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Running Head: Myositis Response Criteria Methodology2016 ACR-EULAR Adult Dermatomyositis and Polymyositis and Juvenile Dermatomyositis Response Criteria—Methodological AspectsLisa G. Rider*1, Nicolino Ruperto*2, Angela Pistorio3, Brian Erman4, Nastaran Bayat1, Peter A. Lachenbruch1, Howard Rockette5, Brian M. Feldman6, Adam M. Huber7, Paul Hansen8, Chester V. Oddis9, Ingrid E. Lundberg10, Anthony A. Amato11, Hector Chinoy12, Robert G. Cooper13, Lorinda Chung14, Katalin Danko15, David Fiorentino16, Ignacio Garcia de la Torre17, Ann M. Reed18, Yeong Wook Song19, Rolando Cimaz20, Rubén J. Cuttica21, Clarissa A. Pilkington22, Alberto Martini2,23, Janjaap van der Net24, Susan Maillard22, Frederick W. Miller1, Jiri Vencovsky**25, and Rohit Aggarwal**9 For the International Myositis Assessment and Clinical Studies Group (IMACS) and the Paediatric Rheumatology International Trials Organisation (PRINTO)26 *co-first and **co-last authors1Lisa G. Rider, MD, Nastaran Bayat, MD, Peter A. Lachenbruch, PhD, Frederick W. Miller, MD, PhD: Environmental Autoimmunity Group, NIEHS, NIH, Bethesda, MD; 2Nicolino Ruperto, MD, MPH, Alberto Martini, MD: Istituto Giannina Gaslini, Pediatria II, PRINTO, Genoa, Italy; 3Angela Pistorio MD PhD: Istituto Giannina Gaslini, Servizio di Epidemiologia e Biostatistica, Genoa, Italy; 4Brian Erman, MS: Social and Scientific Systems, Inc., Durham, NC; 5Howard Rockette, PhD: Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA; 6Brian M. Feldman, MD, MSc, FRCPC: The Hospital for Sick Children, Toronto, Ontario, Canada; 7Adam M. Huber, MD: IWK Health Centre, Halifax, Nova Scotia, Canada; 8Paul Hansen, PhD: University of Otago, Dunedin, New Zealand; 9Chester V. Oddis, MD, Rohit Aggarwal, MD, MSc: Department of Medicine, Division of Rheumatology and Clinical Immunology, University of Pittsburgh, Pittsburgh, PA; 10Ingrid Lundberg, MD: Rheumatology Unit, Karolinska University Hospital, Karolinska Institute, Stockholm, Sweden; 11Anthony A. Amato, MD: Brigham and Women’s Hospital and Harvard Medical School, Boston, MA; 12Hector Chinoy, PhD, MRCP: National Institute of Health Research Manchester Musculoskeletal Biomedical Research Unit, University of Manchester, Manchester, United Kingdom; 13Robert G. Cooper, MD: Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK; 14Lorinda Chung, MD: Division of Rheumatology, Stanford University, Redwood City, CA; 15Katalin Danko, MD, PhD, DSc: University of Debrecen, Debrecen, Hungary; 16David Fiorentino, MD, PhD: Department of Dermatology, Stanford University, Redwood City, CA; 17Ignacio Garcia de la Torre: Hospital General de Occidente de la Secretaría de Salud, Guadalajara, Jalisco, Mexico; 18Ann M. Reed, MD: Duke University, Durham, NC; 19Yeong Wook Song, MD, PhD: Department of Molecular Medicine and Biopharmaceutical Sciences, Medical Research Center, Seoul National University, Seoul, Korea; 20Rolando Cimaz, MD: University of Florence, Florence, Italy; 21Rubén J. Cuttica, MD: Hospital de Ni?os Pedro de Elizalde, University of Buenos Aires, Buenos Aires, Argentina; 22Clarissa A. Pilkington, BSc, MBBS, MRCP, Susan Maillard, MD: Great Ormond Street Hospital for Children NHS Trust, London, United Kingdom; 23Alberto Martini, MD: Università degli Studi di Genova, Dipartimento di Pediatria, Genoa, Italy; 24Janjaap van der Net, PhD, PT, PCS: Wilhelmina Children's Hospital, University Medical Center, Utrecht, The Netherlands; 25Jiri Vencovsky, MD, PhD: Institute of Rheumatology and Department of Rheumatology, Charles University, Prague, Czech Republic Running Title: Myositis Response Criteria MethodologyKey words: dermatomyositis, polymyositis, juvenile dermatomyositis, response criteria, 1000Minds software, conjoint analysis, hybrid measure, outcome assessmentThis work was supported in part by the American College of Rheumatology, the European League Against Rheumatism, the intramural research program of the National Institutes of Health, National Institute of Environmental Health Sciences, the National Center for Advancing Translational Sciences, and the National Institute of Arthritis and Musculoskeletal and Skin Diseases, Istituto Giannina Gaslini Genova (Italy) and the Paediatric Rheumatology International Trials Organisation (PRINTO), Cure JM Foundation, Myositis UK, and The Myositis Association. Address correspondence to:Rohit Aggarwal M.D., M.Sc.Division of Rheumatology and Clinical Immunology Department of Medicine University of Pittsburgh 3601 5th Avenue, Suite 2BPittsburgh, PA 15261, USAPhone: 412-383-8100Fax: 412-383-8864E-mail: aggarwalr@upmc.edu26Appendix of contributors: Steering Committee: Lisa Rider (Co-Principal Investigator), Nicolino Ruperto (Co-Principal Investigator), Rohit Aggarwal (Methodology Lead), Frederick Miller, Jiri VencovskyStatistical Team: Rohit Aggarwal, Brian Erman, Nastaran Bayat, Angela Pistorio, Adam Huber, Paul Hansen, Brian Feldman, Howard Rockette, Peter Lachenbruch, Nicolino Ruperto, Lisa RiderAdult Core Set Survey Group: Anthony A. Amato, Hector Chinoy, Lisa Christopher-Stine, Lorinda Chung, Robert Cooper, Lisa Criscione-Schreiber, Leslie Crofford, Mary E. Cronin, David Fiorentino, Ignacio Garcia de la Torre, Katalin Dankó, Patrick Gordon, Gerald Hengstman, James D. Katz, Andrew Mammen, Galina Marder, Neil McHugh, Chester Oddis, Elena Schiopu, Albert Selva-O'Callaghan, Yeong Wook Song, Jiri Vencovsky, Gil Wolfe, Robert Wortmann Pediatric Core Set Survey Group: Maria Apaz, Suzanne Bowyer, Rolando Cimaz, Tamás Constantin, Megan Curran, Joyce Davidson, Brian Feldman, Thomas Griffin, Adam Huber, Olcay Jones, Susan Kim, Bianca Lang, Carol Lindsley, Daniel Lovell, Claudia Saad Magalhaes, Lauren M. Pachman, Clarissa Pilkington, Andrea Ponyi, Marilynn Punaro, Pierre Quartier, Athimalaipet V. Ramanan, Angelo Ravelli, Ann Reed, Robert Rennebohm, Annet Van Royen-Kerkhof, David D. Sherry, Clovis A. Silva, Elizabeth Stringer, Carol WallaceClinical trial or natural history study data set contributors: Anthony A. Amato, Hector Chinoy, Lorinda Chung, Robert Cooper, Katalin Dankó, David Fiorentino, Ignacio Garcia de la Torre, Mark Gourley, Ingrid E. Lundberg, Frederick Miller, Chester Oddis, Paul Plotz, Ann Reed, Lisa Rider, Nicolino Ruperto and members of PRINTO, Yeong Wook Song, Jiri VencovskyAdult Patient Profile Working Group: Rohit Aggarwal, Anthony A. Amato, Dana Ascherman, Richard Barohn, Olivier Benveniste, Jan De Bleecker, Jeffrey Callen, Christina Charles-Schoeman, Hector Chinoy, Lisa Christopher-Stine, Lorinda Chung, Robert Cooper, Leslie Crofford, Mary E. Cronin, Katalin Dankó, Sonye Danoff, Maryam Dastmalchi, Ignacio Garcia de la Torre, Mazen Dimachkie, Steve DiMartino, Lyubomir Dourmishev, Floranne Ernste, David Fiorentino, Takahisa Gono, Patrick Gordon, Mark Gourley, David Isenberg, Yasuhiro Katsumata, James D. Katz, John Kissel, Richard L. Leff, Todd Levine, Ingrid E. Lundberg, Andrew Mammen, Herman Mann, Galina Marder, Isabelle Marie, Neil McHugh, Joseph Merola, Frederick Miller, Chester Oddis, Marzena Olesinska, Nancy Olsen, Nicolo Pipitone, Sindhu Ramchandren, Seward Rutkove, Lesley Ann Saketkoo, Adam Schiffenbauer, Albert Selva-O'Callaghan, Samuel Katsuyuki Shinjo, Rachel Shupak, Yeong Wook Song, Katarzyna Swierkocka, Jiri Vencovsky, Marianne de Visser, Julia Wanschitz, Victoria P. Werth, Irene Whitt, Robert Wortmann, Steven YtterbergPediatric Patient Profile Working Group: Maria Apaz, Tadej Avcin, Mara Becker, Michael W. Beresford, Rolando Cimaz, Tamás Constantin, Megan Curran, Ruben Cuttica, Joyce Davidson, Frank Dressler, Jeffrey Dvergsten, Brian Feldman, Virginia Paes Leme Ferriani, Berit Flato, Valeria Gerloni, Thomas Griffin, Michael Henrickson, Claas Hinze, Mark Hoeltzel, Adam Huber, Maria Ibarra, Norman Ilowite, Lisa Imundo, Olcay Jones, Susan Kim, Daniel Kingsbury, Bianca Lang, Carol Lindsley, Daniel Lovell, Alberto Martini, Claudia Saad Magalhaes, Bo Magnusson, Sheilagh Maguiness, Susan Maillard, Pernille Mathiesen, Liza McCann, Susan Nielsen, Sheila Knupp Feitosa de Oliveira, Lauren M. Pachman, Murray Passo, Clarissa Pilkington, Marilynn Punaro, Pierre Quartier, Egla Rabinovich, Athimalaipet V. Ramanan, Angelo Ravelli, Ann Reed, Robert Rennebohm, Lisa Rider, Rafael Rivas-Chacon, Angela Byun Robinson, Kelly Rouster-Stevens, Annet Van Royen-Kerkhof, Ricardo Russo, Lidia Rutkowska-Sak, Adriana Sallum, Helga Sanner, Heinrike Schmeling, Duygu Selcen, Bracha Shaham, David D. Sherry, Clovis A. Silva, Charles H. Spencer, Robert Sundel, Marc Tardieu, Akaluck Thatayatikom, Janjaap Van Der Net, Dawn Wahezi, Carol Wallace, Francesco ZulianConjoint Analysis—Adult Group: Rohit Aggarwal, Anthony A. Amato, Hector Chinoy, Lisa Christopher-Stine, Lorinda Chung, Robert Cooper, Mary E. Cronin, Katalin Dankó, Mazen Dimachkie, Steve Di Martino, David Fiorentino, Ignacio Garcia