Background Increased risk of some comorbidities has been reported in spondyloarthritis (SpA). Recommendations for detection/management of some of these comorbidities have been proposed, and it is known that a gap exists between these and their implementation in practice.
Objective To evaluate (1) the prevalence of comorbidities and risk factors in different countries worldwide, (2) the gap between available recommendations and daily practice for management of these comorbidities and (3) the prevalence of previously unknown risk factors detected as a result of the present initiative.
Methods Cross-sectional international study with 22 participating countries (from four continents), including 3984 patients with SpA according to the rheumatologist.
Statistical analysis The prevalence of comorbidities (cardiovascular, infection, cancer, osteoporosis and gastrointestinal) and risk factors; percentage of patients optimally monitored for comorbidities according to available recommendations and percentage of patients for whom a risk factor was detected due to this study.
Results The most frequent comorbidities were osteoporosis (13%) and gastroduodenal ulcer (11%). The most frequent risk factors were hypertension (34%), smoking (29%) and hypercholesterolaemia (27%). Substantial intercountry variability was observed for screening of comorbidities (eg, for LDL cholesterol measurement: from 8% (Taiwan) to 98% (Germany)). Systematic evaluation (eg, blood pressure (BP), cholesterol) during this study unveiled previously unknown risk factors (eg, elevated BP (14%)), emphasising the suboptimal monitoring of comorbidities.
Conclusions A high prevalence of comorbidities in SpA has been shown. Rigorous application of systematic evaluation of comorbidities may permit earlier detection, which may ultimately result in an improved outcome of patients with SpA.
- Cardiovascular Disease
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Spondyloarthritis (SpA) regroup several disorders such as psoriatic arthritis, arthritis related to inflammatory bowel disease (IBD), reactive arthritis and ankylosing spondylitis.1
Apart from the risk of suffering from musculoskeletal manifestations or non-rheumatological features (eg, psoriasis, IBD) directly related to SpA, patients may also suffer from other diseases (here called comorbidities). The risk seems to be higher in SpA than in the general population, particularly with regard to some specific disorders (eg, cardiovascular (CV) and osteoporosis).2–5 Such an increased risk in comparison with the general population can be explained by the treatment of SpA (eg, Non-steroidal anti-inflammatory drugs (NSAIDs),5 corticosteroids) and also by other factors that can be observed in patients with SpA (eg, metabolic syndrome, systemic inflammation).
An excess mortality has also been demonstrated in patients with ankylosing spondylitis and/or psoriatic arthritis,2–4 which seems to be mainly related not only to an increased risk of CV disease6–8 but also to osteoporosis,9 due to the complications of spinal fractures.10 ,11 Malignancies do not seem to be responsible for an excess mortality in SpA,12 ,13 and no increased risk of infections has ever been demonstrated in SpA, except in patients concomitantly treated with drugs such as corticosteroids and/or Tumor Necrosis Factor inhibitors (TNFi).14 The most frequently reported renal disease associated with SpA is amyloidosis,15 ,16 but, surprisingly, there are virtually no data on the nephrotoxicity of NSAIDs in patients with SpA.
For some of these comorbidities (eg, CV diseases, infections, cancers, osteoporosis), recommendations for their detection/prevention have been proposed in the general population, but also specific recommendations have been specifically proposed for the prevention of CV diseases and infections in patients with inflammatory rheumatic diseases.17 ,18 For rheumatoid arthritis (RA), it has been shown that there is a gap between the ideal situation laid down in recommendations and the reality obtained in daily practice.19–21 However, no data on the adherence to recommendations for comorbidities in SpA have been reported so far.
The international Assessment in SpondyloArthritis International Society (ASAS)-COMOSPA study had three main objectives and because of its goals was set up to be the largest in the field. First, to evaluate the prevalence of comorbidities and their risk factors in patients with SpA; second, to evaluate the gap between the available recommendations and their implementation in daily practice and third, to evaluate the number of patients in whom a risk factor was detected due to the systematic evaluation of risk factors during this initiative.
Observational, cross-sectional, multicentric and international study, with 22 participating countries from four continents (Africa, America, Asia and Europe).
