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Studies of rare side effects of new drugs with limited exposure may require pooling of multiple data sources to achieve sufficient precision. In a review of all post-authorisation safety studies assessed by the EMA during 2019, 74% (20/27 comparative studies) reported issues with lack of precision in spite of mean study periods of 9.3 years. Federated Analyses (FA) allow real-time, interactive, centralized statistical processing of individual-level data from different data sets without transfer of sensitive personal data. Depending on the statistical model, the federated approach can generate identical results to a standard analysis. FA may be particularly attractive for repeated collaborative projects where data is regularly updated. We review IT-architecture, legal considerations, and statistical methods in FA, discussed in four reports from a Swedish Medical Products Agency project. While FA may facilitate studies using multiple data sources, there are important limitations. Detailed agreements between involved parties are strongly recommended to anticipate potential issues and conflicts, document a shared understanding of the project, and fully comply with legal obligations regarding ethics and data protection. FA do not remove the data harmonisation step, which remains essential and often cumbersome. Reliable support for technical integration with the local server architecture and security solutions is required. Common statistical methods are available, but adaptations may be required. In conclusion, Federated Analyses require competent and active involvement of all collaborating parties but have the potential to facilitate collaboration across institutional and national borders and improve the precision of postmarketing drug safety studies. This article is protected by copyright. All rights reserved.

ObjectiveObservational studies have reported an increased risk of infections associated with glucocorticoids in RA, not supported by evidence from randomized controlled trials. Inappropriately accommodating time-varying exposure and confounding in observational studies might explain the conflicting results. Therefore, we compared the incidence of serious infections between different oral glucocorticoid dose patterns over three years in a prospective inception cohort, adjusting for time-varying confounders in marginal structural models.MethodsWe included 9654 newly diagnosed RA patients from the Swedish Rheumatology Quality Register between 2007–2018 and followed them for three years after the first rheumatology visit. Follow-up was divided into 90-day periods. A mean oral prednisone daily dose was calculated for each period and categorized into ‘no use’, ‘low’ (≤10 mg/day) and ‘high’ (>10 mg/day) doses. The incidence of serious infections (hospitalization for infection) over follow-up periods was modelled by pooled logistic regression allowing separate effects for recent and past exposure.ResultsAn increased incidence of serious infections was associated with higher compared with lower doses and with more recent compared with past glucocorticoid exposure. Over 3 years of follow-up, the marginal structural models predicted one additional serious infection for every 83 individuals treated with low GC doses for the first 6 months, and for every 125 individuals treated with high GC doses for the first 3 months, compared with no GC use.ConclusionOur results broadly agree with previous observational studies showing a dose dependent increased risk of infection associated with (recent) use of oral glucocorticoids.

ObjectivesTo estimate absolute and relative risks for seasonal influenza outcomes in patients with inflammatory joint diseases (IJDs) and disease-modifying antirheumatic drugs (DMARDs). To contextualise recent findings on corresponding COVID-19 risks.MethodsUsing Swedish nationwide registers for this cohort study, we followed 116 989 patients with IJD and matched population comparators across four influenza seasons (2015–2019). We quantified absolute risks of hospitalisation and death due to influenza, and compared IJD to comparators via Cox regression. We identified 71 556 patients with IJD on active treatment with conventional synthetic DMARDs and biological disease-modifying antirheumatic drugs (bDMARDs)/targeted synthetic disease-modifying antirheumatic drug (tsDMARDs) at the start of each influenza season, estimated risks for the same outcomes and compared these risks across DMARDs via Cox regression.ResultsPer season, average risks for hospitalisation listing influenza were 0.25% in IJD and 0.1% in the general population, corresponding to a crude HR of 2.38 (95% CI 2.21 to 2.56) that decreased to 1.44 (95% CI 1.33 to 1.56) following adjustments for comorbidities. For death listing influenza, the corresponding numbers were 0.015% and 0.006% (HR=2.63, 95% CI 1.93 to 3.58, and HR=1.46, 95% CI 1.07 to 2.01). Absolute risks for influenza outcomes were half (hospitalisation) and one-tenth (death) of those for COVID-19, but relative estimates comparing IJD to the general population were similar.ConclusionsIn absolute terms, COVID-19 in IJD outnumbers that of average seasonal influenza, but IJD entails a 50%–100% increase in risk for hospitalisation and death for both types of infections, which is largely dependent on associated comorbidities. Overall, bDMARDs/tsDMARDs do not seem to confer additional risk for hospitalisation or death related to seasonal influenza.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/., Background: Comedication with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) during treatment with tumour necrosis factor inhibitors (TNFi) is extensively used in psoriatic arthritis (PsA), although the additive benefit remains unclear. We aimed to compare treatment outcomes in patients with PsA treated with TNFi and csDMARD comedication versus TNFi monotherapy. Methods: Patients with PsA from 13 European countries who initiated a first TNFi in 2006-2017 were included. Country-specific comparisons of 1 year TNFi retention were performed by csDMARD comedication status, together with HRs for TNFi discontinuation (comedication vs monotherapy), adjusted for age, sex, calendar year, disease duration and Disease Activity Score with 28 joints (DAS28). Adjusted ORs of clinical remission (based on DAS28) at 12 months were calculated. Between-country heterogeneity was assessed using random-effect meta-analyses, combined results were presented when heterogeneity was not significant. Secondary analyses stratified according to TNFi subtype (adalimumab/infliximab/etanercept) and restricted to methotrexate as comedication were performed. Results: In total, 15 332 patients were included (62% comedication, 38% monotherapy). TNFi retention varied across countries, with significant heterogeneity precluding a combined estimate. Comedication was associated with better remission rates, pooled OR 1.25 (1.12-1.41). Methotrexate comedication was associated with improved remission for adalimumab (OR 1.45 (1.23-1.72)) and infliximab (OR 1.55 (1.21-1.98)) and improved retention for infliximab. No effect of comedication was demonstrated for etanercept. Conclusion: This large observational study suggests that, as used in clinical practice, csDMARD and TNFi comedication are associated with improved remission rates, and specifically, comedication with methotrexate increases remission rates for both adalimumab and infliximab.