de la Torre, Patrick Gordon, Ingrid E. Lundberg, Herman Mann, Frederick Miller, Chester Oddis, Albert Selva-O'Callaghan, Jiri Vencovsky, Victoria P. Werth, Robert Wortmann, Steven YtterbergConjoint Analysis—Pediatric Group: Rolando Cimaz, Tamás Constantin, Ruben Cuttica, Joyce Davidson, Frank Dressler, Brian Feldman, Thomas Griffin, Michael Henrickson, Adam Huber, Lisa Imundo, Bianca Lang, Carol Lindsley, Claudia Saad Magalhaes, Bo Magnusson, Susan Maillard, Sheila Knupp Feitosa de Oliveira, Lauren M. Pachman, Murray Passo, Clarissa Pilkington, Marilynn Punaro, Angelo Ravelli, Ann Reed, Lisa Rider, Kelly Rouster-Stevens, Annet Van Royen-Kerkhof, Ricardo Russo, Bracha Shaham, Robert Sundel, Janjaap Van der NetAbstractObjective. To describe the methodology used to develop new response criteria for adult dermatomyositis (DM)/polymyositis (PM) and juvenile dermatomyositis (JDM).Methods. Patient profiles from prospective natural history data and clinical trials were rated by myositis specialists to develop consensus gold-standard ratings of minimal, moderate, and major improvement. Experts completed a survey regarding clinically meaningful improvement in the core set measures (CSM) and a conjoint-analysis survey (using 1000Minds software) to derive relative weights of CSM and candidate definitions. Six types of candidate definitions for response criteria were derived using survey results, logistic regression, conjoint analysis, applying conjoint-analysis weights to CSM, and published definitions. Sensitivity, specificity, and area under the curve (AUC) were defined for candidate criteria using consensus patient profile data, and selected definitions were validated using clinical trial data.Results. Myositis specialists defined the degree of clinically meaningful improvement in CSM for minimal, moderate, and major improvement. The conjoint-analysis survey established the relative weights of CSM, with muscle strength and Physician Global Activity as most important. Many candidate definitions showed excellent sensitivity, specificity, and AUC in the consensus profiles. Trial validation showed that a number of candidate criteria differentiated between treatment groups. Top candidate criteria definitions were presented at the consensus conference.Conclusion. Consensus methodology with definitions tested on patient profiles and validated using clinical trials, led to 18 definitions for adult PM/DM and 14 for JDM as excellent candidates for consideration in the final consensus on new response criteria for myositis. Significance and InnovationsThese updated criteria for minimal, moderate, and major response will enable researchers to meaningfully compare data across studies, conduct more efficient drug trials, and may lead to new therapies for myositis.The response criteria are both data- and expert consensus-driven, with excellent sensitivity, specificity, and face validity.The novel 1000Minds software and conjoint analysis were used to derive these criteria.Myositis is a heterogeneous, systemic autoimmune disease requiring multiple outcome measures and composite response criteria for meaningful clinical trials and therapeutic development. Myositis core set activity measures (CSM) for patients with adult dermatomyositis or polymyositis (DM/PM) or juvenile dermatomyositis (JDM) were established and validated by the International Myositis Assessment and Clinical Studies Group (IMACS) and the Paediatric Rheumatology International Trials Organisation (PRINTO) PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJpZGVyPC9BdXRob3I+PFllYXI+MjAxMTwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA [1, 2]. The IMACS CSM include Physician and Patient/Parent Global Activity, muscle strength measured by manual muscle testing (MMT), physical function measured by the (Childhood) Health Assessment Questionnaire (CHAQ or HAQ), Extramuscular Global Activity measured using Myositis Disease Activity Assessment Tool (MDAAT), and the most abnormal serum muscle enzyme (Supplementary Table 1) PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJpZGVyPC9BdXRob3I+PFllYXI+MjAxMTwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA [1, 3]. The PRINTO CSM are similar but include the Childhood Myositis Assessment Scale (CMAS) instead of MMT, the global Disease Activity Score (DAS) instead of Extramuscular Global Activity, and health-related quality of life (Physical Summary Score of the Child Health Questionnaire [CHQ-PhS]), but not muscle enzymes PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJ1cGVydG88L0F1dGhvcj48WWVhcj4yMDA4PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA [11-15], may increase the sensitivity and specificity of response criteria. Trial validation is also now required for final response criteria per American College of Rheumatology and European League Against Rheumatism guidelines ADDIN REFMGR.CITE <Refman><Cite><Author>Singh</Author><Year>2006</Year><RecNum>11872</RecNum><IDText>Development of classification and response criteria for rheumatic diseases</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>11872</Ref_ID><Title_Primary>Development of classification and response criteria for rheumatic diseases</Title_Primary><Authors_Primary>Singh,J.A.</Authors_Primary><Authors_Primary>Solomon,D.H.</Authors_Primary><Authors_Primary>Dougados,M.</Authors_Primary><Authors_Primary>Felson,D.</Authors_Primary><Authors_Primary>Hawker,G.</Authors_Primary><Authors_Primary>Katz,P.</Authors_Primary><Authors_Primary>Paulus,H.</Authors_Primary><Authors_Primary>Wallace,C.</Authors_Primary><Date_Primary>2006/6/15</Date_Primary><Keywords>Americas</Keywords><Keywords>arthritis</Keywords><Keywords>AS</Keywords><Keywords>classification</Keywords><Keywords>clinical</Keywords><Keywords>criteria</Keywords><Keywords>Disease</Keywords><Keywords>Editorial</Keywords><Keywords>Endpoint Determination</Keywords><Keywords>ERYTHEMATOSUS</Keywords><Keywords>La</Keywords><Keywords>lupus</Keywords><Keywords>lupus erythematosus</Keywords><Keywords>methods</Keywords><Keywords>Outcome Assessment (Health Care)</Keywords><Keywords>Patients</Keywords><Keywords>Research</Keywords><Keywords>Rheumatic Diseases</Keywords><Keywords>rheumatoid arthritis</Keywords><Keywords>RHEUMATOID-ARTHRITIS</Keywords><Keywords>Rheumatology</Keywords><Keywords>Science</Keywords><Keywords>Societies,Scientific</Keywords><Keywords>standards</Keywords><Keywords>systemic lupus erythematosus</Keywords><Keywords>THERAPY</Keywords><Keywords>treatment</Keywords><Keywords>Treatment Outcome</Keywords><Reprint>Not in File</Reprint><Start_Page>348</Start_Page><End_Page>352</End_Page><Periodical>Arthritis Rheum.</Periodical><Volume>55</Volume><Issue>3</Issue><Web_URL>PM:16739201</Web_URL><ZZ_JournalStdAbbrev><f name="System">Arthritis Rheum.</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>[16]. Our objective was to use data-driven and expert group decision-making (consensus) processes to develop new response criteria for DM/PM and JDM based on the six CSM of IMACS or PRINTO with data from new cohorts and clinical trials. METHODS Overview. Adult and juvenile myositis experts with experience in using the CSM participated in expert working groups (Supplementary Table 2). They rated clinically meaningful improvement in the CSM for minimal, moderate, and major improvement. Next, patient profiles were developed from natural history data and clinical trials PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJ1cGVydG88L0F1dGhvcj48WWVhcj4yMDAzPC9ZZWFyPjxS
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ADDIN EN.CITE.DATA [4, 5, 8] (Supplementary Figure 1). Experts then rated the degree of improvement in patient profiles using Delphi technique PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJ1cGVydG88L0F1dGhvcj48WWVhcj4yMDA4PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA [17, 18]; ≥70% consensus was reached on minimal, moderate, and major improvement. Conjoint-analysis surveys (using 1000Minds software) ADDIN REFMGR.CITE <Refman><Cite><Author>Hansen</Author><Year>2008</Year><RecNum>12436</RecNum><IDText>A new method for scoring additive multi-attribute value models using pairwise rankings of alternatives</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>12436</Ref_ID><Title_Primary>A new method for scoring additive multi-attribute value models using pairwise rankings of alternatives</Title_Primary><Authors_Primary>Hansen,P.</Authors_Primary><Authors_Primary>Ombler,F.</Authors_Primary><Date_Primary>2008</Date_Primary><Reprint>In File</Reprint><Start_Page>87</Start_Page><End_Page>107</End_Page><Periodical>J Multi-Crit Decis Anal</Periodical><Volume>15</Volume><ZZ_JournalFull><f name="System">J Multi-Crit Decis Anal</f></ZZ_JournalFull><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>[11] were completed by a subset of experts, and relative weights of CSM and conjoint analysis–based candidate definitions for response criteria were derived. Sensitivity, specificity, and area under the curve (AUC) were derived for each candidate definition by using experts’ consensus ratings of improvement from patient profiles as a gold standard. The best-performing candidate definitions were validated using data from randomized clinical trials, and top candidate definitions were taken to the consensus conference to develop new myositis response criteria for PM/DM and JDM (Supplementary Figure 1) PFJlZm1hbj48Q2l0ZT48QXV0aG9yPkhhc2lqYTwvQXV0aG9yPjxZZWFyPjIwMTE8L1llYXI+PFJl