Under the umbrella of ASAS, the scientific committee selected national principal investigators for this study for each participating country among the ASAS members. Several countries per continent were selected in order to ensure representativeness. The national principal investigator's task was to invite rheumatologists in their country to participate in order to ensure national representation and to conduct the study according to good clinical practice at the local level. Consecutive adult patients (eg, at least 18 years old) fulfilling the ASAS criteria (either axial or peripheral)22 and who were able to understand and complete questionnaires were included. The study was conducted according to guidelines for good clinical practice in all countries. Written informed consent was obtained from all subjects before enrolment.
Sample size calculation
The sample size was based on the width of the 95% CI of the proportion of expected events (the prevalence of each comorbidity), assuming that a 3000-patient sample would allow an observed 40% prevalence of a comorbidity to be estimated with a precision of less than 2% (95% CI 38.2% to 41.7%). Investigators in each country were expected to enrol at least 200 patients.
A case report form was used to collect four different chapters of data:
Demographics and disease characteristics: age, gender, body mass index, smoking status (past and current), alcohol (past and current) intake, highest level of education completed and current marital status. History and current disease characteristics such as axial, peripheral articular, enthesitis involvement, dactylitis and non-rheumatological manifestations were collected. Current disease activity was measured by the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI),23 the Ankylosing Spondylitis Disease Activity Score was calculated with the CRP (ASDAS)24 ,25 and the number of swollen joints (44 joint count). Disease severity: a history of SpA-related surgeries, the presence of bamboo spine and the current Bath Ankylosing Spondylitis Functional Index (BASFI).26 Past and current medications (NSAIDs, corticosteroids, conventional and biological disease-modifying antirheumatic drugs (DMARDs)) were also collected.
Comorbidities: CV: a history of ischaemic CV disease (myocardial infarction and stroke); Cancer: a history of colon, skin (ie, melanoma and basocellular carcinoma), breast and cervix for women, prostate for men and lymphoma; Infections: a history of hepatitis B virus (HBV), hepatitis C virus (HCV), HIV, severe infection requiring hospitalisation and a history of active tuberculosis disease; Osteoporosis: a history of osteoporosis, defined as either (a) a T-score <−2.5 SDs at either the total hip or the lumbar spine or the femoral neck or (b) a history of a vertebral or peripheral non-traumatic fracture or (c) a past history or current treatment with a specific antiosteoporotic drug or (d) a history of diagnosis of secondary osteoporosis; Gastrointestinal disease: a history of gastroduodenal ulcer and diverticulitis; Amyloidosis (history); Vasculitis (history).
Risk factors for comorbidities: Risk factors for CV disease: hypertension (defined as a history of hypertension or antihypertensive therapy or blood pressure (BP) >140/90 mm Hg (>130/80 mm Hg in case of history of diabetes or renal insufficiency) at the study visit), hypercholesterolaemia (defined as a history of hypercholesterolaemia or cholesterol-lowering therapy or an Low-density lipoprotein (LDL) cholesterol above target according to the French recommendations27), hyperglycaemia (defined as a history of diabetes or glycaemia >7.0 mmol/L, a family history of sudden death or myocardial infarction in a first-degree relative); Risk factors for cancer: family history of cancer (for breast, prostate and colon), personal history of IBD (for colon) and personal history of >40 naevi (for skin cancer); Risk factors for osteoporosis: family history of hip fracture.
Monitoring of comorbidities and risk factors according to recommendations. The definition of optimal monitoring according to recommendations for each comorbidity is described in detail in the ‘Data analysis’ section of this manuscript.
All information was obtained by a study investigator or research nurse during a face-to-face interview at a study visit, including a review of the medical record, and was entered in a centralised electronic case report form.
