Key words. - University of Manchester
There is a need for new systemic sclerosis subset criteria. A content analytic approachSindhu R Johnson, Medha L Soowamber, Jaap Fransen, Dinesh Khanna, Frank van den Hoogen, Murray Baron, Marco Matucci-Cerinic, Christopher P. Denton, Thomas A. Medsger, Jr, Patricia E Carreira, Gabriela Riemekasten, Jorg Distler, Armando Gabrielli, Virginia Steen, Lorinda Chung, Richard Silver, John Varga, Ulf Müller-Ladner, Madelon C. Vonk, Ulrich A. Walker, Frank A. Wollheim, Ariane Herrick, Daniel E Furst, Laszlo Czirjak, Otylia Kowal-Bielecka, Francesco Del Galdo, Maurizio Cutolo, Nicolas Hunzelmann, Charles D Murray, Ivan Foeldvari, Luc Mouthon, Nemanja Damjanov, Bashar Kahaleh, Tracy Frech, Shervin Assassi, Lesley Ann Saketkoo, Janet E Pope.Sindhu R. Johnson MD PhD, Toronto Scleroderma Program, Division of Rheumatology, Department of Medicine, Toronto Western Hospital; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada;Medha L. Soowamber MD, Toronto Scleroderma Program, Division of Rheumatology, Department of Medicine, Toronto Western Hospital; University of Toronto, Toronto, Ontario, Canada;Jaap Fransen PhD, The Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands; Dinesh Khanna MD MSc, Division of Rheumatology, University of Michigan Scleroderma Program, Ann Arbor, MI, USA;Frank van den Hoogen, The Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands;Murray Baron, Division of Rheumatology, Department of Medicine, Jewish General Hospital, McGill University, Montreal, QC, Canada;Marco Matucci-Cerinic, Department of Rheumatology AVC, Department of BioMedicine, Division of? Rheumatology AOUC, Department of Medicine & Denothe centre, University of ?Florence, Firenze, Italy;Christopher P. Denton, Centre for Rheumatology and Connective Tissue Diseases, Royal Free Hospital, London, United KingdomThomas A. Medsger, Jr, Department of Medicine, Division of Rheumatology and Clinical Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA;Patricia E. Carreira, Servicio de Reumatología, Hospital Universitario 12 de Octubre, Madrid, SpainGabriela Riemekasten, Department of Rheumatology, University of Lübeck, Lung Research Center Borstel, a Leibniz institute, GermanyJorg Distler, Department of Internal Medicine 3 and Institute for Clinical Immunology, University of Erlangen-Nuremberg, 91054 Erlangen, GermanyArmando Gabrielli, Dipartimento di Scienze Cliniche e Molecolari, Clinica Medica, Università Politecnica delle Marche, Ancona, ItalyVirginia Steen, Department of Medicine,?Division of Rheumatology, Clinical Immunology and Allergy,?Georgetown University School of Medicine, USA;Lorinda Chung, Department of Medicine and Dermatology, Division of Immunology and Rheumatology, Stanford University, Stanford, CA, USARichard Silver, Department of Medicine, Division of Rheumatology & Immunology, Medical University of South Carolina, USAJohn Varga, Department of Medicine,?Division of Rheumatology, Clinical Immunology and Allergy,?Northwestern University, USAUlf Müller-Ladner, Department of Rheumatology and Clinical Immunology, Justus-Liebig University Giessen, Kerckhoff Clinic, Bad Nauheim, GermanyMadelon C. Vonk, Department of Rheumatic Diseases, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands Ulrich A. Walker, Rheumatology Department, University of Basel, Basel, SwitzerlandFrank A. Wollheim, Department of Rheumatology, Lund University Hospital, Lund, SwedenAriane L. Herrick, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United KingdomDaniel E Furst, Division of Rheumatology, University of California Los Angeles (UCLA), Los Angeles, CA, 90024, USA.Laszlo Czirjak, Department of Rheumatology and Immunology, University of Pécs, Clinical Center, Pécs, HungaryOtylia Kowal-Bielecka, Department of Rheumatology and Internal Medicine, Medical University of Bialystok, Bia?ystok, PolandFrancesco Del Galdo, Scleroderma Programme, Leeds Institute of Rheumatic and Musculoskeletal Medicine, LMBRU, University of Leeds, Leeds, United KingdomMaurizio Cutolo, Research Laboratory and Academic Division of Clinical Rheumatology, University of Genova, IRCCS AOU S. Martino, Genova, Italy.Nicolas Hunzelmann, Department of Dermatology, University of Cologne, Cologne, GermanyCharles D. Murray, Inflammatory Bowel Disease Unit, Royal Free London NHS Foundation Trust, London, UKIvan Foeldvari, Hamburger Zentrum für Kinder- und Jugend Rheumatologie, Klinikum Eilbek, Hamburg, GermanyLuc Mouthon, Université Paris Descartes, Assistance Publique-H?pitaux de Paris, Paris, FranceNemanja Damjanov, Institute of Rheumatology, University of Belgrade School of Medicine, Belgrade, SerbiaBashar Kahaleh, Division of Rheumatology, Department of Internal Medicine, University of Toledo Medical Center, Toledo, USATracy Frech, Division of Rheumatology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City USAShervin Assassi, University of Texas Health Science Center at Houston, Houston, USA.Lesley Ann Saketkoo, New Orleans Scleroderma and Sarcoidosis Patient Care and Research Center; Tulane University Lung Center; New Orleans, USAJanet E. Pope MD MPH, Division of Rheumatology, Department of Medicine, St Joseph Health Care, University of Western Ontario, London, ON, Canada.Corresponding Author. Sindhu Johnson MD, Division of Rheumatology, Ground Floor, East Wing, Toronto Western Hospital, 399 Bathurst Street, Toronto, Ontario, Canada, M5T 2S8. Phone 1-416-603-6417 Fax.1-416-603-4348. Email: Sindhu.Johnson@uhn.on.caKey words. Systemic Sclerosis, Scleroderma, Classification Criteria, Subsets, Content analysis, Qualitative ResearchWord Count 2609, Abstract 243Manuscript type ArticleABSTRACTObjectives. Systemic sclerosis (SSc) is heterogeneous. The objectives of this study were to evaluate the purpose, strengths and limitations of existing SSc subset criteria, and identify ideas among experts about subsets. Methods. We conducted semi-structured interviews with randomly sampled international SSc experts. The interview transcripts underwent an iterative process with text deconstructed to single thought units until a saturated conceptual framework with coding was achieved and respondent occurrence tabulated. Serial cross-referential analyses of clusters were developed.Results. Thirty experts from 13 