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ADDIN EN.CITE.DATA [10, 19]. The overview and time line of the methodology is given in Figure 1.Clinically meaningful improvement in myositis CSM. Adult and juvenile myositis specialists completed an online Delphi expert survey regarding the degree of change in each CSM deemed clinically significant, including the relative percent change (defined as final minus baseline value, divided by baseline, multiplied by 100) and the absolute change deemed necessary for minimal, moderate, and major clinical improvement in a therapeutic trial. The survey also assessed the minimum number of, and which, CSM must improve and the maximum number of, and which, CSM can worsen for a patient to be considered improved ADDIN REFMGR.CITE <Refman><Cite><Author>Rider</Author><Year>2011</Year><RecNum>11758</RecNum><IDText>Defining clinically relevant changes in core set activity measures for adult and juvenile idiopathic inflammatory myopathies (IIM)</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>11758</Ref_ID><Title_Primary>Defining clinically relevant changes in core set activity measures for adult and juvenile idiopathic inflammatory myopathies (IIM)</Title_Primary><Authors_Primary>Rider,L.G.</Authors_Primary><Authors_Primary>Lee,J</Authors_Primary><Authors_Primary>Jansen,A.</Authors_Primary><Authors_Primary>Ruperto,N.</Authors_Primary><Authors_Primary>Huber,A.M.</Authors_Primary><Authors_Primary>Oddis,C.V.</Authors_Primary><Authors_Primary>Feldman,B.M.</Authors_Primary><Authors_Primary>Lachenbruch,P.</Authors_Primary><Authors_Primary>Aggarwal,R.</Authors_Primary><Authors_Primary>Miller,F.W.</Authors_Primary><Authors_Primary>IMACS Group</Authors_Primary><Authors_Primary>PRINTO</Authors_Primary><Date_Primary>2011</Date_Primary><Keywords>activity</Keywords><Keywords>Adult</Keywords><Keywords>core set</Keywords><Keywords>IIM</Keywords><Keywords>juvenile</Keywords><Keywords>measures</Keywords><Keywords>myopathy</Keywords><Reprint>Not in File</Reprint><Start_Page>S89</Start_Page><Periodical>Arthritis Rheum</Periodical><Volume>63 (Suppl)</Volume><ZZ_JournalStdAbbrev><f name="System">Arthritis Rheum</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>[20]. Adult and pediatric patient profiles. Six natural history studies and five trials were used to create 270 adult DM/PM patient profiles consisting of IMACS CSM (Supplementary Table 3) PFJlZm1hbj48Q2l0ZT48QXV0aG9yPkx1bmRiZXJnPC9BdXRob3I+PFllYXI+MjAxMzwvWWVhcj48
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ADDIN EN.CITE.DATA [7, 8]. The Bohan and Peter criteria were used for classification ADDIN REFMGR.CITE <Refman><Cite><Author>Bohan</Author><Year>1975</Year><RecNum>2225</RecNum><IDText>Polymyositis and dermatomyositis (parts 1 and 2).</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>2225</Ref_ID><Title_Primary>Polymyositis and dermatomyositis (parts 1 and 2).</Title_Primary><Authors_Primary>Bohan,A.</Authors_Primary><Authors_Primary>Peter,J.B.</Authors_Primary><Date_Primary>1975</Date_Primary><Keywords>IIM</Keywords><Reprint>In File</Reprint><Start_Page>344-347,</Start_Page><End_Page>403-407</End_Page><Periodical>New Engl.J.Med.</Periodical><Volume>292</Volume><ZZ_JournalFull><f name="System">New Engl.J.Med.</f></ZZ_JournalFull><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>[26]. The PRINTO prospective cohort and IMACS natural history study were used to create 299 JDM patient profiles PFJlZm1hbj48Q2l0ZT48QXV0aG9yPkxhemFyZXZpYzwvQXV0aG9yPjxZZWFyPjIwMTM8L1llYXI+
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ADDIN EN.CITE.DATA [9, 10]. For each JDM patient, two profiles were created, one using IMACS and one using PRINTO CSM. These IMACS and PRINTO profiles were administered separately to the pediatric experts in a randomized order. For each profile, the CSM at baseline and at 4–12 months’ follow-up, the absolute change, and relative percent change in each measure were presented. Raters scored each profile as “unchanged or worse,” “minimally improved,” “moderately improved,” or “majorly improved” and rated the degree of improvement on a scale of 0–10 (Supplementary Figure 1). Profiles that did not reach consensus were re-rated, and those without consensus after two rounds were discarded. Derivation of candidate definitions. Candidate definitions for response criteria were derived and tested for sensitivity, specificity, and AUC, using the experts’ consensus ratings of patient profiles as the gold standard (Supplementary Table 4). Definitions were examined using relative and absolute percent change (final minus baseline divided by the range, multiplied by 100) in CSM. Supplementary Table 4 shows the types of candidate definitions. Three types of candidate definitions were categorical, which included previously published, newly drafted definitions using Delphi expert survey, and weighted definitions. The previously published and newly drafted categorical candidate definitions required a certain number of CSM to improve by varying thresholds while allowing up to two CSM to worsen by certain thresholds. The weighted definitions were derived by applying relative weights to the categorical definitions. Three other types of candidate definitions were continuous definitions, where total improvements score are generated with thresholds for minimal, moderate, and major improvement. These included logistic regression, CSM weighted and conjoint analysis–based definitions (Supplementary Table 4). Continuous candidate definitions were hybrid definitions where the same definition can be used either as a continuous outcome measure using the total improvement score or as a categorical outcome measure using the thresholds for minimal, moderate, and major improvement. The logistic regression–derived definitions were developed using randomly selected patient profile data (two-thirds of the dataset) and standard logistic regression modeling. Expert consensus rating of minimal, moderate, and major improvement was the dependent variable (gold standard), and relative or absolute percent changes in each CSM were independent variables. The cutoff for an optimum sensitivity-specificity trade-off for improved versus not improved was selected based on the Youden index ADDIN REFMGR.CITE <Refman><Cite><Author>Youden</Author><Year>1950</Year><RecNum>12447</RecNum><IDText>Index for rating diagnostic tests</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>12447</Ref_ID><Title_Primary>Index for rating diagnostic tests</Title_Primary><Authors_Primary>Youden,WJ</Authors_Primary><Date_Primary>1950</Date_Primary><Keywords>index</Keywords><Reprint>In File</Reprint><Start_Page>32</Start_Page><End_Page>35</End_Page><Periodical>Cancer</Periodical><Volume>3</Volume><ZZ_JournalStdAbbrev><f name="System">Cancer</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>[27]. Each model underwent internal validation using the remaining third of the dataset and external validation using clinical trial data. Weighted CSM candidate definitions were derived by multiplying the relative or absolute percent improvement or worsening in each CSM by its relative weight (developed in the conjoint-analysis surveys) and then summing the results of all CSM as total improvement score. Conjoint-analysis surveys and candidate definitions. Conjoint-analysis surveys were administered to subgroups of myositis experts using 1000Minds online software ADDIN REFMGR.CITE <Refman><Cite><Author>Hansen</Author><Year>2008</Year><RecNum>12436</RecNum><IDText>A new method for scoring additive multi-attribute value models using pairwise rankings of alternatives</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>12436</Ref_ID><Title_Primary>A new method for scoring additive multi-attribute value models using pairwise rankings of alternatives</Title_Primary><Authors_Primary>Hansen,P.</Authors_Primary><Authors_Primary>Ombler,F.