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•  Rheumatoidarthritis– PubMed– “rheumatoidarthritisreview”– Review–Lancet2010

www.imbm.sk

Seminar

1094 www.thelancet.com Vol 376 September 25, 2010

Lancet 2010; 376: 1094–1108

Department of Rheumatology, King’s College London School

of Medicine, London, UK (Prof D L Scott FRCP); National

Data Bank for Rheumatic Diseases, and University of Kansas School of Medicine,

Wichita, KS, USA (Prof F Wolfe MD); and

Department of Rheumatology, Leiden University Medical

Center, Leiden, Netherlands (Prof T W J Huizinga MD)

Correspondence to:Prof David L Scott, Department

of Rheumatology, King’s College London School of Medicine,

Weston Education Centre, London SE5 9RJ, UK

[email protected]

Rheumatoid arthritisDavid L Scott, Frederick Wolfe, Tom W J Huizinga

Rheumatoid arthritis is characterised by persistent synovitis, systemic infl ammation, and autoantibodies (particularly to rheumatoid factor and citrullinated peptide). 50% of the risk for development of rheumatoid arthritis is attributable to genetic factors. Smoking is the main environmental risk. In industrialised countries, rheumatoid arthritis aff ects 0·5–1·0% of adults, with 5–50 per 100 000 new cases annually. The disorder is most typical in women and elderly people. Uncontrolled active rheumatoid arthritis causes joint damage, disability, decreased quality of life, and cardiovascular and other comorbidities. Disease-modifying antirheumatic drugs (DMARDs), the key therapeutic agents, reduce synovitis and systemic infl ammation and improve function. The leading DMARD is methotrexate, which can be combined with other drugs of this type. Biological agents are used when arthritis is uncontrolled or toxic eff ects arise with DMARDs. Tumour necrosis factor inhibitors were the fi rst biological agents, followed by abatacept, rituximab, and tocilizumab. Infections and high costs restrict prescription of biological agents. Long-term remission induced by intensive, short-term treatment selected by biomarker profi les is the ultimate goal.

Introduction Rheumatoid arthritis has 19th century roots and a 20th century pedigree. Although its name was introduced in the 1850s,1 classifi cation criteria were only developed 50 years ago.2,3 Observational studies in which these criteria are used portray treated rheumatoid arthritis as a serious long-term disease with dominant extra-articular features, limited treatment options, and poor outcomes.4,5

Tumour necrosis factor (TNF) inhibitors and other biological agents have heralded a so-called therapeutic revolution, transforming the outlook for patients with rheumatoid arthritis. However, improved disease outcomes preceded biological agents, refl ecting early use of conventional drugs, ambitious treatment goals, and better management of comorbidities. An historic parallel is the 1950s revolution in tuberculosis care, when improved conventional management followed by eff ective chemotherapy made tuberculosis curable.6

Pathophysiology Rheumatoid arthritis is best considered a clinical syndrome spanning several disease subsets.7 These diff erent subsets entail several infl ammatory cascades,8 which all lead towards a fi nal common pathway in which persistent synovial infl ammation and associated damage to articular cartilage and underlying bone are present.

Infl ammation One key infl ammatory cascade includes overproduction and overexpression of TNF.9 This pathway drives both synovial infl ammation and joint destruction. TNF overproduction has several causes, including interactions between T and B lymphocytes, synovial-like fi broblasts, and macrophages. This process leads to overproduction of many cytokines such as interleukin 6, which also drives persistent infl ammation and joint destruction.10 Overproduction of other proinfl ammatory cytokines (eg, interleukin 1) diff ers from the process for interleukin 6 in that production is either less marked or is specifi c to

one or more disease subsets, as best shown by the eff ects of interleukin 1 blockade in subforms of juvenile idiopathic arthritis or adult-onset Still’s disease.

Synovial cells and cartilage cellsThe dominant local cell populations in joints aff ected by rheumatoid arthritis are synovial and cartilage cells. Synovial cells can be divided into fi broblast-like and macrophage-like synoviocytes. Overproduction of proinfl ammatory cytokines is believed to be led predominantly by macrophage-like synoviocytes. Fibroblast-like synoviocytes show abnormal behaviour in rheumatoid arthritis. In experimental models, co-implantation of fi broblast-like synoviocytes with cartilage leads to fi broblasts invading cartilage,11 behaviour that correlates with joint destruction.12 Considerable information has accumulated about joint destruction and the role of osteoclast activation as a key process leading to bone erosion. This association is proven because specifi c inhibition of osteoclast activation can reduce joint destruction yet not aff ect joint

Search strategy and selection criteria

We searched the Cochrane Library (2000–09), Medline (2000–09), and Embase (2000–09). We used the search term “rheumatoid arthritis” in combination with terms relevant for every section of the article, including: “cytokines”, auto-antibodies”, genetic risk factors”, “prevalence”, “incidence”, “assessments”, “outcome measures”, “co-morbidities”, and every specifi c treatment approach. We mainly selected publications from the past 5 years, although we did not exclude commonly referenced and highly regarded older publications. We also searched the reference lists of articles identifi ed by this search strategy and selected those we judged relevant. We selected high-quality systematic reviews in preference to individual studies. Other review articles and books were cited to provide readers with more details and references than this Seminar can accommodate.

Lancet

•  IF:53•  Isitaloworahighimpactfactor?•  Whatdidyoufindoutintheabstract?•  Whatdoyouthinkyoucanexpectreadingthisarticle?

Seminar


Lancet 2010; 376: 1094–1108

Department of Rheumatology, King’s College London School

of Medicine, London, UK (Prof D L Scott FRCP); National

Data Bank for Rheumatic Diseases, and University of Kansas School of Medicine,

Wichita, KS, USA (Prof F Wolfe MD); and

Department of Rheumatology, Leiden University Medical

Center, Leiden, Netherlands (Prof T W J Huizinga MD)

Correspondence to:Prof David L Scott, Department

of Rheumatology, King’s College London School of Medicine,

Weston Education Centre, London SE5 9RJ, UK

[email protected]

Rheumatoid arthritisDavid L Scott, Frederick Wolfe, Tom W J Huizinga

Rheumatoid arthritis is characterised by persistent synovitis, systemic infl ammation, and autoantibodies (particularly to rheumatoid factor and citrullinated peptide). 50% of the risk for development of rheumatoid arthritis is attributable to genetic factors. Smoking is the main environmental risk. In industrialised countries, rheumatoid arthritis aff ects 0·5–1·0% of adults, with 5–50 per 100 000 new cases annually. The disorder is most typical in women and elderly people. Uncontrolled active rheumatoid arthritis causes joint damage, disability, decreased quality of life, and cardiovascular and other comorbidities. Disease-modifying antirheumatic drugs (DMARDs), the key therapeutic agents, reduce synovitis and systemic infl ammation and improve function. The leading DMARD is methotrexate, which can be combined with other drugs of this type. Biological agents are used when arthritis is uncontrolled or toxic eff ects arise with DMARDs. Tumour necrosis factor inhibitors were the fi rst biological agents, followed by abatacept, rituximab, and tocilizumab. Infections and high costs restrict prescription of biological agents. Long-term remission induced by intensive, short-term treatment selected by biomarker profi les is the ultimate goal.

Introduction Rheumatoid arthritis has 19th century roots and a 20th century pedigree. Although its name was introduced in the 1850s,1 classifi cation criteria were only developed 50 years ago.2,3 Observational studies in which these criteria are used portray treated rheumatoid arthritis as a serious long-term disease with dominant extra-articular features, limited treatment options, and poor outcomes.4,5

Tumour necrosis factor (TNF) inhibitors and other biological agents have heralded a so-called therapeutic revolution, transforming the outlook for patients with rheumatoid arthritis. However, improved disease outcomes preceded biological agents, refl ecting early use of conventional drugs, ambitious treatment goals, and better management of comorbidities. An historic parallel is the 1950s revolution in tuberculosis care, when improved conventional management followed by eff ective chemotherapy made tuberculosis curable.6

Pathophysiology Rheumatoid arthritis is best considered a clinical syndrome spanning several disease subsets.7 These diff erent subsets entail several infl ammatory cascades,8 which all lead towards a fi nal common pathway in which persistent synovial infl ammation and associated damage to articular cartilage and underlying bone are present.

Infl ammation One key infl ammatory cascade includes overproduction and overexpression of TNF.9 This pathway drives both synovial infl ammation and joint destruction. TNF overproduction has several causes, including interactions between T and B lymphocytes, synovial-like fi broblasts, and macrophages. This process leads to overproduction of many cytokines such as interleukin 6, which also drives persistent infl ammation and joint destruction.10 Overproduction of other proinfl ammatory cytokines (eg, interleukin 1) diff ers from the process for interleukin 6 in that production is either less marked or is specifi c to

one or more disease subsets, as best shown by the eff ects of interleukin 1 blockade in subforms of juvenile idiopathic arthritis or adult-onset Still’s disease.

Synovial cells and cartilage cellsThe dominant local cell populations in joints aff ected by rheumatoid arthritis are synovial and cartilage cells. Synovial cells can be divided into fi broblast-like and macrophage-like synoviocytes. Overproduction of proinfl ammatory cytokines is believed to be led predominantly by macrophage-like synoviocytes. Fibroblast-like synoviocytes show abnormal behaviour in rheumatoid arthritis. In experimental models, co-implantation of fi broblast-like synoviocytes with cartilage leads to fi broblasts invading cartilage,11 behaviour that correlates with joint destruction.12 Considerable information has accumulated about joint destruction and the role of osteoclast activation as a key process leading to bone erosion. This association is proven because specifi c inhibition of osteoclast activation can reduce joint destruction yet not aff ect joint

Search strategy and selection criteria

We searched the Cochrane Library (2000–09), Medline (2000–09), and Embase (2000–09). We used the search term “rheumatoid arthritis” in combination with terms relevant for every section of the article, including: “cytokines”, auto-antibodies”, genetic risk factors”, “prevalence”, “incidence”, “assessments”, “outcome measures”, “co-morbidities”, and every specifi c treatment approach. We mainly selected publications from the past 5 years, although we did not exclude commonly referenced and highly regarded older publications. We also searched the reference lists of articles identifi ed by this search strategy and selected those we judged relevant. We selected high-quality systematic reviews in preference to individual studies. Other review articles and books were cited to provide readers with more details and references than this Seminar can accommodate.

Seminar

www.thelancet.com Vol 376 September 25, 2010 1105

complications. TWH was mainly responsible for sections on pathophysiology and classifi cation and diagnosis. All authors contributed equally to revision of the report and fi nalisation of the text. The corresponding author had fi nal responsibility for the decision to submit for publication.

Confl icts of interest DLS has received lecture fees from Merck Sharp and Dhome, Pfi zer, Novartis, Roche, and Wyeth, consultancy fees from Novartis and Schering Plough, and support for travelling to EULAR meetings from Pfi zer, Bristol-Myers Squibb, and Schering Plough. FW is director of the National Data Bank for Rheumatic Diseases, which has received support for implementing safety registries from Bristol-Myers Squibb, UCB, and Centocor, and for research studies from Pfi zer, Amgen, and Abbott. TWJH has received lecture or consultancy fees from Schering Plough, Bristol-Myers Squibb, Biotest AG, Wyeth and Pfi zer, Novartis, Roche, Sanofi -Aventis, Abbott, and Axis-Shield diagnostics, and support for travelling to EULAR and ACR meetings from Roche.

AcknowledgmentsDLS receives support from the Arthritis Research UK and is a National Institute for Health Research Senior Investigator. TWJH receives support from the European Union-funded FP7-integrated project Masterswitch no 223404, and a core grant from “Het nationaal reumafonds” (Dutch Arthritis Association). The funding sources had no role in this Seminar.

References1 Storey GO, Comer M, Scott DL. Chronic arthritis before 1876: early

British cases suggesting rheumatoid arthritis. Ann Rheum Dis 1994; 53: 557–60.

2 Ropes MW, Bennett GA, Cobb S, Jacox R, Jessar RA. 1958 revision of diagnostic criteria for rheumatoid arthritis. Arthritis Rheum 1959; 2: 16–20

3 Arnett FC, Edworthy SM, Bloch DA, et al. The American Rheumatism Association 1987 revised criteria for the classifi cation of rheumatoid arthritis. Arthritis Rheum 1988; 31: 315–24.

4 Scott DL, Coulton BL, Symmons DPM, Popert AJ. Long-term outcome of treating rheumatoid arthritis: results after 20 years. Lancet 1987; 329: 1108–11.

5 Pincus T, Brooks RH, Callahan LF. Prediction of long-term mortality in patients with rheumatoid arthritis according to simple questionnaire and joint count measures. Ann Intern Med 1994; 120: 26–34.

6 Wilson LG. Commentary: medicine, population, and tuberculosis. Int J Epidemiol 2005; 34: 521–24.

7 van der Helm-van Mil AHM, Huizinga TWJ. Advances in the genetics of rheumatoid arthritis point to subclassifi cation into distinct disease subsets. Arthritis Res Ther 2008; 10: 205.