countries were included; 67% were male, 63% were from Europe and 37% from North America; median experience of 22.5 years, with a median of 55 new SSc patients annually. Three thematic clusters regarding subsetting were identified: research and communication; management; and prognosis (prediction of internal organ involvement, survival). The strength of the limited/diffuse system was its ease of use, however 10% stated this system had marginal value. Shortcomings of the diffuse/limited classification were the risk of misclassification, predictions/generalizations did not always hold true, and that the elbow or knee threshold was arbitrary. Eighty-seven percent use more than 2 subsets including: SSc sine scleroderma, overlap conditions, antibody-determined subsets, speed of progression, and age of onset (juvenile, elderly). Conclusions. We have synthesized an international view of the construct of SSc subsets in the modern era. We found a number of factors underlying the construct of SSc subsets. Considerations for the next phase include rate of change and hierarchal clustering (e.g. limited/diffuse, then by antibodies). IntroductionSystemic sclerosis (SSc) is a family of conditions unified by the presence of immune activation, systemic vasculopathy and fibrosis. These may result in internal organ involvement, variable disease trajectory and survival. Classification criteria for subsets of patients with SSc are widely used in clinical research. ADDIN EN.CITE <EndNote><Cite><Author>Johnson</Author><Year>2007</Year><RecNum>303</RecNum><DisplayText>(1)</DisplayText><record><rec-number>303</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1327445532">303</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Johnson, S. R.</author><author>Feldman, B. M.</author><author>Hawker, G. A.</author></authors></contributors><auth-address>Division of Rheumatology, University Health Network, University of Toronto, Toronto, Ontario, Canada. Sindhu.Johnson@uhn.on.ca</auth-address><titles><title>Classification criteria for systemic sclerosis subsets</title><secondary-title>J Rheumatol</secondary-title></titles><periodical><full-title>J Rheumatol</full-title></periodical><pages>1855-63</pages><volume>34</volume><number>9</number><edition>2007/08/19</edition><keywords><keyword>Humans</keyword><keyword>Scleroderma, Systemic/*classification/diagnosis</keyword><keyword>Sensitivity and Specificity</keyword><keyword>*Severity of Illness Index</keyword></keywords><dates><year>2007</year><pub-dates><date>Sep</date></pub-dates></dates><isbn>0315-162X (Print)
0315-162X (Linking)</isbn><accession-num>17696271</accession-num><urls><related-urls><url> [pii]</electronic-resource-num><language>eng</language></record></Cite></EndNote>(1) Sixteen clinically based criteria sets have been proposed ranging from 2 to 6 subsets, usually based on the extent of skin involvementPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5CYXJuZXR0PC9BdXRob3I+PFllYXI+MTk2OTwvWWVhcj48
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ADDIN EN.CITE.DATA (2-18) The most frequently used are those proposed by LeRoy et al in 1988 which classify SSc patients as limited or diffuse cutaneous subtypes. ADDIN EN.CITE <EndNote><Cite><Author>LeRoy</Author><Year>1988</Year><RecNum>238</RecNum><DisplayText>(6)</DisplayText><record><rec-number>238</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1327445532">238</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>LeRoy, E. C.</author><author>Black, C.</author><author>Fleischmajer, R.</author><author>Jablonska, S.</author><author>Krieg, T.</author><author>Medsger, T. A., Jr.</author><author>Rowell, N.</author><author>Wollheim, F.</author></authors></contributors><auth-address>Medical University of South Carolina, Charleston.</auth-address><titles><title>Scleroderma (systemic sclerosis): classification, subsets and pathogenesis</title><secondary-title>J Rheumatol</secondary-title></titles><periodical><full-title>J Rheumatol</full-title></periodical><pages>202-5</pages><volume>15</volume><number>2</number><edition>1988/02/01</edition><keywords><keyword>Antigens/analysis</keyword><keyword>Blood Vessels/pathology</keyword><keyword>Female</keyword><keyword>HLA Antigens/analysis/classification</keyword><keyword>Humans</keyword><keyword>Middle Aged</keyword><keyword>Prognosis</keyword><keyword>Raynaud Disease/complications</keyword><keyword>Scleroderma, Systemic/*classification/diagnosis/etiology/pathology</keyword></keywords><dates><year>1988</year><pub-dates><date>Feb</date></pub-dates></dates><isbn>0315-162X (Print)
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ADDIN EN.CITE.DATA .CITE <EndNote><Cite><Author>Assassi</Author><Year>2013</Year><RecNum>575</RecNum><record><rec-number>575</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw">575</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Assassi, S.</author><author>Radstake, T. R.</author><author>Mayes, M. D.</author><author>Martin, J.</author></authors></contributors><auth-address>Division of Rheumatology and Clinical Immunogenetics, The University of Texas Health Science Center at Houston, 6431 Fannin Street, Houston, TX 77030, USA. shervin.assassi@uth.tmc.edu</auth-address><titles><title>Genetics of scleroderma: implications for personalized medicine?</title><secondary-title>BMC Med</secondary-title></titles><periodical><full-title>BMC Med</full-title></periodical><pages>9</pages><volume>11</volume><edition>2013/01/15</edition><keywords><keyword>Genetic Markers</keyword><keyword>*Genetic Predisposition to Disease</keyword><keyword>Humans</keyword><keyword>Individualized Medicine/*methods</keyword><keyword>Scleroderma, Systemic/diagnosis/*genetics/therapy</keyword></keywords><dates><year>2013</year></dates><isbn>1741-7015 (Electronic)
1741-7015 (Linking)</isbn><accession-num>23311619</accession-num><urls><related-urls><url> [pii]