</Authors_Primary><Date_Primary>2008</Date_Primary><Reprint>In File</Reprint><Start_Page>87</Start_Page><End_Page>107</End_Page><Periodical>J Multi-Crit Decis Anal</Periodical><Volume>15</Volume><ZZ_JournalFull><f name="System">J Multi-Crit Decis Anal</f></ZZ_JournalFull><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>[11]. Experts were presented with pairs of hypothetical patients; each patient had different levels of improvement in the same two CSM, assuming other CSM remained the same. Experts chose which patient had greater improvement, that both had equal improvement, or that the scenario was not possible (Supplementary Figure 2). Based on the rater’s response, all other hypothetical patients that could be pairwise ranked were eliminated via the property of transitivity, thereby significantly reducing the number of scenarios presented. The PAPRIKA (Potentially All Pairwise Rankings of All Possible Alternatives) method determined the mean weights and relative importance of the CSM, using mathematical methods based on linear programming ADDIN REFMGR.CITE <Refman><Cite><Author>Hansen</Author><Year>2008</Year><RecNum>12436</RecNum><IDText>A new method for scoring additive multi-attribute value models using pairwise rankings of alternatives</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>12436</Ref_ID><Title_Primary>A new method for scoring additive multi-attribute value models using pairwise rankings of alternatives</Title_Primary><Authors_Primary>Hansen,P.</Authors_Primary><Authors_Primary>Ombler,F.</Authors_Primary><Date_Primary>2008</Date_Primary><Reprint>In File</Reprint><Start_Page>87</Start_Page><End_Page>107</End_Page><Periodical>J Multi-Crit Decis Anal</Periodical><Volume>15</Volume><ZZ_JournalFull><f name="System">J Multi-Crit Decis Anal</f></ZZ_JournalFull><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>[11]. Adult PM/DM conjoint-analysis surveys were administered using pairs of patients representing different degrees of improvement in IMACS CSM, whereas two separate surveys representing the same patients were administered for JDM using IMACS and PRINTO CSM. For each CSM, the total potential range of the relative percent improvement was divided into five levels, ensuring that the patient profile data were distributed among them. Six CSM with five levels resulted in an average of 85 pairwise-ranking questions. Results from the conjoint-analysis surveys resulted in development of six conjoint-analysis candidate definitions that combine continuous improvement scores and categorical threshold criteria into a single definition (therefore called a hybrid definition) ADDIN REFMGR.CITE <Refman><Cite><Author>American College of Rheumatology Committee to Reevaluate Improvement Criteria</Author><Year>2007</Year><RecNum>12507</RecNum><IDText>A proposed revision to the ACR20: the hybrid measure of American College of Rheumatology response</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>12507</Ref_ID><Title_Primary>A proposed revision to the ACR20: the hybrid measure of American College of Rheumatology response</Title_Primary><Authors_Primary>American College of Rheumatology Committee to Reevaluate Improvement Criteria</Authors_Primary><Date_Primary>2007</Date_Primary><Keywords>Rheumatology</Keywords><Reprint>In File</Reprint><Start_Page>193-202</Start_Page><Periodical>Arthritis Rheum</Periodical><Volume>57</Volume><Issue>2</Issue><User_Def_1>Erratum in Arthritis Rheum. 2007 Dec 15;57(8):1574</User_Def_1><ZZ_JournalStdAbbrev><f name="System">Arthritis Rheum</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>[28]. Relative weights of CSMs and their levels of improvement were used to develop a scoring system such that when all six CSMs are considered together, the maximum score possible for representing a patient's improvement is 100 and the minimum score is 0. The performance of each candidate criterion was evaluated by using randomly selected two-thirds of the patient profile data and by using consensus ratings for minimal, moderate, or major improvement as the gold standard. Appropriate improvement thresholds in adult and pediatric patients were selected for each conjoint-analysis definition based on optimum sensitivity and specificity [using the Youden index ADDIN REFMGR.CITE <Refman><Cite><Author>Youden</Author><Year>1950</Year><RecNum>12447</RecNum><IDText>Index for rating diagnostic tests</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>12447</Ref_ID><Title_Primary>Index for rating diagnostic tests</Title_Primary><Authors_Primary>Youden,WJ</Authors_Primary><Date_Primary>1950</Date_Primary><Keywords>index</Keywords><Reprint>In File</Reprint><Start_Page>32</Start_Page><End_Page>35</End_Page><Periodical>Cancer</Periodical><Volume>3</Volume><ZZ_JournalStdAbbrev><f name="System">Cancer</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>[27]]. We simplified the points given to each level of improvement in CSMs by rounding to the nearest multiple of 2.5, and then we re-evaluated the sensitivity, specificity, and AUC. These thresholds for minimal, moderate, and major improvement were then validated on the remaining third of the patient profile data and further validated using clinical trial data. The thresholds differed for adult PM/DM and JDM for each candidate definition. External validation. The candidate definitions that performed well using consensus profile data were externally validated using data from two controlled trials. The Rituximab in Myositis (RIM) trial PFJlZm1hbj48Q2l0ZT48QXV0aG9yPk9kZGlzPC9BdXRob3I+PFllYXI+MjAxMzwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA [23], which was used for adult DM/PM patients (n = 142), was a randomized double-blind placebo-phased trial where one group received active treatment early (week 0) and the other group received treatment late (week 8); primary outcome was time to improvement. Since the trial did not discriminate between treatment arms, we were unable to determine whether the candidate definitions differentiated between early vs. late treatments. The treating physician’s rating of improvement (0-7 scale) at 24 weeks in the RIM trial was used for validation, and each point change in physician rating was considered clinically significant. Mann-Whitney U-test was used to evaluate whether each candidate definition could differentiate between the treating physician’s median rating of improvement, if the improvement criteria were met compared to not met. For JDM, data from 48 patients in the RIM trial were used with IMACS CSM, as described for adults. We also utilized data from 139 patients in a PRINTO trial of prednisone alone versus prednisone combined with either methotrexate or cyclosporine, which utilized both IMACS and PRINTO CSM PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJ1cGVydG88L0F1dGhvcj48WWVhcj4yMDE2PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA [19]. For the PRINTO trial, the ability of a candidate definition to differentiate between treatment arms at 24 weeks was evaluated using a chi-square test to compare the frequency of patients meeting the candidate response criteria between the two treatment arms. The candidate definitions for JDM had to meet performance standards for both IMACS and PRINTO measures. After external validation, we selected top candidate definitions for response criteria to be evaluated by expert consensus at the conference held in Paris on June 9-10, 2014. Adult and pediatric expert groups ranked them using nominal group technique to achieve consensus on final adult and pediatric response criteria PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJpZGVyPC9BdXRob3I+PFllYXI+MjAxNjwvWWVhcj48UmVj
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bj4A
ADDIN EN.CITE.DATA [29, 30]. RESULTSClinically meaningful improvement in myositis CSM. Adult and pediatric myositis experts required a median of 20% relative percent change in each IMACS CSM to classify adult DM/PM and JDM patients as having minimal improvement, respectively (Table 1), except for muscle enzymes, which required greater improvement. The absolute percent change values were similar, but sometimes of lower magnitude, to classify patients as improved. Greater degrees of change were required for moderate and major improvement (Table 1).For adult DM/PM and JDM, muscle strength was ranked as the most important CSM, followed by Physician Global Activity, and must improve for a patient to be considered clinically improved. Experts suggested that 2-4 measures must improve for a patient to be considered improved. A small degree of deterioration was allowable in up to two measures. Inter-rater reliability. There was substantial agreement among all raters (kappa 0.64). There was high agreement between groups of raters (e.g., adult vs. pediatric, rheumatologists vs. other specialists, North America vs. other geographic region, more vs. less experienced) for minimal improvement (kappa 0.74–1.0, 90–100% agreement) and major improvement (kappa 0.83–0.93, 93–97% agreement). The intra-class correlation coefficient was high for all raters (0.82) and among different groups of raters (0.80–0.83). Among pediatric raters, agreement for both minimal and major