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Abstract Number: 1577

Value and Prediction of Minimal Disease Activity in Patients with Psoriatic Arthritis

Arthur Kavanaugh1, Philip J. Mease2, Laura C. Coates3, Iain B. McInnes4, Maja Hojnik5, Alex Dorr6, Ying Zhang6, Benoit Guerette6, Alan Friedman6 and Dafna D. Gladman7, 1University of California San Diego, La Jolla, CA, 2Swedish Medical Center and University of Washington, Seattle, WA, 3NIHR Leeds Musculoskeletal Biomedical Research Unit, Leeds, United Kingdom, 4Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom, 5AbbVie, Ljubljana, Slovenia, 6AbbVie, Inc., North Chicago, IL, 7University of Toronto, Toronto Western Hospital, Toronto, ON, Canada

Meeting: 2014 ACR/ARHP Annual Meeting

Keywords: Disease Activity, psoriatic arthritis and treatment

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Session Information

Title: Spondyloarthropathies and Psoriatic Arthritis - Clinical Aspects and Treatment II

Session Type: Abstract Submissions (ACR)

Background/Purpose

The prediction of treatment outcomes based on early response could be useful in guiding decisions to adjust therapy. The objective was to determine if week (wk) 12 SJC and TJC, DAS28, CDAI and RAPID3 scores are predictive of achievement of a minimal disease activity (MDA) target at wk 24 in patients (pts) with Psoriatic Arthritis (PsA) and to evaluate patient-reported outcomes (PROs) associated with achieving MDA.

Methods

This post hoc analysis used pt data from ADEPT, a double blind randomized trial of adalimumab (ADA) versus placebo (PBO) in pts with moderate to severely active PsA and an inadequate response to NSAIDs. Pts who achieved MDA at wk 24 were termed as “achievers”, while those who did not, were termed “non-achievers” (NAs). PROs studied in association with MDA were: quality of life by DLQI and SF-36 scores (total, physical and mental component summary scores (P/MCS)), and fatigue by FACIT scores. The following criteria at wk 12 were considered as possible predictors of achieving MDA at wk 24: tender joint count (TJC) of 28 and 78 joints and swollen joint count (SJC) of 28 and 76 joints, DAS28, CDAI and RAPID3. The likelihood of predicting achievement of wk 24 MDA was assessed by ROC-AUC analysis, negative and positive predictive values (N/PPV).

Results

At wk 24, 24/62 pts (38.7%) on ADA treatment, and 4/60 pts (6.7%) on PBO treatment achieved MDA. While radiographic progression was low, overall, in the ADEPT trial, achievers had no progression compared to mild progression in NAs, although this difference was not statistically significant (-0.31±1.88 vs. 1.26±5.93, p= 0.201). Achievers also had higher total SF-36 scores (81.6±16.8 vs. 52.1±21.2, p<0.001), SF-36 PCS (51.0±7.2 vs. 35.0±10.8, p<0.001) and FACIT scores (43.5±10.6 vs. 30.5±12.2, p<0.05). There was no difference in the SF-36 MCS and DLQI scores of achievers compared to that of NAs. MDA achievers had lower mean SJC 76, TJC 78, DAS28(CRP), RAPID3 and CDAI scores at wk 12 than NAs, and greater improvement from BL to wk 12 in mean SJC 76 and TJC 78 scores. Wk 12 DAS28, CDAI and RAPID3 all predicted wk 24 MDA with an AUC 0.94-0.96 (table); Wk 12 TJC was a slightly better predictor than wk 12 SJC, with 28 joint-counts having similar accuracy to 78 joint-counts. All of the criteria cut points, as determined by ROC analysis, had high NPV for wk 24 MDA (table).

Wk 12 criterion

Area under the Curve (CL)

ROC Threshold

PPV

NPV

TJC28

0.89 (0.83, 0.94)

1.00

0.60

0.95

TJC78

0.91 (0.86, 0.97)

3.00

0.61

0.96

SJC28

0.80 (0.72, 0.89)

3.00

0.46

0.98

SJC76

0.84 (0.76, 0.91)

4.00

0.46

0.94

DAS28 (CRP)

0.96 (0.92, 0.99)

2.84

0.75

0.97

CDAI

0.97 (0.94, 1.00)

10.00

0.80

0.97

RAPID3

0.95 (0.90, 1.00)

1.30

0.75

0.97

Conclusion

In pts with PsA, the achievement of MDA was associated with improvements in HRQoL, physical function and fatigue. Wk 12 composite scores such as CDAI or RAPID3 remission and DAS28(CRP) LDA, as well as SJC and TJC had good ability to predict the likelihood of achieving MDA at wk 24, with 28 joint counts being as informative as 78 joint counts in this analysis. These quick and convenient tools can be used to guide treatment decisions at an early timepoint.


Disclosure:

A. Kavanaugh,

AbbVie Inc., Amgen, Astra-Zeneca, BMS, Celgene, Janssen, Pfizer, Roche, and UCB.,

2,

AbbVie Inc., Amgen, Astra-Zeneca, BMS, Celgene, Janssen, Pfizer, Roche, and UCB.,

9;

P. J. Mease,

AbbVie, Amgen, Biogen Idec, Bristol Myers, Celgene, Genentech, Janssen, Lilly, Merck, Novartis, Pfizer, UCB, and Vertex,

2,

AbbVie, Amgen, Biogen Idec, Bristol Myers, Celgene, Genentech, Janssen, Lilly, Merck, Novartis, Pfizer, UCB, and Vertex,

5,

AbbVie, Amgen, Biogen Idec, Bristol Myers, Celgene, Genentech, Janssen, Lilly, Merck, Novartis, Pfizer, UCB, and Vertex,

8;

L. C. Coates,

AbbVie, Celgene, Janssen, Novartis, Pfizer and UCB. ,

2,

AbbVie, Celgene, Janssen, Novartis, Pfizer and UCB. ,

5,

AbbVie, Celgene, Janssen, Novartis, Pfizer and UCB. ,

8;

I. B. McInnes,

AbbVie, Amgen, Janssen, Novartis, Pfizer, and UCB. ,

2,

AbbVie, Amgen, Janssen, Novartis, Pfizer, and UCB. ,

5;

M. Hojnik,

AbbVie,

1,

AbbVie,

3;

A. Dorr,

AbbVie,

1,

AbbVie,

3;

Y. Zhang,

AbbVie,

1,

AbbVie,

3;

B. Guerette,

AbbVie,

1,

AbbVie,

3;

A. Friedman,

AbbVie, Inc.,

1,

AbbVie, Inc.,

3;

D. D. Gladman,

Abbvie, Amgen, Celgene, Janssen, Pfizer, UCB,

2,

Abbvie, Amgen, BMS, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, UCB,

5.

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