Objectives Many axial spondylarthritis (axSpA) patients receive a conventional synthetic DMARD (csDMARD) in combination with a TNF inhibitor (TNFi). However, the value of this co-therapy remains unclear. The objectives were to describe the characteristics of axSpA patients initiating a first TNFi as monotherapy compared with co-therapy with csDMARD, to compare one-year TNFi retention and remission rates, and to explore the impact of peripheral arthritis. Methods Data was collected from 13 European registries. One-year outcomes included TNFi retention and hazard ratios (HR) for discontinuation with 95% CIs. Logistic regression was performed with adjusted odds ratios (OR) of achieving remission (Ankylosing Spondylitis Disease Activity Score (ASDAS)-CRP Results Amongst 24 171 axSpA patients, 32% received csDMARD co-therapy (range across countries: 13.5% to 71.2%). The co-therapy group had more baseline peripheral arthritis and higher CRP than the monotherapy group. One-year TNFi-retention rates (95% CI): 79% (78, 79%) for TNFi monotherapy vs 82% (81, 83%) with co-therapy (P Conclusion This large European study of axial SpA patients showed similar one-year treatment outcomes for TNFi monotherapy and csDMARD co-therapy, although considerable heterogeneity across countries limited the identification of certain subgroups (e.g. peripheral arthritis) that may benefit from co-therapy.

First of all, we would like to thank Dr Kaltsonoudis et al for their interest in our study. Dr Kaltsonoudis et al 1 have raised an interesting suggestion in their correspondence based on their study from 2014.2 They suggest that all patients who are candidates for tumour necrosis factor alpha inhibitor (TNFi) therapy should have a thorough neurological assessment (including brain MRI and neurophysiological tests) before commencing TNFi treatment. Moreover, they believe that the risk of neuroinflammatory events following treatment with TNFis is not disease-dependent, but agent-dependent, and that part of the observed risks following treatment …

Objectives To investigate whether patient-reported outcomes vary across countries and are influenced by cultural/contextual factors. Specifically, we aimed to assess inter-country differences in tender joint count (TJC), pain and patient’s global health assessment (PGA), and their impact on disease activity (DAS28-CRP) in RA patients from five Nordic countries. Methods We collected data (baseline, 3- and 12-months) from rheumatology registers in the five countries comprising RA patients starting a first ever MTX or a first ever TNF inhibitor (TNFi). In order to assess the role of context (=country), we separately modelled TJC, pain and PGA as functions of objective variables (CRP, swollen joint count, age, sex, calendar period and disease duration) with linear models. Analyses were performed at each time point and for both treatments. We further assessed the impact of inter-country differences on DAS28-CRP. Results A total of 27 645 RA patients started MTX and 19 733 started a TNFi. Crude inter-country differences at MTX start amounted to up to 4 points (28 points scale) for TJC, 10 and 27 points (0–100 scale) for pain and PGA, respectively. Corresponding numbers at TNFi start were 3 (TJC), 27 (pain) and 24 (PGA) points. All differences were reduced at 3- and 12-months, and attenuated when adjusting for the objective variables. The variation in predicted DAS28-CRP across countries amounted to Conclusions Inter-country differences in TJC, pain and PGA are greater than expected based on differences in objective measures, but have a small clinical impact on DAS28-CRP across countries.

ObjectivesTo investigate whether tumour necrosis factor alpha inhibitors (TNFis) are associated with an increased risk of neuroinflammatory diseases among patients with arthritic diseases.MethodsCohorts of patients with rheumatoid arthritis (RA, n=25 796), psoriatic arthritis (PsA, n=8586) and ankylosing spondylitis (AS, n=9527) who initiated a TNFi treatment year 2000–2017 were identified from nationwide clinical rheumatology registers in Sweden and Denmark. Information on demyelinating disease and inflammatory neuropathy diagnoses was retrieved from prospective linkage to National Patients Register. A Cox proportional hazard model was used to estimate HRs and 95% CI comparing TNFi exposed and non-exposed, by disease and country.ResultsAmong 111 455 patients with RA, we identified 270 (Sweden) and 51 (Denmark) events (all types of neuroinflammatory diseases combined), corresponding to crude incidence rates (per 1000 person-years) of 0.37 (Sweden) and 0.39 (Denmark) in TNFi-treated patients vs 0.39 (Sweden) and 0.28 (Denmark) in unexposed patients, and an age-sex-calendar-period-adjusted HR (95% CI) of 0.97 (0.72 to 1.33) (Sweden) and 1.45 (0.74 to 2.81) (Denmark) in TNFi exposed compared with non-exposed patients. For a total of 64 065 AS/PsA patients, the corresponding numbers were: 196 and 32 events, crude incidence rates of 0.59 and 0.87 in TNFi-treated patients vs 0.40 and 0.19 in unexposed patients, and HRs of 1.50 (1.07 to 2.11) and 3.41 (1.30 to 8.96), for Sweden and Denmark, respectively. For multiple sclerosis, the patterns of HRs were similar.ConclusionsUse of TNFi in AS/PsA, but not in RA, was associated with increased risk of incident neuroinflammatory disease, though the absolute risk was below one in 1000 patients/year.

Objectives To compare treatment retention between biosimilars and their originator products among first starters (etanercept, infliximab, adalimumab and rituximab), as well as after non-medical switch. Methods Patients with rheumatic diseases starting, for the first time, an originator or biosimilar etanercept, infliximab, adalimumab or rituximab were identified in the national Swedish Rheumatology Quality Register. Moreover, patients switching from an originator to its biosimilar were identified and individually matched to patients continuing on the originator. One-year treatment retention was calculated and hazard ratios (HR) for discontinuation with 95% CIs were estimated, adjusting for comorbidities and socio-economic factors. Results In total, 21 443 first treatment courses were identified. The proportion of patients still on the drug at 1 year and the HR for discontinuation revealed no differences across adalimumab (Humira, Imraldi, Amgevita and Hyrimoz) nor across rituximab products (Mabthera, Ritemvia/Truxima and Rixathon). The proportions on the drug at 1 year were similar for Benepali (77%) and Enbrel (75%) and the adjusted HR for Benepali compared with Enbrel was 0.91 (95% CI 0.83, 0.99). For infliximab, the proportion still on the drug at 1 year was 67% for Remicade and 66% for Remsima/Inflectra and the HR compared with Remicade was 1.16 (95% CI 1.02, 1.33). Among 2925 patients switching from an originator drug to one of its biosimilars, we noted no statistically significant or clinically relevant differences in drug survival compared with those who remained on originator therapy. Conclusion This large observational study supports the equivalence of biologic DMARD biosimilar products and originators when used in routine rheumatology care.

