STudying Ageing in Rheumatic Diseases (STAR)

NCT ID: NCT05463666

Last Updated: 2025-10-01

Basic Information

• Recruitment Status: ACTIVE_NOT_RECRUITING
• Total Enrollment: 840 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2022-12-01
• Study Completion Date: 2027-12-31

Brief Summary

The primary objective of the STAR study is to investigate how measures of disease activity and measures for cognition, physical activity and performance behave in ageing population controls and patients with rheumatoid arthritis (RA). If an differential effect of age on outcome over time is apparent, the presence of an inclination point will be assessed. The secondary objective is to investigate additional factors (e.g. lifestyle factors) that might explain any differences between ageing controls and RA patients.

The STAR study is an observational cross-sectional matched case-control study including 420 RA patients and 420 population controls between 55-85 years of age, stratified by five year intervals. All participants will complete generic and RA-specific questionnaires. A subset of 180 participants will be visiting the research center for physical examination and performance tests. Expected outcomes include practical age-specific reference curves that will be constructed for a selection of outcomes (e.g. DAS28).

It is expected that as RA is characterized by tender and painful joints, e.g. the number of tender joints has a higher starting point in RA patients than in the general population. This will most likely increase in both groups with age, although the general population may catch up at an older age. Measures of cognitive status may show a steeper decline with age in RA patients compared to the general population. Measures of physical activity and performance will presumably have a worse starting point in RA patients than in the general population, and might show a steep decline with age. The general population might however catch up with the patients with RA. Most probably, age will not be the only factor explaining 'worse' outcomes in both RA patients and the general population. Other factors such as lifestyle factors (e.g. smoking, diet, BMI, occupation) and comorbidities will probably play a role.

Detailed Description

Rationale:

As the population ages and the lifespan of people with rheumatoid arthritis (RA) extends, more insight into the effect of ageing on RA is needed. Currently, it is unclear whether ageing has an impact on the interpretation of disease activity measures, specifically the (components of the) DAS28. In addition, the effect of RA on cognitive function, physical activity and performance, three outcomes that will influence treatment decisions, is underinvestigated.

Objectives:

The objectives of this study are to gain insight into the effect of ageing on the result of disease activity measures, decline in cognition, physical activity and performance. A first step towards such understanding is construction of population reference curves in function of age. These curves can be used to discern whether the change in an outcome measure can be explained by age. If age is the only important factor, a similar change in the age-specific curve of both the population and RA patients would be observed. In case of differences in the curve inclination point, it is of interest exploring variables explaining such differences (e.g. lifestyle factors).

Study design:

Observational cross-sectional matched case-control study.

Study population:

In total, 420 RA patients and 420 population controls between 55 and 85 years of age, stratified according to age at five year intervals, will be included.

Main study parameters/endpoints:

A total of 840 participants will complete generic and RA-specific questionnaires. Out of these 840 participants, 180 (21%) will also visit the research center for a physical examination and performance tests. Reference curves will be constructed according to the method described by Wright and Royston for among others components of the DAS28. In case of a difference between population controls and RA patients, the investigators will further explore to gain insight which variables explain the difference.

Statistical analyses:

Total test scores will be computed for each questionnaire. Subsequently, descriptive statistics i.e. the mean, SD and range of each questionnaire will compared. Continuous determinants including biomarkers (e.g. ESR and CRP) will be presented as either mean with corresponding standard deviation for normally and median with corresponding inter-quartile range for non-normally distributed variables. Dichotomous determinants, including fulfillment of criteria, will be presented as N (%).

For the primary objective, reference curves will be developed by using data of the population controls by the method described by Wright and Royston (modelling variables as fractional polynomial functions of age). By including 70 patients per 5-year interval, reference curves can reliably be constructed. Reference curves will, if needed, be adjusted for comorbidity level and gender, when this adjustment improves substantially the fit of the data; otherwise, the model will be kept as simple as possible, which also contributes to their more feasible application in practice. The data from RA patients will be 'plotted' in population reference curves.

For the secondary objective, exploratory analyses of factors associated with ≥2 standard deviations (SD) (or Z-scores) change from the population average, will be performed for the outcomes of interest (disease activity measures, cognition, physical activity and performance). Univariate analysis is used for variable selection: logistic regression techniques (after checking assumptions) will be applied to test the association between age and other covariates (example: RA disease duration, lifestyle factors or differences in socio-economic background) on the outcomes (≥2 SD below reference value) of interest. A p-value below 0.05 is set to indicate a statistically significant difference. Next multivariable regression analyses will be performed with the same outcomes while forcing age into the models and further including all univariately significant covariates in a hierarchical approach (after checking co-linearity).

Nature and extent of the burden and risks associated with participation, benefit and group relatedness:

All participants need to complete generic and RA-specific questionnaires. Patients > 80 years who are physically unable to complete the whole study procedure (i.e. geriatric patients who are considered frail by the rheumatologist / researcher and/or patient itself), are allowed to undergo only part of the study measurements / questionnaires.

All 180 patients and controls will be seen in one study visit by 1-2 trained research assistant(s), using standardized protocols. Participants will undergo a physical examination, physical and laboratory (three blood samples; one venepuncture) testing.

Conditions

Rheumatoid Arthritis

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

Population controls

Participants between 55 and 85 years of age without a diagnosis of RA, or other inflammatory RMD (osteoarthritis allowed). Controls \> 80 years who are physically unable to complete the whole study procedure, are allowed to undergo only part of the study measurements.

No interventions assigned to this group

RA patients

Participants between 55 and 85 years of age with a diagnosis of RA by the treating rheumatologist. Patients \> 80 years who are physically unable to complete the whole study procedure, are allowed to undergo only part of the study measurements.

Rheumatoid arthritis

Intervention Type: OTHER

A diagnosis of rheumatoid arthritis.

Interventions

Rheumatoid arthritis

A diagnosis of rheumatoid arthritis.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Age between 55-85 years at baseline.
• Diagnosis of RA by treating rheumatologist.

• Age between 55-85 years at baseline.
• No diagnosis of RA, or other inflammatory RMD (osteoarthritis allowed).

Exclusion Criteria

• Subject is the spouse/partner of the included RA patient.
• Have severe comorbidity and the treating rheumatologist and/or research team decides they should not be included in the study because of health reasons.
• A diagnosis of dementia or mental incompetency is always reason for exclusion.
• Persons of whom the research team estimates that his/her life expectancy is less than 2 years.
• Do not understand the Dutch language and/or are notable to understand the study information.

• Minimum Eligible Age: 55 Years
• Maximum Eligible Age: 85 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Zuyderland Medical Centre

OTHER

Sponsor Role: collaborator

Maastricht University Medical Center

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Marloes van Onna, Dr

Role: PRINCIPAL_INVESTIGATOR

Maastricht University Medical Center

Locations

Maastricht UMC+

Maastricht, Limburg, Netherlands

Countries

Netherlands

References

Royston, P., & Wright, E. M. (1998). A Method for Estimating Age-Specific Reference Intervals ('Normal Ranges') Based on Fractional Polynomials and Exponential Transformation. Journal of the Royal Statistical Society. Series A (Statistics in Society), 161(1), 79-101. http://www.jstor.org/stable/2983555

Reference Type: BACKGROUND

Other Identifiers

NL71972.068.19

Identifier Type: -

Identifier Source: org_study_id