improvement between IMACS and PRINTO measures was excellent (81–90%, kappa 0.67 for both). Patient profiles. Baseline and follow-up CSM values, as well as relative and absolute percent changes in the consensus profiles rated as minimally, moderately, and majorly improved, are presented in Supplementary Tables 4 and 5. Consensus was achieved for 157 profiles (48%) as minimally improved, 72 profiles (22%) as moderately improved, and 12 (4%) as majorly improved for adult DM/PM. Similarly, 231 profiles (86%), 155 (58%), and 63 (24%) profiles were rated as minimally, moderately, and majorly improved, respectively, for both IMACS and PRINTO JDM cases. Conjoint-analysis survey. Table 2 shows the relative weights and rank order of importance for each CSM derived from the conjoint-analysis survey. In the survey of adult myositis experts, the weights were as follows: baseline weight 1.0 for Patient Global Activity; MMT, 2.0; Physician Global Activity, HAQ, and Extramuscular Activity, 1.5; and muscle enzyme 0.5. For the pediatric IMACS survey, baseline weight 1.0 for Parent Global Activity; MMT, 3.0; Physician Global Activity, 2.0; and CHAQ and Extramuscular Activity, 1.5; and muscle enzyme 0.5. For the pediatric PRINTO survey, baseline weight 1.0 for Parent Global Activity; CMAS, 3.5; Physician Global Activity and DAS, 2.0; and CHAQ and CHQ-Phs 1.0. Based on myositis experts’ preferences for various CSM, all CSM were ranked in each conjoint-analysis survey (Table 2), with the rank order paralleling the relative weights in the CSM. Candidate definitions for response criteria and their performance in patient profiles and trial analysis. A total of 287 adult, 284 pediatric IMACS, and 312 pediatric PRINTO candidate definitions were derived and tested for sensitivity, specificity, and AUC, using the consensus patient profile ratings as the gold standard (Supplementary Table 6): 102 adult, 101 pediatric IMACS, and 99 PRINTO candidate definitions with sensitivity and specificity ≥80%, AUC ≥0.9 for minimal, and AUC ≥0.8 for moderate and major improvement in the patient profile analysis were evaluated in trial analysis. For adult DM/PM, 36 candidate definitions with significant differentiating potential in the RIM trial and with AUC ≥ 0.7 were advanced to final selection. For JDM, 29 IMACS and 30 PRINTO candidate definitions with significant differentiating potential in the RIM (P<0.05) and PRINTO trials (P≤0.057) as well as AUC ≥ 0.8 for minimal and AUC ≥ 0.7 for moderate/major improvement advanced to final selection. Up to four top-performing candidate definitions from each category were selected for presentation at the consensus conference. Thus, 18 adult and 14 pediatric candidate definitions for the response criteria were evaluated at the consensus conference using nominal group technique. Results of the consensus conference and final adult and pediatric myositis response criteria are described in the final response criteria manuscripts PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJpZGVyPC9BdXRob3I+PFllYXI+MjAxNjwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA [29, 30]. DISCUSSIONThrough the efforts of many experts, by combining datasets from observational studies and clinical trials, and by using several different statistical approaches, we developed new candidate definitions for response criteria for minimal, moderate, and major improvement in adult DM/PM and JDM. Experts’ consensus ratings of a large number of patient profiles were used as a gold standard to evaluate the candidate definitions. There was high inter-rater reliability among the experts.Clinical trial data from two studies were used to validate the top-performing candidate definitions. Because there was no difference between the treatment arms in the primary endpoint in the RIM trial, we used the treating physician’s rating of improvement to evaluate the candidate definitions’ performance as the criterion for trial validation. For the PRINTO trial of new-onset JDM patients PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJ1cGVydG88L0F1dGhvcj48WWVhcj4yMDE2PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA [19], we examined the discriminative power of each candidate definition by examining the magnitude of difference between prednisone-alone versus the combined-treatment arm (prednisone plus either methotrexate or cyclosporine). We used a rigorous, systematic approach to determine candidate definitions for consideration in a final consensus meeting to select a new response criterion for adult DM/PM and JDM, based on data-driven development of candidate definitions and validation with real patient and trial data in the selection process. One strength of this approach was that we allowed many different methods to compete in the data-driven process and in final expert consensus. We used the results from the first expert survey and previously published criteria to draft traditional categorical candidate response criteria that combined different CSM for minimal, moderate, and major improvement. Per guidance from representatives of the Food and Drug Administration, we also tested candidate response criteria that required patient-reported outcome measures to improve or be weighted more heavily; however, those definitions did not perform as well as the general definitions. The conjoint-analysis surveys had been used to weight clinical and laboratory features differentially to develop scoring systems, as has been done for new classification criteria for rheumatoid arthritis, systemic sclerosis, and gout PFJlZm1hbj48Q2l0ZT48QXV0aG9yPk5lb2dpPC9BdXRob3I+PFllYXI+MjAxNTwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA [12, 31-33]. We administered conjoint-analysis surveys in which experts chose the more improved hypothetical patient in a pair, defined by the degree of change in two CSM at a time and involving a tradeoff between them. These expressed choices served to efficiently reveal each CSM’s relative importance and were used to differentially weight CSM in the candidate response criteria. This process also generated continuous definitions where the continuous improvement score corresponded to the magnitude of improvement, with categorical thresholds for achieving minimal, moderate, and major improvement ADDIN REFMGR.CITE <Refman><Cite><Author>American College of Rheumatology Committee to Reevaluate Improvement Criteria</Author><Year>2007</Year><RecNum>12507</RecNum><IDText>A proposed revision to the ACR20: the hybrid measure of American College of Rheumatology response</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>12507</Ref_ID><Title_Primary>A proposed revision to the ACR20: the hybrid measure of American College of Rheumatology response</Title_Primary><Authors_Primary>American College of Rheumatology Committee to Reevaluate Improvement Criteria</Authors_Primary><Date_Primary>2007</Date_Primary><Keywords>Rheumatology</Keywords><Reprint>In File</Reprint><Start_Page>193-202</Start_Page><Periodical>Arthritis Rheum</Periodical><Volume>57</Volume><Issue>2</Issue><User_Def_1>Erratum in Arthritis Rheum. 2007 Dec 15;57(8):1574</User_Def_1><ZZ_JournalStdAbbrev><f name="System">Arthritis Rheum</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>[28]. Therefore, they are truly hybrid definitions in which the same definitions can be used as a continuous outcome measure by calculating the degree of improvement, as well as a categorical outcome measure by using thresholds of improvement. Similar hybrid candidate definitions were also developed through traditional logistic regression approaches, as well as by applying a relative weight to the degree of change in each CSM. The improvement score as a continuous outcome measure could also be used to differentiate between treatment and placebo by comparing mean improvement scores between treatment arms, and such scores could potentially provide more discriminative power, resulting in smaller sample size requirements in future trials ADDIN REFMGR.CITE <Refman><Cite><Author>Streiner</Author><Year>2002</Year><RecNum>12504</RecNum><IDText>Breaking up is hard to do: the heartbreak of dichotomizing continuous data</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>12504</Ref_ID><Title_Primary>Breaking up is hard to do: the heartbreak of dichotomizing continuous data</Title_Primary><Authors_Primary>Streiner,D.L.</Authors_Primary><Date_Primary>2002/4</Date_Primary><Keywords>AS</Keywords><Keywords>Bias (Epidemiology)</Keywords><Keywords>Clinical Trials as Topic</Keywords><Keywords>Data Interpretation,Statistical</Keywords><Keywords>Humans</Keywords><Keywords>La</Keywords><Keywords>outcome</Keywords><Keywords>Outcome Assessment (Health Care)</Keywords><Keywords>Probability</Keywords><Keywords>Psychiatric Status Rating Scales</Keywords><Keywords>Psychometrics</Keywords><Keywords>Research</Keywords><Keywords>statistics & numerical data</Keywords><Keywords>Universities</Keywords><Reprint>Not in File</Reprint><Start_Page>262</Start_Page><End_Page>266</End_Page><Periodical>Can.J.Psychiatry.</Periodical><Volume>47</Volume><Issue>3</Issue><Address>Department of Psychiatry, University of Toronto, Kunin-Lunenfeld Applied Research Unit, Baycrest Centre for Geriatric Care, Toronto, ON. dstreiner@klaru-baycrest.on.ca</Address><Web_URL>PM:11987478</Web_URL><ZZ_JournalFull><f name="System">Canadian Journal of Psychiatry.Revue Canadienne de Psychiatrie</f></ZZ_JournalFull><ZZ_JournalStdAbbrev><f name="System">Can.J.Psychiatry.</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>[34]. Lastly, we selected the top-performing candidate definitions from each category for presentation at the consensus conference, as we did not know which response criterion structure would have better face validity and acceptability to expert physicians. The results of the consensus conference are published elsewhere PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJpZGVyPC9BdXRob3I+PFllYXI+MjAxNjwvWWVhcj48UmVj