10.1186/1741-7015-11-9</electronic-resource-num><language>eng</language></record></Cite></EndNote>(22), the construct of ‘subsets in SSc’ may have evolved. Development of new subset criteria for SSc is being undertaken, led by the international steering committee of American College of Rheumatology (ACR) and European League Against Rheumatism (EULAR) classification criteria for SSc. An important first step is to evaluate the current construct underpinning the meaning and utility of SSc subset criteria. It is also important to understand the strengths and limitations of previous iterations of SSc subset criteria so that a new iteration of SSc subset criteria will build upon the strengths and address the limitations.The aim of this study is to evaluate the construct of SSc subsets in the modern era. Specifically, the objectives of this study are to evaluate the meaning and purpose of SSc subset criteria; determine the strengths and limitations of existing SSc subset criteria, and identify potential areas for improvement. An accurate understanding of the construct underlying SSc subsets will inform the study design of the new iteration of SSc subset classification criteria development.MethodsStudy design. We conducted a cross-sectional study, with face-to-face interviews, to determine the purpose, strengths, limitations and areas of improvement for SSc subset criteria.Sample. Our previous work found that the most valid and reliable beliefs are elicited from individuals who have a greater depth of knowledge and experience. ADDIN EN.CITE <EndNote><Cite><Author>Johnson</Author><Year>2010</Year><RecNum>286</RecNum><DisplayText>(28)</DisplayText><record><rec-number>286</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1327445532">286</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Johnson, S. R.</author><author>Tomlinson, G. A.</author><author>Hawker, G. A.</author><author>Granton, J. T.</author><author>Feldman, B. M.</author></authors></contributors><auth-address>Division of Rheumatology, Department of Medicine, University Health Network, Toronto, Ontario M5T 2S8, Canada. Sindhu.Johnson@uhn.on.ca</auth-address><titles><title>Methods to elicit beliefs for Bayesian priors: a systematic review</title><secondary-title>J Clin Epidemiol</secondary-title></titles><periodical><full-title>J Clin Epidemiol</full-title></periodical><pages>355-369</pages><volume>63</volume><number>4</number><reprint-edition>NOT IN FILE</reprint-edition><keywords><keyword>analysis</keyword><keyword>Canada</keyword><keyword>Comparative Study</keyword><keyword>Cross-Sectional Studies</keyword><keyword>methods</keyword><keyword>Ontario</keyword><keyword>Probability</keyword><keyword>Research</keyword><keyword>Rheumatology</keyword></keywords><dates><year>2010</year></dates><urls><related-urls><url>PM:19716263</url></related-urls></urls></record></Cite></EndNote>(28) Thus we interviewed experts in SSc. SSc experts were defined as individuals who participate in a referral center for or conduct human research in SSc. A list of attendees at the Systemic Sclerosis World Congress (n=771) was used to identify SSc experts (those who publish in SSc and/or have a SSc program) (n=69). Each SSc expert was assigned a number. SSc experts were randomly sampled from the SSc expert list using a computerized random number generator. Subjects were contacted using a standardized letter by email inviting them to participate in a recorded interview. This recruitment strategy has been successfully used in previous work.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Kb2huc29uPC9BdXRob3I+PFllYXI+MjAxMjwvWWVhcj48
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ADDIN EN.CITE.DATA (29) An interview time was arranged. Each participant was assigned a study identification code to maintain anonymity. Characteristics of the participants collected included sex, pediatric/adult rheumatology/other, years in practice, number of new SSc patients seen per year, participation in SSc research, and location of practice. There is no consensus on the sample size for a belief elicitation study. ADDIN EN.CITE <EndNote><Cite><Author>Johnson</Author><Year>2010</Year><RecNum>286</RecNum><DisplayText>(28)</DisplayText><record><rec-number>286</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1327445532">286</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Johnson, S. R.</author><author>Tomlinson, G. A.</author><author>Hawker, G. A.</author><author>Granton, J. T.</author><author>Feldman, B. M.</author></authors></contributors><auth-address>Division of Rheumatology, Department of Medicine, University Health Network, Toronto, Ontario M5T 2S8, Canada. Sindhu.Johnson@uhn.on.ca</auth-address><titles><title>Methods to elicit beliefs for Bayesian priors: a systematic review</title><secondary-title>J Clin Epidemiol</secondary-title></titles><periodical><full-title>J Clin Epidemiol</full-title></periodical><pages>355-369</pages><volume>63</volume><number>4</number><reprint-edition>NOT IN FILE</reprint-edition><keywords><keyword>analysis</keyword><keyword>Canada</keyword><keyword>Comparative Study</keyword><keyword>Cross-Sectional Studies</keyword><keyword>methods</keyword><keyword>Ontario</keyword><keyword>Probability</keyword><keyword>Research</keyword><keyword>Rheumatology</keyword></keywords><dates><year>2010</year></dates><urls><related-urls><url>PM:19716263</url></related-urls></urls></record></Cite></EndNote>(28) Using central limit theorem, an a priori sample size of 30 was chosen to assume a normal distribution to the mean values of summarized data. This conservative approach provides a larger and more robust sample size than usually recommended for content analytic studies. ADDIN EN.CITE <EndNote><Cite><Author>Guest</Author><Year>2006</Year><RecNum>621</RecNum><DisplayText>(30)</DisplayText><record><rec-number>621</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1462220604">621</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Guest, G.</author><author>Bunce, A.</author><author>Johnson, L.</author></authors></contributors><titles><title>How many interviews are enough? An experiment with data saturation and variability.