8 van Oosterhout M, Bajema I, Levarht EW, Toes RE, Huizinga TW, van Laar JM. Diff erences in synovial tissue infi ltrates between anti-cyclic citrullinated peptide-positive rheumatoid arthritis and anti-cyclic citrullinated peptide-negative rheumatoid arthritis. Arthritis Rheum 2008; 58: 53–60.

9 Feldmann M, Brennan FM, Maini RN. Rheumatoid arthritis. Cell 1996; 85: 307–10.

10 Choy EH, Isenberg DA, Garrood T, et al. Therapeutic benefi t of blocking interleukin-6 activity with an anti-interleukin-6 receptor monoclonal antibody in rheumatoid arthritis: a randomized, double-blind, placebo-controlled, dose-escalation trial. Arthritis Rheum 2002; 46: 3143–50.

11 Müller-Ladner U, Kriegsmann J, Franklin BN, et al. Synovial fi broblasts of patients with rheumatoid arthritis attach to and invade normal human cartilage when engrafted into SCID mice. Am J Pathol 1996; 149: 1607–15.

12 Tolboom TCA, van der Helm-Van Mil AHM, Nelissen RGHH, Breedveld FC, Toes REM, Huizinga TWJ. Invasiveness of fi broblast-like synoviocytes is an individual patient characteristic associated with the rate of joint destruction in patients with rheumatoid arthritis. Arthritis Rheum 2005; 52: 1999–2002.

13 Cohen SB, Dore RK, Lane NE, et al, and the Denosumab Rheumatoid Arthritis Study Group. Denosumab treatment eff ects on structural damage, bone mineral density, and bone turnover in rheumatoid arthritis: a twelve-month, multicenter, randomized, double-blind, placebo-controlled, phase II clinical trial. Arthritis Rheum 2008; 58: 1299–309.

14 Schett G, Firestein GS. Mr Outside and Mr Inside: classic and alternative views on the pathogenesis of rheumatoid arthritis. Ann Rheum Dis 2010; 69: 787–89.

15 Lefèvre S, Knedla A, Tennie C, et al. Synovial fi broblasts spread rheumatoid arthritis to unaff ected joints. Nat Med 2009; 15: 1414–20.

16 Charbonnier LM, Han WG, Quentin J, et al. Adoptive transfer of IL-10-secreting CD4(+)CD49b(+) regulatory T cells suppresses ongoing arthritis. J Autoimmun 2010; 34: 390–99.

17 Morgan ME, Flierman R, van Duivenvoorde LM, et al. Eff ective treatment of collagen-induced arthritis by adoptive transfer of CD25+ regulatory T cells. Arthritis Rheum 2005; 52: 2212–21.

18 van der Linden MP, van der Woude D, Ioan-Facsinay A, et al. Value of anti-modifi ed citrullinated vimentin and third-generation anti-cyclic citrullinated peptide compared with second-generation anti-cyclic citrullinated peptide and rheumatoid factor in predicting disease outcome in undiff erentiated arthritis and rheumatoid arthritis. Arthritis Rheum 2009; 60: 2232–41.

19 Verpoort KN, Jol-van der Zijde CM, Papendrecht-van der Voort EA, et al. Isotype distribution of anti-cyclic citrullinated peptide antibodies in undiff erentiated arthritis and rheumatoid arthritis refl ects an ongoing immune response. Arthritis Rheum 2006; 54: 3799–808.

20 Ioan-Facsinay A, Willemze A, Robinson DB, et al. Marked diff erences in fi ne specifi city and isotype usage of the anti-citrullinated protein antibody in health and disease. Arthritis Rheum 2008; 58: 3000–08.

21 Uysal H, Bockermann R, Nandakumar KS, et al. Structure and pathogenicity of antibodies specifi c for citrullinated collagen type II in experimental arthritis. J Exp Med 2009; 206: 449–62.

22 Schuerwegh AJ, Ioan-Facsinay A, Dorjée AL, et al. Evidence for a functional role of IgE anticitrullinated protein antibodies in rheumatoid arthritis. Proc Natl Acad Sci USA 2010; 107: 2586–91.

23 van der Helm-van Mil AHM, Verpoort KN, Breedveld FC, Toes REM, Huizinga TWJ. Antibodies to citrullinated proteins and diff erences in clinical progression of rheumatoid arthritis. Arthritis Res Ther 2005; 7: R949–58.

24 van der Woude D, Houwing-Duistermaat JJ, Toes RE, et al. Quantitative heritability of anti-citrullinated protein antibody-positive and anti-citrullinated protein antibody-negative rheumatoid arthritis. Arthritis Rheum 2009; 60: 916–23.

25 Barton A, Worthington J. Genetic susceptibility to rheumatoid arthritis: an emerging picture. Arthritis Rheum 2009; 61: 1441–46.

26 Orozco G, Eyre S, Hinks A, et al. Association of CD40 with rheumatoid arthritis confi rmed in a large UK case-control study. Ann Rheum Dis 2010; 69: 813–16.

27 Stahl EA, Raychaudhuri S, Remmers EF, et al. Genome-wide association study meta-analysis identifi es seven new rheumatoid arthritis risk loci. Nat Genet 2010; 42: 508–14.

28 Plenge RM. Recent progress in rheumatoid arthritis genetics: one step towards improved patient care. Curr Opin Rheumatol 2009; 21: 262–71.

29 Huizinga TWJ, Amos CI, van der Helm-van Mil AHM, et al. Refi ning the complex rheumatoid arthritis phenotype based on specifi city of the HLA-DRB1 shared epitope for antibodies to citrullinated proteins. Arthritis Rheum 2005; 52: 3433–38.

30 Hill JA, Southwood S, Sette A, Jevnikar AM, Bell DA, Cairns E. Cutting edge: the conversion of arginine to citrulline allows for a high-affi nity peptide interaction with the rheumatoid arthritis-associated HLA-DRB1*0401 MHC class II molecule. J Immunol 2003; 171: 538–41.

31 Källberg H, Padyukov L, Plenge RM, et al, and the Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study group. Gene-gene and gene-environment interactions involving HLA-DRB1, PTPN22, and smoking in two subsets of rheumatoid arthritis. Am J Hum Genet 2007; 80: 867–75.

32 Banal F, Dougados M, Combescure C, Gossec L. Sensitivity and specifi city of the American College of Rheumatology 1987 criteria for the diagnosis of rheumatoid arthritis according to disease duration: a systematic literature review and meta-analysis. Ann Rheum Dis 2009; 68: 1184–91.

33 Morvan J, Berthelot J, Devauchelle-Pensec V, et al. Changes over time in the diagnosis of rheumatoid arthritis in a 10 year cohort. J Rheumatol 2009; 36: 2428–34.

Seminar


Severe disability in rheumatoid arthritis equates with high health-care expenses.120 Disability can progress rapidly in some patients treated with DMARDs. Economic models justify the high costs of biological agents by showing that they reduce progression of disability compared with conventional treatments, thus cutting long-term expenditure. Some models include increased workforce participation and productivity of people with rheumatoid arthritis, which is a result of biological treatment.

Economic models simplify complex issues and use historical data for comparison. Some models suggest TNF inhibitors—with costs for these biological agents in the region of £10 000 (US$14 900) per year—are generally cost eff ective;121 others draw opposite conclusions.122 To give no patients biological agents seems unsupportable, yet to treat all patients with them is economically unaff ordable. Various health-care systems have made diff erent choices about access to biological agents based on diverse interpretations of available evidence.

Tight controlThe key treatment aim should be remission or sustained low disease. This goal can be achieved with DMARD monotherapy, combinations of DMARDs (with or without glucocorticoids), and DMARD–biological combinations. So-called tight control entails increasing treatment until remission or low disease activity is achieved. Many trials use DAS2853 to monitor disease control; fi ndings of most studies show tight control is eff ective.123,124 Limitations of tight control include the need for frequent follow-up and reluctance of clinicians and patients with longstanding rheumatoid arthritis to adhere to intensive treatment strategies. Another

drawback is that patients’ perspectives of the benefi ts of intensive treatment diff er from those of clinicians.125 Many individuals fi nd taking medication unpleasant, and many specialist appointments take time and result in loss of autonomy. The cost-eff ectiveness equation seems very diff erent viewed from patients’ perspectives.

Treatment of early rheumatoid arthritisMethotrexate is usually the fi rst DMARD administered to people with rheumatoid arthritis. It should be initiated when the disease is fi rst diagnosed. The dose used and escalation of dosing have increased in recent years. Folic acid is given to limit toxic eff ects. When methotrexate is contraindicated, sulfasalazine or lefl unomide are alternatives. Findings of observational studies show many patients remain on methotrexate and it achieves good outcomes.126

Active rheumatoid arthritis needs intensive treatment. Figure 5 shows the main choices. Step-up DMARDs, with extra DMARDs added to achieve disease control, is the most conservative strategy. Initial methotrexate–biological combinations are the most expensive alternative. Parallel treatment, with several DMARDs started concurrently, is an intermediate option. DMARD combinations or methotrexate–TNF inhibitor regimens have similar effi cacy (fi gure 6).127 Early addition of biological agents for patients with incomplete responses to DMARDs seems highly eff ective, but cost-eff ectiveness of this approach is unknown.128,129

When patients achieve remission they should be stabilised on one DMARD alone. Biological agents have been tapered and stopped in individuals with early rheumatoid arthritis in remission,130 although further research is needed to ensure withdrawal is feasible. Because cessation of all DMARDs risks fl are-ups of rheumatoid arthritis, this approach is not currently recommended for most patients.131 However, some individuals can have treatment then withdraw methotrexate without the disease fl aring up. Whatever strategy is followed, patients with persistently active synovitis will eventually receive biological agents.

One unresolved diffi culty is identifi cation of subgroups of patients who are most likely to benefi t from intensive initial treatment. Another issue is deciding the best care for people with very mild early rheumatoid arthritis.

Treatment of established rheumatoid arthritisThe key aim of treatment for established rheumatoid arthritis is minimisation of disease activity. This goal can be achieved with DMARDs and biological agents singly or in combination, with or without glucocorticoids. Flare-ups and persistently active disease are treated by switching or combining DMARDs, adding glucocorticoids, and starting or switching biological agents.

TNF inhibitors are the dominant biological agent. In established disease they are usually continued unless they become ineff ective or a relevant adverse eff ect arises; this

Figure 5: Treatment strategies in early active rheumatoid arthritisDMARD=disease-modifying antirheumatic drug. TNF=tumour necrosis factor. These strategies follow recommendations from the American College of Rheumatology, European League Against Rheumatism, and the UK’s National Institute for Health and Clinical Excellence.77–79

Trea

tmen

t (m

onth

s)

Step-upConservative

InitialMethotrexatemonotherapy

If still activeAdd or switch to second

DMARD or steroids

If still activeAdd TNF inhibitor

If inactiveMethotrexatemonotherapy

ParallelIntensive

InitialMethotrexate & second

DMARD or steroids

If still activeIncrease intensity

or switch DMARDs

If still activeAdd TNF inhibitor


Early biological agentsExpensive

InitialMethotrexate plus

TNF inhibitor

If still activeContinue or switch

TNF inhibitor

If still activeSwitch biological agent


0–3

3–6

6–12

Intensity and cost of treatment

HowcanIfindanewerreview?

•  PubMed•  “rheumatoidarthritisreview”•  “Mostrecent”