Objectives To investigate whether TNF inhibitors (TNFi) are associated with increased risk of solid cancer in patients with psoriatic arthritis (PsA). Methods From the Nordic clinical rheumatology registers (CRR) here: SRQ/ARTIS (Sweden), DANBIO (Denmark), NOR-DMARD (Norway), ROB-FIN (Finland) and ICEBIO (Iceland) we identified PsA patients who started a first TNFi 2001–2017 (n = 9655). We identified patients with PsA not treated with biologics from (i) the CRR (n = 14 809) and (ii) the national patient registers (PR, n = 31 350). By linkage to the national cancer registers, we collected information on incident solid cancer overall and for eight cancer types. We used Cox regression to estimate hazard ratio (HR) with 95% CI of cancer (per country and pooled) in TNFi-exposed vs biologics-naïve, adjusting for age, sex, calendar period, comorbidities and disease activity. We also assessed standardized incidence ratios (SIR) in TNFi-exposed PsA vs the general population (GP). Results We identified 296 solid cancers among the TNFi-exposed PsA patients (55 850 person-years); the pooled adjusted HR for solid cancer overall was 1.0 (0.9–1.2) for TNFi-exposed vs biologics-naïve PsA from the CRR, and 0.8 (0.7–1.0) vs biologics-naïve PsA from the PRs. There were no significantly increased risks for any of the cancer types under study. The pooled SIR of solid cancer overall in TNFi treated PsA vs GP was 1.0 (0.9–1.1). Conclusion In this large cohort study from five Nordic countries, we found no increased risk of solid cancer in TNFi-treated PsA patients, neither for solid cancer overall nor for eight common cancer types.

Objectives To estimate absolute and relative risks for all-cause mortality and for severe COVID-19 in inflammatory joint diseases (IJDs) and with antirheumatic therapies. Methods Through Swedish nationwide multiregister linkages, we selected all adult patients with rheumatoid arthritis (RA, n=53 455 in March 2020), other IJDs (here: spondyloarthropathies, psoriatic arthritis and juvenile idiopathic arthritis, n=57 112), their antirheumatic drug use, and individually matched population referents. We compared annual all-cause mortality March-September 2015 through 2020 within and across cohorts, and assessed absolute and relative risks for hospitalisation, admission to intensive care and death due to COVID-19 March-September 2020, using Cox regression. Results During March-September 2020, the absolute all-cause mortality in RA and in other IJDs was higher than 2015-2019, but relative risks versus the general population (around 2 and 1.5) remained similar during 2020 compared with 2015-2019. Among patients with IJD, the risks of hospitalisation (0.5% vs 0.3% in their population referents), admission to intensive care (0.04% vs 0.03%) and death (0.10% vs 0.07%) due to COVID-19 were low. Antirheumatic drugs were not associated with increased risk of serious COVID-19 outcomes, although for certain drugs, precision was limited. Conclusions Risks of severe COVID-19-related outcomes were increased among patients with IJDs, but risk increases were also seen for non-COVID-19 morbidity. Overall absolute and excess risks are low and the level of risk increases are largely proportionate to those in the general population, and explained by comorbidities. With possible exceptions, antirheumatic drugs do not have a major impact on these risks. Funding Agencies|Swedish research CouncilSwedish Research CouncilEuropean Commission; Swedish Heart-Lung foundationSwedish Heart-Lung Foundation; Swedish Cancer SocietySwedish Cancer Society; NordForsk; Foundation for Research in Rheumatology (FOREUM); Region Stockholm; Karolinska Institutet (ALF)Karolinska Institutet

Objectives Comorbidities contribute to the morbidity and mortality in RA, and are thus important to capture and treat early. In contrast to the well-studied comorbidity risks in established RA, less is known about the comorbidity pattern up until diagnosis of RA. We therefore compared whether the occurrence of defined conditions, and the overall comorbidity burden at RA diagnosis, is different from that in the general population, and if it differs between seropositive and seronegative RA. Methods Using Swedish national clinical and demographic registers, we identified new-onset RA patients (n = 11 086), and matched (1:5) to general population controls (n = 54 813). Comorbidities prior to RA diagnosis were identified in the Patient and Prescribed Drug Registers, and compared using logistic regression. Results At diagnosis of RA, respiratory (odds ratio (OR) = 1.58, 95% CI: 1.44, 1.74), endocrine (OR = 1.39, 95% CI: 1.31, 1.47) and certain neurological diseases (OR = 1.73, 95% CI: 1.59, 1.89) were more common in RA vs controls, with a similar pattern in seropositive and seronegative RA. In contrast, psychiatric disorders (OR = 0.87, 95% CI: 0.82, 0.92) and malignancies (OR = 0.88, 95% CI: 0.79, 0.97) were less commonly diagnosed in RA vs controls. The comorbidity burden was slightly higher in RA patients compared with controls (P Conclusion We found several differences in comorbidity prevalence between patients with new-onset seropositive and seronegative RA compared with matched controls from the general population. These findings are important both for our understanding of the evolvement of comorbidities in established RA and for early detection of these conditions.

