Abstract: Emerging observational data have shown that rheumatic patients seem not to be more susceptible to SARS-CoV-2 infection neither to worse outcomes. However, the true prevalence of COVID19 is still unknown due to the high proportion of subclinical infection. In this scenario, measuring the seroprevalence of SARS-CoV-2 may be crucial to improve the knowledge about the impact of COVID19 in rheumatic patients. Objectives: To estimate in a COVID19 high-endemic area (Lombardy, Italy) the prevalence of anti-SARS-CoV-2 antibodies in a large cohort of patients with rheumatoid arthritis (RA) or spondyloarthritis (SpA) treated with biologic (b-) or targeted synthetic (ts-) disease modifying drugs (DMARDs). Methods: A seroprevalence cross-sectional study was conducted in the period between 4 th May and 16 th June 2020, including patients with confirmed RA or SpA treated with b- or tsDMARDs. Patients were tested for anti-SARS-CoV-2 IgG, IgM and IgA antibodies against main viral antigens (nucleoprotein [N], spike 1 [S1] , receptor-binding domain [RBD]) using ELISA. These data were compared with those observed in the healthy population in the same period and region. Patients also answered a questionnaire on history of symptoms consistent with COVID19, risk factors and comorbidities. Serological response to RBD was evaluated according to symptom severity (asymptomatic, minor, or major [respiratory and fever 〉 37.5°C] symptoms). Results: The study population included 300 patients (62% females, mean age 53 years, 20% over 65 years old) diagnosed with RA (56%), psoriatic arthritis (23%), or ankylosing spondylitis (21%), treated with anti-TNF (57%), abatacept (20%), anti-IL6 (11%), or JAK inhibitors (5%). Four patients (1.3%) referred a prior diagnosis of COVID19 defined by nasopharyngeal swab. Immunoglobulin titers were evaluated resulting in 9%, 13.6%, and 13.3% positive patients for IgG, IgM and IgA, respectively (Table 1), with no significant difference to the healthy population. Among seropositive patients, 55.3% were asymptomatic, 16% had minor and 19.6% major symptoms, 7.1% were hospitalized. No deaths or admission to intensive care units occurred. IgM, IgG and IgA titers to RBD were higher in patients with both minor and major symptoms compared with asymptomatic ones (Figure 1). No differences were found between seronegative and seropositive patients in relation to age, sex, rheumatic diagnosis, and treatments with b- or tsDMARDs. A relative lower risk of seropositivity was observed in patients receiving concomitant methotrexate (RR 0.49, 95% CI 0.25-0.94; p 0.04), while an increased risk was associated with obesity (RR 2.33, 95% CI 1.26-3.79; p 0.019) and presence of at least 2 comorbidities (RR 1.94, 95% CI 1.11-3.15; p 0.037). Corticosteroids use was numerically more frequent in seropositive than seronegative patients (18% vs 14%). Conclusion: This study confirms that, even in a cohort of rheumatic patients, the spread of SARS-CoV-2 infection is much greater than that observed by capturing only swab-diagnosed COVID19 cases. The underlying rheumatic disease and ongoing therapy with b/ts-DMARDs do not seem to impact SARS-CoV-2 antibody positivity, which conversely seems to be proportional to the intensity of COVID19 symptoms and less frequent in patients receiving concomitant methotrexate. The project was co-financed by Lombardy Region 2014-2020 Regional Operational Programme under the European Regional Development Fund. Table 1. Prevalence of specific anti-SARS-CoV-2 antibodies. Antibodies Posivite(n) Seroprevalence (%) (95% CI) IgG 27 9% (6.2 – 12.7) IgG anti-N 26 8.6% (5.9 – 12.3) IgG anti-RBD 20 6.6% (4.3 – 10) IgG anti-S1 18 6% (3.8 – 9.2) IgM 41 13.6% (10.2 – 18) IgM anti-N 35 11.6% (8.5 – 15.7) IgM anti-RBD 25 8.3% (5.7 – 12) IgA 40 13.3% (9.9 – 17.6) IgA anti-N 37 12.3% (9.0 – 16.5) IgA anti-RBD 25 8.3% (5.7 – 12) IgG+IgM 23 7.6% (5.1 – 11.2) IgG+IgM+IgA 22 7.3% (4.9 – 10.5) IgG+IgA 24 8% (5.4 – 11.6) IgG/IgM/IgA 56 18.6% (14.6 – 23.4) Figure 1. Antibody levels (S/Co) against SARS-CoV-2 RBD. Disclosure of Interests: None declared.