•  Articlefrom2018,fromjournalwithIF8,AutoimmunityReview,reviewpaper

Review2,year2018

Contents lists available at ScienceDirect

Autoimmunity Reviewsjournal homepage: www.elsevier.com/locate/autrev

Guidelines for biomarkers in autoimmune rheumatic diseases - evidencebased analysisRoberto Giacomellia,⁎, Antonella Afeltrab, Alessia Alunnoc, Elena Bartoloni-Boccic,Onorina Berardicurtia, Michele Bombardierid, Alessandra Bortoluzzie, Roberto Caporalif,Francesco Casog, Ricard Cerverah, Maria Sole Chimentii, Paola Cipriania, Emmanuel Colomah,Fabrizio Contij, Salvatore D’Angelok, Salvatore De Vital, Salvatore Di Bartolomeoa,Oliver Distlerm, Andrea Dorian, Eugen Feisto, Benjamin A. Fisherp, Maria Gerosaq, Michele Giliok,Giuliana Gugginor, Vasiliki Liakoulia, Domenico Paolo Emanuele Margiottab, Pierluigi Meroniq,Gianluca Moroncinis, Federico Perosat, Marcella Pretet, Roberta Priorij, Chiara Rebuffiu,Piero Ruscittia, Raffaele Scarpag, Yehuda Shoenfeldv, Monica Todoertif, Francesco Ursiniw,Guido Valesinij, Serena Vettorix, Claudio Vitaliy, Athanasios G. Tzioufasza Department of Biotechnological and Applied Clinical Science, Rheumatology Unit, School of Medicine, University of L'Aquila, Delta 6 Building, Via dell'Ospedale, 67100L'Aquila, ItalybDepartment of Medicine, Unit of Allergology, Immunology, Rheumatology, Campus Bio-Medico University of Rome, Via Álvaro del Portillo 21, 00128 Rome, Italyc Rheumatology Unit, Department of Medicine, University of Perugia, Perugia, Italyd Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Queen Mary University of London, London, UK.e Department of Medical Science, Section of Rheumatology, University of Ferrara and Azienda Ospedaliero-Universitaria S.Anna, Cona, Ferrara, Italyf IRCCS Policlinico San Matteo Foundation, Division of Rheumatology, University of Pavia, Pavia, Italyg Department of Clinical Medicine and Surgery, Rheumatology Unit, University of Naples Federico II, Naples, ItalyhDepartment of Autoimmune Diseases, Hospital Clínic, Barcelona, Catalonia, SpainiDepartment of Medicina dei Sistemi, Rheumatology, Allergology and Clinical Immunology, University of Rome Tor Vergata, Rome, ItalyjDepartment of Internal Medicine and Medical Specialties, Rheumatology Unit, Sapienza University of Rome, Rome, Italyk PhD Scholarship in Life Sciences, Department of Health Sciences, University of Catanzaro "Magna Graecia", Catanzaro, Italy.l Department of Medical and Biological Sciences, Rheumatology Clinic, Azienda Ospedaliero Universitaria S. Maria della Misericordia, University of Udine, Udine, ItalymDepartment of Rheumatology, University Hospital Zurich, Zurich, Switzerlandn Rheumatology Unit, Department of Medicine, DIMED, University of Padua, Padua, Italyo Department of Rheumatology and Clinical Immunology of the Charité, Universitätsmedizin Berlin, Berlin, Germanyp Rheumatology Research Group and Arthritis Research UK Rheumatoid Arthritis Pathogenesis Centre of Excellence (RACE), University of Birmingham, Birmingham, UK;Department of Rheumatology, University Hospitals Birmingham NHS Trust, Birmingham, UKq Immunorheumatology Research Laboratory, Istituto Auxologico Italiano, Milan, Italyr Dipartimento Biomedico di Medicina Interna e Specialistica, Rheumatology section, University of Palermo, Italy.sDepartment of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, ItalytDepartment of Biomedical Sciences and Human Oncology (DIMO), Systemic Rheumatic and Autoimmune Diseases Unit, University of Bari Medical School, Bari, ItalyuGrant Office and Scientific Documentation Center, IRCCS Policlinico San Matteo Foundation, Pavia, Italyv Zabludowitz Centre for Autoimmune Diseases, Sheba Medical Centre, Tel-Hashomer, Israelw Department of Health Sciences, University of Catanzaro "Magna Graecia", Catanzaro, Italyx Department of Precision Medicine, University of Campania "Luigi Vanvitelli", Naples, Italy.y Villa San Giuseppe, Istituto S. Stefano, Como, Italyz Pathophysiology Department, General Hospital of Athens "Laiko", Medical School, National and Kapodistrian University of Athens, Greece

A R T I C L E I N F O

Keywords:BiomarkerRheumatoid arthritisSpondyloarthritidesSystemic sclerosis

A B S T R A C T

Autoimmune rheumatic diseases are characterised by an abnormal immune system response, complement ac-tivation, cytokines dysregulation and inflammation. In last years, despite many progresses in managing thesepatients, it has been shown that clinical remission is reached in less than 50% of patients and a personalised andtailored therapeutic approach is still lacking resulting in a significant gap between guidelines and real-world

https://doi.org/10.1016/j.autrev.2018.08.003Received 6 August 2018; Accepted 11 August 2018

⁎ Corresponding author at: Department of Biotechnological and Applied Clinical Science, Rheumatology Unit, School of Medicine, University of L'Aquila, Delta 6Building, Via dell'Ospedale, 67100 L'Aquila, Italy.

E-mail address: [email protected] (R. Giacomelli).

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2. Methods

2.1. Aims of the project

The overarching aim of this workshop is to clarify the meaning ofspecific biomarkers during autoimmune diseases; their possible role inconfirming diagnosis, predicting outcome and suggesting specifictreatments. The general methodology based on a Delphi Technique-based aimed at producing, starting from the results of a systematic re-view of available literature, a set of statements summarising the con-sensus among the Experts, as previously reported [12]. This systematicreview has been designed to be included in an International projectnamed “Clinical and biological biomarkers in conventional and/or biolo-gical therapies. From pathology to treatment: what evidence in rheumaticand autoimmune diseases? 2th International workshop” aimed to updatesome features in management of patients affected by autoimmunedisease. As a part of an International project, a Scientific Committeecomposed by a group of experts and bibliographic fellows identifiedsome relevant clinical questions on biomarkers in autoimmune diseases,needing further and updated clarifications according to available sci-entific evidence and joined Experts’ opinion. These invitations were aconsequence of the individuals’ contributions to the specific fields in-cluded in the topics of the meeting as well as deliberations amongmembers of the steering committee. Six autoimmune diseases wereselected and evaluated: rheumatoid arthritis (RA), spondyloarthritides(SpA), systemic sclerosis (SSc), systemic lupus erythematosus (SLE),antiphospholipid syndrome (APS), primary Sjogren’s syndrome (pSS).These topics were developed and updated throughout an extensivebibliographic review by the Steering Board, after joining common limitsand methods of search. For each selected topic, preliminary statementsbased on available scientific results have been presented in accordancewith their level of evidence, discussed, eventually reformulated, andvoted through a Delphi-method during a Consensus involving a panel ofInternational Experts. Statements supported by ≥ 66% of votes wereaccepted as final statements, while the others were rejected outright.This project has been concluded in Italy on October 6-7, 2017.

2.2. Search design

For each of these 6 topics, a systematic literature search was per-formed in indexed international Journals (Medline via Pubmed, Scopus,Cochrane database). The Scientific Committee decided to analyse theliterature from July 1, 2007 – July 1, 2017. The choices of temporallimits, online databases and methodology were originally discussed andshared by participants in order to gain homogeneous results.

2.3. Search strategy

The search strategy combined indexed and free-text terms, inter-ventions and outcomes of interest in Medline via Pubmed, Scopus,Cochrane database, as requested for each single topic. PICO strategywas also joined as shared rephrasing strategy across working groups,along with pre-defined “Population”, “Intervention”, “Comparison”,“Outcomes”, as requested by single topic research question. The mainsearch was thus formulated using a string of relevant terms of research.In addition, the main keywords were used in different combinations inorder to improve the sensitivity of the search strategy. The bibliographyof relevant articles was also hand-searched for identification of otherpotentially suitable studies.

2.4. Eligibility criteria

Included studies were full-text manuscripts in English languageconducted in adult patients with autoimmune diseases. To be includedin the final analysis, studies had to meet the following joined inclusioncriteria: 1) study design: systematic review and meta-analysis,

randomised controlled trial (RCT), quasi-RCT (trials in which allocationto treatment was made by alternation, use of alternate medical records,date of birth or other expected methods), observational cohort studiesor case series; 2) data concerning population, intervention, comparisonand outcomes were requested for each single selected topic. Narrativereviews, editorials, scientific conference abstracts, case reports and pre-clinical studies have been excluded from the purpose of this work.Papers retrieved by literature search but reporting insufficient dataaccording to selected PICO strategy were excluded from the review. Thehierarchy of study types was indicated by levels of evidence suggestedby Oxford University (http://www.cebm.net/oxford-centre-evidence-based-medicine-levels-evidence-march-2009/).

2.5. Study identification and data extraction

In each group working on a single topic, full-text articles werescreened and selected analysing titles and abstracts by bibliographicfellows, then independently verified by corresponding senior reviewers.After the screening phase, the bibliographic fellows also independentlyevaluated the selected abstracts and the full-text of these studies todetermine eligibility according to the eligibility criteria. Any un-certainties and/or disagreements were resolved by discussion untilreaching a final consensus. Data extraction was also performed bybibliographic fellows and independently verified by corresponding se-nior reviewers. After that, the results of the analysis of literature weresummarised, presented, and further inputs were obtained from ex-panded working groups with other authors. Conflicting results wereanalysed by discussion taking into account quality of assessed studiesuntil reaching an agreement into the single working group. The state-ments were thus formulated according to results and quality of eval-uated works. Further disagreements were resolved by discussion untilreaching a final consensus. In the subsequent plenary session, thestatements were subjected to be voted as ‘yes’ (agreement) or ‘no’(disagreement) from the entire panel of Experts. Statements supportedby ≥ 66% of positive votes were accepted while the others were re-jected outright. At this final stage, only suggestions for improvements ofclarity of wording or addressing redundancies were considered, whileany change to the meaning was not accepted.

3. RA working group

To date, recognition and better definition of disease-specific bio-markers, easily and routinely detectable in patients serum samples,could be relevant for diagnostic and prognostic purposes in the view ofa more patients’ tailored approach, regardless of the underlying con-dition. Anti-citrullinated protein antibodies (ACPA) and rheumatoidfactor (RF) are well recognized clinically relevant biomarkers in rheu-matoid arthritis (RA) patients [13]. Their pathogenic role has been wellcharacterized, being detectable in the serum in pre-clinical phase manyyears before clinical presentation of the disease. Moreover, both bio-markers have been included in the new 2010 RA classification criteriainto a score-based algorithm where both qualitative (negative versuspositive) and quantitative (low level versus high level) evaluations havebeen inserted, with high level (predefined as≥3 times the ULN for thelaboratory test and assay) having greater weight in substantially con-tributing to RA diagnosis [14]. In the 2016 update of EULAR re-commendations for RA management, either presence and levels of RFand/or ACPA have been listed among several other prognostic factors tobe considered during therapeutic management, too. Moving from thisstarting point, it could be clarified whether a better definition of suchbiomarkers (high versus low serum levels) might help clinicians in termof discriminative ability in diagnostic accuracy (as diagnostic and dif-ferential diagnostic tool) and prognostic stratification (disease course,radiographic damage, response to therapy). In other words, throughoutan extended systematic review on the topic in line with joined pre-specified limits and settings, the clinical meaning of “level criterion” of

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Review

•  Summary,analysis,comparison•  Definegapsandproblems•  Recommendfutureresearch•  Donotpresentnewresearchdata•  Threetypes– Literaturereviews– Systematicreview– Meta-analysis

Whatisthetherapyforrheumatoidarthritis?

•  DMARDs•  Biologictherapy

of rheumatoid arthritis: a study of serial measurements in blood donors. ArthritisRheum 2004 Feb;50(2):380–6.

[14] Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham CO 3rd, BirnbaumNS, Burmester GR, Bykerk VP, Cohen MD, Combe B, Costenbader KH, DougadosM, Emery P, Ferraccioli G, Hazes JM, Hobbs K, Huizinga TW, Kavanaugh A, Kay J,Kvien TK, Laing T, Mease P, Ménard HA, Moreland LW, Naden RL, Pincus T,Smolen JS, Stanislawska-Biernat E, Symmons D, Tak PP, Upchurch KS, VencovskyJ, Wolfe F, Hawker G. 2010 rheumatoid arthritis classification criteria: anAmerican College of Rheumatology/European League Against Rheumatism colla-borative initiative. Ann Rheum Dis 2010 Sep;69(9):1580-8.

[15] Demoruelle MK, Parish MC, Derber LA, Kolfenbach JR, Hughes-Austin JM,Weisman MH, et al. Performance of anti-cyclic citrullinated Peptide assays differsin subjects at increased risk of rheumatoid arthritis and subjects with establisheddisease. Arthritis Rheum 2013 Sep;65(9):2243–52.

[16] Hensvold AH, Frisell T, Magnusson PK, Holmdahl R, Askling J, Catrina AI. Howwell do ACPA discriminate and predict RA in the general population: a study basedon 12 590 population-representative Swedish twins. Ann Rheum Dis 2017Jan;76(1):119–25.

[17] Abolghasemi S, et al. The sensitivity, specificity and accuracy of anti-citrullineantibody test in diagnosis of rheumatoid arthritis. Rheumatol Int 2013Apr;33(4):1027–30.

[18] Payet J, et al. Anticyclic citrullinated peptide antibodies in rheumatoid and non-rheumatoid rheumatic disorders: experience with 1162 patients. J Rheumatol2014 Dec;41(12):2395–402.

[19] Heidari B, et al. The prevalence and diagnostic performance of anti-cyclic ci-trullinated peptide antibody in rheumatoid arthritis: the predictive and dis-criminative ability of serum antibody level in recognizing rheumatoid arthritis.Ann Saudi Med 2009 Nov-Dec;29(6):467–70.

[20] Li H, et al. Diagnostic value of anti-cyclic citrullinated peptide antibodies innorthern Chinese Han patients with rheumatoid arthritis and its correlation withdisease activity. Clin Rheumatol 2010 Apr;29(4):413–7.

[21] Kim DA, et al. Is serum anti-cyclic citrullinated peptide level useful in the diagnosisof rheumatoid arthritis? Clin Chim Acta 2012 Apr 11;413(7-8):831–2.

[22] Pietrapertosa D, et al. Diagnostic performance of anti-citrullinated peptide anti-bodies for the diagnosis of rheumatoid arthritis: the relevance of likelihood ratios.Clin Chem Lab Med 2010 Jun;48(6):829–34.

[23] Syversen SW, et al. High anti-cyclic citrullinated peptide levels and an algorithm offour variables predict radiographic progression in patients with rheumatoid ar-thritis: results from a 10-year longitudinal study. Ann Rheum Dis 2008Feb;67(2):212–7.