Background:Rheumatoid Arthritis (RA) is associated with increased cardiovascular co-morbidity including acute coronary syndrome (ACS), partly due to effects of systemic inflammation. Disease-modifying anti-rheumatic drugs (DMARDs) may reduce RA disease activity, but act through several pathways and may themselves have an impact on cardiovascular risks. Whether the risks of ACS associated with biologic (b) and targeted synthetic (ts) DMARDs differ is still unknown.Objectives:To assess and compare incidences of ACS during treatment of RA with etanercept (ETA), adalimumab (ADA), infliximab (INF), certolizumab pegol (CTZ), golimumab (GOL), rituximab (RIT), abatacept (ABA), tocilizumab (TCZ), baricitinib (BAR) or tofacitinib (TOF).Methods:We defined and pooled treatment cohorts of patients starting any of the above treatments between 2008 and 2017 from clinical rheumatology registers in Denmark (DK), Finland (FI), Norway (NO), and Sweden (SE). One patient could contribute several treatment episodes. Age, sex, co-medication (methotrexate, prednisolone), number of previous b/tsDMARDs, CRP, comorbidities (cardiovascular (including ACS (defined as ICD-10: I20.0, I21.0-4, I21.9) and cerebrovascular disease, thromboembolic events, diabetes, hospitalized infection, cancer, kidney failure, COPD) and associated drugs were extracted and used as adjustment in Cox regression analyses comparing the incidence of ACS between treatments. We used several follow-up lengths (1, 2, and up to 5 years) and two different risk windows (ACS on drug [ending follow-up on treatment discontinuation] and ACS ever since treatment start [disregarding any treatment discontinuation]). We also stratified by age and number of previous b/tsDMARDs.Results:We included 40850 treatment courses in 24083 patients (DK 7271, FI 3732, NO 1540, and SE 11540; around 75% women). ETA was the most common treatment (27%) whereas BAR and TOF comprised We found 780 incident ACS events during 141 326 person-years (pyrs) in the 5-year follow-up time and “ACS ever since treatment start” risk window, resulting in a crude incidence rate of 5.5 events per 1000 pyrs. No event was recorded for BAR nor TOF, which also had the shortest follow-up. Adjusted hazard ratios (HR) increased slightly with longer follow-up times, but the two risk windows provided similar HRs. For the 5-year follow-up, RIT was associated with an increased risk of ACS compared to ETA (Table), while no association was observed for shorter follow-up times. Stratifying on age did not modify the associations. Separate analyses by number of previous b/tsDMARDs suggested that ABA (HR=1.8, 95% CI 1.0-3.3), INF (HR=2.2, 95% CI 1.0-4.6) and RIT (HR=1.9, 95% CI 1.1-3.4) were associated with increased risks of ACS compared to ETA in the subgroup of patients with two or more previous bDMARDs (Figure), whereas no differences were found among patients starting either drug as 1st/2nd bDMARD.Table 1.Comparisons of risks for ACS during a 5-year follow-up since start of bDMARD treatment.DrugN eventspyrsCrude incidence rate/ 1000 pyrsHR (95% CI)1ETA175359174.9ref.ADA115240934.81.0 (0.8-1.3)CTZ54141583.80.9 (0.6-1.2)GOL4090064.41.1 (0.8-1.5)INF106178036.01.2 (0.9-1.5)ABA70107956.51.1 (0.8-1.4)RIT158166229.51.3 (1.0-1.6)TCZ62128664.80.9 (0.5-1.2)BAR036TOF030Pyrs: person-years; HR: hazards ratio1 adjustment: see text.Conclusion:In this cohort including ≥ 24,000 patients followed for up to 5 years, the ACS incidence rate was 5.5/1000 pyrs, with RIT showing an increased risk compared to ETA. In clinical practice, the choice of bDMARD does not seem to influence ACS risk in the short term. In the longer term, differences in ACS risk between bDMARDs may reflect channeling to these, or truly differential effects in subpopulations of patients.Acknowledgements:Partly funded by Nordforsk and ForeumDisclosure of Interests:Bénédicte Delcoigne: None declared, Lotta Ljung: None declared, Sella Aa. Provan Speakers bureau: Novartis, Consultant of: Novartis, Grant/research support from: Boehringer- Ingelheim, Bente Glintborg Grant/research support from: Pfizer, BMS, AbbVie, Kathrine Lederballe Gron Grant/research support from: BMS, Merete L. Hetland Consultant of: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis, Grant/research support from: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis, Niels Steen Krogh: None declared, Nina Trokovic: None declared, Heikki Relas Speakers bureau: Abbvie, Celgene, Pfizer, Grant/research support from: Abbvie, Celgene, Pfizer, Carl Turesson Speakers bureau: Abbvie, Bristol-Myers Squibb, Medac, Pfizer, Roche, Consultant of: Roche, Brigitte Michelsen Consultant of: Novartis (paid to employer), Grant/research support from: Novartis (paid to employer), Johan Askling Consultant of: Abbvie, Astra-Zeneca, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB. These entities have entered into agreements with Karolinska Institutet with JA as principal investigator, mainly in the context of safety monitoring of biologics via the ARTIS national safety monitoring system.