First, a descriptive analysis of the enrolled patients by country was performed, including the demographic and disease characteristics, activity and severity. Second, the prevalences (and 95% CIs) of each comorbidity and its risk factors were estimated (Wald method28). Third, in order to evaluate the gap between the available recommendations and their implementation in daily practice, the percentage of optimally monitored patients according to the recommendations was calculated. The ‘optimal’ definition was derived from international recommendations,17 ,18 and/or national healthcare institutions,27 and/or recommendations of the French Society of Rheumatology29 for management/detection of comorbidities for which international recommendations were lacking. CV disease: a patient was considered as optimally monitored if all measurable risk factors for CV disease (ie, BP, glycaemia, cholesterol, creatinine) were monitored at least once during the previous year.17 Infections: a patient was considered as optimally monitored (a) if dental examination had been conducted in the prior year;29 (b) if diphtheria–tetanus–poliomyelitis (DTP) vaccination had been administered in the last 10 years;29 (c) for patients aged >65 years or receiving biological DMARDs, they were considered as optimally vaccinated if they had received an influenza vaccination within the past 12 months and a pneumococcal vaccination within the past 5 years29 and (d) for patients ever exposed to biological DMARDs, they were considered as optimally screened for viral hepatitis (HBV and HCV) if they had ever been screened.29 Cancer: for each cancer, optimal monitoring was determined only for the population at risk (ie, depending on the gender and age), according to each cancer screening recommendation. For breast cancer, individuals at risk were (a) women older than 50 years with no history of breast cancer and (b) women of all ages with no personal history of breast cancer but with a family history of breast cancer; both groups were considered as optimally monitored if they had received a mammogram during the past 2 years.30 For cervix cancer screening, population at risk were women of all ages with no past history of cervix cancer; they were considered as optimally monitored if they had received a cervical smear test within the past 3 years.31 For colon cancer, optimal monitoring was dependent on the presence of risk factors: all patients older than 50 years were considered as optimally monitored if they had been tested for faecal occult blood at least once during the past 2 years; however, patients with at least one risk factor for colorectal cancer (ie, a history of IBD, a family history of colon cancer or a family history of adenomatous polyposis) were only considered as optimally monitored if they had undergone a colonoscopy at least once.32 ,33 For skin cancer, the individuals at risk were patients with >40 naevi or who were ever exposed to biological DMARDs; they were considered as optimally monitored if they had visited a dermatologist within the last 12 months29
Finally, for some CV risk factors (ie, hypertension, hypercholesterolaemia and hyperglycaemia), it was possible to evaluate the percentage of patients (without previously known history of such risk factors) for whom an abnormality (elevated BP, LDL-cholesterol above target and hyperglycaemia) was detected as a result of the systematic evaluation during the study visit.
All analyses were conducted with the statistical software SAS V.9.4.
Investigators from 22 countries recruited a total of 4028 patients from January 2013 to September 2014. Forty-four patients were excluded because all data in their forms except for the identification numbers were missing, resulting in 3984 patients included in the analysis.
Demographics and disease characteristics are summarised in table 1. Most patients presented axial involvement (89%), but a great intercountry variability was observed for some characteristics: for example, patients from Asia were younger, and the disease activity defined by ASDAS-CRP ranged from 1.4 in Spain to 2.7 in Germany. Similarly, the presence of a bamboo spine was overall low (7%); the percentage was high in some countries (eg, 25% in Egypt). Overall, almost half of patients (44%) had ever received a TNFi, but this proportion was lower in some of the Asian countries compared with some European countries. Detailed demographics and disease characteristics per country are summarised in online supplementary appendix tables 1 and 2.
Prevalence of comorbidities
The estimated prevalences and 95% CIs of the evaluated comorbidities are summarised in figure 1, and detailed comparisons depending on the country are presented in online supplementary appendix tables 3– 8.
Global prevalences of ischaemic heart disease and stroke in the study population were 2.7% (95% CI 2.2 to 3.2) and 1.3% (95% CI 0.9 to 1.7), respectively; higher prevalences (10%) for any CV disease (ie, ischaemic heart disease or stroke) were observed in Northern European countries and the USA (see online supplementary appendix table 3).
Overall prevalence for any type of cancer was estimated at 3.0% (95% CI 2.46 to 3.52), and the most prevalent cancer was cervical cancer (1.2% (95% CI 0.3 to 1.7). Prevalences of basocellular carcinoma and melanoma were 0.8% (95% CI 0.6 to 1.2) and 0.7% (95% CI 0.4 to 1.0), respectively (see online supplementary appendix table 4).
