scholarly journals Comparison of two approaches to measuring change in health status in rheumatoid arthritis: the Health Assessment Questionnaire (HAQ) and modified HAQ.

1992 ◽  
Vol 51 (11) ◽  
pp. 1202-1205 ◽  
Author(s):  
S Ziebland ◽  
R Fitzpatrick ◽  
C Jenkinson ◽  
A Mowat ◽  
A Mowat
Keyword(s):  
Rheumatoid Arthritis ◽  
Health Status ◽  
Health Assessment Questionnaire ◽  
Health Assessment ◽  
Measuring Change ◽  
Assessment Questionnaire

What Factors Influence the Health Status of Patients with Rheumatoid Arthritis Measured by the SF-12v2 Health Survey and the Health Assessment Questionnaire?

2009 ◽  
Vol 36 (10) ◽  
pp. 2183-2189 ◽  
Author(s):  
LOUISE LINDE ◽  
JAN SØRENSEN ◽  
MIKKEL ØSTERGAARD ◽  
KIM HØRSLEV-PETERSEN ◽  
CLAUS RASMUSSEN ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Health Status ◽  
Health Survey ◽  
Health Assessment Questionnaire ◽  
Health Assessment ◽  
Physical Component Score ◽  
Related Factors ◽  
Component Score ◽  
Patient Reported ◽  
Assessment Questionnaire

Objective.The Health Assessment Questionnaire Disability Index (HAQ) is a widely used outcome measure in rheumatoid arthritis (RA), whereas the SF-12v2 Health Survey (SF-12) was introduced recently. We investigated how the HAQ and SF-12 were associated with socio-demographic, lifestyle, and disease- and treatment-related factors in patients with RA.Methods.In RA patients from 11 Danish centers, clinical and patient-reported data, including the HAQ and SF-12, were collected. Three multiple linear regression models were estimated, with the HAQ, SF-12 physical component score (PCS), and SF-12 mental component score (MCS) as outcome and sociodemographic, lifestyle, and RA-related treatment and comorbidity characteristics as explanatory variables.Results.In total, 3156 (85%) of 3704 invited patients participated — 75% women, 76% rheumatoid factor-positive, median age 61 years (range 15–93 yrs), disease duration 7 years (range 0–68 yrs), Disease Activity Score on 28 joints (DAS28) 2.97 (range 0.96–8.61), HAQ score 0.63 (range 0–3), SF-12 PCS 56 (range 6–99), and SF-12 MCS 57 (range 16–99). Variation in HAQ was associated with 12 of 15 possible variables (R2 0.41), in PCS and MCS with 6 of 15 variables (R2 0.02 and 0.05). Patients with moderate to high DAS28 and ≥ 3 comorbid conditions had consistently worse HAQ and SF-12 scores compared to the reference groups, while weekly exercise was associated with better scores compared to no exercise.Conclusion.The HAQ was more sensitive to differences in demographic, lifestyle, and disease- and treatment-related factors than the SF-12. The established clinical value and feasibility of the HAQ highlights its advantages over the SF-12 in describing health status in RA.

scholarly journals AB0140 A HIGH-CONFIDENCE DEFINITION OF THERAPEUTIC RESPONSE IN RHEUMATOID ARTHRITIS USING A MONTE CARLO SIMULATION APPROACH

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1097.2-1098
Author(s):  
V. Strand ◽  
S. Cohen ◽  
L. Zhang ◽  
T. Mellors ◽  
A. Jones ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Monte Carlo ◽  
Disease Activity ◽  
Health Assessment Questionnaire ◽  
Health Assessment ◽  
High Confidence ◽  
Response Status ◽  
Definition Of ◽  
Fidelity Score ◽  
Assessment Questionnaire