Abstract: Rheumatic musculoskeletal diseases (RMD) are pathological conditions characterized by an impaired immunological system that is determinant both in the pathogenesis and in the inadequate response to infections. The use of disease-modifying anti-rheumatic drugs (DMARDs), which include conventional synthetic (cs) or biologic and targeted synthetic (b/ts) DMARDs, contribute to compromise immunological reactivity. Objectives To analyze the immune response to SARS-CoV-2 in patients with rheumatoid arthritis (RA) or spondyloarthritis (SpA) receiving treatment with DMARDs and to investigate the effect of the different classes of drugs on humoral and cellular response. Methods Patients were tested for anti-SARS-CoV-2 IgG, IgM and IgA antibodies to nucleoprotein (N) and receptor-binding domain (RBD) through ELISA and neutralization assays. Then, we performed a flow cytometry analysis of monocytes, NK cells, B and T lymphocytes from PBMCs of serologically positive patients. We also included a cohort of non-RMD individuals recovered from COVID-19 as a reference group of non-immunosuppressed subjects. A first recruitment occurred in May-June 2020 (T1) and a second recruitment, 3-4 months after (T2), allowed to evaluate the persistence of the antibody response over time and to investigate the cellular immune response to SARS-CoV-2 in RMD patients having resolved the infection. Results During T1, 358 patients with RA (n=200) or SpA (n=158) were recruited. Mean age was 52.8, 64% were female. All patients were treated with DMARDs, 299 with b/tsDMARDs and 59 received csDMARDs alone. One third was also receiving corticosteroids (CS). At T2, 36 subjects were recruited. We found a seroprevalence rate of 18.4%, which did not significantly differ between RA and SpA groups, and between patients treated with b/ts-DMARD or csDMARDs, either alone or in combination with CS (Table 1). Antibody levels of RMD patients were lower than non-RMD individuals (Figure 1), with CTLA4-Ig-treated patients having the lowest IgG levels. This difference was less marked in symptomatic RMD patients. 72% of seropositive patients elicited neutralizing sera. Despite an overall decrease in anti-RBD and anti-N titers, more than two-third of patients maintained antibodies titers above positivity threshold at T2. Concerning cellular response, we found that CD8+ T-cells frequency was overall comparable between RMD and non-RMD convalescents, and did not differ in b- or cs-DMARD treated ones. Conversely, CD4+ T-cell frequencies were significantly lower in RMD patients, especially those treated with anti-IL6R and CTLA4-Ig. B-cell subpopulations (class-switched, memory, and IgG+ memory B-cells) had sustained frequencies in anti-TNFα treated patients, while they had a trend of reduction in patients treated with anti-IL6R and CTLA4-Ig. Table 1. Anti-RBD seroprevalence Total Seropositive, n (%) IgM (n) (%) IgG (n) (%) IgA (n) (%) COVID19 symptomatic 77 25 32.5 19 24.7 17 22.1 17 22.1 COVID19 asymptomatic 281 41 14.6* 23 8.2* 13 4.6 * 26 9.3* RA 200 36 19 23 11.5 20 10 27 13.5 SpA 158 30 19 19 12 10 6.3 16 10.1 b/ts-DMARD 299 55 18.4 35 11.7 24 8 36 12 cs-DMARD 59 11 18.6 7 11.9 6 10.2 7 11.9 csDMARD+b/tsDMARD 112 26 23.2 8 7.1 8 7.1 9 8 a-TNFa 173 37 21.4 25 14.5 16 9.1 21 12.1 a-IL-6R 35 8 22.9 5 14.3 6 17.1 8 22.9 CTLA4-Ig 42 5 11.9 3 7.1 1 2.4 4 7.1 * P value 〈 0,005 Figure 1. Magnitude of the anti-RBD and anti-N antibody response Conclusion Our data provide a comprehensive picture of the humoral and cellular immune responses to SARS-CoV-2 