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Abstract Number: 114

Treat-to-Target (T2T) and Measuring Outcomes in RA Care:  a 2014 Longitudinal Survey of US Rheumatologists

John J. Cush1 and Jeffrey R. Curtis2, 1Baylor Research Institute and Baylor University Medical Center, Dallas, TX, 2University of Alabama at Birmingham, Division of Clinical Immunology and Rheumatology, Birmingham, AL

Meeting: 2014 ACR/ARHP Annual Meeting

Keywords: Biologic agents, clinical practice and rheumatoid arthritis (RA), Disease Activity

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Session Information

Title: Health Services Research

Session Type: Abstract Submissions (ACR)

Background/Purpose: Changes in US rheumatologic practice for rheumatoid arthritis (RA) patients in the past decade have been influenced by novel therapies, increasing disease metric use and practice economics. This survey of US rheumatologists (Rheums) examined how commonly disease activity measures are used in clinical practice and if they inform decision-making or alter clinical practices over time.  

Methods: In 2014, 2027 US Rheums were invited (via 2 emails) to an online survey that included 26 questions on demographics, practice characteristics,  RA care practices, DMARDs/biologic use and the use of disease activity metrics. This 2014 cross-sectional survey of Rheums was compared with 2005 and 2008 responses (Table) to assess changes over time. Rheums doing metrics (Metric Rheums) were compared to those who do not (Non-Metric Rheums) with regard to their treatments and practices.

Results: Recruitment for this survey is ongoing. Thus far there are 317 respondents (18% response), with responders being mostly male (71%) with a mean age of 52.8 yrs.  40% of Rheums were in practice >25 yrs; up from 18.2% in 2005. Respondents were largely from private practice (67%) or academics (24%). Compared to 2005, US Rheums do fewer annual x-rays (16 vs 48%), MRI (1.7 vs 8%), or ultrasound (3.9 vs 1.9%). Rheums reported they achieve high rates of ACR 20-like responses (72.6%) and remission (39%) in their patients. Disease activity measures increased since 2005, with the HAQ or its variants being most measured at each visit, followed by the RAPID3 and the CDAI (Table). Metrics were done by 45% of Rheums – owing to improved care (76%), decision making (67%) and ease of use (50%).  More than half (55%) did not collect formal measures largely because of the time required (63%), not on their EMR (32%) or just not needed (32%).   Metric and non-Metric Rheums were equally committed to research, joint exams and lab testing.  Metric and non-Metric Rheums did not differ in the number of patients on TNF inhibitors (47.1 vs 47.4%), or in the management of 3 clinical vignettes differing only in the amount of metric data provided.  All rheums were more likely to inject joints when less data was provided and more likely to change or add biologics when more metrics were available.  For those failing their first TNFi, 66.7% would choose another TNFi (down from 74.5%), while with others switched to abatacept (19%), tocilizumab (7%), rituximab (2%) or tofacitinib (1%).  While a minority (20%) of Rheums don’t believe in the T2T “hype”, 43% assert they have always practiced in a T2T manner and 37% have adopted a T2T strategy for RA care.

Conclusion: Routine use of RA disease activity measures has become a practice standard in less than half of US  rheumatologists. Despite their collection, there is little evidence that metrics are changing how patients are managed

Changes over time in practice, TNFi and clinical metric use*

 

2005

2008

2014

N

1140

446

317[

Mean Age (yrs)

49

53

58

TNFi use > 50%

44.2

69

75

Use of RA Disease Activity Metrics at Routine Visits

HAQ or MDHAQ

17.6

22.9

36.1

RAPID3

ND

3.1

26.7

DAS28

5.9

12.2

16.5

CDAI

ND

2.3

16.2

Vectra MBDA

ND

ND

11.7

SDAI

ND

0.8

3.5

ACR20

1.7

3.9

1.4

None of the above

ND

ND

55

*all results expressed as percents unless noted


Disclosure:

J. J. Cush,

Pfizer, Celgene, CORRONA, Amgen, NIH, Novartis, UCB Pharma,

2;

J. R. Curtis,

Roche, Genentech, UCB Pharma, Janssen, CORRONA, Amgen, Pfizer, BMS, Crescendo, AbbVie,

2,

Roche, Genentech, UCB Pharma, Janssen, CORRONA, Amgen, Pfizer, BMS, Crescendo, AbbVie,

5.

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