Overall prevalence of HBV infection was 3.5% (95% CI 2.9 to 4.0), with the highest prevalence observed in China and Turkey (12%). Regarding HCV infection, the highest prevalences were found in Egypt (4%) and Turkey (5%) compared with the rest of the countries (1.2% (95% CI 0.9 to 1.6)). The prevalence of active tuberculosis was 2.5% (95% CI 2.0 to 3.0), ranging from 0% in most countries to 9% in South Korea (see online supplementary appendix table 5).
Gastrointestinal ulcer was frequent in our study population (10.7% (95% CI 9.7 to 11.7)), with prevalences ranging from 1% in Morocco to 47% in Egypt. On the other hand, overall prevalence of diverticulitis requiring surgery was low at 0.3% (95% CI 0.1 to 0.5) (see online supplementary appendix table 6).
Osteoporosis was the most frequent comorbidity, with a prevalence of 13.4% (95% CI 12.3 to 14.4). However, the prevalences of vertebral and proximal hip fractures were very low (2% and 0.2%, respectively) (see online supplementary appendix table 7).
Prevalence of risk factors for comorbidities
The estimated prevalences and 95% CIs of the collected risk factors for CV disease, some cancers and osteoporosis are represented in figure 2. The detailed data on the prevalence of each risk factor by country are available in online supplementary appendix tables 9–11.
Hypertension was the most prevalent CV disease risk factor with 33.5% (95% CI 32.0 to 35.0), and particularly in the Northern European countries (ie, 60% in the Netherlands). Smoking was the second most prevalent risk factor for CV disease, with 29.3% (95% CI 27.9 to 30.7). Global prevalence of hypercholesterolaemia was 27.3% (95% CI 25.9 to 28.7) (see online supplementary appendix table 9).
The most prevalent risk factor for cancer was a family history of breast cancer (15.0% (95% CI 13.1 to 16.9)), followed by a history of family colon cancer (8.0% (95% CI 7.2 to 8.9)) (see online supplementary appendix table 10).
The prevalence of a family history of hip fracture was 3.7% (95% CI 3.2 to 4.3) (see online supplementary appendix table 11).
Optimal monitoring of comorbidities/risk factors
Percentage of patients optimally monitored for the selected comorbidities and/or risk factors are represented in figure 3 (detailed data by country are summarised in online supplementary appendix tables 12–15).
A complete yearly evaluation of all CV risk factors was only performed 1996 of the 3956 patients for whom this information was available, in 50.5% (95% CI 48.9 to 52.0) of patients, but these percentages differed greatly depending on the country, ranging from 3% in Taiwan to 98% in Italy. However, BP and creatinine evaluations were frequently performed 3210/3962 (81%) and 3213/3957 (81%), respectively while annual cholesterol evaluation was only performed in 56% of patients (see online supplementary appendix table 12).
Optimal cancer screening was more frequently performed in feminine cancers, that is, in 262 (44.0%) of the 596 patients at risk for breast cancer and in 514 (39.8%) of the 1290 patients at risk for cervical cancer. Colon cancer was optimally screened in 455 (32.7%) of the 1392 patients at risk. Skin cancer was the least optimally screened type of cancer, with only 184 (10.7%), with a great intercountry variability (see online supplementary appendix table 13).
An annual dental visit was performed in 1672 of the 2681 patients fr whom this information was available 62.4% of patients, while only 8.9% patients had received a DTP vaccination within the past 10 years. Among the 1911 patients at risk (ie, patients older than 65 years or receiving a biological DMARD), only 332 (17.3%) had received a pneumococcal vaccination within the past 5 years and 726 (38.0%) had received an influenza vaccination within the past 12 months.
Of the 1751 patients at risk (ie, patients ever exposed to a biological DMARD), 1347 (76.9%) underwent a screening test for viral hepatitis with large variability across countries (see online supplementary appendix table 14).