infection in RMD patients. We showed that DMARDs treatments did not alter a successful antibody response to the virus and did not hamper the antibody neutralizing ability. However, the magnitude of antibody response was slightly reduced compared to non-RMD individuals, especially in patients receiving CTLA4-Ig. We did not observe marked differences in the B- and T-cell populations between RMD patients compared to non-RMD individuals. However, in patients receiving anti-TNFα we found a higher relative abundance of effector adaptive population compared to other bDMARDs. Acknowledgements The project was co-financed by Lombardy 2014-2020 Operational Program under the European Regional Development Fund. Disclosure of Interests None declared

Abstract: To compare the efficacy of a treatment with cisplatin plus cyclophosphamide given for 5 months and a short treatment with cisplatin alone in advanced ovarian cancer, we conducted a multicenter randomized clinical trial. PATIENTS AND METHODS Eligibility criteria were as follows: first diagnosis of histologically confirmed invasive epithelial ovarian cancer of International Federation of Gynecology and Obstetric (FIGO) stage III-IV, age younger than 75 years, and Eastern Cooperative Oncology Group (ECOG) performance status 0, 1, or 2. Within 28 days of cytoreductive surgery, eligible women were randomly assigned treatment with weekly cisplatin 50 mg/m2 for nine courses or cisplatin 75 mg/m2 plus cyclophosphamide 750 mg/m2 every 21 days for six courses. RESULTS A total of 607 women were entered onto the study. There was no difference in the response to treatment. Pathologic complete response (CR) was documented in 63 of the weekly cisplatin cases and 70 of the cisplatin plus cyclophosphamide group (chi 1(2) = 1.43; P = .23). The median follow-up time was 3 years. There were 151 and 148 deaths in the weekly cisplatin and cyclophosphamide plus cisplatin arms, respectively. Survival curves were similar in the two groups, with a 3-year percent survival estimate of 44.1 (SE = 3.4) in the weekly cisplatin and 44.6 (SE = 3.4) in the cisplatin plus cyclophosphamide group (log-rank test chi 1(2) = 0.004; P = .96). CONCLUSION This study found that 2-month monochemotherapy treatment with cisplatin was as effective as 5-month polychemotherapy including cisplatin at a similar doses but different dose-intensity plus cyclophosphamide.

Abstract: On 17 January 2002, the Nyiragongo volcano (1.52°S, 29.25°E, 3469 meters above sea level), located about 18 kilometers north of Lake Kivu in the Democratic Republic of Congo, erupted, releasing a volume of 14–34 million cubic meters of lava. Lava flows originated from north‐south oriented fractures that rapidly developed along the southern flank of the volcano. Two lava flows divided the nearby city of Goma (∼500,000 people) into two parts, forcing a rapid exodus of the population into Rwanda. One of these lava flows ran into Lake Kivu, encroaching 60 meters below lake level with a submerged lava volume of 1 million cubic meters. About 15% of the town was directly affected, leaving approximately 120,000 people homeless. At least 170 people died as a direct consequence of the eruption.