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bj4A
ADDIN EN.CITE.DATA [29, 30].We encountered several issues while developing these new response criteria: the CSM have varying relative importance, with muscle strength followed by Physician Global Activity as the most important measures. However, muscle strength changed much less than other CSM, particularly in adult patients, but was nevertheless considered by the experts to be important. Consequently, trials that rely on improvement in muscle strength as a sole primary endpoint PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlZpbGxhbGJhPC9BdXRob3I+PFllYXI+MTk5ODwvWWVhcj48
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ADDIN EN.CITE.DATA [29, 30]. A uniform and consensus-driven, validated response criteria in myositis, along with new and improved classification criteria that are being developed PFJlZm1hbj48Q2l0ZT48QXV0aG9yPkx1bmRiZXJnPC9BdXRob3I+PFllYXI+MjAxNjwvWWVhcj48
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ADDIN EN.CITE.DATA [37], may lead to better clinical trials in myositis. Acknowledgements. We thank Saad Feroz for assistance in drafting candidate definitions for response criteria and developing patient profiles. We thank the following people for invaluable input and feedback on project development and support: Brian Feldman, American College of Rheumatology; Daniel Aletaha, European League Against Rheumatism; Suzette Peng and Sarah Yim, the U.S. Food and Drug Administration; Thorsten Vetter and Richard Vesely, European Medicines Agency; Bob Goldberg and Theresa Curry, The Myositis Association; Rhonda McKeever and Patti Lawler, Cure JM Foundation; and Irene Oakley, Myositis UK. We thank Drs. Michael Ward and Steven Pavletic for critical reading of the manuscript. Paul Hansen owns the 1000Minds software referred to in this article, which he co-invented with Franz Ombler. Jiri Vencovsky’s work in myositis is supported by the project (Ministry of Health, Czech Republic) for conceptual development of research organization 00023728 (Institute of Rheumatology). Hector Chinoy is supported by an Arthritis Research UK (18474) and the National Institute for Health Research (NIHR) Biomedical Research Unit Funding Scheme. ADDIN REFMGR.REFLIST References1. Rider LG, Werth VP, Huber AM et al. 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Development of classification and response criteria for rheumatic diseases. Arthritis Rheum 2006;55:348-52.17. Ruperto N, Meiorin S, Iusan SM, Ravelli A, Pistorio A, Martini A. Consensus procedures and their role in pediatric rheumatology. Curr Rheumatol Rep 2008;10:142-6.18. Delbecq A, Van de Ven A, Gustafson D. Group techniques for program planning. A guide to nominal group and delphi processes. Glenview, IL: Scott, Foresman and Company, 1975.19. Ruperto N, Pistorio A, Oliveira S et al. Prednisone versus prednisone plus ciclosporin versus prednisone plus methotrexate in new-onset juvenile dermatomyositis: a randomised trial. Lancet 2016;387:671-8.20. Rider LG, Lee J, Jansen A et al. Defining clinically relevant changes in core set activity measures for adult and juvenile idiopathic inflammatory myopathies (IIM). Arthritis Rheum 2011;63 (Suppl):S89.21. Lundberg IE, Svensson J. Registries in idiopathic inflammatory myopathies. Curr Opin Rheumatol 2013;25:729-34.22. 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Neogi T, Aletaha D, Silman AJ et al. The 2010 American College of Rheumatology/European League Against Rheumatism classification criteria for rheumatoid arthritis: Phase 2 methodological report. Arthritis Rheum 2010;62:2582-91.32. Johnson SR, Naden RP, Fransen J et al. Multicriteria decision analysis methods with 1000Minds for developing systemic sclerosis classification criteria. J Clin Epidemiol 2014;67:706-14.33. Van Den Hoogen F, Khanna D, Fransen J et al. 2013 classification criteria for systemic sclerosis: an American College of Rheumatology/European League against Rheumatism collaborative initiative. Arthritis Rheum 2013;65:2737-47.34. Streiner DL. Breaking up is hard to do: the heartbreak of dichotomizing continuous data. Can J Psychiatry 2002;47:262-6.35. Villalba L, Hicks JE, Adams EM et al. Treatment of refractory myositis: a randomized crossover study of two new cytotoxic regimens. Arthritis Rheum 1998;41:392-9.36. Cherin P, Herson S, Wechsler B et al. Efficacy of intravenous gammaglobulin therapy in chronic refractory polymyositis and dermatomyositis: an open study with 20 adult patients. Am J Med 1991;91:162-8.37. Lundberg IE, Miller FW, Tjarnlund A, Bottai M. Diagnosis and classification of idiopathic inflammatory myopathies. J Intern Med 2016;280:39-51. ADDIN REFMGR.REFLIST Table 1. Results of the core set measure survey showing the degree of change deemed clinically relevant by an expert panel of myositis clinicians for minimal, moderate, and major improvement for adult (dermatomyositis/polymyositis) and pediatric (juvenile dermatomyositis) groups*?Minimal improvementModerate improvementMajor improvementCore set measureRelative % change?Absolute % change?Relative % change?Absolute % change?Relative % change?Absolute % change?Adult???MD Global 20 [15, 30]20 [10, 20]30 [25, 40]35 [20, 40]50 [40, 70]50 [30, 70]Patient/parent global activity20 [15, 30]20 [15, 30]30 [25, 40]35 [25, 40]50 [40, 60]50 [35, 60]MMT20 [10, 20]13 [10, 20]30 [20, 40]31 [10, 44]50 [30, 70]50 [23, 63]HAQ20 [15, 25]33 [10, 33]30 [30, 40]33 [20, 50]50 [40, 60]67 [33, 67]ExtraMusc20 [15, 25]20 [10, 20]30 [25, 40]40 [20, 40]50 [30, 60]50 [30, 60]Enzyme?30 [20, 40]20 [10, 20]40 [30, 50]30 [20, 50]55 [50, 80]50 [30, 100]PediatricMD Global 20 [20, 30]20 [20, 20]40 [30, 50]40 [24, 40]60 [50, 70]50 [40, 70]Patient/parent global activity20 [20, 30]20 [20, 30]40 [30, 50]30 [30, 50]60 [50, 70]60 [40, 70]MMT20 [15, 30]19 [12, 25]40 [25, 50]36 [23, 45]50 [50, 70]50 [33, 66]CHAQ20 [20, 30]17 [13, 33]40 [30, 50]33 [20, 33]60 [50, 70]67 [40, 67]ExtraMusc20 [20, 30]20 [20, 30]30 [30, 50]30 [30, 50]50 [50, 70]55 [50, 70]Enzyme?30 [23, 50]25 [15, 30]50 [30, 60]50 [30, 50]70 [50, 80]60 [50, 75]CMAS20 [15, 30]13 [10, 19]40 [25, 50]20 [19, 38]50 [50, 70]49 [29, 58]DAS20 [20, 30]20 [20, 25]30 [30, 50]40 [25, 50]50 [50, 70]60 [40, 75]CHQ-PF5020 [20, 30]15 [13, 25]40 [30, 50]25 [25, 38]55 [50, 70]40 [38, 53]Abbreviations as in Table 1. HAQ, Health Assessment Questionnaire.*Results are presented as median and interquartile [25%, 75%].?Relative % change = [(final – baseline value) / baseline value]*100?Absolute % change = [(final – baseline value) / potential range for test]*100 ?Enzyme (expressed as percentage of upper limits of normal) details for patients include aldolase, alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, and creatine kinase.Table 2. Rounded weights* and relative rank of importance of each core set measure based on the 1000Minds surveyAdult IMACS Pediatric IMACS Pediatric PRINTO Core set measureWeightRelative rankWeightRelative RankWeightRelative RankMD global activity1.522.022.0 2Patient/parent global activity1.051.061.04MMT82.013.01N/AN/ACMASN/AN/AN/AN/A3.51HAQ/CHAQ1.541.541.03Extramuscular activity1.531.53N/AN/ADASN/AN/AN/AN/A2.02Enzyme0.561.05N/AN/ACHQ-PhSN/AN/AN/AN/A1.05Abbreviations as in Tables 1 and 2. MMT8 = Manual Muscle Test on 8 muscles; N/A = not applicable.*Weights were rounded to nearest multiple of 0.5 from their original weightings and were derived as the average weights of all adult or pediatric experts participating in the conjoint analysis surveys, with higher weight indicating experts’ stronger importance associated with a particular core set measure in defining the degree of improvement in patients. Relative rank is based on mean relative importance scores, which consist of the average rank order of core set measures among experts participating in the conjoint analysis surveys, with lower scores indicating a higher degree of importance of that measure in determining whether a patient is improved or not. Supplementary Table 1. 