Development of a Composite Index for Clinical Trials in Early Diffuse Cutaneous Systemic sclerosis—the Combined Response Index in Systemic Sclerosis

Dinesh Khanna¹, Veronica Berrocal², Edward Giannini³, Maureen Mayes⁴, Peter A. Merkel⁵, Jeffrey Siegel⁶, James R. Seibold⁷, Murray Baron⁸, Philip J. Clements⁹, Yannick Allanore¹⁰, Virginia D. Steen¹¹, Christopher P. Denton¹², Oliver Distler¹³, Sindhu R. Johnson¹⁴, Marco Matucci-Cerinic¹⁵, Lazlo Czirjak¹⁶, Janet E. Pope¹⁷, Susanna Proudman¹⁸, Weng Kee Wong¹⁹, Athol U. Wells²⁰ and Daniel E. Furst⁹, ¹University of Michigan Scleroderma Program, Ann Arbor, MI, ²Department of Biostatistics- School of Public Health, University of Michigan, Ann Arbor, MI, ³Ped Rheum/Pav 2-129, Childrens Hosp Med Ctr, Cincinnati, OH, ⁴Internal Medicine/Rheumatology, University of TX Health Science Center -Houston, Houston, TX, ⁵Vasculitis Center, E5, Boston University School of Medicine, Boston, MA, ⁶Genentech, South San Francisco, CA, ⁷Scleroderma Research Consultants LLC, Avon, CT, ⁸Pavillion A, Rm 216, Lady David Institute for Medical Research and Jewish General Hospital, Montreal, QC, Canada, ⁹University of California, Los Angeles, Department of Medicine, Los Angeles, CA, ¹⁰Department of Rheumatology, University Paris Descartes and Cochin Hospital, Paris, France, ¹¹Department of Rheumatology, Georgetown University Medical Center, Washington, DC, ¹²Centre for Rheumatology and Connective Tissue Diseases, UCL Medical School Royal Free Campus, London, United Kingdom, ¹³Division of Rheumatology, University Hospital Zurich, Zurich, Switzerland, ¹⁴Medicine, Division of Rheumatology, Toronto Western Hospital, University Health Network Pulmonary Hypertension Programme, Toronto General Hospital, Mount Sinai Hospital and University of Toronto, Toronto, ON, Canada, ¹⁵Dept of Medicine/Div of Rheum, University of Florence, Florence, Italy, ¹⁶Immunology and Rheumatology, University of Pécs, Pécs, Hungary, ¹⁷Medicine, Western University, London, ON, Canada, ¹⁸Rheumatology Unit, Royal Adelaide Hospital, Adelaide, Australia, ¹⁹Biostatistics, UCLA Fielding School of Public Health, Los Angeles, CA, ²⁰Royal Brompton and Harefield NHS Foundation Trust, Department of Radiology, London, United Kingdom

Meeting: 2014 ACR/ARHP Annual Meeting

Keywords: RCT and scleroderma

Session Information

Title: Systemic Sclerosis, Fibrosing Syndromes and Raynaud's - Clinical Aspects and Therapeutics III: Updates in Predictors and Outcomes in Systemic Sclerosis

Session Type: Abstract Submissions (ACR)

Background/Purpose: Diffuse systemic sclerosis (dcSSc) is a multisystem disease that involves skin and internal organs. Our objective was to develop a composite response index in dcSSc (CRISS) for use in clinical trials using expert consensus and data driven approaches.

Methods: Consensus was achieved on core set measures for a 1-year multicenter trial where 11 domains and 31 core items were proposed. Subsequently, a prospective NIH-funded observational cohort of 200 early dcSSc (disease duration < 5 years) was established to assess psychometric properties of the core measures. Using data from the cohort study and literature review, the steering committee assessed the feasibility, reliability, validity, and sensitivity to change for each core set measure. For endorsed core measures, paper patient profiles (n=150) were developed using cohorts from NIH and the Canadian Scleroderma Research Group. The literature was searched to assess the most prevalent/ bothersome issues faced by patients with SSc. 54 SSc experts were invited to participate in web-based evaluation to rate 20 patient profiles each on: 1. whether each patient had improved, worsened, or stabilized, and 2. rank the 3 most important variables that influenced their decision regarding change. Cluster analysis was conducted on the experts’ answers to determine clusters that identified the most influential core items. We defined consensus as 75% agreement among the experts of a patient’s status (improved, worsened or stabilized). Using only profiles where consensus was reached, we fit logistic regression models to the experts’ ratings for patients being improved vs. not and the core items as covariates. For each model, sensitivity, specificity and AUC were computed and predicted probabilities of improvement were derived for each patient profile. CRISS algorithm was subsequently evaluated in a RCT of methotrexate vs. placebo of dcSSc (Pope A&R 2001).

Results: 16 of 31 variables were chosen to be included as part of the patient profiles after review of test characteristics and available literature by the Steering Committee. Literature review suggested pain and fatigue as important attributes in SSc and were also included. 40 experts rated patient profiles and consensus was achieved in 118 of 150 profiles. Patients were not considered improved if they developed: 1. New renal crisis; 2. New decline in FVC% predicted by 15% (relative) and confirmed after 1 month; and 3. New onset left ventricular failure (systolic ejection fraction< 45%) or PAH. Ranking and cluster analysis indicated that the change in the modified Rodnan skin score, FVC% predicted, patient and physician global assessments, and HAQ-DI had an AUC of 0.986; sensitivity of 0.982 (95%CI 0.981-0.983) and specificity of 0.931 (95% CI 0.929-0.932). A cut-off at 0.6 in the predicted probability of being improved yielded the smallest misclassification error. In the patients with complete data in the MTX trial, 58% of MTX group vs. 19% in placebo group were considered improved.

Conclusion: We’ve developed a feasible composite response index with strong ability to discriminate patients who have improved vs. those who have not. The CRISS is currently being validated in RCTs of dcSSc.

Disclosure:

D. Khanna,

NIH Scleroderma Foundation, Pulmonary Hypertension Association,

University of Michigan,

Actelion, Bayer, Biogen-Idec, BMS, DIGNA, Genentech/Roche, Gilead, InterMune, Merck, Sanofi-Aventis, United Therapeutics,

Patient Health Organization member), Scleroderma Foundation medical advisory board) ,

V. Berrocal,
None;

E. Giannini,
None;

M. Mayes,
None;

P. A. Merkel,
None;

J. Siegel,

Genentech and Biogen IDEC Inc.,

J. R. Seibold,

Bayer,

Aries,

EMD Serono,

Gilead,

United Therapeutics,

Sigma Tau,

InterMune,

Boehringer Ingelheim,

M. Baron,
None;

P. J. Clements,
None;

Y. Allanore,
None;

V. D. Steen,

Actelion Pharmaceuticals US,

United Therapeutics,

Gilead Science,

Roche Pharmaceuticals,

Sanofi-Aventis Pharmaceutical,

CSL Berhing,

Intermune,

Bayer,

C. P. Denton,

Actelion Pharmaceuticals US,

O. Distler,
None;

S. R. Johnson,
None;

M. Matucci-Cerinic,

Actelion Pharmaceuticals US,

L. Czirjak,
None;

J. E. Pope,
None;

S. Proudman,
None;

W. K. Wong,
None;

A. U. Wells,
None;

D. E. Furst,
None.

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