Abstract: Previous studies have compared Patient-Reported Outcomes (PROs) in Spondyloarthritis (SpA); a recent one has found similarity in Psoriatic Arthritis (PsA) and axial patients 1 . Objectives: To describe PROs at SpA diagnosis (new or confirmed), by type of SpA and by gender. Methods: SIRENA is an Italian, prospective Registry of SpA patients diagnosed according to ASAS criteria and naïve to any DMARDs. At inclusion, patients were classified as predominant axial (AxSpA) or mainly peripheral (pSpA). PROs showed in the Table 1 were collected and analysed descriptively. Table 1. PhGA and PROs at diagnosis* AxSpA* pSpA All (n=123 ) Women (n=64 ) Men (n=58 ) All (n=227 ) Women (n=109 ) Men (n=118 ) PhGA, n 115 60 54 222 105 117 mean (SD) 50.2 (28.6) 54.8 (26.7) 45.0 (30.1) 45.4 (25.9) 49.9 (25.6) 41.3 (25.6) median (min, max) 52.0 (0-100) 62.0 (0-100) 43.5 (0-100) 48.5 (0-100) 50.0 (1.0-100) 40.0 (0-95.0) PtGA, n 112 59 52 209 102 107 mean (SD) 56.4 (27.8) 61.5 (25.8) 50.3 (29.2) 50.3 (26.2) 56.4 (23.1) 44.5 (27.7) median (min, max) 63.0 (0-100) 70.0 (2.0-100) 50.0 (0-100) 50.0 (0-100) 58.5 (7.0-100) 47.0 (0-100) Pain VAS score, n 113 60 52 207 101 106 mean (SD) 56.7 (28.3) 61.1 (26.6) 50.6 (29.1) 51.9 (26.8) 57.4 (25.3) 46.8 (27.3) median (min, max) 60.0 (0-100) 69.5 (2.0-100) 50.0 (0-100) 53.0 (0-100) 61.0 (0-100) 48.5 (0-100) Sleep VAS score, n 113 60 52 211 103 108 mean (SD) 55.3 (29.3) 57.4 (29.5) 52.3 (29.2) 44.0 (30.1) 50.4 (29.8) 37.9 (29.2) median (min, max) 59.0 (0-100) 61.5 (0-100) 53.0 (0-100) 44.0 (0-100) 53.0 (0-100) 34.0 (0-100) BASFI, n 110 58 51 133 65 68 mean (SD) 4.6 (2.8) 5.2 (2.6) 3.9 (2.8) 3.5 (2.6) 4.0 (2.6) 3.1 (2.4) median (min, max) 5.1 (0-9.7) 5.8 (0-9.4) 3.6 (0-9.6) 2.9 (0-10.0) 3.9 (0-10.0) 2.45 (0-8.9) BASDAI, n 112 59 52 139 70 69 mean (SD) 5.2 (2.4) 5.8 (2.3) 4.5 (2.3) 5.2 (2.3) 5.8 (2.1) 4.6 (2.3) median (min, max) 5.5 (0-9.3) 6.2 (0-9.3) 4.5 (0.3-9.2) 5.5 (0.2-10.0) 6.1 (1.0-10.0) 4.8 (0.2-9.2) HAQ-DI score, n 109 58 50 203 99 104 mean (SD) 0.9 (0.7) 1.1 (0.7) 0.6 (0.6) 0.7 (0.7) 0.9 (0.7) 0.6 (0.6) median (min, max) 0.8 (0.0-2.5) 1.1 (0-2.5) 0.5 (0-2.3) 0.6 (0.0-2.8) 0.8 (0-2.8) 0.4 (0-2.6) WPAI % work time missed, n 49 19 30 107 45 62 mean (SD) 7.3 (21.4) 4.2 (9.5) 9.2 (26.3) 8.8 (24.7) 8.6 (25.6) 8.9 (24.3) median (min, max) 0 (0-100) 0 (0-35.1) 0 (0-100) 0 (0-100) 0 (0-100) 0 (0-100) % impairment at work, n 67 33 34 134 61 73 mean (SD) 48.2 (31.9) 58.5 (26.6) 38.2 (33.7) 39.7 (31.4) 45.4 (30.9) 34.9 (31.2) median (min, max) 50.0 (0-100) 60.0 (0-100) 25.0 (0-100) 40.0 (0-100) 50.0 (0-100) 30.0 (0-100) % overall work impairment, n 48 19 29 106 45 61 mean (SD) 44.1 (33.0) 52.4 (27.9) 38.7 (35.3) 40.1 (33.0) 45.1 (33.1) 36.4 (32.7) median (min, max) 45.0 (0-100) 60.0 (0-100) 20.0 (0-100) 40.0 (0-100) 50.0 (0-100) 30.0 (0-100) % activity impairment, n 100 53 46 183 93 90 mean (SD) 56.7 (28.6) 63.4 (23.9) 48.0 (31.0) 48.5 (30.3) 55.3 (28.7) 41.4 (30.4) median (min, max) 60.0 (0-100) 70.0 (0-100) 50.0 (0-100) 50.0 (0-100) 60.0 (0-100) 40.0 (0-100) * The sum does not add up to the total because of some missing values. Results: From 23 sites, 123 AxSpA and 227 pSpA patients were analysed. Diagnosis was new in 58% of AxSpA and 77% of pSpA. 85.5% of the pSpA had PsA, while in AxSpA the most frequent type was Ankylosing Spondylitis (48.8%). Time from symptom onset to diagnosis was higher in AxSpA than in pSpA (median 36 vs 24 months, respectively). At inclusion, composite disease activity measures showed high disease activity for AxSpA (mean ASDAS-CRP 3.1) and moderate disease activity for pSpA (mean DAS28 3.6; mean DAPSA 22.5). AxSpA patients had numerically worse values than pSpA in all the PROs collected, except for BASDAI score that was similar (mean 5.2). For both AxSpA and pSpA, all PROs were worse in women than men, except for the % of work time missed. PtGA scores were higher than PhGA, in