Background:Studies from COVID-19 case-repositories among patients with rheumatic diseases have assessed associations (relative risks) between characteristics of the disease and adverse COVID-19 outcomes. Such designs are susceptible to bias from selection of cases reported. Few studies have assessed absolute and relative risks for COVID-19 outcomes in population-based cohorts of patients with inflammatory joint diseases, nor compared these risks to those in the general population.Objectives:To estimate all-cause mortality, absolute and relative risks for severe COVID-19 in patients with chronic inflammatory joint diseases, compared over time and to the general population.Methods:We updated a multi-register nationwide linkage (“ARTIS”) on adults with RA, PsA, AS, SpA or JIA and population referents (matched on sex, age, and region), with data on hospitalizations, admission to intensive care (ICU), and deaths due to COVID-19. We calculated all-cause mortality March-September 2015-2020, and absolute and relative risks for COVID-19 outcomes March-September 2020. Patients were compared to population referents using hazard ratios (HR) from Cox models adjusted for comorbidities and socio-economy.Results:We identified 110567 individuals with inflammatory joint disease (53455 with RA) in Sweden on March 1st 2020, and 484277 matched general population subjects. In all cohorts, the absolute risk of death from any cause in 2020 was higher than 2015-2019 (Figure 1), with a peak in mid-April, but the relative risks of death (vs. the general population) 2020 remained similar to HRs for 2015-2019 (HR for 2020 in Table 1).Among all individuals with inflammatory joint disease in 2020, the risk for hospitalization, admission to ICU, and death due to COVID-19 was 0.5%, 0.04% and 0.1%, respectively (Table 1). HRs (vs. the general population) were elevated for almost all outcomes. HRs for COVID-19 related outcomes (Table 1) were higher than for non-COVID-19 outcomes; adjustment for co-morbidities and socio-economy explained much of these increases, somewhat less so for the former.Figure 1.All-cause mortality in Swedish individuals with inflammatory joint disease and general population, March-September 2020 and the average 2015-2019Table 1.Absolute and relative risks for COVID-19 outcomes in Swedish individuals with inflammatory joint disease compared to general population comparators March-September 2020OutcomeEvents(risk, %)Events (risk, %), general populationHR1*HR2**AllHospitalization, all causes8971 (8.1%)24273 (5.0%)1.65(1.61, 1.69)1.18 (1.15, 1.21)Hospitalization, COVID-19581 (0.5%)1443 (0.3%)1.77 (1.61, 1.95)1.32 (1.19, 1.46)ICU, COVID-1945 (0.04%)162 (0.03%)1.22 (0.88, 1.70)1.17 (0.82, 1.66)Death, all causes1310 (1.2%)3036 (0.6%)1.90 (1.78, 2.02)1.13 (1.05, 1.21)Death, COVID-19161 (0.1%)338 (0.07%)2.09 (1.73, 2.52)1.18 (0.97, 1.44)RAHospitalization, all causes5275 (9.9%)13072 (5.9%)1.71 (1.66, 1.77)1.21 (1.17, 1.25)Hospitalization, COVID-19379 (0.7%)784 (0.4%)2.02 (1.78, 2.28)1.40 (1.23, 1.60)ICU, COVID-1931 (0.06%)79 (0.04%)1.63 (1.08, 2.48)1.53 (0.98, 2.40)Death, all causes968 (1.8%)2026 (0.9%)1.99 (1.85, 2.15)1.18 (1.09, 1.28)Death, COVID-19134 (0.3%)245 (0.11%)2.28 (1.85, 2.81)1.27 (1.02, 1.59)PsA AS SpA JIAHospitalization, all causes3696 (6.5%)11201 (4.3%)1.54 (1.48, 1.59)1.16 (1.11, 1.20)Hospitalization, COVID-19202 (0.4%)659 (0.3%)1.41 (1.20, 1.65)1.20 (1.02, 1.41)ICU, COVID-1914 (0.02%)83 (0.03%)0.78 (0.44, 1.37)0.76 (0.43, 1.37)Death, all causes342 (0.6%)1010 (0.4%)1.56 (1.38, 1.76)0.98 (0.86, 1.12)Death, COVID-1927 (0.05%)93 (0.04%)1.34 (0.87, 2.05)0.83 (0.54, 1.28)*HR1 unadjusted, matched (age, sex, and region)**HR2, as HR1 but adjusted for comorbidities and socio-economyConclusion:Risks of severe COVID-19 were increased among patients with inflammatory joint diseases, but similar increases were seen for non-COVID-19 morbidity. Co-morbidities and socio-economy explain much of this increase.Disclosure of Interests:Hannah Bower: None declared, Thomas Frisell: None declared, Daniela Di Giuseppe: None declared, Bénédicte Delcoigne: None declared, Gerd-Marie Alenius: None declared, Eva Baecklund: None declared, Katerina Chatzidionysiou Speakers bureau: Eli Lilly, AbbVie and Pfizer, Consultant of: Eli Lilly, AbbVie and Pfizer, Nils Feltelius Employee of: Nils Feltelius is employed by the Medical Products Agency (MPA), which is a governmental body. The views in this abstract may not represent the views of the MPA, Helena Forsblad-d’Elia: None declared, Alf Kastbom Employee of: Former employee of Sanofi, Lars Klareskog: None declared, Elisabet Lindqvist: None declared, Ulf Lindström: None declared, Carl Turesson Speakers bureau: Roche, AbbVie and Pfizer, Consultant of: Roche, Grant/research support from: Research grant from Bristol-Myers Squibb, Christopher Sjowall: None declared, Johan Askling Grant/research support from: PI for agreements between Karolinska Institutet and Abbvie, BMS, Eli Lilly, Pfizer, Roche, Samsung Bioepis, and Sanofi for safety monitoring of anti-rheumatic therapies (ARTIS).

Publisher's version (útgefin grein), [No abstract available], This study was partly funded by grants from Nord-Forsk and FOREUM.

BACKGROUND It is not uncommon for investigators to conduct further analyses of subgroups, using data collected in a nested case-control design. Since the sampling of the participants is related to the outcome of interest, the data at hand are not a representative sample of the population, and subgroup analyses need to be carefully considered for their validity and interpretation. METHODS We performed simulation studies, generating cohorts within the proportional hazards model framework and with covariate coefficients chosen to mimic realistic data and more extreme situations. From the cohorts we sampled nested case-control data and analysed the effect of a binary exposure on a time-to-event outcome in subgroups defined by a covariate (an independent risk factor, a confounder or an effect modifier) and compared the estimates with the corresponding subcohort estimates. Cohort analyses were performed with Cox regression, and nested case-control samples or restricted subsamples were analysed with both conditional logistic regression and weighted Cox regression. RESULTS For all studied scenarios, the subgroup analyses provided unbiased estimates of the exposure coefficients, with conditional logistic regression being less efficient than the weighted Cox regression. CONCLUSIONS For the study of a subpopulation, analysis of the corresponding subgroup of individuals sampled in a nested case-control design provides an unbiased estimate of the effect of exposure, regardless of whether the variable used to define the subgroup is a confounder, effect modifier or independent risk factor. Weighted Cox regression provides more efficient estimates than conditional logistic regression.