[24] Vastesaeger N, et al. A pilot risk model for the prediction of rapid radiographicprogression in rheumatoid arthritis. Rheumatology (Oxford) 2009Sep;48(9):1114–21. https://doi.org/10.1093/rheumatology/kep155.

[25] van der Linden MP, et al. Van Der Linden MPM, et al. Toward a data-drivenevaluation of the 2010 American College of Rheumatology/European LeagueAgainst Rheumatism Criteria for rheumatoid arthritis. Is it sensible to look at levelsof rheumatoid factor? Arthritis Rheum 2011;63(5):1190–9.

[26] Hecht C, et al. Additive effect of anti-citrullinated protein antibodies and rheu-matoid factor on bone erosions in patients with RA. Ann Rheum Dis 2015Dec;74(12):2151–6.

[27] Shiozawa K, et al. Anticitrullinated protein antibody, but not its titer, is a predictorof radiographic progression and disease activity in rheumatoid arthritis. JRheumatol 2012 Apr;39(4):694–700.

[28] Aletaha D, et al. Rheumatoid factor determines structural progression of rheu-matoid arthritis dependent and independent of disease activity. Ann Rheum Dis2013 Jun;72(6):875–80.

[29] Avdeeva AS, et al. The relationship of antibodies to modified citrullinated vi-mentin and markers of bone and cartilage destruction in rheumatoid arthritis. Int JRheumatol 2014;2014:464585.

[30] Syversen SW, et al. Prediction of radiographic progression in rheumatoid arthritisand the role of antibodies against mutated citrullinated vimentin: results from a10-year prospective study. Ann Rheum Dis 2010 Feb;69(2):345–51.

[31] Koga T, et al. Anti-citrullinated peptide antibodies are the strongest predictor ofclinically relevant radiographic progression in rheumatoid arthritis patientsachieving remission or low disease activity: A post hoc analysis of a nationwidecohort in Japan. PLoS One 2017;12(5).

[32] Miriovsky BJ, et al. Anti-CCP antibody and rheumatoid factor concentrationspredict greater disease activity in men with rheumatoid arthritis. Ann Rheum Dis2010 Jul;69(7):1292–7.

[33] Pomirleanu C, et al. A predictive model for remission and low disease activity inpatients with established rheumatoid arthritis receiving TNF blockers. ClinRheumatol 2013 May;32(5):665–70.

[34] Salgado E, et al. Rheumatoid factor and response to TNF antagonists in rheumatoidarthritis: systematic review and meta-analysis of observational studies. Joint BoneSpine 2014 Jan;81(1):41–50.

[35] Klaasen R, et al. The value of rheumatoid factor and anti-citrullinated proteinantibodies as predictors of response to infliximab in rheumatoid arthritis: an ex-ploratory study. Rheumatology (Oxford) 2011 Aug;50(8):1487–93.

[36] Salgado E, et al. Rheumatoid factor does not predict response to TNF antagonists inrheumatoid arthritis: three centers experience. Joint Bone Spine 2013Jul;80(4):438–40.

[37] Lal P, et al. Inflammation and autoantibody markers identify rheumatoid arthritispatients with enhanced clinical benefit following rituximab treatment. ArthritisRheum 2011 Dec;63(12):3681–91.

[38] Cuchacovich M, et al. Basal anti-cyclic citrullinated peptide (anti-CCP) antibodylevels and a decrease in anti-CCP titersare associated with clinical response to

adalimumab in rheumatoid arthritis. Clin Exp Rheumatol 2008 Nov-Dec;26(6):1067–73.

[39] Narvaez J, et al. Predictors of response to rituximab in patients with activerheumatoid arthritis and inadequate response to anti-TNF agents or traditionalDMARDs. Clin Exp Rheumatol 2011 Nov-Dec;29(6):991–7. Epub 2011 Dec 22.

[40] Sokolove J, et al. Impact of baseline anti-cyclic citrullinated peptide-2 antibodyconcentration on efficacy outcomes following treatment with subcutaneous aba-tacept or adalimumab: 2-year results from the AMPLE trial. Ann Rheum Dis2016;75(4):709–14.

[41] Pruijn GJ. Citrullination and carbamylation in the pathophysiology of rheumatoidarthritis. Front Immunol 2015 Apr 27;6:192.

[42] Verheul MK, van Veelen PA, van Delft MAM, de Ru A, Janssen GMC, Rispens T,et al. Pitfalls in the detection of citrullination and carbamylation. Autoimmun Rev2018 Feb;17(2):136–41.

[43] Li L, Deng C, Chen S, Zhang S, Wu Z, Hu C, et al. Meta-Analysis: DiagnosticAccuracy of Anti-Carbamylated Protein Antibody for Rheumatoid Arthritis. PLoSOne 2016 Jul 20;11(7):e0159000.

[44] Shi J, Knevel R, Suwannalai P, van der Linden MP, Janssen GM, van Veelen PA,et al. Autoantibodies recognizing carbamylated proteins are present in sera ofpatients with rheumatoid arthritis and predict joint damage. Proc Natl Acad Sci US A 2011 Oct 18;108(42):17372–7.

[45] Ajeganova S, van Steenbergen HW, Verheul MK, Forslind K, Hafström I, Toes RE,et al. The association between anti-carbamylated protein (anti-CarP) antibodiesand radiographic progression in early rheumatoid arthritis: a study exploring re-plication and the added value to ACPA and rheumatoid factor. Ann Rheum Dis2017 Jan;76(1):112–8.

[46] Brink M, Verheul MK, Rönnelid J, Berglin E, Holmdahl R, Toes RE, et al. Anti-carbamylated protein antibodies in the pre-symptomatic phase of rheumatoid ar-thritis, their relationship with multiple anti-citrulline peptide antibodies and as-sociation with radiological damage. Arthritis Res Ther 2015 Feb 7;17:25.

[47] Spinelli FR, Pecani A, Ciciarello F, Colasanti T, Di Franco M, Miranda F, et al.Association between antibodies to carbamylated proteins and subclinical athero-sclerosis in rheumatoid arthritis patients. BMC Musculoskelet Disord 2017 May25;18(1):214.

[48] Vidal-Bralo L, Perez-Pampin E, Regueiro C, Montes A, Varela R, Boveda MD.Gomez-Reino JJ Gonzalez A. Anti-carbamylated protein autoantibodies associatedwith mortality in Spanish rheumatoid arthritis patients. PLoS One 2017 Jul3;12(7):e0180144.

[49] Peabody JW, Strand V, Shimkhada R, Lee R, Chernoff D. Impact of rheumatoidarthritis disease activity test on clinical practice. PLoS One 2013 May7;8(5):e63215.

[50] Fleischmann R, Connolly SE, Maldonado MA, Schiff M. Brief Report: EstimatingDisease Activity Using Multi-Biomarker Disease Activity Scores in RheumatoidArthritis Patients Treated With Abatacept or Adalimumab. Arthritis Rheum 2016Sep;68(9):2083–9.

[51] Bakker MF, Cavet G, Jacobs JW, Bijlsma JW, Haney DJ, Shen Y, et al. Performanceof a multi-biomarker score measuring rheumatoid arthritis disease activity in theCAMERA tight control study. Ann Rheum Dis 2012 Oct;71(10):1692–7.

[52] Bouman CAM, van der Maas A, van Herwaarden N, Sasso EH, van den HoogenFHJ, den Broeder AA. A multi-biomarker score measuring disease activity inrheumatoid arthritis patients tapering adalimumab or etanercept: predictive valuefor clinical and radiographic outcomes. Rheumatology (Oxford) 2017 Jun1;56(6):973–80.

[53] Hambardzumyan K, Bolce R, Saevarsdottir S, Cruickshank SE, Sasso EH, ChernoffD, et al. Pretreatment multi-biomarker disease activity score and radiographicprogression in early RA: results from the SWEFOT trial. Ann Rheum Dis 2015Jun;74(6):1102–9.

[54] Krabbe S, Bolce R, Brahe CH, Døhn UM, Ejbjerg BJ, Hetland ML, et al.Investigation of a multi-biomarker disease activity score in rheumatoid arthritis bycomparison with magnetic resonance imaging, computed tomography, ultra-sonography, and radiography parameters of inflammation and damage. Scand JRheumatol 2017 Sep;46(5):353–8.

[55] Hambardzumyan K, Saevarsdottir S, Forslind K, Petersson IF, Wallman JK,Ernestam S, et al. A multi-biomarker disease activity score and the choice ofsecond-line therapy in early rheumatoid arthritis after methotrexate failure.Arthritis Rheum 2017 May;69(5):953–63.

[56] Rech J, Hueber AJ, Finzel S, Englbrecht M, Haschka J, Manger B, et al. Predictionof disease relapses by multibiomarker disease activity and autoantibody status inpatients with rheumatoid arthritis on tapering DMARD treatment. Ann Rheum Dis2016 Sep;75(9):1637–44.

[57] Sieper J, Poddubnyy D. Axial spondyloarthritis. Lancet 2017;390(10089):73–84.[58] Chimenti MS, Ballanti E, Perricone C, Cipriani P, Giacomelli R, Perricone R.

Immunomodulation in Psoriatic arthritis: Focus on cellular and molecular path-ways. Autoimmun Rev 2013;12(5):599–606.

[59] Scarpa R, Caso F, Costa L, Peluso R, Del Puente A, Olivieri I. Psoriatic Disease 10Years Later. J Rheumatol 2017 Sep;44(9):1298–301.

[60] Salvarani C, Cantini F, Olivieri I, Macchioni P, Niccoli L, Padula A, et al. Isolatedperipheral enthesitis and/or dactylitis: a subset of psoriatic arthritis. J Rheumatol1997 Jun;24(6):1106–10.

[61] Caso F, Costa L, Atteno M, Del Puente A, Cantarini L, Lubrano E, et al. Simpleclinical indicators for early psoriatic arthritis detection. Springerplus 2014;3:759.

[62] D'Angelo S, Tramontano G, Gilio M, Leccese P, Olivieri I. Review of the treatmentof psoriatic arthritis with biological agents: choice of drug for initial therapy andswitch therapy for non-responders. Open Access Rheumatol 2017 Mar 2;9:21–8.

[63] Carvalho PD, Duarte C, Vieira-Sousa E, Cunha-Miranda L, Avila-Ribeiro P, SantosH, et al. Predictors of response to TNF blockers in patients with polyarticular


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poorly correlated with MRI/US indexes of inflammation, elevated va-lues were determined in patients characterised by more severe radio-graphic damage [54].

Analysing MBDA and response to treatment, Hambardzumyan et al.described the MBDA to be predictive for optimal add-on treatment innon-responder RA patients [55]. Authors assessed data from 157 pa-tients enrolled in SWEFOT trial, after 3 months of methotrexate (MTX)therapy. A significant percentage of patients characterised by a lowMBDA score experienced a good clinical response to subsequent tripletherapy (MTX+sulfasalazine+hydroxychloroquine), whereas in pa-tients displaying a high MBDA score, a significant percentage experi-enced a good clinical response to subsequent combination therapy withTNFi (MTX+infliximab) [55]. Finally, in the analysis of RETRO studyMBDA scores were investigated to be predictive of disease relapse.RETRO was a phase-3, multicentre, randomised, open, prospective,controlled, parallel-group study in patients were allocated to continueconventional and/or biological DMARD regimen at full dose for 12months, to reduce the dose of all conventional and/or biologicalDMARDs by 50% or to reduce the dose of all conventional and/orbiological DMARDs by 50% for the first 6 months before to entirely stopall DMARDs. The results showed that higher values of MBDA scores inpatients experiencing disease relapse after tapering and/or stoppingconventional and/or biological DMARDs treatment, allowing a predic-tion of relapse in more than 80% of the patients [56].

Future specific designed and adequately powered studies with alonger follow up are needed to fully clarify the role of MBDA in man-agement of RA patients, in predicting radiographic progression as wellas response to therapeutic strategies.

4. Spondyloarthritides working group

The spondyloarthritis (SpA) complex includes a group of in-flammatory rheumatic diseases with peculiar clinical and radiologicalfeatures including sacroiliitis, enthesitis, and dactylitis [57]. AmongSpA, psoriatic arthritis (PsA) is characterized for a broad and hetero-geneous spectrum of clinical features and courses [58,59]. In somecases, PsA can occur with peripheral enthesitis, particularly Achillestendinitis, and/or dactylitis [60,61]. In the last decades, an increasingattention has been paid to the erosive and deforming course of PsA(40%–60% of patients) [62]. The identification of clinical and biolo-gical predictors of response to different biological disease-modifyinganti-rheumatic drugs (bDMARDs) might help clinicians to make evi-dence-based decisions that maximise the benefits from treatment bytargeting subsets of patients. In addition, this approach could also im-prove the cost/benefit and benefit/risk ratios in patients selected tostart bDMARDs treatment [63].