</title><secondary-title>Field Methods</secondary-title></titles><periodical><full-title>Field Methods</full-title></periodical><pages>59-82</pages><volume>18</volume><number>1</number><dates><year>2006</year></dates><urls></urls></record></Cite></EndNote>(30) Institutional research ethics approval was obtained and participants provided written informed consent.Interview. A 10-minute interview was conducted individually with each expert. Using a standardized semi-structured interview template, experts were asked open-ended questions investigating their beliefs about the purpose and limitations of SSc subset criteria. Appendix 1. The investigator used probes (e.g. can you tell me more about that?) to facilitate elaboration of an expert’s comments. The interview was recorded using a dictaphone and transcribed verbatim. Analysis. Participant characteristics were double entered into a computerized database and summarized using descriptive statistics. Hsieh and Shannon’s qualitative content analytic approach was used to analyze the interview data. ADDIN EN.CITE <EndNote><Cite><Author>Hsieh</Author><Year>2005</Year><RecNum>568</RecNum><DisplayText>(31)</DisplayText><record><rec-number>568</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1390420448">568</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Hsieh, H. F.</author><author>Shannon, S. E.</author></authors></contributors><auth-address>Fooyin University, Kaohsiung Hsien, Taiwan.</auth-address><titles><title>Three approaches to qualitative content analysis</title><secondary-title>Qual Health Res</secondary-title></titles><periodical><full-title>Qual Health Res</full-title></periodical><pages>1277-88</pages><volume>15</volume><number>9</number><edition>2005/10/06</edition><keywords><keyword>Humans</keyword><keyword>*Qualitative Research</keyword><keyword>*Research</keyword><keyword>*Terminal Care</keyword></keywords><dates><year>2005</year><pub-dates><date>Nov</date></pub-dates></dates><isbn>1049-7323 (Print)
1049-7323 (Linking)</isbn><accession-num>16204405</accession-num><urls><related-urls><url> [pii]
10.1177/1049732305276687</electronic-resource-num><language>eng</language></record></Cite></EndNote>(31) Independently, 2 investigators (SRJ, MS) read all the transcripts repeatedly to achieve immersion and obtain a sense of the whole data set. The transcripts were re-read word by word to derive codes by first highlighting the exact words from the text that appear to capture key thoughts or concepts. The investigators made notes of the initial analysis, and created labels for codes that are reflective of the thoughts. The codes were organized into meaningful clusters. The incidence of codes and rank order frequency are reported. The results of the 2 independent analyses were compared. The aggregate results were presented to an independent, international group of SSc experts (n=6) for comment and identification of conceptual links amongst the themes to develop an analytical thematic schema. This research triangulation enhances the credibility of the findings and ensures the analysis reflects the full breadth and depth of the data. ADDIN EN.CITE <EndNote><Cite><Author>Nakayama</Author><Year>2016</Year><RecNum>614</RecNum><DisplayText>(32)</DisplayText><record><rec-number>614</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1461611807">614</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Nakayama, A.</author><author>Tunnicliffe, D. J.</author><author>Thakkar, V.</author><author>Singh-Grewal, D.</author><author>O'Neil, S.</author><author>Craig, J.C.</author><author>Tong, A.</author></authors></contributors><titles><title>Patients' perspectives and experiences living with systemic sclerosis: systematic review and thematic synthesis of qualitative studies.</title><secondary-title>J Rheumatol</secondary-title></titles><periodical><full-title>J Rheumatol</full-title></periodical><volume>In Press</volume><dates><year>2016</year></dates><urls></urls></record></Cite></EndNote>(32) Descriptive statistics were used to summarize the data. Quantitative analyses were conducted using RStudio (version 0.97.248).RESULTSSSc experts. Thirty experts from 13 countries were successfully recruited. The participants were predominantly male (67%), European (63%) and practiced adult rheumatology (87%) with a median of 22.5 (interquartile range 17.3) years in practice seeing SSc patients. Two investigators were involved in previous SSc subset classification criteria development. Table 1 summarizes participant characteristics. Meaning of SSc subsets. The term SSc subsets meant ‘distinguish patients’ into ‘distinct groups’ using terms ‘differentiate’, ‘stratify’, ‘separate’, ‘divide’ and ‘characterized subgroups.’ There was no ambiguity in the meaning of SSc subset criteria.Purpose of SSc subsets. The purpose of SSc subset criteria fell into 3 thematic clusters. Under the cluster Management, experts stated that SSc subsets should ‘guide intensity of investigations at baseline’; ‘intensity of monitoring over time’; inform management, treatment/therapeutics, ‘aggressiveness of therapy’ and inform ‘response to treatment’. A second thematic cluster Prognosis was identified, with 2 sub-clusters: ‘internal organ involvement’ and ‘survival.’ Experts stated that SSc subsets should inform prognosis, namely ‘outcomes’, ‘course of disease’, ‘changes over time’, ‘disease progression’; ‘function as prognostic indicators’ or ‘assist with risk stratification, ideally informing time to organ failure’. A third thematic cluster Research and Communication was identified. Experts stated that SSc subsets be used ‘during study sample selection to reduce the heterogeneity of disease.’ SSc subsets can be used to ‘educate’ patients, trainees and medical colleagues about SSc. It facilitates communication among health professionals in the patient’s circle of care (see Figure 2).Strengths of Limited/Diffuse classification system. 100% of experts endorsed using the limited/diffuse cutaneous subset system. Experts stated the strengths of the limited/diffuse subset system are its ‘ease of use’ and ‘simple to understand.’ It ‘has prognostic value,’ ‘informs what to look for,’ ‘useful for management’ and ‘applicable for research.’ However, 10% of experts stated that this system has little or no value. One expert stated, ‘I put it in the note to communicate to other physicians…. I have more tools and am more comprehensive in how we evaluate patient.’ Another expert stated ‘I hate these criteria, the skin is the wrong thing.’ The shortcomings of the limited cutaneous and diffuse cutaneous SSc system grouped into 4 thematic clusters. Under thematic cluster “Misclassification” experts expressed concern relating to the observation that ‘all diffuse starts as limited, and limited can extend to diffuse.’ ‘Everyone starts as limited,’ and this system requires ‘expert clinicians and expert centers’ to prevent misclassification. A second thematic cluster was ‘predictions or generalizations do not always hold true.’ Participants observed that ‘pulmonary arterial hypertension can occur in both types,’ and ‘some patients don’t behave the way they are supposed to.’ The beliefs that the ‘diffuse type has a worse prognosis,’ ‘anticentromere is associated with limited and Scl70 (Topoisomerase1) is associated with diffuse’ are not always true. This system is ‘not good enough for predicting organ involvement,’ and ‘doesn’t work for lung.’ A third thematic cluster related to the use of the elbow as a cutaneous threshold as participants felt that it is an ‘absolute breakdown without context,’ is ‘arbitrary,’ and that the ‘forearm are diffuse in action. A fourth thematic cluster related to dependence on the skin for classification. Participants expressed the 2 subset system ‘does not account for progression or regression,’ does not reflect the intermediate subtype, and ‘only includes observed skin thickening. Participants opined that ‘in early disease the skin is not the major organ,’ and ‘skin alone is not useful.’ Other comments included ‘limited is not well defined,’ ‘the system does not capture disease severity or disease activity,’ ‘is missing antibodies,’ does not account ‘for rate of physiologic change,’ and is an ‘oversimplification.’Number and types of subsets. Eighty-seven percent of experts use more than 2 SSc subsets. In practice, the participants endorsed using 2 to 10 subsets. Figure 5. SSc sine scleroderma was considered a subset (n=7), whereas others explicitly stated SSc sine scleroderma is not a separate subtype (n=2). Overlap patients were considered a distinct subset (n=6). Some participants subset SSc by autoantibody or antinuclear antibody pattern (n=6), explicitly describing centromere, topoisomerase, RNA polymerase, nucleolar pattern and U1RNP antibodies. Some participants subset SSc by rate of skin progression (n=3) distinguishing ‘rapidly progressive’ from ‘slowly progressive.’ Experts subset SSc based on stage of disease, distinguishing ‘early’ versus ‘late’ or ‘established.’ Experts also subset based on age of onset distinguishing ‘juvenile onset’ and ‘geriatric onset.’ Other described subsets included ‘pre-SSc or undifferentiated,’ ‘single organ dominant,’ intermediate,’ ‘fibrotic or vasculopathic with or without inflammation,’ and considered gene expression and interferon signatures.DISCUSSIONWe have found that the concept of SSc subsets exists as a multidimensional and complex latent construct. It cannot be easily measured but is considered to be real by international SSc experts. Ontology is the philosophical study of the nature of being, and the categories of being and their relations. Our work addresses the ontological questions: ‘what is it?’ and ‘what is it for?’ SSc subset criteria have wide ranging utility as they may inform patient care, predict internal organ involvement and survival; are needed to identify more homogeneous groups of patients for SSc studies and inform medical communication. The limited and diffuse cutaneous SSc subset system has been extensively adopted over the past 25 years. However, limitations to their use have been identified. Our findings suggest there is a need for new systemic sclerosis classification criteria.Our results provide important considerations for the next phase of criteria development. Experts continue to be influenced by the degree of skin involvement. Skin involvement is a manifestation that is relatively easy to measure, is low cost and can be ascertained in any setting. However, an emerging concept not included in previous iterations of SSc subset criteria is the rate of skin change. 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ADDIN EN.CITE.DATA (37) The limited and diffuse cutaneous system includes centromere and topoisomerase antibodies, yet is not always consistent. A wider array of scleroderma-specific antibodies has been studied. RNA polymerase3 antibodies have been associated with renal crisis. However, the inclusion of a greater number of scleroderma specific antibodies in SSc subset criteria will need to tempered against their broad availability and cost. Furthermore, there appears to be geographic variation in the prevalence of antibodies, notably the prevalence of RNA polymerase III antibodies in the US versus southern Europe. ADDIN EN.CITE <EndNote><Cite><Author>Domsic</Author><Year>2014</Year><RecNum>620</RecNum><DisplayText>(38)</DisplayText><record><rec-number>620</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1462219591">620</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Domsic, R. T.</author></authors></contributors><auth-address>Division of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.</auth-address><titles><title>Scleroderma: the role of serum autoantibodies in defining specific clinical phenotypes and organ system involvement</title><secondary-title>Curr Opin Rheumatol</secondary-title><alt-title>Current opinion in rheumatology</alt-title></titles><periodical><full-title>Curr Opin Rheumatol</full-title><abbr-1>Current opinion in rheumatology</abbr-1></periodical><alt-periodical><full-title>Curr Opin Rheumatol</full-title><abbr-1>Current opinion in rheumatology</abbr-1></alt-periodical><pages>646-52</pages><volume>26</volume><number>6</number><keywords><keyword>Autoantibodies/*blood</keyword><keyword>Humans</keyword><keyword>Phenotype</keyword><keyword>Prognosis</keyword><keyword>Scleroderma, Systemic/blood/*immunology</keyword></keywords><dates><year>2014</year><pub-dates><date>Nov</date></pub-dates></dates><isbn>1531-6963 (Electronic)