Detected risk factors due to systematic assessment of comorbidities in the ASAS-COMOSPA Initiative
Due to the systematic evaluation during the study visit of the measurable parameters (ie, BP, LDL-cholesterol and glycaemia) used to define CV risk factors (ie, hypertension, hypercholesterolaemia and diabetes), we were able to detect abnormalities in patients without any previously known history for such CV risk factors. Among the 3055 patients without a history of hypertension, a BP measure was available in 2839 patients, and high BP was detected in 416 (14.7%) of them at the study visit; among 3739 patients with no history of diabetes, glycaemia at the study visit was available in 2809 patients, and an elevated blood glucose level was detected in 147 (5.2%); finally, among the 3244 patients with no history of hypercholesterolaemia, an LDL determination was available at the study visit in 1817 patients, and an LDL above the optimal target was detected in 384 (21.1%) of them (see online supplementary appendix table 15).
This is the first and largest cross-sectional observational prevalence study assessing comorbidities and risk factors and their monitoring in a worldwide population of patients with SpA.
In our study, the most prevalent comorbidities were osteoporosis (13.4%) and a history of gastrointestinal ulcer (10.7%), the two comorbidities classically reported to be more frequent in patients with SpA.
Osteoporosis was more frequent than what has been reported in healthy young men (around 5%),34 but with a prevalence comparable with what has been reported in the literature in SpA.35–38 Gastrointestinal ulcer was the second most prevalent comorbidity, but there was a major intercountry variability (from 47% in Egypt to 2% in China).
The prevalence of CV disease was not higher than what has been reported for individuals in the general population,39 ,40 while it is worth noting that this is a very young population (mean age 44 years). Regarding the worldwide distribution of comorbidities, as described in the literature, CV 41 and cancer diseases were strikingly more frequent in Northern Europe and in the USA42–44 compared with Asian and Northern African countries. However, these particular comorbidities (CV and cancer) are well known to be age related, and in our study Asian patients were younger than European patients (eg, mean age of 29 years for China vs 53 years for Belgium or 52 years for the Netherlands).
A high percentage of patients were not monitored according to prevailing recommendations. Optimal monitoring of CV disease was only attained in 50% of patients, whereas optimal cancer screening (eg, according to general population recommendations for most cancers and treatment-related-specific recommendations for skin cancer45) was only attained in 11–44% of patients. Even lower percentages were found for optimal vaccination, particularly for the DTP (8%). This wide gap between recommendations for cancer screening46–48 and vaccination programmes49 and performance in real life has already been reported for the general population, and in patients with rheumatic diseases21 and/or under immunosuppressive treatment.50
The systematic evaluation performed in our study allowed us to detect some abnormalities in the parameters defining CV risk factors in patients without any previous history. These results reinforce the idea that systematic evaluation and screening of comorbidities and risk factors in patients with SpA may allow an earlier detection, which may result in an improved outcome of these patients.
This study has several weaknesses but also some strengths. First, the prevalence of some comorbidities might have been overestimated due to diagnostic bias: patients with SpA might have been screened for comorbidities that have been classically related to the disease (eg, osteoporosis). On the other hand, the prevalence of some comorbidities might have been underestimated by selection: patients with most relevant comorbidities may have been unable to participate or even died at a premature age preventing them to participate in this present study (left-censorship bias). Also, great disparities were found with regard to the prevalence of comorbidities across countries. While this might be explained by ethnicity and socioeconomic differences, it is not impossible that this would be explained by the patient selection depending on the country. Finally, the recommendations used for defining the optimal monitoring were sometimes based on local recommendations and applied to the global group. Therefore, the results could have been different if country-specific recommendations would have been used. However, it is highly unlikely that the use of such country-specific recommendations would have yielded optimal screening percentages: there is still a lot of room for improvement in detecting and monitoring comorbidities in SpA, as it has already been shown for the general population48 and for RA.21 Further studies confirming the impact of a systematic assessment of comorbidities and their risk factors on better outcomes for patients with SpA are needed. If confirmed, these studies should lead to develop standardised programmes for the screening/management of comorbidities in rheumatic diseases, and in particular in SpA.
This study was conducted under the umbrella of the International Society for Spondyloarthritis Assessment (ASAS).
Handling editor Tore K Kvien
Correction notice This article has been corrected since it was published Online First. Figure 3 has been corrected and also under the heading 'Infection' on page 5 values listed in the first sentence of the second paragraph have been corrected.