4.1. Although enthesitis may be considered a clinical marker of PsA, there isno evidence showing that its presence at baseline predicts the response todifferent bDMARDs (TNFis, IL17is, IL12/IL23is). LoE 5

Enthesitis is the inflammation of the insertion of tendons and liga-ments into the bone and represents a hallmark of PsA and SpA [64]. Itcan be considered among the first signs of PsA, occurring independentlyof arthritis [60]. The role of enthesitis as a predictor of treatment re-sponse in ankylosing spondylitis (AS) has been well defined in 2011 byVastesaeger et al. [65]. Thereafter, in 2013, in a retrospective study,Spadaro et al. and co-workers showed that in AS patients treated withadalimumab, etanercept or infliximab, the probability of obtainingpartial remission was significantly lower when enthesitis was present atbaseline [66]. In PsA patients, there are no studies evaluating the role ofenthesitis as an independent clinical biomarker predicting the responseamong different bDMARDs (TNFis, IL17is, IL12/IL23is).

4.2. Although data available on biomarkers for predicting therapeuticresponse in SpA are scarce, CRP in clinical practice may be useful inpredicting TNFis response. LoE 2b

Only few articles addressed the potential role of soluble biomarkersin prediction of treatment response to TNFis in SpA patients. The ma-jority of these studies were characterised by a weak methodology,mainly due to low power or lack of power calculation and an un-controlled design. Amongst the potential biomarkers, baseline serumlevels of matrix metalloproteinase-3 (MMP-3) [67,68], serum type Icollagen C-telopeptide (sCTX) [69], complement fraction C3 [70],serum amyloid A (SAA) [71], anti-drug antibodies (ADAbs) [72], andIL-6 [73] have been reported to predict treatment response in in-dividual studies. Moreover, two well-designed sub-studies of RCTsevaluated the predictivity of a large pool of soluble biomarkers in ASand PsA [74,75]. In particular, baseline levels of insulin, apolipoproteinC3, leptin, haptoglobin, IL-6, osteocalcin, procollagen type 1 amino-terminal propeptide (P1NP) and deoxypyridinoline were associatedwith ASAS20 response at week 14 in AS patients while baseline levels ofadiponectin, prostatic acid phosphatase (PAP) and vascular endothelialgrowth factor (VEGF) predicted at least two out of the three clinicalendpoints (ACR20, DAS28, PASI75) after 14 weeks in PsA patients. Theresults of the systematic review showed that only higher baseline C-reactive protein CRP values were consistently reported to predict re-sponse to treatment with TNFis in SpA patients, although this evidencerelies mainly on observational studies [71,74,76] and only one RCT[73].

5. SSc working group

SSc has the highest fatality rate among connective tissue diseasesand is characterized by cellular and humoral immunological abnorm-alities, fibroproliferative vasculopathy, and fibrosis of the skin andvarious internal organs. Pulmonary involvement, including both inter-stitial lung disease (ILD) and pulmonary arterial hypertension (PAH) iscurrently the primary cause of morbidity and mortality in SSc [77]. Thecourse of ILD is highly variable, and patients may develop severe andrapidly progressive interstitial lung involvement during the early phaseof the disease, while others may have a limited and non-progressivecourse [78–81]. The clinical course of untreated PAH is in most casesrapidly progressive leading to respiratory failure or death within 2–3years after it becomes clinically detectable [82]. In this context, theidentification of biomarkers for assessing certain phenotypes associatedwith an increased risk of developing severe and rapidly progressive ILDand/or PAH is extremely important [83]. At present, despite intenseinvestigation, only a few biomarkers for SSc have been fully validatedand widely accepted. On this background, five statements were for-mulated and voted.

5.1. Anti-topoisomerase 1 antibody is a biomarker for faster progression ofSSc-ILD. LoE 2b

Anti-topoisomerase 1 antibody is directed against DNA topoisome-rase I and is strongly associated with the diffuse form of SSc and withthe development and/or faster progression of ILD. The Genetics versusEnvironment in Scleroderma Outcome Study (GENISOS), based on aprospective, observational cohort of 266 patients with early systemicsclerosis, confirmed that the presence of anti-topoisomerase 1 antibodywas the only variable associated with differential forced vital capacity(FVC) levels, predicting the rate of decline in FVC within the first 3years of follow-up [80]. Subsequently, a study cohort consisting of 398consecutive SSc patients with follow-up for up to 15 years confirmedthat anti–topoisomerase 1 antibody remained a significant predictor ofthe development of clinically significant pulmonary fibrosis togetherwith other variables such as dcSSc, lower FVC, and lower diffusing lungcapacity for carbon monoxide (DLCO). In this study, SSc-ILD was


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•  Impactfactor6

of rheumatoid arthritis: a study of serial measurements in blood donors. ArthritisRheum 2004 Feb;50(2):380–6.

[14] Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham CO 3rd, BirnbaumNS, Burmester GR, Bykerk VP, Cohen MD, Combe B, Costenbader KH, DougadosM, Emery P, Ferraccioli G, Hazes JM, Hobbs K, Huizinga TW, Kavanaugh A, Kay J,Kvien TK, Laing T, Mease P, Ménard HA, Moreland LW, Naden RL, Pincus T,Smolen JS, Stanislawska-Biernat E, Symmons D, Tak PP, Upchurch KS, VencovskyJ, Wolfe F, Hawker G. 2010 rheumatoid arthritis classification criteria: anAmerican College of Rheumatology/European League Against Rheumatism colla-borative initiative. Ann Rheum Dis 2010 Sep;69(9):1580-8.

[15] Demoruelle MK, Parish MC, Derber LA, Kolfenbach JR, Hughes-Austin JM,Weisman MH, et al. Performance of anti-cyclic citrullinated Peptide assays differsin subjects at increased risk of rheumatoid arthritis and subjects with establisheddisease. Arthritis Rheum 2013 Sep;65(9):2243–52.

[16] Hensvold AH, Frisell T, Magnusson PK, Holmdahl R, Askling J, Catrina AI. Howwell do ACPA discriminate and predict RA in the general population: a study basedon 12 590 population-representative Swedish twins. Ann Rheum Dis 2017Jan;76(1):119–25.

[17] Abolghasemi S, et al. The sensitivity, specificity and accuracy of anti-citrullineantibody test in diagnosis of rheumatoid arthritis. Rheumatol Int 2013Apr;33(4):1027–30.

[18] Payet J, et al. Anticyclic citrullinated peptide antibodies in rheumatoid and non-rheumatoid rheumatic disorders: experience with 1162 patients. J Rheumatol2014 Dec;41(12):2395–402.

[19] Heidari B, et al. The prevalence and diagnostic performance of anti-cyclic ci-trullinated peptide antibody in rheumatoid arthritis: the predictive and dis-criminative ability of serum antibody level in recognizing rheumatoid arthritis.Ann Saudi Med 2009 Nov-Dec;29(6):467–70.

[20] Li H, et al. Diagnostic value of anti-cyclic citrullinated peptide antibodies innorthern Chinese Han patients with rheumatoid arthritis and its correlation withdisease activity. Clin Rheumatol 2010 Apr;29(4):413–7.

[21] Kim DA, et al. Is serum anti-cyclic citrullinated peptide level useful in the diagnosisof rheumatoid arthritis? Clin Chim Acta 2012 Apr 11;413(7-8):831–2.

[22] Pietrapertosa D, et al. Diagnostic performance of anti-citrullinated peptide anti-bodies for the diagnosis of rheumatoid arthritis: the relevance of likelihood ratios.Clin Chem Lab Med 2010 Jun;48(6):829–34.

[23] Syversen SW, et al. High anti-cyclic citrullinated peptide levels and an algorithm offour variables predict radiographic progression in patients with rheumatoid ar-thritis: results from a 10-year longitudinal study. Ann Rheum Dis 2008Feb;67(2):212–7.

[24] Vastesaeger N, et al. A pilot risk model for the prediction of rapid radiographicprogression in rheumatoid arthritis. Rheumatology (Oxford) 2009Sep;48(9):1114–21. https://doi.org/10.1093/rheumatology/kep155.

[25] van der Linden MP, et al. Van Der Linden MPM, et al. Toward a data-drivenevaluation of the 2010 American College of Rheumatology/European LeagueAgainst Rheumatism Criteria for rheumatoid arthritis. Is it sensible to look at levelsof rheumatoid factor? Arthritis Rheum 2011;63(5):1190–9.

[26] Hecht C, et al. Additive effect of anti-citrullinated protein antibodies and rheu-matoid factor on bone erosions in patients with RA. Ann Rheum Dis 2015Dec;74(12):2151–6.

[27] Shiozawa K, et al. Anticitrullinated protein antibody, but not its titer, is a predictorof radiographic progression and disease activity in rheumatoid arthritis. JRheumatol 2012 Apr;39(4):694–700.

[28] Aletaha D, et al. Rheumatoid factor determines structural progression of rheu-matoid arthritis dependent and independent of disease activity. Ann Rheum Dis2013 Jun;72(6):875–80.

[29] Avdeeva AS, et al. The relationship of antibodies to modified citrullinated vi-mentin and markers of bone and cartilage destruction in rheumatoid arthritis. Int JRheumatol 2014;2014:464585.

[30] Syversen SW, et al. Prediction of radiographic progression in rheumatoid arthritisand the role of antibodies against mutated citrullinated vimentin: results from a10-year prospective study. Ann Rheum Dis 2010 Feb;69(2):345–51.

[31] Koga T, et al. Anti-citrullinated peptide antibodies are the strongest predictor ofclinically relevant radiographic progression in rheumatoid arthritis patientsachieving remission or low disease activity: A post hoc analysis of a nationwidecohort in Japan. PLoS One 2017;12(5).

[32] Miriovsky BJ, et al. Anti-CCP antibody and rheumatoid factor concentrationspredict greater disease activity in men with rheumatoid arthritis. Ann Rheum Dis2010 Jul;69(7):1292–7.

[33] Pomirleanu C, et al. A predictive model for remission and low disease activity inpatients with established rheumatoid arthritis receiving TNF blockers. ClinRheumatol 2013 May;32(5):665–70.

[34] Salgado E, et al. Rheumatoid factor and response to TNF antagonists in rheumatoidarthritis: systematic review and meta-analysis of observational studies. Joint BoneSpine 2014 Jan;81(1):41–50.

[35] Klaasen R, et al. The value of rheumatoid factor and anti-citrullinated proteinantibodies as predictors of response to infliximab in rheumatoid arthritis: an ex-ploratory study. Rheumatology (Oxford) 2011 Aug;50(8):1487–93.

[36] Salgado E, et al. Rheumatoid factor does not predict response to TNF antagonists inrheumatoid arthritis: three centers experience. Joint Bone Spine 2013Jul;80(4):438–40.

[37] Lal P, et al. Inflammation and autoantibody markers identify rheumatoid arthritispatients with enhanced clinical benefit following rituximab treatment. ArthritisRheum 2011 Dec;63(12):3681–91.

[38] Cuchacovich M, et al. Basal anti-cyclic citrullinated peptide (anti-CCP) antibodylevels and a decrease in anti-CCP titersare associated with clinical response to

adalimumab in rheumatoid arthritis. Clin Exp Rheumatol 2008 Nov-Dec;26(6):1067–73.

[39] Narvaez J, et al. Predictors of response to rituximab in patients with activerheumatoid arthritis and inadequate response to anti-TNF agents or traditionalDMARDs. Clin Exp Rheumatol 2011 Nov-Dec;29(6):991–7. Epub 2011 Dec 22.

[40] Sokolove J, et al. Impact of baseline anti-cyclic citrullinated peptide-2 antibodyconcentration on efficacy outcomes following treatment with subcutaneous aba-tacept or adalimumab: 2-year results from the AMPLE trial. Ann Rheum Dis2016;75(4):709–14.

[41] Pruijn GJ. Citrullination and carbamylation in the pathophysiology of rheumatoidarthritis. Front Immunol 2015 Apr 27;6:192.

[42] Verheul MK, van Veelen PA, van Delft MAM, de Ru A, Janssen GMC, Rispens T,et al. Pitfalls in the detection of citrullination and carbamylation. Autoimmun Rev2018 Feb;17(2):136–41.

[43] Li L, Deng C, Chen S, Zhang S, Wu Z, Hu C, et al. Meta-Analysis: DiagnosticAccuracy of Anti-Carbamylated Protein Antibody for Rheumatoid Arthritis. PLoSOne 2016 Jul 20;11(7):e0159000.

[44] Shi J, Knevel R, Suwannalai P, van der Linden MP, Janssen GM, van Veelen PA,et al. Autoantibodies recognizing carbamylated proteins are present in sera ofpatients with rheumatoid arthritis and predict joint damage. Proc Natl Acad Sci US A 2011 Oct 18;108(42):17372–7.

[45] Ajeganova S, van Steenbergen HW, Verheul MK, Forslind K, Hafström I, Toes RE,et al. The association between anti-carbamylated protein (anti-CarP) antibodiesand radiographic progression in early rheumatoid arthritis: a study exploring re-plication and the added value to ACPA and rheumatoid factor. Ann Rheum Dis2017 Jan;76(1):112–8.

[46] Brink M, Verheul MK, Rönnelid J, Berglin E, Holmdahl R, Toes RE, et al. Anti-carbamylated protein antibodies in the pre-symptomatic phase of rheumatoid ar-thritis, their relationship with multiple anti-citrulline peptide antibodies and as-sociation with radiological damage. Arthritis Res Ther 2015 Feb 7;17:25.