1040-8711 (Linking)</isbn><accession-num>25203118</accession-num><urls><related-urls><url>;(38) The impact of geographic variability on the operating characteristics of subset criteria including autoantibodies will need to be evaluated. Similarly, the possible role and contribution of nailfold capillaroscopic SSc patterns may need to be considered. The identification of early, active, and late nailfold capillaroscopic SSc patterns may inform subsetting.The appropriate number of subsets is another important consideration. The majority of experts believe there are more than 2 subsets. Previous iterations of criteria have proposed up to six subsets. However, a 2 subset system has been shown to have the best predictive validity for prognosticating future outcomes in SSc. ADDIN EN.CITE <EndNote><Cite><Author>Johnson</Author><Year>2007</Year><RecNum>303</RecNum><DisplayText>(1)</DisplayText><record><rec-number>303</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1327445532">303</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Johnson, S. R.</author><author>Feldman, B. M.</author><author>Hawker, G. A.</author></authors></contributors><auth-address>Division of Rheumatology, University Health Network, University of Toronto, Toronto, Ontario, Canada. Sindhu.Johnson@uhn.on.ca</auth-address><titles><title>Classification criteria for systemic sclerosis subsets</title><secondary-title>J Rheumatol</secondary-title></titles><periodical><full-title>J Rheumatol</full-title></periodical><pages>1855-63</pages><volume>34</volume><number>9</number><edition>2007/08/19</edition><keywords><keyword>Humans</keyword><keyword>Scleroderma, Systemic/*classification/diagnosis</keyword><keyword>Sensitivity and Specificity</keyword><keyword>*Severity of Illness Index</keyword></keywords><dates><year>2007</year><pub-dates><date>Sep</date></pub-dates></dates><isbn>0315-162X (Print)
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ADDIN EN.CITE.DATA (17)Investigators are encouraged to think carefully about how we approach development of classification criteria for subsets of disease. Classical ‘philosophic realism,’ an underpinning of psychometric science, says that the notion of subsets within a disease is a real thing that we cannot directly observe and therefore called a latent variable or construct. ADDIN EN.CITE <EndNote><Cite><Author>Borsboom</Author><Year>2003</Year><RecNum>615</RecNum><DisplayText>(39)</DisplayText><record><rec-number>615</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1461612098">615</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Borsboom, D.</author><author>Mellenbergh, G. J.</author><author>van Heerden, J.</author></authors></contributors><auth-address>Department of Psychology, Faculty of Social and Behavioral Sciences, University of Amsterdam, The Netherlands. dborsboom@fmg.uva.nl</auth-address><titles><title>The theoretical status of latent variables</title><secondary-title>Psychol Rev</secondary-title></titles><periodical><full-title>Psychol Rev</full-title></periodical><pages>203-19</pages><volume>110</volume><number>2</number><keywords><keyword>Humans</keyword><keyword>*Psychological Theory</keyword><keyword>Psychology/methods</keyword><keyword>Semantics</keyword></keywords><dates><year>2003</year><pub-dates><date>Apr</date></pub-dates></dates><isbn>0033-295X (Print)
0033-295X (Linking)</isbn><accession-num>12747522</accession-num><urls><related-urls><url>;(39) We use combinations of symptoms, signs and test results to indicate the construct (i.e. define the subsets). The items that define the construct should be highly correlated and interchangeable. ADDIN EN.CITE <EndNote><Cite><Author>Duffy</Author><Year>2016</Year><RecNum>613</RecNum><DisplayText>(40)</DisplayText><record><rec-number>613</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1461611433">613</key></foreign-keys><ref-type name="Book">6</ref-type><contributors><authors><author>Duffy, C.M</author><author>Feldman, B. M.</author></authors><secondary-authors><author>Petty, R. E.</author><author>Laxer, R. M.</author><author>Lindsley, C. B.</author><author>Wedderburn, L. R.</author></secondary-authors></contributors><titles><title>Textbook of Pediatric Rheumatology</title></titles><edition>Seventh</edition><section>78-87</section><dates><year>2016</year></dates><publisher>Elsevier</publisher><urls></urls></record></Cite></EndNote>(40) The final system of subset classification should be reflective of the underlying, real, latent construct. However, it may be that subsets within a disease don’t exist as real and independent entities but rather constructed in the minds of experts. ADDIN EN.CITE <EndNote><Cite><Author>Duffy</Author><Year>2016</Year><RecNum>613</RecNum><DisplayText>(40)</DisplayText><record><rec-number>613</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1461611433">613</key></foreign-keys><ref-type name="Book">6</ref-type><contributors><authors><author>Duffy, C.M</author><author>Feldman, B. M.</author></authors><secondary-authors><author>Petty, R. E.</author><author>Laxer, R. M.</author><author>Lindsley, C. B.</author><author>Wedderburn, L. R.</author></secondary-authors></contributors><titles><title>Textbook of Pediatric Rheumatology</title></titles><edition>Seventh</edition><section>78-87</section><dates><year>2016</year></dates><publisher>Elsevier</publisher><urls></urls></record></Cite></EndNote>(40) Under this approach of ‘philosophic constructivism’ the items chosen to define subsets form the construct. As a consequence, the use of different items to define subsets may result in different outcomes. ADDIN EN.CITE <EndNote><Cite><Author>Duffy</Author><Year>2016</Year><RecNum>613</RecNum><DisplayText>(40)</DisplayText><record><rec-number>613</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1461611433">613</key></foreign-keys><ref-type name="Book">6</ref-type><contributors><authors><author>Duffy, C.M</author><author>Feldman, B. M.</author></authors><secondary-authors><author>Petty, R. E.</author><author>Laxer, R. M.</author><author>Lindsley, C. B.</author><author>Wedderburn, L. R.</author></secondary-authors></contributors><titles><title>Textbook of Pediatric Rheumatology</title></titles><edition>Seventh</edition><section>78-87</section><dates><year>2016</year></dates><publisher>Elsevier</publisher><urls></urls></record></Cite></EndNote>(40) For example, defining subsets by autoantibodies, extent of skin involvement or rate of change may differentially predict future organ involvement or survival. Researchers have been advised to investigate how constructivism should be considered when evaluating the validity of and choosing measures to inform patient care or the conduct of research. ADDIN EN.CITE <EndNote><Cite><Author>Duffy</Author><Year>2016</Year><RecNum>613</RecNum><DisplayText>(40)</DisplayText><record><rec-number>613</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1461611433">613</key></foreign-keys><ref-type name="Book">6</ref-type><contributors><authors><author>Duffy, C.M</author><author>Feldman, B. M.