Introduction: Inherited genetic factors contribute significantly to prostate cancer risk and explains 58% of the variability in prostate cancer incidence. It is unclear if the increased genetic risk of prostate cancer, including progression to lethal disease, can be offset by adherence to a healthy lifestyle. Methods: Using a validated polygenic risk score (PRS) for overall prostate cancer, we quantified the genetic risk of prostate cancer in 10,443 men in the Health Professionals Follow-up Study for whom genotype data was available. We applied a validated lifestyle score for lethal prostate cancer (including healthy weight, vigorous physical activity, not smoking, and high consumption of tomatoes, fatty fish, and reduced intake of processed meat) and examined the incidence of overall and lethal (metastatic disease or prostate cancer-specific death) prostate cancer from the date of blood (1993-1999) or cheek collection (2005-2006) through 2014 (2016 for lethal disease). Multivariable Cox proportional hazards models were used to estimate the risk of overall and lethal prostate cancer by joint categories of genetic risk (PRS quartiles) and a time-varying lifestyle score (1-2: least healthy, 3: moderate healthy, and 4-6: most healthy). Both unweighted and inverse probability weighted (IPW) models (to account for possible bias arising from the genotype sampling design) were applied. Lifetime cumulative incidence was estimated using regression standardization. Results: We observed 2,111 prostate cancer and 238 lethal prostate cancer events during a median follow-up of 18 and 22 years, respectively. The PRS enabled risk stratification for both overall and lethal prostate cancer, with men in the highest genetic risk quartile having a 5.4-fold increased risk of overall prostate cancer (HRipw = 5.39, 95% CI = 4.59-6.33) and a 3.5-fold increased risk of lethal prostate cancer (HRipw = 3.53, 95% CI = 2.34-5.32) compared with men in the lowest genetic risk quartile. Among men in the highest genetic risk quartile, adhering to a healthy lifestyle was significantly associated with a decreased risk of lethal prostate cancer (HRipw = 0.54, 95% CI = 0.31-0.94) compared with the least healthy lifestyle. Adhering to healthy lifestyle was not associated with a decreased risk of overall prostate cancer (HRipw = 1.01, 95% CI = 0.84-1.22). In the group of men with highest genetic risk, having a healthy lifestyle at study entry was associated with a lifetime cumulative incidence of lethal prostate cancer of 3%, lower than for men having the least healthy lifestyle (6%) and similar to the population average (3%). Conclusion: In this large prospective cohort of US men, inherited genetic factors increased the risk of both overall and lethal prostate cancer. The associated decreased risk of aggressive disease in those with a favorable lifestyle may suggest that the excess genetic risk of lethal prostate cancer could be offset by adhering to a healthy lifestyle. Citation Format: Anna Plym, Yiwen Zhang, Konrad Stopsack, Bénédicte Delcoigne, Adam S. Kibel, Edward Giovannucci, Kathryn L. Penney, Lorelei A. Mucci. Can the genetic risk of prostate cancer be attenuated by a healthy lifestyle [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 822.

Background:Juvenile idiopathic arthritis (JIA) may have substantial consequences for quality of life, for instance due to chronic pain, restriction of activities, concern about physical appearance, and treatment protocols that may limit interactions with peers. However, it remains unclear whether children and adolescents with JIA sow a higher incidence of psychiatric disorders compared with the general population.Objectives:To examine the incidence of psychiatric disorders during childhood in JIA patients in Sweden relative to general population controls.Methods:We performed a register- and population-based cohort study including new-onset JIA patients aged 0 to 17 years 1st January 2012 through 31st December 2017. Incident JIA patients were followed-up from the date of their 2nd JIA diagnosis. At this date, five sex-age-region matched individuals were sampled from the general population. Nine psychiatric disorders were defined with ICD-10 codes and associated drugs (ATC codes): psychotic disorders (ICD-10: F20-29; ATC: N05A), mood and anxiety disorders (F30-F43; N05B, N06A, R06AD01, R06AD02, N03AX16), sleeping disorders (F51; N05C, N03AE01), eating and personality disorders (F50, F60-61, F69), neuropsychiatric disorders (F70-F79, F84, F90; N06BA, C02AC02), substance misuse (F10-F19; N07B), suicide attempts (X60-X84, Y10-34) and death by suicide or substance abuse, and all these combined. The follow-up stopped at date of first outcome, migration, death, 18th birthday or end of the study period, whichever occurred first. Incidence rates were calculated and compared by Cox regression analyses, adjusted for age, sex, calendar year, patient’s and family’s history of psychiatric disorder, country of birth, parents’ education level, and comorbidities (IBD, obesity and celiac disease). In sensitivity analyses, we (1.) excluded children with a history of a psychiatric diagnosis at start of follow-up, and (2.) defined the psychiatric disorders based on ICD-10 codes only.Results:We identified 2224 JIA patients (64% girls, mean age: 9.8 years) and 10,264 matched controls. In the JIA cohort, 309 patients developed a psychiatric disorder (all outcomes combined) during 4998 person-years (pyrs), which corresponded to a crude incidence rate (IR) of 6.2 per 100 pyrs (95% confidence interval (CI): 5.5-6.9). The corresponding crude IR for the general population matched controls was 3.6 (3.4-3.9). Comparing these incidence rates resulted in a sex-age adjusted hazard ratio (HR) of 1.66 (95% CI: 1.46-1.89) and a fully adjusted HR of 1.68 (1.47-1.91). Considering specific outcomes, the IRs per 100 pyrs in the JIA population ranged from 0.1 (suicide attempt) to 3.7 (mood and anxiety disorders) (Table 1). No death from suicide was recorded. There was an overlap across the seven outcomes: among all individuals diagnosed with at least one of the psychiatric outcomes during follow-up, 58% were diagnosed with one outcome only, 25% with two and 19% with three or more outcome conditions. The Cox analyses of the 7 outcome groups demonstrated four statistically significant increased risks for psychotic, mood and anxiety, sleeping and neuropsychiatric disorders (Figure 1). The three latter outcomes were correlated to each other (with Cramer’s V coefficient between 0.3 and 0.5). The sensitivity analyses did not substantially modify these findings.Conclusion:The burden of psychiatric illness in individuals with JIA is increased compared to the general population.Table 1.Risk of psychiatric disorders in JIA patients and general population controls.DisordersN events JIAN events controlsIR JIA (95% CI)IR controls (95% CI)All combined3099186.2 (5.5-6.9)3.6 (3.4-3.9)Psychotic25440.5 (0.3-0.7)0.2 (0.1-0.2)Mood1945343.7 (3.2-4.3)2.0 (1.9-2.2)Sleeping1483482.8 (2.4-3.3)1.3 (1.2-1.5)Neuropsychiatric1264422.4 (2.0-2.8)1.7 (1.5-1.9)Eating13550.2 (0.1-0.4)0.2 (0.2-0.3)Substance misuse14490.3 (0.2-0.4)0.2 (0.1-0.2)Suicide attempt7550.1 (0.1-0.3)0.2 (0.2-0.3)IR: crude incidence rate per 100 person-years; CI: confidence interval1 adjustment: see text.Figure 1.Disclosure of Interests:Bénédicte Delcoigne: None declared, AnnaCarin Horne Consultant of: SOBI and Novartis, Soley Omarsdottir: None declared, Johan Reutfors: None declared, Johan Askling Consultant of: Abbvie, Astra-Zeneca, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB. These entities have entered into agreements with Karolinska Institutet with JA as principal investigator, mainly in the context of safety monitoring of biologics via the ARTIS national safety monitoring system