[47] Spinelli FR, Pecani A, Ciciarello F, Colasanti T, Di Franco M, Miranda F, et al.Association between antibodies to carbamylated proteins and subclinical athero-sclerosis in rheumatoid arthritis patients. BMC Musculoskelet Disord 2017 May25;18(1):214.

[48] Vidal-Bralo L, Perez-Pampin E, Regueiro C, Montes A, Varela R, Boveda MD.Gomez-Reino JJ Gonzalez A. Anti-carbamylated protein autoantibodies associatedwith mortality in Spanish rheumatoid arthritis patients. PLoS One 2017 Jul3;12(7):e0180144.

[49] Peabody JW, Strand V, Shimkhada R, Lee R, Chernoff D. Impact of rheumatoidarthritis disease activity test on clinical practice. PLoS One 2013 May7;8(5):e63215.

[50] Fleischmann R, Connolly SE, Maldonado MA, Schiff M. Brief Report: EstimatingDisease Activity Using Multi-Biomarker Disease Activity Scores in RheumatoidArthritis Patients Treated With Abatacept or Adalimumab. Arthritis Rheum 2016Sep;68(9):2083–9.

[51] Bakker MF, Cavet G, Jacobs JW, Bijlsma JW, Haney DJ, Shen Y, et al. Performanceof a multi-biomarker score measuring rheumatoid arthritis disease activity in theCAMERA tight control study. Ann Rheum Dis 2012 Oct;71(10):1692–7.

[52] Bouman CAM, van der Maas A, van Herwaarden N, Sasso EH, van den HoogenFHJ, den Broeder AA. A multi-biomarker score measuring disease activity inrheumatoid arthritis patients tapering adalimumab or etanercept: predictive valuefor clinical and radiographic outcomes. Rheumatology (Oxford) 2017 Jun1;56(6):973–80.

[53] Hambardzumyan K, Bolce R, Saevarsdottir S, Cruickshank SE, Sasso EH, ChernoffD, et al. Pretreatment multi-biomarker disease activity score and radiographicprogression in early RA: results from the SWEFOT trial. Ann Rheum Dis 2015Jun;74(6):1102–9.

[54] Krabbe S, Bolce R, Brahe CH, Døhn UM, Ejbjerg BJ, Hetland ML, et al.Investigation of a multi-biomarker disease activity score in rheumatoid arthritis bycomparison with magnetic resonance imaging, computed tomography, ultra-sonography, and radiography parameters of inflammation and damage. Scand JRheumatol 2017 Sep;46(5):353–8.

[55] Hambardzumyan K, Saevarsdottir S, Forslind K, Petersson IF, Wallman JK,Ernestam S, et al. A multi-biomarker disease activity score and the choice ofsecond-line therapy in early rheumatoid arthritis after methotrexate failure.Arthritis Rheum 2017 May;69(5):953–63.

[56] Rech J, Hueber AJ, Finzel S, Englbrecht M, Haschka J, Manger B, et al. Predictionof disease relapses by multibiomarker disease activity and autoantibody status inpatients with rheumatoid arthritis on tapering DMARD treatment. Ann Rheum Dis2016 Sep;75(9):1637–44.

[57] Sieper J, Poddubnyy D. Axial spondyloarthritis. Lancet 2017;390(10089):73–84.[58] Chimenti MS, Ballanti E, Perricone C, Cipriani P, Giacomelli R, Perricone R.

Immunomodulation in Psoriatic arthritis: Focus on cellular and molecular path-ways. Autoimmun Rev 2013;12(5):599–606.

[59] Scarpa R, Caso F, Costa L, Peluso R, Del Puente A, Olivieri I. Psoriatic Disease 10Years Later. J Rheumatol 2017 Sep;44(9):1298–301.

[60] Salvarani C, Cantini F, Olivieri I, Macchioni P, Niccoli L, Padula A, et al. Isolatedperipheral enthesitis and/or dactylitis: a subset of psoriatic arthritis. J Rheumatol1997 Jun;24(6):1106–10.

[61] Caso F, Costa L, Atteno M, Del Puente A, Cantarini L, Lubrano E, et al. Simpleclinical indicators for early psoriatic arthritis detection. Springerplus 2014;3:759.

[62] D'Angelo S, Tramontano G, Gilio M, Leccese P, Olivieri I. Review of the treatmentof psoriatic arthritis with biological agents: choice of drug for initial therapy andswitch therapy for non-responders. Open Access Rheumatol 2017 Mar 2;9:21–8.

[63] Carvalho PD, Duarte C, Vieira-Sousa E, Cunha-Miranda L, Avila-Ribeiro P, SantosH, et al. Predictors of response to TNF blockers in patients with polyarticular


��

ARTHRITIS & RHEUMATOLOGY

Vol. 69, No. 5, May 2017, pp 953–963

DOI 10.1002/art.40019VC 2016, The Authors. Arthritis & Rheumatology published by Wiley Periodicals, Inc.on behalf of American College of Rheumatology. This is an open access article underthe terms of the Creative Commons Attribution-NonCommercial License, whichpermits use, distribution and reproduction in any medium, provided the original workis properly cited and is not used for commercial purposes.

A Multi-Biomarker Disease Activity Score and the Choice ofSecond-Line Therapy in Early Rheumatoid Arthritis After

Methotrexate Failure

Karen Hambardzumyan,1 Saedis Saevarsdottir,1 Kristina Forslind,2 Ingemar F. Petersson,3

Johan K. Wallman,3 Sofia Ernestam,4 Rebecca J. Bolce,5 and Ronald F. van Vollenhoven1

Objective. To investigate whether the Multi-Biomarker Disease Activity (MBDA) score predicts opti-mal add-on treatment in patients with early rheumatoidarthritis (RA) who were inadequate responders to MTX(MTX-IRs).

Methods. We analyzed data from 157 MTX-IRs(with a Disease Activity Score using the erythrocyte sedi-mentation rate [DAS28-ESR] >3.2) from the SwedishPharmacotherapy (SWEFOT) trial who were randomizedto receive triple therapy (MTX plus sulfasalazine plushydroxychloroquine) versus MTX plus infliximab. TheMBDA score as a predictor of the subsequent DAS28-based response to each second-line treatment was analyzedat randomization with the Breslow-Day test for 2 3 2groups, using both validated categories (low [<30], moder-ate [30–44], and high [>44]) and dichotomized categories(lower [£38] versus higher [>38]).

Results. Among the 157 patients, 12% had a lowMBDA score, 32% moderate, and 56% high. Of those with a

low MBDA score, 88% responded to subsequent triple ther-apy, and 18% responded to MTX plus infliximab (P 50.006); for those with a high MBDA score, the responserates were 35% and 58%, respectively (P 5 0.040). Whenusing 38 as a cutoff for the MBDA score (29% patients withlower scores versus 71% with higher scores), the differentialassociations with response to triple therapy versus MTXplus infliximab were 79% versus 44% and 36% versus58%, respectively (P 5 0.001). Clinical and inflammatorymarkers had poorer predictive capacity for response to tri-ple therapy or MTX plus infliximab.

Conclusion. In patients with RA who had an inade-quate response to MTX, the MBDA score categories weredifferentially associated with response to subsequent thera-pies. Thus, patients with post-MTX biochemical improve-ments (lower MBDA scores) were more likely to respond totriple therapy than to MTX plus infliximab. If confirmed,these results may help to improve treatment in RA.

In the standard care of patients with early rheumatoidarthritis (RA) (1,2), inadequate response to methotrexate(MTX) monotherapy is followed by a further intensification

ClinicalTrials.gov identifier: NCT00764725. World HealthOrganization database at Karolinska Institute identifier: CT20080004.

Crescendo Bioscience, Inc., a wholly owned subsidiary of MyriadGenetics, Inc., performed the analyses of serum for the Multi-BiomarkerDisease Activity scores at no cost to the investigators. The Swedish Phar-macotherapy (SWEFOT) trial (2003–2010) was supported in part by agrant from the Swedish Rheumatism Association, clinical research fundsfrom the Stockholm County Council (ALF Project funds), and an unre-stricted grant from Schering-Plough Sweden.

1Karen Hambardzumyan, MSc, Saedis Saevarsdottir, MD,PhD, Ronald F. van Vollenhoven, MD, PhD: Karolinska Institutet,Karolinska University Hospital, Stockholm, Sweden; 2Kristina Forslind,MD, PhD: Lund University and Helsingborg’s Lasarett, Helsingborg,Sweden; 3Ingemar F. Petersson, MD, PhD, Johan K. Wallman, MD,PhD: Lund University, Lund, Sweden; 4Sofia Ernestam, MD, PhD:Institution LIME Medical Management Centre, Karolinska Institutet,Stockholm, Sweden; 5Rebecca J. Bolce, MSN: Crescendo Bioscience,Inc., South San Francisco, California.

Dr. Petersson has received honoraria from AbbVie, UCB,and Pfizer (less than $10,000 each) and research support from thosecompanies. Dr. Wallman has received honoraria from Novartis,Celgene, and UCB (less than $10,000 each). Ms Bolce owns stock orstock options in Myriad Genetics, Inc. Dr. van Vollenhoven hasreceived consulting fees from AbbVie, Biotest, Bristol-Myers Squibb,Crescendo Bioscience, GlaxoSmithKline, Janssen, Lilly, Merck, Pfizer,Roche, UCB, and Vertex (less than $10,000 each) and research sup-port from AbbVie, Bristol-Myers Squibb, GlaxoSmithKline, Pfizer,Roche, and UCB.

Address correspondence to Karen Hambardzumyan, MSc,ClinTRID, Karolinska University Hospital, SE-17176 Stockholm,Sweden. E-mail: [email protected].

Submitted for publication February 22, 2016; accepted inrevised form December 6, 2016.

953

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1Mahmood S, et al. RMD Open 2017;3:e000411. doi:10.1136/rmdopen-2016-000411

INTRODUCTIONAs rheumatoid arthritis (RA) is a potentially disabling disease, affecting up to 1% of the population, structural monitoring of stan-dardised outcomes to identify best healthcare practices is vital to quality improvement.1 2 Seven sets of RA standardised outcomes or ‘quality indicators’ have been described in the literature.3 However, only one group involved patients.4

This lack of patient representation in the current indicator sets might be due to the common methodology of indicator selection: indicators are determined through system-atic searches of evidence-based literature and consultation of experts, usually defined as clinicians or researchers, rather than patients.

Studies have shown that patients and healthcare providers have different perspec-tives regarding quality of care.5 6 As the patient is the customer in the business called ‘health care’, the quality of the product should meet the costumers’ needs. There-fore, we have studied the patient’s perspective on quality of care in order to incorporate this together with the clinician’s perspective into quality indicators.

METHODSPatients were consulted using focus group methodology in combination with an online survey. The focus group method is a well-es-tablished research technique, gathering rich, descriptive data from participants in a small and homogeneous group, who focus on a specific topic, while guided by a neutral moderator.7

Study sample and procedurePhase I: focus group discussionNine patients of the established patient partner network of the Dutch Arthritis

Foundation were invited to the focus group discussion (FGD).

Participants received an invitation and written information on the topic of the study by email. Prior to the meeting all patients gave oral consent to record the meeting and to use the results of this meeting for research purposes. Transcripts of the recording were analysed by one researcher (SM).

The moderator (MvO) explained the purpose of the discussion, created a ‘safe envi-ronment’ and ensured that participants did not deviate too much from the topic. Partic-ipants had the opportunity to give extensive answers to questions.

In the first part of the FGD, patients were asked for their positive and negative experi-ences with rheumatology care and were asked to prioritise three elements that were consid-ered most important for their rheumatology care. The top three answers of each of the participants were then discussed and clus-tered in similar groups, if possible, resulting in domains. Finally patients were asked to vote for the domains that were most important to them.

In the second part of the FGD, a set of nine domains, defined by Dutch rheuma-tologists in a separate, parallel process, was introduced (figure 1). These domains were discussed, compared with the domains chosen by the participants and missing domains were added.