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ADDIN EN.CITE.DATA (37) Abbreviations: CHAQ/HAQ, (Childhood) Health Assessment Questionnaire; CMAS, Childhood Myositis Assessment Scale; DAS, Disease Activity Score; IMACS, International Myositis Assessment and Clinical Studies Group; MDAAT, Myositis Disease Activity Assessment Tool; PRINTO, Pediatric Rheumatology International Trials Organization.*Not recommended for children less than 4 years of age. ?One validated tool is recommended for adults and children more than 4 years of age and 2 tools for children less than 4 years of age.Supplementary Table 2. Clinical trials and natural history studies used for patient profiles and external trial validationName of study or trialPrincipal investigator (reference)Number of adult or juvenile DM/PM patientsAdult DM/PM natural history studies and trials for patient profiles (Total 199 patients)EuroMyositis Natural History Study (Czech Republic)Jiri Vencovsky ADDIN REFMGR.CITE <Refman><Cite><Author>Lundberg</Author><Year>2013</Year><RecNum>12266</RecNum><IDText>Registries in idiopathic inflammatory myopathies</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>12266</Ref_ID><Title_Primary>Registries in idiopathic inflammatory myopathies</Title_Primary><Authors_Primary>Lundberg,I.E.</Authors_Primary><Authors_Primary>Svensson,J.</Authors_Primary><Date_Primary>2013/11</Date_Primary><Keywords>AS</Keywords><Keywords>clinical</Keywords><Keywords>Disease</Keywords><Keywords>Health</Keywords><Keywords>Incidence</Keywords><Keywords>La</Keywords><Keywords>Longitudinal Studies</Keywords><Keywords>Medicine</Keywords><Keywords>myopathy</Keywords><Keywords>myositis</Keywords><Keywords>outcome</Keywords><Keywords>Patients</Keywords><Keywords>Prevalence</Keywords><Keywords>prognosis</Keywords><Keywords>Registries</Keywords><Keywords>Research</Keywords><Keywords>review</Keywords><Keywords>Rheumatology</Keywords><Keywords>Risk</Keywords><Keywords>Risk factors</Keywords><Keywords>Sweden</Keywords><Keywords>treatment</Keywords><Keywords>Treatment Outcome</Keywords><Reprint>Not in File</Reprint><Start_Page>729</Start_Page><End_Page>734</End_Page><Periodical>Curr.Opin.Rheumatol</Periodical><Volume>25</Volume><Issue>6</Issue><Misc_3>10.1097/01.bor.0000434667.55020.e1 [doi]</Misc_3><Address>Rheumatology Unit, Department of Medicine, Karolinska Institutet, Stockholm, Sweden</Address><Web_URL>PM:24047606</Web_URL><ZZ_JournalStdAbbrev><f name="System">Curr.Opin.Rheumatol</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>(21)59EuroMyositis Natural History Study (Sweden)Ingrid E. Lundberg ADDIN REFMGR.CITE <Refman><Cite><Author>Lundberg</Author><Year>2013</Year><RecNum>12266</RecNum><IDText>Registries in idiopathic inflammatory myopathies</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>12266</Ref_ID><Title_Primary>Registries in idiopathic inflammatory myopathies</Title_Primary><Authors_Primary>Lundberg,I.E.</Authors_Primary><Authors_Primary>Svensson,J.</Authors_Primary><Date_Primary>2013/11</Date_Primary><Keywords>AS</Keywords><Keywords>clinical</Keywords><Keywords>Disease</Keywords><Keywords>Health</Keywords><Keywords>Incidence</Keywords><Keywords>La</Keywords><Keywords>Longitudinal Studies</Keywords><Keywords>Medicine</Keywords><Keywords>myopathy</Keywords><Keywords>myositis</Keywords><Keywords>outcome</Keywords><Keywords>Patients</Keywords><Keywords>Prevalence</Keywords><Keywords>prognosis</Keywords><Keywords>Registries</Keywords><Keywords>Research</Keywords><Keywords>review</Keywords><Keywords>Rheumatology</Keywords><Keywords>Risk</Keywords><Keywords>Risk factors</Keywords><Keywords>Sweden</Keywords><Keywords>treatment</Keywords><Keywords>Treatment Outcome</Keywords><Reprint>Not in File</Reprint><Start_Page>729</Start_Page><End_Page>734</End_Page><Periodical>Curr.Opin.Rheumatol</Periodical><Volume>25</Volume><Issue>6</Issue><Misc_3>10.1097/01.bor.0000434667.55020.e1 [doi]</Misc_3><Address>Rheumatology Unit, Department of Medicine, Karolinska Institutet, Stockholm, Sweden</Address><Web_URL>PM:24047606</Web_URL><ZZ_JournalStdAbbrev><f name="System">Curr.Opin.Rheumatol</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>(21)56Mexican Natural History StudyIgnacio Garcia De la Torre (unpublished)21Clinical Trial – Etanercept (randomized)Muscle Study Group PFJlZm1hbj48Q2l0ZT48QXV0aG9yPk11c2NsZSBTdHVkeSBHcm91cDwvQXV0aG9yPjxZZWFyPjIw
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ADDIN EN.CITE.DATA (23)9EuroMyositis Natural History Study (Hungary)Katalin Danko ADDIN REFMGR.CITE <Refman><Cite><Author>Lundberg</Author><Year>2013</Year><RecNum>12266</RecNum><IDText>Registries in idiopathic inflammatory myopathies</IDText><MDL Ref_Type="Journal"><Ref_Type>Journal</Ref_Type><Ref_ID>12266</Ref_ID><Title_Primary>Registries in idiopathic inflammatory myopathies</Title_Primary><Authors_Primary>Lundberg,I.E.</Authors_Primary><Authors_Primary>Svensson,J.</Authors_Primary><Date_Primary>2013/11</Date_Primary><Keywords>AS</Keywords><Keywords>clinical</Keywords><Keywords>Disease</Keywords><Keywords>Health</Keywords><Keywords>Incidence</Keywords><Keywords>La</Keywords><Keywords>Longitudinal Studies</Keywords><Keywords>Medicine</Keywords><Keywords>myopathy</Keywords><Keywords>myositis</Keywords><Keywords>outcome</Keywords><Keywords>Patients</Keywords><Keywords>Prevalence</Keywords><Keywords>prognosis</Keywords><Keywords>Registries</Keywords><Keywords>Research</Keywords><Keywords>review</Keywords><Keywords>Rheumatology</Keywords><Keywords>Risk</Keywords><Keywords>Risk factors</Keywords><Keywords>Sweden</Keywords><Keywords>treatment</Keywords><Keywords>Treatment Outcome</Keywords><Reprint>Not in File</Reprint><Start_Page>729</Start_Page><End_Page>734</End_Page><Periodical>Curr.Opin.Rheumatol</Periodical><Volume>25</Volume><Issue>6</Issue><Misc_3>10.1097/01.bor.0000434667.55020.e1 [doi]</Misc_3><Address>Rheumatology Unit, Department of Medicine, Karolinska Institutet, Stockholm, Sweden</Address><Web_URL>PM:24047606</Web_URL><ZZ_JournalStdAbbrev><f name="System">Curr.Opin.Rheumatol</f></ZZ_JournalStdAbbrev><ZZ_WorkformID>1</ZZ_WorkformID></MDL></Cite></Refman>(21)8Clinical Trial – Rituximab (open label)David Fiorentino/Lorinda Chung PFJlZm1hbj48Q2l0ZT48QXV0aG9yPkNodW5nPC9BdXRob3I+PFllYXI+MjAwNzwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA (4;8)278National Institutes of Health Natural History StudyLisa Rider, Frederick Miller (unpublished)21Randomized controlled trials for validation of definitions of improvement in JDM Clinical Trial – prednisone vs. prednisone + methotrexate or cyclosporineNicolino Ruperto PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJ1cGVydG88L0F1dGhvcj48WWVhcj4yMDE2PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA (23)48Abbreviations: DM/PM, dermatomyositis/polymyositis; JDM, juvenile dermatomyositis; PRINTO, Pediatric Rheumatology International Trials Organization.Note: some patients were used more than once in the creation of patient profiles.Supplementary Table 3. Demographic characteristics of working group membersRatersAdult Working Group (n=60)%Pediatric Working Group (n=69)%Specialty Rheumatology6394 Neurology183 Dermatology90 Other103Region North America6352 Europe3036 Asia50 South America212Number of myositis patients/yr (mean)84.7 ± 85.528.2 ± 37.2Time in practice (years, mean)18.1 ± 9.319.9 ± 10.3Number of CSM used Six (IMACS?)/Nine (IMACS+PRINTO)?1749 Five?/Eight?5419 Four?/Seven?1015 Three-?