  1. Dahaghin S, Bierma-Zeinstra SM, Reijman M, et al. Prevalence and determinants of one month hand pain and hand related disability in the elderly (Rotterdam study). Ann Rheum Dis 2005;64:99-104.
  2. Peters MJ, van H, V, Voskuyl AE, et al. Does rheumatoid arthritis equal diabetes mellitus as an independent risk factor for cardiovascular disease? A prospective study. Arthritis Rheum 2009;61:1571-9.
  3. Gabriel SE. Cardiovascular morbidity and mortality in rheumatoid arthritis. Am J Med 2008;121:S9-14.
  4. Haugeberg G, Uhlig T, Falch JA, et al. Bone mineral density and frequency of osteoporosis in female patients with rheumatoid arthritis: results from 394 patients in the Oslo County Rheumatoid Arthritis register. Arthritis Rheum 2000;43:522-30.

Date of last update: July 28, 2015