each group and gender. Conclusion: At diagnosis, SpA patients perceive a slightly higher disease burden than assessed by Physicians. For PROs other than BASDAI, AxSpA reported a worse impact than pSpA. Overall, women showed a higher disease impact than men. References: [1 ] Michelsen B. et al. PLoS ONE 2015; 10(4): e0123582. Disclosure of Interests: Rosario Foti Speakers bureau: Speaker bureau honoraria from Eli Lilly, Sanofi, MSD, Janssen, AbbVie, Bristol-Myers Squibb, Celgene, Roche, Consultant of: Consultancy fees from Eli Lilly, Sanofi, MSD, Janssen, AbbVie, BMS, Celgene, Roche, Gabriella Cardinale: None declared., Luisa Costa: None declared., Franco Franceschini: None declared., Francesco Ciccia Speakers bureau: Speaker bureau honoraria from AbbVie, Abiogen, Bristol-Myers Squibb, Celgene, Janssen, Eli Lilly, Pfizer, Novartis, Roche, Consultant of: Consultancy fees from Novartis, Pfizer, Janssen, Eli Lilly, Roche, Celgene, Grant/research support from: Grant/research support from Pfizer, Novartis, Celgene, Janssen, Roche, Antonio Marchesoni: None declared., Giuliana Guggino Speakers bureau: Speaker bureau honoraria from Celgene, Sandoz, Pfizer, Grant/research support from: Grant/research support from Pfizer, Celgene, Maurizio Rossini: None declared., Ennio Lubrano Di Scorpaniello: None declared., Bruno Frediani: None declared., Maria Sole Chimenti: None declared., Gerolamo Bianchi: None declared., Giuseppe Galfo: None declared., Silvia Marelli Employee of: Employee of Janssen-Cilag SpA Italy, Ennio Favalli Speakers bureau: Consulting fees and/or speaking engagements from AbbVie, Bristol-Myers Squibb, Lilly, Merck Sharp & Dohme, Pfizer, Galapagos, Sanofi-Genzyme, and UCB.

Abstract: Topotecan is a topoisomerase I inhibitor with preclinical activity against various tumor types. We conducted a large multicenter phase II study with topotecan in ovarian cancer in patients who had failed to respond to one prior cisplatin-based chemotherapeutic regimen. PATIENTS AND METHODS Topotecan 1.5 mg/m2/d was administered intravenously by 30-minute infusion for 5 days repeated every 3 weeks. As the cisplatin-free interval relates to response in subsequent treatment, patients were stratified in subgroups, ie, cisplatin-refractory, cisplatin-resistant, and cisplatin-sensitive. RESULTS One-hundred eleven patients entered the study. Nineteen patients were considered to be ineligible; 92 patients were assessable for response. A total of 552 courses were given (median, four per patient; range, one to 17). The major toxicities were leukocytopenia and neutropenia, which were grade 3 to 4 in 54.2% and 69.1% of courses, respectively, but with only 4.3% of these being grade 4 neutropenia plus fever or infectious complications. Prophylactic granulocyte colony-stimulating factor (G-CSF) was given in 20.5% of courses to maintain dose-intensity. Other relatively frequent side effects were alopecia (82%), nausea (36.4%), and vomiting (17.5%). The overall response rate was 16.3%, with one complete response (CR) and 14 partial responses (PRs). In the cisplatin-refractory, cisplatin-resistant, and cisplatin-sensitive strata, the response rates were 5.9%, 17.8%, and 26.7%, respectively. The median duration of time of documented response was 21.7 weeks (range, 4.6 to 41.9). CONCLUSION Topotecan in a daily-times-five schedule is an effective regimen as second-line treatment in ovarian cancer. Further investigations of topotecan in ovarian cancer, including first-line use and combination with other active agents, are indicated.