Collaborators (1) Fadoua Allali, MD, Mohamed Vth University, URAC 30, Department of Rheumatology, El Ayachi Hospital, Salé, Faculty of Medicine and Pharmacy, Rabat, MOROCCO. firstname.lastname@example.org (2) Raquel Almodovar González, MD, Hospital Fundación Alcorcón, Madrid, SPAIN. email@example.com (3) Elena Alonso Blanco-Morales, MD, Hospital Universitario Juan Canalejo, La Coruña, SPAIN. firstname.lastname@example.org (4) Alejandro Alvarellos, MD. email@example.com Hospital Privado de Córdoba, Argentina. (5) Maria Aparicio Espinar, MD, Hospital Universitario Bellvitge, Barcelona, SPAIN. firstname.lastname@example.org (6) Pamir Atagunduz, MD, Division of Rheumatology, Marmara University, Faculty of Medicine, Istanbul, TURKEY. (7) Pauline Bakker, MD, Department of Rheumatology, Leiden University Medical Center, Leiden, THE NETHERLANDS. P.A.C.Bakker@lumc.nl (8) Juan C. Barreira, MD, email@example.com, Hospital Británico de Buenos Aires, Argentina. (9) Leila Benbrahim, MD, Mohamed Vth University, URAC 30, Department of Rheumatology, El Ayachi Hospital, Salé, Faculty of Medicine and Pharmacy, Rabat, MOROCCO. firstname.lastname@example.org (10) Bahia Benchekroun, MD, Mohamed Vth University, URAC 30, Department of Rheumatology, El Ayachi Hospital, Salé, Faculty of Medicine and Pharmacy, Rabat, MOROCCO. email@example.com (11) Alberto Berman, MD. Albertoberman1@yahoo.com.ar, Centro Médico Privado, Tucumán, Argentina. (12) Juergen Braun, MD, Rheumazentrum Ruhrgebiet, Herne, Germany. firstname.lastname@example.org (13) Alain Cantagrel, MD, PhD, Centre de Rhumatologie, CHU Purpan, Toulouse, FRANCE. (14) Roberto Caporali, MD, University of Pavia, IRCCS Policlinico San Matteo Foundation, Pavia, ITALY (15) Pedro Carvalho, MD, Clínica Universitária de Reumatologia, Hospitais da Universidade de Coimbra, Coimbra, Portugal. (16) Gustavo Casado, MD. email@example.com. Hospital Militar Central, Buenos Aires, Argentina. (17) James Cheng-Chung Wei, MD, PhD, Chung Shan Medical University Hospital, Taichung, Taiwan. e-mail: firstname.lastname@example.org (18) Francisco Colombres, MD. email@example.com. Centro Médico Privado, Tucumán, Argentina. (19) Eugenio del Miguel Mendieta, MD, PhD, Hospital Universitario La Paz, Madrid, SPAIN. firstname.lastname@example.org (20) Juan D. Diaz-Garcia, MD, Escuela Superior de Medicina, Instituto Politécnico Nacional, MEXICO. (21) Michel De Bandt, MD, PhD, Rheumatology Unit, University Hospital of Martinique, Fort de France, FRANCE. (22) Vanesa Duarte, MD. Vane.email@example.com. Hospital Rivadavia, Buenos Aires, Argentina. (23) Cristina Fernandez Carballido, MD, Hospital General Universitario de Elda, Elda, SPAIN. firstname.lastname@example.org (24) Mari Cruz Fernandez Espartero, MD, Hospital de Mostoles, Madrid, SPAIN. email@example.com (25) Manuel Fernandez-Prada, MD, Hospital de Guadalajara, Guadalajara, SPAIN. (26) Rene-Marc Flipo, MD, PhD, Rheumatology Department, CHRU Lille, FRANCE. (27) Pilar Font Ugalde, MD, PhD, Hospital Universitario Reina Sofia, IMIBIC, Córdoba, SPAIN. firstname.lastname@example.org (28) Philippe Gaudin, MD, PhD, Clinique Universitaire de Rhumatologie, Hôpital Sud, Echirolles, and Université Joseph Fournier, Grenoble, FRANCE. (29) Philippe Goupille, MD, Rheumatology Department, Tours University, Tours, FRANCE. 