Background:Therapy choice and therapy change depend on the ability to accurately assess patients’ disease activity. The clinical assessments used to evaluate treatment response in rheumatoid arthritis have inherent variability, normally considered as measurement error, intra-observer variability or within subject variability. Each contribute to variability in deriving response status as defined by composite measures such as the ACR or EULAR criteria, particularly when a one-time observed measurement lies near the boundary defining response or non-response. To select an optimal therapeutic strategy in the burgeoning age of precision medicine in rheumatology, achieve the lowest disease activity and maximize long-term health outcomes for each patient, improved treatment response definitions are needed.Objectives:Develop a high-confidence definition of treatment response and non-response in rheumatoid arthritis that exceeds the expected variability of subcomponents in the composite response criteria.Methods:A Monte Carlo simulation approach was used to assess ACR50 and EULAR response outcomes in 100 rheumatoid arthritis patients who had been treated for 6 months with a TNF inhibitor therapy. Monte Carlo simulations were run with 2000 iterations implemented with measurement variability derived for each clinical assessment: tender joint count, swollen joint count, Health Assessment Questionnaire disability index (HAQ-DI), patient pain assessment, patient global assessment, physician global assessment, serum C-reactive protein level (CRP) and disease activity score 28-joint count with CRP.1-3 Each iteration of the Monte Carlo simulation generated one outcome with a value of 0 or 1 indicating non-responder or responder, respectively.Results:A fidelity score, calculated separately for ACR50 and EULAR response, was defined as an aggregated score from 2000 iterations reported as a fraction that ranges from 0 to 1. The fidelity score depicted a spectrum of response covering strong non-responders, inconclusive statuses and strong responders. A fidelity score around 0.5 typified a response status with extreme variability and inconclusive clinical response to treatment. High-fidelity scores were defined as >0.7 or <0.3 for responders and non-responders, respectively, meaning that the simulated clinical response status label among all simulations agreed at least 70% of the time. High-confidence true responders were considered as those patients with high-fidelity outcomes in both ACR50 and EULAR outcomes.Conclusion:A definition of response to treatment should exceed the expected variability of the clinical assessments used in the composite measure of therapeutic response. By defining high-confidence responders and non-responders, the true impact of therapeutic efficacy can be determined, thus forging a path to development of better treatment options and advanced precision medicine tools in rheumatoid arthritis.References:[1]Cheung, P. P., Gossec, L., Mak, A. & March, L. Reliability of joint count assessment in rheumatoid arthritis: a systematic literature review. Semin Arthritis Rheum43, 721-729, doi:10.1016/j.semarthrit.2013.11.003 (2014).[2]Uhlig, T., Kvien, T. K. & Pincus, T. Test-retest reliability of disease activity core set measures and indices in rheumatoid arthritis. Ann Rheum Dis68, 972-975, doi:10.1136/ard.2008.097345 (2009).[3]Maska, L., Anderson, J. & Michaud, K. Measures of functional status and quality of life in rheumatoid arthritis: Health Assessment Questionnaire Disability Index (HAQ), Modified Health Assessment Questionnaire (MHAQ), Multidimensional Health Assessment Questionnaire (MDHAQ), Health Assessment Questionnaire II (HAQ-II), Improved Health Assessment Questionnaire (Improved HAQ), and Rheumatoid Arthritis Quality of Life (RAQoL). Arthritis Care Res (Hoboken) 63 Suppl 11, S4-13, doi:10.1002/acr.20620 (2011).Disclosure of Interests:Vibeke Strand Consultant of: Abbvie, Amgen, Arena, BMS, Boehringer Ingelheim, Celltrion, Galapagos, Genentech/Roche, Gilead, GSK, Ichnos, Inmedix, Janssen, Kiniksa, Lilly, Merck, Novartis, Pfizer, Regeneron, Samsung, Sandoz, Sanofi, Setpoint, UCB, Stanley Cohen: None declared, Lixia Zhang Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Ted Mellors Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Alex Jones Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Johanna Withers Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation, Viatcheslav Akmaev Shareholder of: Scipher Medicine Corporation, Employee of: Scipher Medicine Corporation