</author></authors><secondary-authors><author>Petty, R. E.</author><author>Laxer, R. M.</author><author>Lindsley, C. B.</author><author>Wedderburn, L. R.</author></secondary-authors></contributors><titles><title>Textbook of Pediatric Rheumatology</title></titles><edition>Seventh</edition><section>78-87</section><dates><year>2016</year></dates><publisher>Elsevier</publisher><urls></urls></record></Cite></EndNote>(40) Combining items of different attributes in a hierarchical form (e.g. extent of skin involvement and autoantibodies) may address this issue. Figure 6.One may argue that there may not be 1 subset classification system that serves all purposes. Subclassification will create more homogeneous groups, but the groups may need to be different based on the intended purpose (to understand pathophysiology, prevention or prognosis). The question then, is which is needed most by clinicians? Our findings suggest the international expert community prefers subset criteria to be associated with future outcomes, namely response to therapy and prognosis. For example, experts in this study stated it would be ‘helpful to identify patients who have a poor prognosis’ and ‘warrant more aggressive therapy’, thereby conferring more personalized medicine. Ideally subset criteria would help facilitate giving the right drug to the right patient. Once subsets are identified, it is important to evaluate predictors of trajectory, and then ascertain if these predictors can guide treatment. However, it should be remembered that subset classification based on pathophysiology and prognosis may not be stable over time as future outcomes can change.Strengths of this study include interview of a large number of SSc experts, and broad representation of SSc experts from both Europe and North America. We have included the perspective of pediatric rheumatology, dermatology and gastroenterology, which was a limitation of the 2013 ACR EULAR SSc classification criteria. ADDIN EN.CITE <EndNote><Cite><Author>Johnson</Author><Year>2015</Year><RecNum>630</RecNum><DisplayText>(41)</DisplayText><record><rec-number>630</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1467924884">630</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Johnson, S. R.</author></authors></contributors><auth-address>Toronto Scleroderma Program, Mount Sinai Hospital, Toronto Western Hospital, Division of Rheumatology, Department of Medicine, University of Toronto, Ground Floor, East Wing, 399 Bathurst Street, Toronto, ON, Canada, M5T 2S8, Sindhu.Johnson@uhn.ca.</auth-address><titles><title>New ACR EULAR guidelines for systemic sclerosis classification</title><secondary-title>Curr Rheumatol Rep</secondary-title><alt-title>Current rheumatology reports</alt-title></titles><periodical><full-title>Curr Rheumatol Rep</full-title><abbr-1>Current rheumatology reports</abbr-1></periodical><alt-periodical><full-title>Curr Rheumatol Rep</full-title><abbr-1>Current rheumatology reports</abbr-1></alt-periodical><pages>32</pages><volume>17</volume><number>5</number><keywords><keyword>Autoantibodies/blood</keyword><keyword>Conflict (Psychology)</keyword><keyword>Humans</keyword><keyword>*Practice Guidelines as Topic</keyword><keyword>Scleroderma, Systemic/classification/*diagnosis/immunology</keyword><keyword>Sensitivity and Specificity</keyword></keywords><dates><year>2015</year><pub-dates><date>May</date></pub-dates></dates><isbn>1534-6307 (Electronic)
1523-3774 (Linking)</isbn><accession-num>25874345</accession-num><urls><related-urls><url>;(41) However, since we randomly sampled participants from the list of SSc experts attending the Systemic Sclerosis World Congress; and the meeting was predominantly attended by SSc experts from Europe and North America, no SSc experts currently practicing in Asia, Africa or South America were included in this study. In order to develop SSc subset classification criteria that are generalizable globally, it is advised to include the perspectives of these regions in the subsequent phases of criteria development.We used research triangulation in data analysis and provided raw data including quotations, i.e. indicators of qualitative research of high quality.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5OYWtheWFtYTwvQXV0aG9yPjxZZWFyPjIwMTY8L1llYXI+
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ADDIN EN.CITE.DATA (43) The false positive, false negative rates, positive and negative predictive value of the next iteration of subset classification criteria should be evaluated and compared against pre-existing subset criteria. ADDIN EN.CITE <EndNote><Cite><Author>Johnson</Author><Year>2007</Year><RecNum>299</RecNum><DisplayText>(44)</DisplayText><record><rec-number>299</rec-number><foreign-keys><key app="EN" db-id="zst925ashtsrenewferv5d2ppfxaptz0t2zw" timestamp="1327445532">299</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Johnson, S. R.</author><author>Goek, O. N.</author><author>Singh-Grewal, D.</author><author>Vlad, S. C.</author><author>Feldman, B. M.</author><author>Felson, D. T.</author><author>Hawker, G. A.</author><author>Singh, J. A.</author><author>Solomon, D. H.</author></authors></contributors><auth-address>University Health Network, Toronto, Ontario, Canada.</auth-address><titles><title>Classification criteria in rheumatic diseases: a review of methodologic properties</title><secondary-title>Arthritis Rheum</secondary-title></titles><periodical><full-title>Arthritis Rheum</full-title></periodical><pages>1119-33</pages><volume>57</volume><number>7</number><edition>2007/10/02</edition><keywords><keyword>Humans</keyword><keyword>Psychometrics</keyword><keyword>Reproducibility of Results</keyword><keyword>Research Design</keyword><keyword>Rheumatic Diseases/*classification/*drug therapy</keyword></keywords><dates><year>2007</year><pub-dates><date>Oct 15</date></pub-dates></dates><isbn>0004-3591 (Print)