30. Dolors Grados Cánovas, MD, Hospital San Rafael, Barcelona, SPAIN. email@example.com (31) Jordi Gratacós Masmitjá, MD, PhD. Hospital Universitario Parc Taulí, Badalona, SPAIN. firstname.lastname@example.org (32) Vittorio Grosso, MD, University of Pavia, IRCCS Policlinico San Matteo Foundation, Pavia, ITALY. (33) Naomi Ichikawa, MD, Institute of Hematology, Tokyo Women's Medical University, JAPAN. Naomu@twmu.ac.jp 34. Hisashi Inoue, MD, Juntendo University School of Medicine, JAPAN. email@example.com (35) Yuko Kaneko, MD, PhD, Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, JAPAN. firstname.lastname@example.org (36) Taku Kawasaki, MD, PhD, Department of Orthopaedic Surgery, Shiga University of Medical Science, JAPAN. email@example.com (37) Shigeto Kobayashi, MD, Juntendo University School of Medicine, JAPAN. firstname.lastname@example.org (38) Manjari Lahiri, MD, Division of Rheumatology, National University Hospital, SINGAPORE. Manjari_lahiri@nuhs.edu.sg. (39) Hernán Maldonado-Ficco, MD. email@example.com. Clinica Regional del Sud, Rio Cuarto (Córdoba), Argentina. (40) Marhadour, MD, Rheumatology Department, CHRU Cavale Blanche, Brest, FRANCE, (41) Alejandro Martínez, MD. Ale_mmzgonc@yahoo.com.ar. Hospital Tornú, Buenos Aires, Argentina. (42) Kazuo Matsui, MD, Department of Rheumatology, Kameda Medical Center, JAPAN. PXU17054@nifty.com (43) Ramón Mazzuchelli Esteban, MD, Hospital Fundación Alcorcón, Madrid, SPAIN. firstname.lastname@example.org (44) Corinne Micelli, MD, PhD, Rheumatology Department, Kremlin-Bicêtre Hospital, Paris VII University, Paris, FRANCE. (45) Chisun Min, MD, Immuno-Rheumatology Center, St Luke’s International Hospital, JAPAN. email@example.com (46) Mitsuhiro Morita, MD, PhD, Department of Orthopaedic Surgery, Fujita Health University, JAPAN. firstname.lastname@example.org (47) Juan Mulero Mendoza, MD, PhD, Hospital Universitario ‘Puerta de Hierro’, Madrid, SPAIN. email@example.com (48) Jose Raul Noguera Pons, MD, Hospital de Elche, Elche, SPAIN. firstname.lastname@example.org (49) Masato Okada, MD, Immuno-Rheumatology Center, St Lukès International Hospital, JAPAN. email@example.com (50) Alberto Ortiz, MD. Albertoortiz_4@hotmail.com Hospital Provincial Dr. José Cullen, Santa Fe, Argentina. (51) Jon Packham, DM, FRCP, Keele University. Jon.Packham@uhns.nhs.uk (52) Gisela Pendón, MD. firstname.lastname@example.org. Hospital Ricardo Gutierrez, La Plata, Argentina. (53) Dora Pereira, MD. email@example.com. Hospital Ricardo Gutiérrez, La Plata, Argentina. (54) José A Pereira da Silva, MD, Clínica Universitária de Reumatologia, Hospitais da Universidade de Coimbra, Coimbra, Portugal. (55) Fernando Pimentel-Santos, MD, Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Lisbon, Portugal. (56) Hanan Rkain, MD, Mohamed Vth University, URAC 30, Department of Rheumatology, El Ayachi Hospital, Salé, Faculty of Medicine and Pharmacy, Rabat, MOROCCO. firstname.lastname@example.org (57) Oscar Rillo, MD. Rillo.email@example.com. Hospital Pirovano, Buenos Aires, Argentina. (58) Carlos Rodriguez Lozano, MD, Hospital Universitario Negrin, Tenerife, SPAIN. firstname.lastname@example.org (59) Adeline Ruyssen-Witrand, MD, PhD, Centre de Rhumatologie, CHU Purpan, Toulouse, FRANCE (60) Adrián Salas, MD. email@example.com. Hospital General San Martín, La Plata. Argentina. (61) Carlos Salinas-Ramos, MD, Escuela Superior de Medicina, Instituto Politécnico Nacional, MEXICO. (62) Amelia Santosa, MD, Division of Rheumatology, National University Hospital, SINGAPORE. Amelia_santosa@nuhs.edu.sg (63) Alain Saraux, MD, PhD, Rheumatology