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Abstract Number: 1370

Not All Joints Are Equal: Challenge DAS28 System and Identify Factors Leading to a Mismatch Between T2T and HAQ Among RA Patients Through Data Mining from Smart System of Disease Management (SSDM)

Jing Yang1, Zhenbiao Wu 2, Yongfu Wang 3, Hua Wei 4, Yu Zhang 1, Xiaoling Liu 5, Xiaofeng Rong 6, Jinmei Zou 1, Xiaofei Shi 7, Hongbin Li 8, Rui Wu 9, Xiaoli Deng 10, Huiqiong Zhou 11, Yuan Jia 12, Wei Zhao 13, Shi Chen 12, Xuewu Zhang 12, Yingnan Li 14, Yingkun Nie 14, Yifang Mei 15, Jianyu Zhang 16, Hanyou Mo 17, li Sun 18, Yanfei Chen 19, Haili Shen 20, Dongsheng Li 21, Yonggang Zhao 22, Hui Xiao 23, Bing Wu 24, Yuhua Jia 22 and Fei Xiao 25, 1Central Hospital of MianYang, Mianyang, Sichuan, China (People's Republic), 2The First Affiliated Hospital of The Fourth Military Medical University, Xian, Shanxi, China (People's Republic), 3The First Affiliated Hospital of BaoTou Medical College, Baotou, Nei Mongol, China (People's Republic), 4Northern Jiangsu People's Hospital, Yangzhou, China (People's Republic), 5The 1st Affiliated Hospital of Guangzhou University of TCM, Guangzhou, China (People's Republic), 6The 1st Affiliated hospital of Chongqing medical University, Chongqing, Chongqing, China (People's Republic), 7First Affiliated Hospital of Henan University of Science and Technology, luoyang, Henan, China (People's Republic), 8The Affiliated Hospital of Inner Mongolia Medical University, Huhhot, Nei Mongol, China (People's Republic), 9The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China (People's Republic), 10Peking University Third Hospital, Beijing, Beijing, China (People's Republic), 11Fourth Medical Center of PLA Genal Hospital, Beijing, Beijing, China (People's Republic), 12Peking University People's Hospital, Beijing, Beijing, China (People's Republic), 13Chinese PLA General Hospital, Beijing, Beijing, China (People's Republic), 14The 2nd Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China (People's Republic), 15The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China (People's Republic), 16The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China (People's Republic), 17Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China (People's Republic), 18The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China (People's Republic), 19The First Hospital of Lanzhou University, Lanzhou, Gansu, China (People's Republic), 20The Second Hospital of Lanzhou University, Lanzhou, Gansu, China (People's Republic), 21Ganzhou People's Hospital, Ganzhou, Jiangxi, China (People's Republic), 22Shanghai Gothic Internet Technology Co., Ltd., Shanghai, Shanghai, China (People's Republic), 23Shanghai Gothic Internet Technology Co., Ltd, shanghai, Shanghai, China (People's Republic), 24Shanghai Gothic Internet Technology Co., Ltd, Shanghai, China (People's Republic), 25Shanghai Gothic Internet Technology Co., Ltd., shanghai, China (People's Republic)

Meeting: 2019 ACR/ARP Annual Meeting

Keywords: Big data, Disease Activity and self-management, Health Assessment Questionnaire, Rheumatoid arthritis (RA)

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Session Information

Date: Monday, November 11, 2019

Title: RA – Diagnosis, Manifestations, & Outcomes Poster II: Treatments, Outcomes, & Measures

Session Type: Poster Session (Monday)

Session Time: 9:00AM-11:00AM

Background/Purpose: Treat to target (T2T), achieving a DAS28 score lower than 3.2, is the strategy recommended by ACR and EULAR. Health assessment questionnaire (HAQ) is the most widely used in assessment of physical function in RA. However, the T2T may not be always associated with low HAQ score. The purpose of this study is to quantify phenomena of mismatch between T2T and HAQ in RA patients and identify influential factors from real-world data mining in SSDM.

Methods: SSDM are mobile APPs of disease management. The patients were trained by physician to conduct their DAS28 and HAQ self-assessments with SSDM. The data were synchronized with physicians’ and uploaded onto cloud for analysis.