Phase II: surveyAll unique domains were presented to a panel of 1132 Dutch patients with RA. This estab-lished panel can be consulted by the Dutch Arthritis Foundation in case of healthcare-re-lated questions or for research purposes. Patients are invited to participate for each study separately. Also, patients are free to leave the panel without explanation regarding their decision. Due to the voluntary and

SHORT REPORT

Evaluating quality of care in rheumatoid arthritis: the patient perspective

Sehrash Mahmood,1 Marianne van Oosterhout,2 Sija de Jong,2 Robert Landewé,1 Piet van Riel,3 Lilian H D van Tuyl1

To cite: Mahmood S, van Oosterhout M, de Jong S, et al. Evaluating quality of care in rheumatoid arthritis: the patient perspective. RMD Open 2017;3:e000411. doi:10.1136/rmdopen-2016-000411

Received 21 November 2016Revised 29 March 2017Accepted 6 April 2017

1Amsterdam Rheumatology and Immunology Center, Amsterdam, The Netherlands2Dutch Arthritis Foundation, Amsterdam, The Netherlands3Department of Rheumatology, Radboud University Medical Center, Nijmegen, The Netherlands

Correspondence toDr Sehrash Mahmood; sehrash_ 01@ hotmail. com

Rheumatoid arthritis

Clinicalcasestudy

•  Realpatientcases•  Discusssigns,symptoms,diagnosisandtreatment

•  Contributetotheexistingknowledge•  Notsuitableforearlycareerresearchers

CONCISE REPORT

Erosion healing in rheumatoid arthritis after anakinratreatmentR Rau, O Sander, S Wassenberg. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Ann Rheum Dis 2003;62:671–673

Disruption of the cortical plate and erosive destruction ofthe subchondral bone are characteristic features ofactive rheumatoid arthritis (RA), potentially leading to

progressive damage. Until recently, damage progression asdocumented on radiographs has been regarded as an irrevers-ible process. However, several case reports now indicate thatthis process may be stopped or even reversed, leading to heal-ing or repair of bone lesions. Under physiological conditionsthere is a balance between bone resorption by osteoclasts andbone formation by osteoblasts. In a state of active inflamma-tion, bone resorption usually exceeds new bone formation,resulting in bone destruction. However, as soon as the inflam-matory process has been stopped in an individual joint, osteo-blastic activity may exceed bone resorption, leading to newbone formation and repair. This process is regulated byosteoprotegerin.1 2 Because bone formation takes time, repara-tive changes can be expected to be clearly visible onradiographs only 6–12 months after distinct clinical improve-ment occurred. These may present as reappearance of the cor-tical plate or filling in of erosions. As clinical remission rarelyoccurs within the timeframe of clinical trials, and as patientsexperiencing remission outside clinical trials often do not visittheir rheumatologist, x ray pictures showing healing phenom-ena have only occasionally been reported.3–11 Recent clinicaltrials with tumour necrosis factor α inhibitors12–15 indicate thatclinical improvement and halting of radiographic progressionoccur earlier than with conventional disease modifyingantirheumatic drugs (DMARDs). They have also shown areduction in the radiographic scores in a considerable numberof patients, probably indicating repair if measurement errorcan be excluded. As interleukin 1 (IL1) plays an importantpart in bone destruction, its inhibition might also result in apreponderance of repair over further destruction in erodedjoints.

We wish to demonstrate here an example of healing duringtreatment with the IL1 receptor antagonist (IL1Ra) anakinrain a patient with active RA who did not respond sufficiently toconventional DMARD treatment.

CASE REPORTIn 1991, the patient, who was then 55 years old, firstexperienced pain and some swelling in several joints (feet,wrists, elbows, shoulders, knee joints, etc). She also had earlymorning stiffness lasting 2–3 hours. At her first presentation inNovember 1991, there was tenderness of the metacarpo-phalangeal joints, and some swelling of the metatarsophalan-geal (MTP) joints and the left ankle joint. The erythrocyte sedi-mentation rate (ESR) was 41/77 mm/1st h, rheumatoid factorwas positive (latex test 149 U/ml, Rose-Waaler test 1/160).

Radiographically, there was soft tissue swelling of the MTPjoints I–V on both feet, and erosions at the left first MTP jointand the interphalangeal (IP) joint of the left great toe. Therewere no changes indicative of RA in the hands or wrists.

Non-steroidal anti-inflammatory drugs and parenteral goldtreatment were started. Gold had to be stopped three monthslater because of an exanthema. DMARD treatment was

continued with 10 mg methotrexate intramuscularly a week.This dose was increased to 15 mg intramuscularly a weekowing to increasing disease activity, with an ESR of 58/96mm/1st h. Methotrexate had to be withdrawn in June 1993because the patient reported retrosternal pain after eachapplication. In January 1994 treatment with sulfasalazine (3g/day) was started. One year later, in April 1995, the diseasewas still active with a C reactive protein (CRP) of 43 mg/l, anESR of 29 mm/1st h, although rheumatoid factor had becomenegative. Most importantly, an x ray examination demon-strated severe radiographic progression in the forefeet. For thisreason, the patient was included in a randomised, doubleblind, placebo controlled trial with IL1Ra (anakinra) over sixmonths,12 where she was treated with subcutaneous injectionsof 75 mg anakinra a day. Clinical improvement was seenwithin four weeks. The patient also participated in a six monthcontinuation study. After one year, her RA was almost inremission (ESR 10 mm/1st h, CRP <5 mg/l).

When the study ended the patient continued to be treatedwith the same dose of anakinra until January 2001.

Radiographs of the forefeetThe following radiographs of the forefeet were obtained:

1991: Small erosions were seen at the IP I joint and the MTP Ijoint of the left great toe and a small erosion at the right MTPIV.

1992: New erosions had developed at the IP joint of the leftgreat toe, the MTP III and IV joints of the left foot, and at theright MTP II joint.

1995: Severe destruction of the IP joint of the left great toe.Erosions of the left MTP I and II joints had increased. At theright foot, erosions at the IP joint of the right great toe, theMTP III and IV joints (here with luxation) were visible.

1996: All erosions appeared to be stabilised/inactivated.

The radiographs from 1997 to 1999 showed no progression,which indicates that the process continued to be inactive.

Radiographs of the hands and wristsThe following results were shown in the radiographs of thehands and wrist:

1991 and 1992: No inflammatory changes.

1993: Several erosions at the right wrist and the metacarpalbasis had developed.

1995: Severe erosive damage of the right wrist could be seen.

1997 and in the following years: Signs of inactivation andrepair. No changes in the left hand and wrist were seen at anytime.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Abbreviations: CRP, C reactive protein; DMARDs, disease modifyingantirheumatic drugs; ESR, erythrocyte sedimentation rate; IL1Ra,interleukin 1 receptor antagonist; IP, interphalangeal; MTP,metatarsophalangeal; RA, rheumatoid arthritis

671

www.annrheumdis.com

Clinicaltrial

•  Methodology,implementation,resultsofcontrolledstudieswithlargepatientgroups

•  Highstandardsofethicsorreliability

Original article

Comparing biosimilar SB2 with reference infliximabafter 54 weeks of a double-blind trial: clinical,structural and safety results

Josef S. Smolen1, Jung-Yoon Choe2, Nenad Prodanovic3,Jaroslaw Niebrzydowski4, Ivan Staykov5, Eva Dokoupilova6,Asta Baranauskaite7, Roman Yatsyshyn8, Mevludin Mekic9,Wieskawa Porawska10, Hana Ciferska11, Krystyna Jedrychowicz-Rosiak12,Agnieszka Zielinska13, Jasmine Choi14 and Young Hee Rho14

Abstract

Objectives. SB2 is a biosimilar to the reference infliximab (INF). Similar efficacy, safety and immunogen-icity between SB2 and INF up to 30 weeks were previously reported. This report investigates such clinicalsimilarity up to 54 weeks, including structural joint damage.

Methods. In this phase III, double-blind, parallel-group, multicentre study, patients with moderate tosevere RA despite MTX were randomized (1:1) to receive 3 mg/kg of either SB2 or INF at 0, 2, 6 andevery 8 weeks thereafter. Dose escalation by 1.5 mg/kg up to a maximum dose of 7.5 mg/kg wasallowed after week 30. Efficacy, safety and immunogenicity were measured at each visit up to week54. Radiographic damage evaluated by modified total Sharp score was measured at baseline andweek 54.

Results. A total of 584 patients were randomized to receive SB2 (n = 291) or INF (n = 293). The rate ofradiographic progression was comparable between SB2 and INF (mean modified total Sharp score dif-ference: SB2, 0.38; INF, 0.37) at 1 year. ACR responses, 28-joint DAS, Clinical Disease Activity Index andSimplified Disease Activity Index were comparable between SB2 and INF up to week 54. The incidence oftreatment-emergent adverse events and anti-drug antibodies were comparable between treatment groups.Such comparable trends of efficacy, safety and immunogenicity were consistent from baseline up to54 weeks. The pattern of dose increment was also comparable between SB2 and INF.

Conclusion. SB2 maintained similar efficacy, safety and immunogenicity with INF up to 54 weeks inpatients with moderate to severe RA. Radiographic progression was comparable at 1 year.

Trial registration: ClinicalTrials.gov (http://clinicaltrials.gov; NCT01936181) and EudraCT (https://www.clinicaltrialsregister.eu; 2012-005733-37)

Key words: biosimilar, infliximab, Flixabi, Renflexis, Remicade, rheumatoid arthritis, tumour necrosis factorblocker, radiographic progression, Sharp score, monoclonal antibody

1Division of Rheumatology, Department of Medicine, MedicalUniversity of Vienna, Vienna, Austria, 2Division of Rheumatology,Daegu Catholic University Medical Center, Daegu, South Korea,3Department of Rheumatology and Clinical Immunology, ClinicalCenter Banja Luka, Banja Luka, Bosnia and Herzegovina, 4Divison ofRheumatology, Medica Pro Familia, Gdynia, Poland, 5Divison ofRheumatology, MHAT ‘‘Dr. Ivan Seliminski’’, Sliven, AD, Bulgaria,6Divison of Rheumatology, MEDICAL PLUS s.r.o, Uherske Hradiste,Czech Republic, 7Division of Rheumatology, Lithuanian University ofHealth Sciences, Kaunas, Lithuania, 8Division of Rheumatology, SHEIIvano-Frankivsk NMU, Ivano-Frankivsk, Ukraine, 9Department ofHealth, Diseases and Rheumatism, University Clinic Centre Sarajevo,

Sarajevo, Bosnia and Herzegovina, 10Division of Rheumatology,Poznanski Osrodek Medyczny NOVAMED, Poznan, Poland, 11Divisionof Rheumatology, Revmatologicky ustav, Praha, Czech Republic,12Divison of Rheumatology, MCBK S.C., Grodzisk Mazowiecki,13Divison of Rheumatology, Medica Pro Familia, Warszawa, Polandand 14Samsung Bioepis, Incheon, South Korea

Correspondence to: Josef S. Smolen, Division of Rheumatology,Department of Medicine 3, Medical University of Vienna, WaehringerGuertel 18-20, A-1090 Vienna, Austria.E-mail: [email protected]

Submitted 13 December 2016; revised version accepted 2 June 2017

! The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use,

distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact [email protected]

RHEUMATOLOGYRheumatology 2017;56:1771!1779

doi:10.1093/rheumatology/kex254

Advance Access publication 25 July 2017

CL

INIC

AL

SC

IEN

CE

•  Perspective–  Essayspresentingapersonalpointofview– Around2000words–  Critiquingwidespreadnotionsinthefield

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–  Saywhyitisinterestingforreaders

Letter to the EditorComment on (Long-Term Dietary Changes after Diagnosis ofRheumatoid Arthritis in Swedish Women: Data from aPopulation-Based Cohort)

Velammal Petchiappan ,1 Preethi Priyadarshini,1 and V. N. Nagaprabu2

1Department of Medicine, PSG Institute of Medical Sciences and Research, Coimbatore, India2Sakthi Rheumatology Centre, Coimbatore, India

Correspondence should be addressed to Velammal Petchiappan; [email protected]

Academic Editor: Bruce M. Rothschild

Copyright © 2019 Velammal Petchiappan et al.This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

We read with great interest the article published in Inter-national Journal of Rheumatology, “Long-Term DietaryChanges after Diagnosis of Rheumatoid Arthritis in SwedishWomen: Data from a Population-Based Cohort” by CeciliaLourdudoss et al. [1].The role of diet in rheumatoid arthritis(RA) remains an ever-burning question for both the patientand the treating physician and, while it is quite acceptablefor the lay person to think that the occurrence of thearthritis is influenced by the diet, unfortunately the scientificcommunity is yet to produce a definite answer.

In a systematic review of dietary intervention studiesin RA, it was concluded that the effect of various dietarymanipulations on the disease is uncertain [2]. The potentialrisks associated with such intervention were also highlightedin that review. The present study is among the importantobservations in this field and the authors give specific dietaryrecommendations for patients with RA in the future. Theauthors noted that there was no change in dietary pattern inRA patients, whereas those without RAmade certain changesto their dietary pattern during the study period.Thismight bebecause of the relatively small RApopulationwhen comparedto the controls in this cohort.The duration of the disease, thedisease activity, and the occurrence of comorbid illness alsowere not taken into consideration.

We did a study that assessed the role of diet in RA patientsand its impact on arthritis-related symptoms as perceived by

the patients themselves, using a simple questionnaire in theirown language [3]. We categorized them as diet restrictorsand nonrestrictors based on whether they are following anychange in dietary pattern depending upon the aggravation ofjoint symptoms following a specific food intake.We also con-sidered associated comorbidities and alternative medicineintake, which can influence the dietary pattern. Out of a totalof 101 patients with an average disease duration of 50.2 ±65.4months, 44 (43.6%) followed dietary restriction while 57(56.4%) did not observe any restriction. 20 of the 44 patientswho restricted their diet (45.5%) felt a difference in jointsymptoms on exposure to particular diet; 52 out of 57 (91.2%)nonrestrictors did not experience any influence of diet ontheir symptoms. Patients who observed changes in their jointsymptoms on exposure to a particular diet adopted dietaryrestriction and we observe this association as statisticallysignificant in our study (p <0.0001). 20 out of the 44 and 52out of 57 patients in either group appeared to be correctlyjudging whether or not to restrict their diets.