scholarly journals THU0106 PREDICTORS OF FLARE IN RHEUMATOID ARTHRITIS PATIENTS WITH LOW DISEASE ACTIVITY

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 267.1-267
Author(s):  
K. W. Moon
Keyword(s):  
Rheumatoid Arthritis ◽  
Multivariate Analysis ◽  
Observational Study ◽  
Disease Activity ◽  
Health Assessment Questionnaire ◽  
Health Assessment ◽  
Low Disease Activity ◽  
Erythrocyte Sedimentation ◽  
Euroqol 5D ◽  
Assessment Questionnaire

Background:Low disease activity (LDA) in patients with rheumatoid arthritis (RA) are usually recognized as stable state. In according to most guidelines for RA, monotherapy of disease modifying anti-rheumatic drug (DAMRD) was recommended for RA patents with LDA. But some of patients with LDA suffer from flare in their disease course. Until now, we don’t have enough data on factors that can predict flare in RA patients with LDA.Objectives:The aim of this study is to evaluate predictor of flare in RA patient with LDA from long-term (3 year) cohort data.Methods:Korean observational study network for arthritis (KORONA) registry is a nationwide Korean RA specific cohort registry that collecting data annually from 5,376 RA patients in 23 centers across South Korea. We include the data from 1, 801 RA patients with LDA (28 –joint disease activity score (DAS 28) < 3.2 at enrollment) who had consecutive data of DAS28 for 3 years. Flare was defined as an increase in DAS28 compared with baseline of >1.2 or >0.6 if concurrent DAS28 ≥3.2. Cox regression analysis was used to identify baseline predictors of flare.Results:Among 1,801 RA patients, 673 patients (37.4%) experienced flare in 3 years. When we compare the baseline characteristics of both flare and non-flare group, more women and more non-adherent patients for medication were observed in flare group. Flare group had longer disease duration, lower EuroQol 5D score, higher health assessment questionnaire (HAQ) score, and higher erythrocyte sedimentation rate (ESR) than non-flare group at baseline. In multivariate analysis, physician’s VAS, HAQ score, ESR, and poor adherence for medication were significant predictors of flare (Table 1).Table 1.Multivariate analysis of prediction of flare with baseline variablesMeasureHazard ratio95% Confidence IntervalP-valueFemale1.1300.906-1.4090.280Age0.9960.988-1.0050.414Physician’s VAS1.0081.002-1.013<0.01Pain VAS1.0020.998-1.0060.34EQ5D0.9520.534-1.6960.87HAQ1.4071.109-1.786<0.01ESR1.0081.002-1.014<0.01Poor adherence1.2721.047-1.545<0.05VAS: Visual Analogue Scale; EQ5D: EuroQol 5D; HAQ: Health Assessment Questionnaire; ESR: Erythrocyte Sedimentation RateConclusion:RA patient who have risk factors for flare, even though their disease activity was low, require more proactive treatment.References:[1]Bechman K, Tweehuysen L, Garrood T, Scott DL, Cope AP, Galloway JB, et al. Flares in Rheumatoid Arthritis Patients with Low Disease Activity: Predictability and Association with Worse Clinical Outcomes. J Rheumatol. 2018;45(11):1515-21.[2]Singh JA, Saag KG, Bridges SL, Jr., Akl EA, Bannuru RR, Sullivan MC, et al. 2015 American College of Rheumatology Guideline for the Treatment of Rheumatoid Arthritis. Arthritis Rheumatol. 2016;68(1):1-26.[3]Sung YK, Cho SK, Choi CB, Park SY, Shim J, Ahn JK, et al. Korean Observational Study Network for Arthritis (KORONA): establishment of a prospective multicenter cohort for rheumatoid arthritis in South Korea. Semin Arthritis Rheum. 2012;41(6):745-51.Disclosure of Interests:None declared

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