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Abstract Number: 422

Correlation of RAPID3, DAS28 and CDAI in Disease Activity and Effects of Education Level and Co-Morbid Diseases on This Assesment in RA

Kubilay Sahin1, Yasar Karaaslan2,3, Zeynep Ozbalkan1, Ahmet Omma1 and Nesibe Yesil1, 1Rheumatology, Ankara Numune Education and Research Hospital, Ankara, Turkey, 2Rheumatology, Hitit University, Corum, Turkey, 3Ankara Numune Training and Research Hospital, Ankara, Turkey

Meeting: 2014 ACR/ARHP Annual Meeting

Keywords: Co-morbidities, Disease Activity, education and rheumatoid arthritis (RA)

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Session Information

Title: Rheumatoid Arthritis - Clinical Aspects: Novel Biomarkers and Other Measurements of Disease Activity

Session Type: Abstract Submissions (ACR)

Background/Purpose

RAPID3 is an activity index based on only the patient’s report in RA. It doesn’t require joint counts and it isn’t time consuming. Therefore this situation makes the index very attractive for physicians. It has been shown in clinical studies that RAPID3 gives corralated information with DAS28 and CDAI.

In this study, we aimed to determine the correlation of RAPID3, DAS28 and CDAI in the assesment of disease activity and effects of education level and co-morbid diseases on this assesment in RA patients who were followed in a tertiary rheumatology clinic of Turkey.

Methods

246 RA patients (80.1% female, mean age: 53.2±12.1 years) followed up for at least 3 months between January-June 2013 were included to the study. All patients were asked to fill out RAPID3 questionnaires. Uneducated patients completed the survey with the help of medical secretary. RAPID3, DAS28 and CDAI was calculated in all patients. Patients were subdivided according to disease severity as group A (remission-minimal disease activity) and group B (medium-severe disease activity) for all scoring systems. All  data were analyzed using statistical software; SPSS (Statistical Package For Social Sciences) for Windows 20 (SPSS Inc, Chicago, IL). One way Annova, Kruskal Wallis analysis, kappa analysis and Spearman correlation were used for statistics.  A level of  p < 0.05 was considered significant.

Results

27.2% of the patients were uneducated, the rest were educated  graduating from 50.8% primary school, 16.6% secondary/high school and 5.3% university. Mean training period of the patients was 4.9 years. 47.6% of the patients had at least one comorbid disease (i.e. hypertension, diabetes, hypo/hyperthyroidism, coronary artery disease, lung disease or obesity). Correlation of  RAPID3 with the DAS28 and CDAI score was statistically significant (p<0.001). Similarly, educational status and  the presence of comorbid disease didn’t effect this correlation (p<0.001). Kappa analysis showing compliance of RAPID3 with DAS28 and CDAI scores was also significant (p<0.001).

100% of the patients with severe disease activity according to DAS28 also had moderate/severe disease activity according to the RAPID3. 77% of patients who were in remission according to DAS28 have near remission–minimal disease activity according to  RAPID3. Patients with high disease activity according to the CDAI also had severe disease activity (100%) according to RAPID3,  while 97% of patients who were in remission according to the CDAI have near remission-minimal disease activity according to RAPID3.

Conclusion

Similar to previous studies, RAPID3 was significantly correlated with DAS28 and CDAI score. Even though RAPID3 could be effected by patients educational status, when we compared the patients as educated/uneducated, there was no significancy. At the same time, presence of co-morbid diseases didn’t effect the correlation of RAPID3 with DAS28 and CDAI. RAPID3 can provide quantitative information in uneducated patients and with presence of comorbid diseases just like DAS28 and CDAI.


Disclosure:

K. Sahin,
None;

Y. Karaaslan,
None;

Z. Ozbalkan,
None;

A. Omma,
None;

N. Yesil,
None.

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