Department, CHRU Cavale Blanche, Brest, FRANCE. (64) Raj Sengupta, FRCP, PGCME, Royal Bath Hospital for Rheumatic Diseases, Bath, UNITED KINGDOM. firstname.lastname@example.org (65) Stefan Siebert, PhD, University of Glasgow, UNITED KINGDOM. email@example.com (66) Martin Soubrier, MD, PhD, CHU Clermont-Ferrand, Dpt of Rheumatology, UMR 1019 INRA/Clermont 1 University, Clermont-Ferrand, FRANCE. (67) Caroline Spiegel, Rheumazentrum Ruhrgebiet, Herne, Germany. firstname.lastname@example.org (68) Carmen Stolwijk, MD, Maastricht University Medical Center, Maastricht, THE NETHERLANDS. (69) Kurisu Tada, MD, Juntendo University School of Medicine, JAPAN. email@example.com (70) Naoho Takizawa, MD, Department of Rheumatology, Kameda Medical Center, JAPAN. firstname.lastname@example.org (71) Yoshinori Taniguchi, MD, PhD, Department of Endocrinology, Metabolism, Nephrology and Rheumatology, Kochi University, JAPAN. email@example.com (72) Atsuo Taniguchi, MD, PhD, Institute of Rheumatology, Tokyo Women’s Medical University, JAPAN. firstname.lastname@example.org (73) Chung Tei Chou, MD, Veterans General Hospital, Taipei, Taiwan. email@example.com (74) Lay-Keng Teoh, Division of Rheumatology, National University Hospital, SINGAPORE. firstname.lastname@example.org (75) Tetsuya Tomita, MD, PhD, Department of Orthopaedic Biomaterial Science, Osaka University Graduate School of Medicine, JAPAN. email@example.com (76) Wen-Chan Tsai, MD, PhD, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan; email: firstname.lastname@example.org (77) Shigeyoshi Tsuji, MD, PhD, Department of Orthopedic surgery, Osaka Minami Medical Center, JAPAN. email@example.com (78) Olga Tsyplenkova, Rheumazentrum Ruhrgebiet, Herne, Germany. firstname.lastname@example.org (79) Astrid van Tubergen, MD, PhD, Maastricht University Medical Center, Maastricht, THE NETHERLANDS (80) Kiana Vakil-Gilani, BS, MPH, Oregon Health & Science University, Portland, USA (81) Rafael Valle-Oñate, MD, Rheumatology Department, Faculty of Medicine, HMC/UMNG, Bogota, COLOMBIA. (82) Gaelle Varkas, MD, Department of Rheumatology, Ghent University Hospital, Ghent, BELGIUM. (83) Virginia Villaverde, MD, Hospital de Mostoles. Madrid. SPAIN. email@example.com (84) Ai Yap, Division of Rheumatology, National University Hospital, SINGAPORE. B.Sc firstname.lastname@example.org (85) Pedro Zarco Montejo, MD, PhD. Hospital Fundación Alcorcón, Madrid, SPAIN. email@example.com.
Contributors The authors take responsibility for the integrity of the work as a whole, from inception to published article and they should indicate that they had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Funding This study was conducted with the financial support of Abbvie, Pfizer and UCB, who provided an unrestricted grant. The funders did not have any role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript and decision to submit the manuscript for publication.
Competing interests None declared.
Ethics approvalAll local ethics committees approved the ASAS-COMOSPA study protocol.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement Researchers willing to use data collected during the study should contact the first author, who will send a study proposal template to be completed by the applicant. Thereafter, the steering committee of the ASAS-COMOSPA study will approve (or not) the proposal and proceed to the data sharing.
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