Two phases studies were designed. Phase I: from June of 2015 to May of 2018, to identify impact factor for mismatch; phase II: from June 2018 to May 2019, validation.

Results: From June 2015 to May 2019, 54,149 RA patients from 587 hospitals in China used SSDM, of which 41,234 patients made 84,538 times of DAS28 & HAQ self-assessments. Phase I: Total 48,751 assessment from 25,151 patients included. Among them, 25,738 assessments from 13,110 patients reached T2T. The mean numbers of tender and swollen joints were 1.53 and 1.32, respectively. However, 8,762 assessments (34.04%) of 5,905 patients had abnormal physical function (HAQ > 0), which score for 8 functional tests was 3.67. The “Bend down to pick up cloth from the floor” was the commonest, with a mean score of 0.81, significantly higher than other functional test score, P< 0.001. The analysis of correlation between physical dysfunction and the affected joints showed the knees were the major contributor to the mismatch, following by wrists and shoulders. Table 1 showed the mean scores for each functioning category in HAQ and the top target joints. According to the cluster weights for the impacts of affected joints on physical function, the weighted coefficient of impacting factors (IF) on physical function was obtained: knee=4, followed by wrist=3.4, shoulder=2.3, middle finger=2.1, elbow=2, index finger=2, other finger=1. Phase II: total 35,787 assessments from19,941 patients were included. Among them, 18,618 assessments from 10,776 patients achieved T2T, but 5,500 assessments from 3,979 patients (29.54%) had abnormal physical function (HAQ > 0, mean 3.49). After excluding 1,621 assessments without joint involvements, 3,879 left for validation. With standard DAS28 calculator, IFs of knee*4, wrist*3.4, shoulder*2.3, middle finger*2, orther finger*1 were applied for calculation, and 3,373 (86.96%) assessments turn out to be DAS28 >3.2(Mean: 4.19±0.01, Median: 4.08), major mismatches were overcome.

Conclusion: Over 1/4 RA patients suffer from physical dysfunctions though T2T are achieved. Diseased knees, wrists and shoulders are the major contributors to physical dysfunction and to the mismatch between T2T and HAQ. While elbow and finger joints influence on HAQ less. Therefore, not all joints are equal and T2T guided by current DAS28 may mislead. Joints of knees, wrists and middle fingers deserve higher IF (2.1-4) in DAS28. A modified DAS28 should be considered and a special attention should also be paid on these top three joints for rehabilitations.

Table 1. The mean scores for each functioning category in HAQ and the top 3 target joints.


Disclosure: J. Yang, None; Z. Wu, None; Y. Wang, None; H. Wei, None; Y. Zhang, None; X. Liu, None; X. Rong, None; J. Zou, None; X. Shi, None; H. Li, None; R. Wu, None; X. Deng, None; H. Zhou, None; Y. Jia, None; W. Zhao, None; S. Chen, None; X. Zhang, None; Y. Li, None; Y. Nie, None; Y. Mei, None; J. Zhang, None; H. Mo, None; l. Sun, None; Y. Chen, None; H. Shen, None; D. Li, None; Y. Zhao, None; H. Xiao, None; B. Wu, None; Y. Jia, None; F. Xiao, None.

To cite this abstract in AMA style:

Yang J, Wu Z, Wang Y, Wei H, Zhang Y, Liu X, Rong X, Zou J, Shi X, Li H, Wu R, Deng X, Zhou H, Jia Y, Zhao W, Chen S, Zhang X, Li Y, Nie Y, Mei Y, Zhang J, Mo H, Sun l, Chen Y, Shen H, Li D, Zhao Y, Xiao H, Wu B, Jia Y, Xiao F. Not All Joints Are Equal: Challenge DAS28 System and Identify Factors Leading to a Mismatch Between T2T and HAQ Among RA Patients Through Data Mining from Smart System of Disease Management (SSDM) [abstract]. Arthritis Rheumatol. 2019; 71 (suppl 10). https://acrabstracts.org/abstract/not-all-joints-are-equal-challenge-das28-system-and-identify-factors-leading-to-a-mismatch-between-t2t-and-haq-among-ra-patients-through-data-mining-from-smart-system-of-disease-management-ssdm/. Accessed .
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