Background:Biosimilar products of biological disease-modifying antirheumatic drugs (bDMARDs) entered the Swedish market in 2015, with regulatory approvals based on head to head trials of limited duration. Longer-term comparative drug survival, in clinical practice, remains less well documented.Objectives:To compare survival on drug between biosimilars and their originator products among first starters of etanercept, infliximab, adalimumab and rituximab.Methods:Data from the Swedish Rheumatology Quality register (SRQ) was used to identify and follow patients who started a first ever treatment with etanercept since April 2015 (originator=ETA,biosimilar= SB4), infliximab since March 2014 (originator=IFX,biosimilar= CT-P13), adalimumab since January 2018 (originator=ADA biosimilars=SB5, ABP501), or rituximab since January 2018 (originator=RIT,biosimilar= GP2013), through December 31st, 2019, date of first discontinuation of the drug, or death. Discontinuation was defined as lack of effectiveness or adverse events, while other reasons for interruption of the drug (including non-medical switch) were considered censoring events. Descriptive characteristics were collected from the SRQ and tabulated. Hazard ratios (HR) of discontinuation were estimated using Cox regression, with each drug analyzed separately, adjusted for age,sex,indication,line of treatment,disease duration,year of treatment start,region and concomitant use of csDMARD.Results:9274 patients started etanercept(49% SB4), 3609 started infliximab(64% CT-P13), 3117 started adalimumab(27% SB5, 14% ABP 501), and 763 started rituximab(39% GP2013), Table 1. Patients starting CT-P13 and GP2013 were less likely to be biologics-naïve compared to those starting the originator product. Initiators of SB5,ABP501 and GP2013 were more likely,and those starting CT-P13 were less likely,to be on concomitant csDMARDs compared to those starting the originator products. Patients characteristics of ETA and SB4 were similar.The introduction of a biosimilar was typically followed by a decrease in the uptake of the originator, but for ETA a change in pricing in 2018 later led to a reversal of this pattern (Figure 1).For IFX,ADA,and RIT, survival on drug was similar for the originator and its biosimilar(s). For ETA,risk of discontinuation was somewhat lower for the biosimilar than for the originator(adjusted HR:0.87,95% confidence interval:0.79-0.95), Table 1.Table 1.Hazard ratios of discontinuation and descriptive characteristics of biosimilar vs. originator among first starters of each molecule, until 31st December 2019.EtanerceptInfliximabAdalimumabRituximabOriginatorSB4OriginatorCT-P13OriginatorSB5ABP 501OriginatorGP2013N47214553130823011834852431465298Discontinuation12891236582878399139805726Adjusted hazard ratios*Ref0.87 (0.79-0.95)Ref1.14 (0.99-1.31)Ref1.02 (0.83-1.26)1.16 (0.88-1.52)Ref1.12 (0.68-1.85)Age, mean years (std)51 (16)51 (15)49 (16)49 (16)48 (15)52 (15)51 (15)59 (15)60 (15)Female, %67%65%61%64%62%64%65%75%76%RA, %46%48%39%35%33%42%43%61%76%Bionaïve, %72%72%76%69%45%52%43%53%38%Disease duration, mean years (std)11 (12)11 (11)11 (11)11 (11)12 (13)12 (11)14 (15)14 (19)15 (11)DAS28, mean4.0 (1.3)4.0 (1.4)4.1 (1.4)4.1 (1.4)3.7 (1.4)3.8 (1.3)4.0 (1.3)4.5 (1.4)4.7 (1.4)Concomitant csDMARDs, %45%47%57%48%37%49%42%36%43%Abbreviations: RA=rheumatoid arthritis. csDMARDs=conventional synthetic DMARD, std=standard deviation.Figure 1.Number of starts of biosimilars compared to the originator during the follow-up time, by moleculeConclusion:Despite their identical indications and therapeutic positioning, there are some differences in the baseline characteristics between patients who start ADA, IFX and RIT and their biosimilars. There are no differences in drug survival between originator and biosimilar with the possible exception of etanercept although the observed difference should be interpreted in light of possible unmeasured or residual channeling.Disclosure of Interests:Daniela Di Giuseppe: None declared, Hannah Bower: None declared, Bénédicte Delcoigne: None declared, Thomas Frisell: None declared, Katerina Chatzidionysiou Consultant of: Eli Lilly, AbbVie and Pfizer, Ulf Lindström: None declared, Christopher Sjowall: None declared, Elisabet Lindqvist: None declared, Johan Askling Grant/research support from: Abbvie, Astra-Zeneca, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB

Objective To demonstrate the advantage of using weighted Cox regression to analyze nested case–control data in overcoming limitations encountered with traditional conditional logistic regression. Study Design and Setting We analyzed data from 1,051 women who were sampled in a case–control study of lung cancer nested within a cohort of breast cancer patients. We investigated how lung cancer risk is associated with radiation therapy and modified by smoking, with both conditional logistic regression and weighted Cox regression models. Results In contrast to logistic regression, weighted Cox regression exploited the information regarding radiation dose received by each individual lung. The weighted method also mitigated a problem of overmatching apparent in the data and revealed that the risk of radiotherapy-associated lung cancer was modified by smoking ( P = 0.026) with a hazard ratio of 4.09 (2.31, 7.24) in unexposed smokers and 8.63 (5.04, 14.79) in smokers receiving doses >13 Gy. The cumulative risk of lung cancer increased steadily with increasing radiotherapy dose in smokers, whereas no such effect was found in nonsmokers. Conclusion The weighted Cox regression makes optimal and versatile use of the information in a nested case–control design, allowing dose–response analysis of exposure to paired organs and enabling the estimation of cumulative risk.