/Six or less?1917Median Clinical Experience Score [IQR]§1176 [300, 1450]580 [122, 570]CSM, core set measures; IMACS, International Myositis Assessment and Clinical Studies Group; PRINTO, Pediatric Rheumatology International Trials Organization; IQR, interquartile range. *For the clinically meaningful improvement survey, 24 adult rheumatologists, neurologists, and other specialists and 29 pediatric rheumatologist myositis experts completed the Delphi questionnaire. They saw an average of 104 adult and 34 juvenile myositis patients per year, respectively, and practiced an average of 18 and 19 years, respectively. For the conjoint-analysis survey, 22 adult and 29 pediatric experts participated. They had similar geographic distribution but had higher clinical experience scores, including more experience with the CSM.?Raters of adult profiles only. ?Raters of pediatric profiles only. § Total patients seen per year x years of experience x fraction of core set measures used.Supplementary table 4. IMACS core set measures and their change in consensus patient profiles for adult dermatomyositis/polymyositis by degree of improvementCore set measure (range)Median start valueMedian end valueMedian relative % changeMedian absolute % change[IQR][IQR][IQR][IQR]No improvement (n = 88)MD Global 1 [0.4, 2.8]1.6 [0.5, 3.6]-13 [-96, 19]-1 [-10, 4](0–10 cm)Patient global activity4.7 [2.2, 6.1]5.6 [3.1, 7]-13 [-63, 5]-6 [-21, 2](0–10 cm)MMT73 [67, 78]73 [64, 78]0 [-5, 3]0 [-5, 2](80–0)HAQ0.75 [0.32, 1]0.81 [0.5, 1.19]-14 [-57, 5]-4 [-10, 4](0–3)?ExtraMusc1 [0, 1]1 [0, 3]-32 [-100, 0]-3 [-10, 0](0–10 cm)Enzyme*??1.2 [0.9, 2]1.1 [0.9, 2.2]0 [-37, 22]0 [-9, 5]At least minimal improvement (n = 157)MD Global 2.8 [1.3, 4.5]1 [0.4, 2]58 [30, 78]15 [6, 25](0–10 cm)Patient global activity5.4 [3.2, 7.3]2.8 [1.2, 5.4]40 [14, 63]16 [5, 35](0–10 cm)MMT68 [57, 75]75 [69, 79]8 [1, 18]6 [1, 14](80–0)HAQ1 [0.38, 1.75]0.5 [0.07, 1.13]28 [0, 67]8 [0, 21](0–3)?ExtraMusc 2 [1, 4]1 [0, 2]58 [30, 83]12 [3, 22](0–10 cm)Enzyme*??1.7 [1, 3.7]0.9 [0.6, 1.2]33 [2, 75]9 [1, 25]At least moderate improvement (n = 72)MD Global 4 [2.8, 5.6]1.4 [0.7, 2.5]64 [40, 76]25 [16, 32](0–10 cm)Patient global activity6.4 [5, 7.9]3 [1.1, 5]52 [34, 72]30 [16, 40](0–10 cm)MMT63 [53, 71]75 [69, 77]16 [7, 28]13 [6, 19](80–0)HAQ1.25 [0.63, 2.13]0.5 [0.13, 1]50 [3, 78]19 [2, 42](0–3)?ExtraMusc3 [2, 4]1 [0, 2]62 [41, 83]19 [9, 30](0–10 cm)Enzyme*??3.1 [1.6, 8.1]0.8 [0.6, 1.3]70 [39, 89]24 [11, 89]Major improvement (n = 12)MD Global 5.1 [3.5, 7]1.3 [0.5, 1.8]73 [66, 82]35 [30, 47](0–10 cm)Patient global activity7.6 [6.3, 8.1]2 [0.9, 3.3]73 [58, 87]48 [35, 69](0–10 cm)MMT59 [48, 68]77 [74, 80]30 [16, 45]21 [14, 29](80–0)HAQ1.88 [1.13, 2.69]0.32 [0.07, 0.5]83 [64, 95]50 [31, 75](0–3)?ExtraMusc4 [3, 6]1 [0, 2]86 [71, 93]32 [27, 43](0–10 cm)Enzyme*??4.5 [2.8, 19.7]0.5 [0.3, 0.6]94 [81, 98]76 [23, 157]Abbreviations as in Tables 1 and 2.*Enzyme (expressed as percentage of upper limits of normal) details include the most abnormal enzyme at baseline among aldolase, alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, and creatine kinase.Supplementary table 5. IMACS and PRINTO core set measures and their change in consensus patient profiles for juvenile dermatomyositis by degree of improvement Core set measure (range)Median start valueMedian end valueMedian relative % changeMedian absolute % change[IQR][IQR][IQR][IQR]No improvement (n = 36)*MD Global 4.5 [2, 6.1]5.1 [4, 8.4]-33 [-85, 0]-11 [-26, 0](0–10 cm)Patient global activity 4 [1.2, 5.1]5.1 [2.2, 6.6]-38 [-109, -1]-8 [-24, -1](0–10 cm)MMT 58 [44, 67]51 [30, 64]-11 [-27, 0]-6 [-13, 0](80–0)CHAQ 0.82 [0.38, 1.82]1.32 [0.44, 2.32]-7 [-70, 0]-4 [-21, 0](0–3)?ExtraMusc1 [0, 2]2 [0, 5]-75 [-117, 0]-4 [-27, 0](0–10 cm)Enzyme??0.9 [0.6, 1.6]0.7 [0.5, 0.9]20 [-18, 59]3 [-2, 11]CMAS 38 [24, 45]30 [18, 40]-11 [-32, -2]-8 [-15, -2](52–0)DAS 10 [6, 12]10 [8, 12]-13 [-45, 0]-5 [-15, 0](0–20)CHQ-PhS45 [35, 51]40 [31, 47]-4 [-20, 0]-3 [-10, 0](40–60)At least minimal improvement (n = 231)MD Global 5 [3.1, 6.8]0.7 [0.2, 1.6]84 [56, 96]33 [18, 53](0–10 cm)Patient global activity 5.1 [2.6, 7]0.8 [0, 2.2]76 [44, 100]32 [10, 55](0–10 cm)MMT 51 [35, 66]74 [65, 79]33 [9, 83]21 [8, 40](80–0)CHAQ 1.5 [0.88, 2.38]0.25 [0, 0.75]74 [34, 100]33 [12, 58](0–3)?ExtraMusc2 [1, 5]0 [0, 1]78 [14, 100]13 [1, 33](0–10 cm)Enzyme??1.2 [0.8, 2.3]0.7 [0.5, 0.9]61 [21, 91]12 [2, 29]CMAS 30 [18, 40]47 [40, 50]40 [13, 143]23 [10, 46](52–0)DAS 12 [9, 14]5 [3, 8]56 [31, 75]30 [15, 45](0–20)CHQ-PhS34 [24, 45]49 [40, 54]21 [0, 69]10 [0, 24](40–60)At least moderate improvement (n = 155)MD Global 5.6 [3.9, 7.3]0.5 [0.1, 1.4]88 [73, 97]44 [27, 61](0–10 cm)Patient global activity 6.1 [3.8, 7.5]0.7 [0, 2.1]87 [60, 100]46 [23, 62](0–10 cm)MMT 48 [32, 62]75 [67, 79]46 [21, 112]28 [18, 46](80–0)CHAQ 1.75 [1.25, 2.5]0.13 [0, 0.75]90 [64, 100]46 [25, 71](0–3)?ExtraMusc 2 [1, 5]0 [0, 1]88 [44, 100]17 [4, 40](0–10 cm)Enzyme??1.4 [1, 2.6]0.7 [0.5, 1]72 [37, 95]16 [5, 37]CMAS 27 [14, 36]47 [43, 50]71 [29, 200]37 [17, 56](52–0)DAS 12 [10, 15]4 [2, 6]67 [47, 80]35 [25, 50](0–20)CHQ-PhS31 [23, 40]51 [42, 54]44 [4, 105]18 [2, 29](40–60)Major improvement (n = 63)MD Global 6.1 [5, 7.7]0.3 [0, 0.6]96 [89, 100]58 [47, 72](0–10 cm)Patient global activity 6.8 [5.2, 7.8]0.1 [0, 0.9]97 [87, 100]58 [46, 75](0–10 cm)MMT 38 [25, 50]77 [71, 80]90 [51, 178]45 [32, 58](80–0)CHAQ 2.13 [1.63, 2.63]0 [0, 0.25]100 [85, 100]67 [46, 79](0–3)?ExtraMusc3 [1, 5]0 [0, 0]96 [85, 100]28 [11, 48](0–10 cm)Enzyme??2.3 [1.4, 4.7]0.7 [0.5, 1]90 [65, 98]26 [9, 84]CMAS 19 [9, 29]48 [46, 50]153 [74, 380]54 [40, 65](52–0)DAS 14 [12, 16]4 [2, 5]74 [64, 88]50 [35, 60](0–20)CHQ-PhS26 [19, 35]53 [50, 55]73 [40, 142]26 [16, 38](40–60)Abbreviations as in Tables 1 and 2. Data represent improvement by both IMACS and PRINTO measures. *The number of combined profiles is provided as the final number that reached consensus for both IMACS and PRINTO patient profiles. These consensus profiles were used as gold standard ratings in the development and testing of candidate definitions for response.?Enzyme (expressed as percentage of upper limits of normal) details include the most abnormal enzyme at baseline among aldolase, alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, and creatine kinase.Supplementary table 6. Numbers of types of candidate definitions for response criteria tested at different stages of the processType of candidate definitions of response criteriaAdult IMACSPediatric IMACSPediatric PRINTORelative % changeAbsolute% changeRelative % changeAbsolute% changeRelative % changeAbsolute% changeDrafted definitionsPreviously published definitions8272130Newly drafted definitions647065707386Weighted definitions511248124812Logistic regression343434343434Core set measure-weighted 333333Conjoint analysis333333Total number tested* 163124 160124 174138Results of patient profile analysis?Previously published definitions304090Newly drafted definitions144 10474Weighted definitions154165103Logistic regression232723272327Core set measure-weighted 333333Conjoint analysis333333Total number meeting criteria614159425540Results of trial analysis? ??Previously published definitions202020Newly drafted definitions314040Weighted definitions907070Logistic Regression 5?422? 2? 2?Core set measure-weighted 333333Conjoint analysis333333Total number meeting criteria25?11?21?8?22?8?Presented at final consensus conference§Previously published definitions202020Newly drafted definitions314040Weighted definitions303030Logistic regression220202Core set measure-weighted 200000Conjoint analysis212121Total number presented at consensus conference144113113*Several improvement variations with different cut-points and five variations of worsening were also tested for minimal, moderate, and major improvement, including relative and absolute percent change of newly drafted definitions.?Selection of sensitivity and specificity ≥ 80%, area under the curve (AUC) ≥ 0.9 for minimal, and AUC ≥ 0.8 for moderate and major improvement were required to move a response criterion from patient profile to trial analysis. ??Trial analysis included the Rituximab in Myositis Trial PFJlZm1hbj48Q2l0ZT48QXV0aG9yPk9kZGlzPC9BdXRob3I+PFllYXI+MjAxMzwvWWVhcj48UmVj
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ADDIN EN.CITE.DATA (23) for adult DM/PM. Trial validation consisted of testing the difference between the treating physician’s assessment of change scores between response criterion–improved and response criterion–unimproved patients, with P < 0.001; sensitivity and specificity ≥ 50% and AUC ≥ 0.7 were included in the final selection of candidate response criteria. The Rituximab in Myositis trial was also used for JDM trial validation, and it used the same difference in treating physician’s assessment of change. The response criteria had a sensitivity and specificity ≥ 75%, AUC ≥ 0.8 for minimal improvement and AUC ≥ 0.7 for moderate/major improvement to move to final selection for JDM. The PRINTO trial for JDM PFJlZm1hbj48Q2l0ZT48QXV0aG9yPlJ1cGVydG88L0F1dGhvcj48WWVhcj4yMDE2PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA (19) was used as a second trial for external validation; it examined the frequency of responses by the candidate response criteria between treatment arms (prednisone alone vs. prednisone plus methotrexate or cyclosporine), aiming for a significant difference (P < 0.05) between treatment arms for minimal improvement. §Selected three to five top-performing definitions in each category for presentation at final consensus conference.Figure 1. Overview of the current project and timelines to develop new response criteria for adult dermatomyositis (DM) and polymyositis (PM) and juvenile dermatomyositis (JDM). Supplementary Figure 1: Example of patient profile from online patient profile rating exercises. Supplementary Figure 2: Example of a pairwise-ranking question from the 1000Minds conjoint-analysis survey administered to expert panels. ................
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