0004-3591 (Linking)</isbn><accession-num>17907227</accession-num><urls><related-urls><url>;(44) In summary, we have synthesized an international view of the construct of SSc subsets in the modern era. A good ‘photograph’ of the present situation has been achieved. We found there are a number of factors underlying the construct of SSc subsets including disease trajectory, prediction of internal organ involvement, response to therapy, prognosis including survival. Data improving our understanding of the relevant domains and their relative importance will inform the study design of the next phase of SSc subset criteria development. Conflicts of InterestMaurizio Cutolo received research support from BMS, Actelion, Mundipharm, and Horizon. ?Nemanja Damjanov has receiving Grants/Research support from Pfizer, MSD, Abbvie, Roche; has been Consultant for Pfizer, Abbvie and Roche; has been Speaker for Pfizer, MSD, Abbvie, Roche, Gedeon Richter, and Boehringer Ingelheim.Ulf Müller-Ladner is funded in part by EULAR/EUSTAR.Lesley Ann Saketkoo has been supported by Boerhringer Ingelheim, Gilead pharmaceuticals, United Therapeutics and Mallinckrodt for educational grants and clinical trials.FundingThis work was supported by a grant from the World Scleroderma Foundation and the National Scleroderma Foundation (US). Dr. Johnson is supported by an Ontario Ministry of Research and Innovation, Ministry of Economic Development, Trade and Employment Early Researcher Award; the Oscar and Eleanor Markovitz fund for Scleroderma Research and the Freda Fejer fund for Scleroderma Research.REFERENCES ADDIN EN.REFLIST 1.Johnson SR, Feldman BM, Hawker GA. Classification criteria for systemic sclerosis subsets. J Rheumatol. 2007;34:1855-63.2.Barnett AJ, Coventry DA. Scleroderma. 1. Clinical features, course of illness and response to treatment in 61 cases. Med J Aust. 1969;1:992-1001.3.Goetz R, Berne M. The pathophysiology of progressive systemic sclerosis (generalised scleroderma) with special reference to changes in the viscere. Clin Proc. 1945;4:337-92.4.Goetz RH. The pathophysiology of progressive systemic sclerosis (generalized scleroderma) with special reference to changes in the fiscera. Cape Town Post Graduate Medical Association. 1945;4 337-92.5.Winterbauer RH. 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A working classification of scleroderma spectrum disorders: a proposal and the results of testing on a sample of patients. Clin Exp Rheumatol. 2004;22:S5-13.17.Cottrell TR, Wise RA, Wigley FM, Boin F. The degree of skin involvement identifies distinct lung disease outcomes and survival in systemic sclerosis. Ann Rheum Dis. 2014;73:1060-6.18.Patterson KA, Roberts-Thomson PJ, Lester S, Tan JA, Hakendorf P, Rischmueller M, et al. Interpretation of an Extended Autoantibody Profile in a Well-Characterized Australian Systemic Sclerosis (Scleroderma) Cohort Using Principal Components Analysis. Arthritis Rheumatol. 2015;67:3234-44.19.Barnett AJ, Miller MH, Littlejohn GO. A survival study of patients with scleroderma diagnosed over 30 years (1953-1983): the value of a simple cutaneous classification in the early stages of the disease. JRheumatol. 1988;15:276-83.20.Hesselstrand R, Scheja A, Akesson A. Mortality and causes of death in a Swedish series of systemic sclerosis patients. 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Arthritis Rheum. 2001;44:2828-35.35.Domsic RT, Rodriguez-Reyna T, Lucas M, Fertig N, Medsger TA, Jr. Skin thickness progression rate: a predictor of mortality and early internal organ involvement in diffuse scleroderma. Ann Rheum Dis. 2011;70:104-9.36.Ligon CB, Wigley FM. Editorial: Scleroderma: Bringing a Disease From Black-and-White Into Technicolor. Arthritis Rheumatol. 2015;67:3101-3.37.van den Hoogen F, Khanna D, Fransen J, Johnson SR, Baron M, Tyndall A, et al. 2013 classification criteria for systemic sclerosis: an American College of Rheumatology/European League against Rheumatism collaborative initiative. Arthritis Rheum. 2013;65:2737-47.38.Domsic RT. Scleroderma: the role of serum autoantibodies in defining specific clinical phenotypes and organ system involvement. Curr Opin Rheumatol. 2014;26:646-52.39.Borsboom D, Mellenbergh GJ, van Heerden J. The theoretical status of latent variables. Psychol Rev. 2003;110:203-19.40.Duffy CM, Feldman BM. Textbook of Pediatric Rheumatology. Seventh ed. Petty RE, Laxer RM, Lindsley CB, Wedderburn LR, editors: Elsevier; 2016.41.Johnson SR. New ACR EULAR guidelines for systemic sclerosis classification. Curr Rheumatol Rep. 2015;17:32.42.Johnson SR, O'Brien KK. Qualitative Methods in Systemic Sclerosis Research. J Rheumatol. 2016;43:1265-7.43.Aggarwal R, Ringold S, Khanna D, Neogi T, Johnson SR, Miller A, et al. Distinctions Between Diagnostic and Classification Criteria? Arthritis Care Res (Hoboken). 2015;67:891-7.44.Johnson SR, Goek ON, Singh-Grewal D, Vlad SC, Feldman BM, Felson DT, et al. Classification criteria in rheumatic diseases: a review of methodologic properties. Arthritis Rheum. 2007;57:1119-33.Table 1. Summary of participant characteristicsCharacteristicsn=30Male sex n (%)20 (67%)Geographic region Europe n (%)19 (63%) Sweden 1 United Kingdom 4 Italy 2 Germany 5 France 1 Netherlands 1 Switzerland 1 Hungary 1 Serbia 1 Spain 1 Poland 1 North America n (%)11 (37%) Canada 1 United States of America 10Specialty Adult rheumatology n (%)26 (87%) Pediatric rheumatology n (%) 1 (3%) Adult and pediatric rheumatology n (%)1 (3%) Dermatology n (%)1 (3%) Gastroenterology n (%)1 (3%)Number of years in practice seeing SSc patients median (IQR)22.5 (17.3)Number of new SSc patients seen per year median (IQR)55 (120)Conduct of SSc research n (%)30 (100%)Use of SSc subset criteria n (%)30 (100%)Figure 1. Circle graph illustrating the thematic clusters ‘Management’ for the purpose of systemic sclerosis subset criteria. Figure 2. Circle graph illustrating the thematic cluster ‘Prognosis’ for the purpose of systemic sclerosis subset criteria. Figure 3. Circle graph illustrating the thematic cluster ‘Types of outcomes’ for the purpose of systemic sclerosis subset criteria. Figure 4. Circle graph illustrating the thematic cluster “Research and Communication’ for the purpose of systemic sclerosis subset criteria. Figure 5. Number of subsetsFigure 6. Illustrative example of hierarchical clustering for systemic sclerosis subsets ................
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