We concluded that the decision of modifying diet shouldbe individual case-based rather than a generalized dietaryrestriction, which lacks a solid scientific proof as of now andmight deprive the individual of the benefits of a nutritiousdiet. The voluntary addition or deletion of part of the dietmight well have an influence on the overall dietary habitsof the entire family, as most often RA affects women who

Hindawi

International Journal of Rheumatology

Volume 2019, Article ID 1939686, 2 pages

https://doi.org/10.1155/2019/1939686

Methodologies/Methods

•  Experimentalmethod,test,procedure•  Neworbetterversionofexisting

K/BxN Serum Transfer Arthritis as a Model of Inflammatory Joint Pain

Christina A. Christianson1, Maripat Corr2, Tony L. Yaksh1, and Camilla I. Svensson3

1University of California, San Diego, Dept. of Anesthesiology, La Jolla, CA2University of California, San Diego, Dept. of Medicine, La Jolla, CA3Karolinska Institute, Dept. of Physiology and Pharmacology, Stockholm, Sweden

AbstractIn this chapter, we describe the usage of this rheumatoid arthritis model to investigate pain-like behavior in mice, including the assessment of clinical changes and the time-dependent changes in nociceptive behavior during disease progresses.

KeywordsRheumatoid arthritis; Persistent pain; Mice; Allodynia

1. IntroductionChronic pain is a major health problem affecting approximately 20% of the population, resulting in markedly reduced quality of life for the individual as well as extensive costs for society. Approximately 1% of the population is diagnosed with rheumatoid arthritis (RA), a systemic autoimmune-mediated disease comprising synovial inflammation and matrix destruction. Swelling is particularly prominent in the small joints of the hands and feet. Pain is frequently the most egregious symptom reported and can persist after resolution of joint swelling with anti-inflammatory treatment. The inflammatory processes that result in rheumatoid arthritis are complex, with interactions among the cytokine network, autoantibodies, and the complement cascade. While the peripheral inflammation is an important component in generating pain in RA, the peripheral pathology cannot fully explain the amount of pain the arthritis patient experiences and facilitation of pain processing at the level of the spinal cord has been implicated (1). Despite the efficacy of new therapeutics (e.g., TNF and interleukin blockers) and treatment strategies (e.g., combination therapies), pain is still a significant problem. In a recent survey, more than 85% of RA patients described their RA as somewhat completely controlled, yet greater than 75% of them reported moderate to severe pain within the previous 2 months (2). Drug development in the area of chronic inflammatory pain has hitherto been insufficient. Thus, it is critical to increase our understanding for how chronic pain emerges during and subsequent to joint

Corresponding author: Christina A. Christianson, PhD, [email protected]. Factors contributing to variability in arthritis severity and potentially also hypersensitivity:

HHS Public AccessAuthor manuscriptMethods Mol Biol. Author manuscript; available in PMC 2017 May 11.

Published in final edited form as:Methods Mol Biol. 2012 ; 851: 249–260. doi:10.1007/978-1-61779-561-9_19.

Author Manuscript

Author Manuscript

Author Manuscript

Author Manuscript

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•  Physiologicalreviews– https://www.physiology.org/journal/physrev

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K/BxN Serum Transfer Arthritis as a Model of Inflammatory Joint Pain

Christina A. Christianson1, Maripat Corr2, Tony L. Yaksh1, and Camilla I. Svensson3

1University of California, San Diego, Dept. of Anesthesiology, La Jolla, CA2University of California, San Diego, Dept. of Medicine, La Jolla, CA3Karolinska Institute, Dept. of Physiology and Pharmacology, Stockholm, Sweden

AbstractIn this chapter, we describe the usage of this rheumatoid arthritis model to investigate pain-like behavior in mice, including the assessment of clinical changes and the time-dependent changes in nociceptive behavior during disease progresses.

KeywordsRheumatoid arthritis; Persistent pain; Mice; Allodynia

1. IntroductionChronic pain is a major health problem affecting approximately 20% of the population, resulting in markedly reduced quality of life for the individual as well as extensive costs for society. Approximately 1% of the population is diagnosed with rheumatoid arthritis (RA), a systemic autoimmune-mediated disease comprising synovial inflammation and matrix destruction. Swelling is particularly prominent in the small joints of the hands and feet. Pain is frequently the most egregious symptom reported and can persist after resolution of joint swelling with anti-inflammatory treatment. The inflammatory processes that result in rheumatoid arthritis are complex, with interactions among the cytokine network, autoantibodies, and the complement cascade. While the peripheral inflammation is an important component in generating pain in RA, the peripheral pathology cannot fully explain the amount of pain the arthritis patient experiences and facilitation of pain processing at the level of the spinal cord has been implicated (1). Despite the efficacy of new therapeutics (e.g., TNF and interleukin blockers) and treatment strategies (e.g., combination therapies), pain is still a significant problem. In a recent survey, more than 85% of RA patients described their RA as somewhat completely controlled, yet greater than 75% of them reported moderate to severe pain within the previous 2 months (2). Drug development in the area of chronic inflammatory pain has hitherto been insufficient. Thus, it is critical to increase our understanding for how chronic pain emerges during and subsequent to joint

Corresponding author: Christina A. Christianson, PhD, [email protected]. Factors contributing to variability in arthritis severity and potentially also hypersensitivity:

HHS Public AccessAuthor manuscriptMethods Mol Biol. Author manuscript; available in PMC 2017 May 11.

Published in final edited form as:Methods Mol Biol. 2012 ; 851: 249–260. doi:10.1007/978-1-61779-561-9_19.

Author Manuscript

Author Manuscript

Author Manuscript

Author Manuscript

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•  Elsevier•  Springer•  etc

Retraction

1Scientific RepoRts | 6:2 0 6 | DOI: 10.1038/srep2 0 6

www.nature.com/scientificreports

Retraction: Novel piperazine core compound induces death in human liver cancer cells: possible pharmacological propertiesNima Samie, Sekaran Muniandy, M. S. Kanthimathi, Batoul Sadat Haerian & Raja Elina Raja Azudin

Scientific Reports 6:24172; doi: 10.1038/srep24172; published online 13 April 2016; updated 22 June 2016

This Article has been retracted by the Editors and Publishers of Scientific Reports. Following online criticisms of the published paper, an investigation at the journal has confirmed the manipulation and duplication of data and a level of image processing that is not compliant with the journal’s policies on image data integrity in figures 1–3, 6, 7, 10 and 12. Versions of figures 1–11 and large sections of the text had also previously been published1,2.

All authors acknowledge these issues and agree to the retraction of the Article.

References1. Samie, N. et al. Mechanism of Action of the Novel Nickel(II) Complex in Simultaneous Reactivation of the

Apoptotic Signaling Networks Against Human Colon Cancer Cells. Front. Pharmacol. 6, 313 (2016). doi: 10.3389/fphar.2015.00313

2. Samie, N., Muniandy, S., Kanthimathi, M. S. & Haerian, B. S. Mechanism of action of novel piperazine containing a toxicant against human liver cancer cells. PeerJ 4, e1588 (2016). doi: 10.7717/peerj.1588

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license,

unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

OPEN

1Scientific RepoRts | 6:2 0 6 | DOI: 10.1038/srep2 0 6

www.nature.com/scientificreports

Retraction: Novel piperazine core compound induces death in human liver cancer cells: possible pharmacological propertiesNima Samie, Sekaran Muniandy, M. S. Kanthimathi, Batoul Sadat Haerian & Raja Elina Raja Azudin

Scientific Reports 6:24172; doi: 10.1038/srep24172; published online 13 April 2016; updated 22 June 2016

This Article has been retracted by the Editors and Publishers of Scientific Reports. Following online criticisms of the published paper, an investigation at the journal has confirmed the manipulation and duplication of data and a level of image processing that is not compliant with the journal’s policies on image data integrity in figures 1–3, 6, 7, 10 and 12. Versions of figures 1–11 and large sections of the text had also previously been published1,2.

All authors acknowledge these issues and agree to the retraction of the Article.

References1. Samie, N. et al. Mechanism of Action of the Novel Nickel(II) Complex in Simultaneous Reactivation of the

Apoptotic Signaling Networks Against Human Colon Cancer Cells. Front. Pharmacol. 6, 313 (2016). doi: 10.3389/fphar.2015.00313

2. Samie, N., Muniandy, S., Kanthimathi, M. S. & Haerian, B. S. Mechanism of action of novel piperazine containing a toxicant against human liver cancer cells. PeerJ 4, e1588 (2016). doi: 10.7717/peerj.1588

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license,

unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

OPEN

www.nature.com/scientificreports/

3Scientific RepoRts | 6:24172 | DOI: 10.1038/srep24172

PCC induced membrane blebbing and nuclear condensation. After 24 h treatment of SNU-475, and SNU-423 cells with 6.25 μg/ml of PCC, the apoptotic features were analyzed by fluorescence microscopy. Normal nuclear structure in control cells was displayed as green fluorescence, where as bright green fluorescence was shown in early apoptotic cells, caused by interposition of acridine orange with the fragmented DNA. Nuclear chromatin pucker and membrane zeiosis, as moderate apoptotic features, were detected after 24 and 48 h. Binding

Figure 1. PCC arrests the cell cycle in the S/M phase. Cells were incubated with DMSO (negative control) and PCC (6.25 μg/ml) for 24 h, followed by collection and staining with BrdU and Phopho-Histone H3. Treatment with PCC revealed no significant changes in the BrdU and Phosho-Histone H3 fluorescence intensity which suggests that the cells have not been arrested at S/M phase.

Figure 2. Effect of PCC on development of cell cycle using flow cytometry. Momentous cell cycle arrest was identified at G1 phase after 24 and 48 h incubation of the cells with PCC. All data are expressed as the means ± standard error of triplicate measurements. *P < 0.05 compared with the no-treatment group.

RETRACTED

www.nature.com/scientificreports/

9Scientific RepoRts | 6:24172 | DOI: 10.1038/srep24172

seen as a potential inducer of morphological modifications downstream of apoptotic molecular events in the liver cancer cells associated with its cytotoxic potential.

Piperazines (1, 4-diazacyclohexane) are an extensive group of chemical compounds, containing a core func-tional group with important pharmacological properties. They consist of a six-membered ring containing two nitrogen atoms at opposite positions in the ring. A large number of piperazine compounds have anthelmintic action. They are usually used as anti-helmintic against common roundworms such as ascariasis and pinworms (enterobiasis; oxyuriasis). Their mode of action is generally by paralysing parasites, which allows the host body to easily remove or expel the invading organ26. Based on the literature, unsubstituted piperazine do not show anti-cancer effect however, but when they are incorporated into to another molecule or are used as a derivate, some of them tend to show anti-cancer activity based on the compound’s structure. PCC is a piperazine derivate which has potential cytotoxic effect toward liver cancer cell lines. Nevertheless, there is little data showing that piperazine compounds can induce apoptosis pathways associated with their cytotoxic properties. Recent studies have demonstrated the cytotoxic effect of some piperazine derivatives such as β -elemene piperazine, 1,4-bis- (4-(1H-benzo[d]imidazol-2-yl-phenyl) piperazine and chloroalkyl piperazine and 6-(4-substituted piperazine-1-yl)- 9-(β -D-ribofuranosyl) purine in cancer cells. However, only the extrinsic pathway of apoptosis is activated by these compounds27–31 whereas, PCC simultaneously activates both intrinsic and extrinsic pathways of apoptosis. To further support the role of PCC as a novel piperazine derivative with pro-apoptotic properties, we analyzed the apoptotic pathways in the liver cancer cell lines. Results showed that PCC enhanced the release of mitochon-drial cytochrome c which activated caspase 9 by 4.8–5.0 fold in both liver cancer cells32. Interestingly, activated caspase-8 is also increased by about 5.0 fold in both cancer cell lines, suggesting that PCC-induced apopto-sis is mediated by more than one pathway. Following cell excitation, calcium ions are released from mitochon-dria to regulate several cellular processes such as apoptosis. Therefore, prolonged elevation of cytosolic calcium ions causes cell death33. In addition, mitochondrial calcium ion uptake alters the mitochondrial permeability which switches on the apoptosis event in response to the stress. Increase of calcium ion levels occurs at both the early and late stages of apoptosis. Hence, intracellular calcium ion elevation causes cell death through apop-tosis pathways34–36. On the basis of the absence of cytosolic free calcium evaluated by using a calcium chelator (EGTA/AM) and flow cytometry analysis of Annexin-V in the PCC treated cells, an increase in the number of

Figure 12. Western blot analysis of cancer and normal cell lines. Cells were treated with 3.12 and 6.25 μg/ml of PCC for 24 h. Proteins were transferred to a membrane and followed by probing with antibodies. Normalization of band densities of treated samples were accomplished based on the control. The results represent significant increase in the expression level of caspase 3, 7, 8, 9, p53, Bax and conversion of Bid to its truncated form, where as decrease in Bcl-2 and Bcl-xL levels.

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