Time-averaged disease activity fits better joint destruction in rheumatoid arthritis
Abstract Disease activity of rheumatoid arthritis (RA), evaluated as Disease Activity Score (DAS), is associated with joint destruction. Since joint destruction reflects the history of disease activities, we hypothesized that time-averaged disease activity would better correlate with joint destructi...
Guardado en:
| Autores principales: | , , , , , , , , , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2017
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/4aa944e90d074c348ce5b8cc0e021777 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:4aa944e90d074c348ce5b8cc0e021777 |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:4aa944e90d074c348ce5b8cc0e0217772021-12-02T16:06:59ZTime-averaged disease activity fits better joint destruction in rheumatoid arthritis10.1038/s41598-017-05581-w2045-2322https://doaj.org/article/4aa944e90d074c348ce5b8cc0e0217772017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-05581-whttps://doaj.org/toc/2045-2322Abstract Disease activity of rheumatoid arthritis (RA), evaluated as Disease Activity Score (DAS), is associated with joint destruction. Since joint destruction reflects the history of disease activities, we hypothesized that time-averaged disease activity would better correlate with joint destruction than one-time disease activity. We recruited RA patients in IORRA (n = 557) and KURAMA (n = 204) cohorts, and calculated time-averaged DAS28 to model a modified Sharp/van der Heijde score (SHS). We evaluated the fitting of the model using time-averaged DAS28 among 1000 models in which we randomly picked up one-time DAS28. We also used clinical disease activity index (CDAI) or data in the BeSt study (European population). After conditioning on autoantibody and disease duration, time-averaged DAS28 showed significant improvement of model fitting compared with one-time DAS28 in both cohorts (p = 0.001 and 0.034, respectively). Time-averaged CDAI also showed a better fit. Integration of multiple DAS fit SHS better in the BeSt study. A good fit of time-averaged DAS could be observed using five to six time points of DAS. In conclusion, time-averaged disease activity fits the joint destruction model better than one-time disease activity. Usage of time-averaged disease activity as a covariate would increase the power of studies to identify novel correlates of joint destruction.Hideaki TsujiKoichiro YanoMoritoshi FuruNoriyuki YamakawaKatsunori IkariMotomu HashimotoHiromu ItoTakao FujiiWataru YamamotoKoichiro OhmuraAtsuo TaniguchiShigeki MomoharaFumihiko MatsudaCornelia F. AllaartHisashi YamanakaTsuneyo MimoriChikashi TeraoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-8 (2017) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Hideaki Tsuji Koichiro Yano Moritoshi Furu Noriyuki Yamakawa Katsunori Ikari Motomu Hashimoto Hiromu Ito Takao Fujii Wataru Yamamoto Koichiro Ohmura Atsuo Taniguchi Shigeki Momohara Fumihiko Matsuda Cornelia F. Allaart Hisashi Yamanaka Tsuneyo Mimori Chikashi Terao Time-averaged disease activity fits better joint destruction in rheumatoid arthritis |
| description |
Abstract Disease activity of rheumatoid arthritis (RA), evaluated as Disease Activity Score (DAS), is associated with joint destruction. Since joint destruction reflects the history of disease activities, we hypothesized that time-averaged disease activity would better correlate with joint destruction than one-time disease activity. We recruited RA patients in IORRA (n = 557) and KURAMA (n = 204) cohorts, and calculated time-averaged DAS28 to model a modified Sharp/van der Heijde score (SHS). We evaluated the fitting of the model using time-averaged DAS28 among 1000 models in which we randomly picked up one-time DAS28. We also used clinical disease activity index (CDAI) or data in the BeSt study (European population). After conditioning on autoantibody and disease duration, time-averaged DAS28 showed significant improvement of model fitting compared with one-time DAS28 in both cohorts (p = 0.001 and 0.034, respectively). Time-averaged CDAI also showed a better fit. Integration of multiple DAS fit SHS better in the BeSt study. A good fit of time-averaged DAS could be observed using five to six time points of DAS. In conclusion, time-averaged disease activity fits the joint destruction model better than one-time disease activity. Usage of time-averaged disease activity as a covariate would increase the power of studies to identify novel correlates of joint destruction. |
| format |
article |
| author |
Hideaki Tsuji Koichiro Yano Moritoshi Furu Noriyuki Yamakawa Katsunori Ikari Motomu Hashimoto Hiromu Ito Takao Fujii Wataru Yamamoto Koichiro Ohmura Atsuo Taniguchi Shigeki Momohara Fumihiko Matsuda Cornelia F. Allaart Hisashi Yamanaka Tsuneyo Mimori Chikashi Terao |
| author_facet |
Hideaki Tsuji Koichiro Yano Moritoshi Furu Noriyuki Yamakawa Katsunori Ikari Motomu Hashimoto Hiromu Ito Takao Fujii Wataru Yamamoto Koichiro Ohmura Atsuo Taniguchi Shigeki Momohara Fumihiko Matsuda Cornelia F. Allaart Hisashi Yamanaka Tsuneyo Mimori Chikashi Terao |
| author_sort |
Hideaki Tsuji |
| title |
Time-averaged disease activity fits better joint destruction in rheumatoid arthritis |
| title_short |
Time-averaged disease activity fits better joint destruction in rheumatoid arthritis |
| title_full |
Time-averaged disease activity fits better joint destruction in rheumatoid arthritis |
| title_fullStr |
Time-averaged disease activity fits better joint destruction in rheumatoid arthritis |
| title_full_unstemmed |
Time-averaged disease activity fits better joint destruction in rheumatoid arthritis |
| title_sort |
time-averaged disease activity fits better joint destruction in rheumatoid arthritis |
| publisher |
Nature Portfolio |
| publishDate |
2017 |
| url |
https://doaj.org/article/4aa944e90d074c348ce5b8cc0e021777 |
| work_keys_str_mv |
AT hideakitsuji timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT koichiroyano timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT moritoshifuru timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT noriyukiyamakawa timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT katsunoriikari timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT motomuhashimoto timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT hiromuito timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT takaofujii timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT wataruyamamoto timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT koichiroohmura timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT atsuotaniguchi timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT shigekimomohara timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT fumihikomatsuda timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT corneliafallaart timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT hisashiyamanaka timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT tsuneyomimori timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis AT chikashiterao timeaverageddiseaseactivityfitsbetterjointdestructioninrheumatoidarthritis |
| _version_ |
1718384773672468480 |