Abstract: SIRENA is an Italian, prospective Registry in Spondyloarthritis (SpA) patients, naïve to conventional, targeted and biological DMARDs. Patients are diagnosed, newly or confirmed, according to ASAS criteria and classified in subjects with predominant axial (AX ) or with mainly peripheral manifestations (PER ). Objectives: To compare descriptively AX vs PER subgroups of patients. Methods: Demographic data, diagnostic delay and subtypes of SpA as well as clinical features and comorbidities are collected. Results: 282 patients were enrolled: 101 (35.8%) AX and 181 (64.2%) PER. Baseline data are shown in Table 1. There were more obese patients in AX (21.4% AX vs 16.1% PER) and more overweight ones in PER (19.4% AX vs 23.8% PER). The % of subjects with diagnostic delay was higher in AX (65.7% vs 53.9% PER) and the delay longer (mean of 73.1 months vs 47.8). In both groups, main reason of the delay was incorrect referrals (41.5% for AX and 45.3% for PER). Noteworthy the fact that in PER, the 75.7% of patients had a newly diagnosed SpA. In PER, the most frequent SpA type was PsA (82.3%), followed by undifferentiated SpA (8.8%) and enteropathic SpA (7.5%), while in AX, 49.5% were ankylosing spondylitis, 21.8% nr-ax-SpA and only 4% PsA. The majority of PER patients reported as first symptom peripheral arthritis (80/181), psoriasis (57/181) and enthesitis while in AX referred inflammatory back pain (80/101). High percentages of comorbidities were reported: psoriasis (65.8%) and cardiometabolic diseases (34.8%) were higher in PER while depression/anxiety and GI diseases were higher in AX (Table 2). At the baseline, the mean PhGA score (0-100) was 51.5 for AX and 43.8 for PER. Conclusion: SIRENA study highlights relevant differences in AX vs PER patients, expecially in terms of diagnostic delay, clinical presentation and comorbidities. Table 1. Mean AX n=101 Mean PER n=181 Age (years) 47.3 52.8 Sex (female/male - %) 50.5/49.5 47.5/52.5 Weight (Kg) 73.0 73.9 BMI 25.3 25.4 Diagnostic Delay (yes - %) 65.7% 53.9% Time of delay (mean - months) 71.3 47.8 Newly SpA diagnosis (%) 55.5% 75.7% Table 2. A) First Symptom (more than 1 symptom referred ) AX n=101 N. Patients PER n=181 N. Patients Arthritis 23 122 Enthesitis 16 54 Dactylitis 7 28 Inflammatory Back Pain 80 34 Psoriasis skin 10 57 Psoriasis nails 2 19 Uveitis 4 1 IBD 7 9 B) Comorbidities (more than 1 comorbidity referred ) % Patients % Patients Cardiometabolic 20.8% 34.8%  -Hypertension 19.8% 30.9%  -Dyslipidemia 17.8% 11.6%  -Diabetes 6.0% 7.7%  -MetS 5.0% 6.6% Psoriasis 22.8% 65.8% Gastrointestinal 20.8 (16.9% CD) 12.8 (4.4% CD) Depression/Anxiety 11.9% 2.2% Endocrine 6.9% 11.1% Osteoporosis 3% 5.5% Hepatic 4% (3% NAFLD) 4.4% (2.2% NAFLD) Infections 3% 3.9% Malignancies 0% 4.4% Acknowledgments: This study was sponsored by Janssen Italy. We thank the Investigators and their staff at all of the study sites. Disclosure of Interests: Rosario Foti Speakers bureau: Abbvie, BMS, ROCHE, Janssen, Celgene, Gabriella Cardinale: None declared, Luisa Costa: None declared, Franco Franceschini Consultant of: Eli-Lilly, Janssen, Pfizer, Sanofi-Genzyme, UCB Pharma, GSK, Francesco Ciccia Grant/research support from: Pfizer, Novartis, Celgene, Janssen, Consultant of: Lilly, Novartis, Pfizer, Janssen, Roche, Celgene, Speakers bureau: Pfizer, Novartis, Celgene, Janssen, Roche, Abiogen, BMS, Antonio Marchesoni Speakers bureau: Abbvie, Pfizer, UCB, Novartis, Celgene, Eli Lilly, Giuliana Guggino Grant/research support from: Pfizer, Celgene, Speakers bureau: Celgene, Sandoz, Pfizer, Maurizio Rossini Speakers bureau: AbbVie, Abiogen, Amgen, BMS, Eli-Lilly, Novartis, Pfizer, Sanofi, Sandoz and UCB, Ennio Lubrano: None declared, Mauro Galeazzi: None declared, Mariasole Chimenti: None declared, Gerolamo Bianchi Grant/research support from: Celgene, Consultant of: Amgen, Janssen, Merck Sharp & Dohme, Novartis, UCB, Speakers bureau: Abbvie, Abiogen, Alfa-Sigma, Amgen, BMS, Celgene, Chiesi, Eli Lilly, GSK, Janssen, Medac, Merck Sharp & Dohme, Novartis, Pfizer, Roche, Sanofi Genzyme, Servier, UCB, Giuseppe Galfo: None declared, Silvia Marelli Employee of: Janssen, Ennio Favalli Speakers bureau: BMS, Eli-Lilly, MSD, UCB, Pfizer, Sanofi-Genzyme, Novartis and Abbvie