Background:Axial spondylarthritis (axSpA) patients treated with a tumour necrosis factor inhibitor (TNFi) may receive a concomitant conventional synthetic disease-modifying anti-rheumatic drug (csDMARD), although the value of combination therapy remains unclear.Objectives:Describe the proportion and phenotype of patients with axSpA initiating their first TNFi as monotherapy compared to TNFi+csDMARD combination therapy, and to compare the 1-year TNFi retention between the two groups.Methods:Data from 13 European registries was collected. Two exposure treatment groups were defined: TNFi monotherapy at baseline (=TNFi start date) and TNFi+csDMARD combination therapy. TNFi retention rates were assessed with Kaplan-Meier curves for each country and combined. Hazard ratios (HR, 95% CI) for discontinuing the TNFi were obtained with Cox models: (i) crude; adjusted for (ii) country, and (iii) country, sex, age, calendar year, disease duration and BASDAI. Participating countries were dichotomized into two strata, depending on their 1-year retention rate being above (stratum A) or below (stratum B) the average retention rate across all countries.Results:22,196 axSpA patients were included with 34% on TNFi+csDMARD combination therapy. Baseline characteristics are presented in table 1. Overall, the crude TNFi retention rate was marginally longer in the combination therapy group (80% (79-81%)) compared to the monotherapy group (78% (77-79%)) and was primarily driven by differences in stratum B (fig. 1). TNFi retention rates varied significantly across countries (range:-11.0% to +11.3%), with a clear distinction between the 2 strata. The HRs for discontinuation over 1-year (reference=TNFi monotherapy) in the 3 models were: (i) 0.88 (0.82-0.93), (ii) 0.87 (0.82-0.92), (iii) 0.88 (0.82-0.93).Table 1Baseline characteristicsAll patients(n=22196)Country stratum ACountry stratum BTNFi mono(n=4940)csDMARD + TNFi(n=2547)TNFi mono(n=9693)csDMARD + TNFi(n=5016)Age (years), mean (SD)42.6 (12.5)43.4 (12.0)42.8 (12.2)41.6 (12.7)43.7 (12.7)Females, %41.137.738.242.044.2Disease duration (yrs), mean (SD)5.7 (8.0)6.2 (7.7)6.7 (7.4)4.9 (8.2)6.1 (8.2)Enthesitis, %50.316.733.957.859.7SJC-28, median (IQR)0 (0-1)0 (0-0)0 (0-2)0 (0-0)0 (0-2)VAS pain (0-100), mean (SD)60.9 (24.5)63.3 (26.5)67.8 (23.3)60.2 (23.4)57.2 (24.3)CRP (mg/L), median (IQR)8 (3-20)7.8 (2-20)18 (6.7-32.6)6.0 (2.7-15)8.0 (3-22)BASDAI (0-10), mean (SD)5.7 (2.1)5.7 (2.2)6.2 (2.1)5.6 (2.0)5.4 (2.2)BASFI (0-10), mean (SD)4.4 (2.5)4.4 (2.6)4.9 (2.5)4.3 (2.4)4.2 (2.9)ASDAS, mean (SD)3.5 (1.1)3.7 (1.0)4.0 (1.0)3.3 (1.0)3.3 (1.1)On Infliximab, %25.721222436Baseline csDMARD use, %-Methotrexate045063-Sulfasalazine068033-Leflunomide0801Conclusion:Considerable differences were observed across countries in the use of combination therapy and TNFi retention in axSpA patients. The overall 1-year TNFi retention was higher with csDMARD co-therapy compared to TNFi monotherapy. TNFi monotherapy had a 12-13% higher risk of treatment discontinuation.Acknowledgments:Novartis Pharma AG and IQVIAMN and BD participated equallyDisclosure of Interests:Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Bénédicte Delcoigne: None declared, Daniela Di Giuseppe: None declared, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis and Pfizer, Karen Fagerli: None declared, Anne Gitte Loft Grant/research support from: Novartis, Consultant of: AbbVie, MSD, Novartis, Pfizer and UCB, Speakers bureau: AbbVie, MSD, Novartis, Pfizer and UCB, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Dan Nordström Consultant of: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Speakers bureau: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Maria Jose Santos Speakers bureau: Novartis and Pfizer, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Heřman Mann: None declared, Nurullah Akkoc: None declared, Catalin Codreanu Consultant of: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Speakers bureau: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Irene van der Horst-Bruinsma Grant/research support from: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Consultant of: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Brigitte Michelsen: None declared, Gary Macfarlane: None declared, Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, Matija Tomsic: None declared, Burkhard Moeller: None declared, Pedro Ávila-Ribeiro Grant/research support from: Novartis, Carlos Sánchez-Piedra: None declared, Heikki Relas Grant/research support from: Abbvie., Consultant of: Abbvie, Celgene, and Pfizer., Speakers bureau: Abbvie, Celgene, and Pfizer., Arni Jon Geirsson: None declared, Lucie Nekvindova: None declared, Gozde Yildirim Cetin Speakers bureau: AbbVie, Novartis, Pfizer, Roche, UCB, MSD, Ruxandra Ionescu Consultant of: Consulting fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Speakers bureau: Consulting and speaker fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Niels Steen Krogh: None declared, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Ulf Lindström: None declared

Using both simulated and real datasets, we compared two approaches for estimating absolute risk from nested case-control (NCC) data and demonstrated the feasibility of using the NCC design for estimating absolute risk. In contrast to previously published results, we successfully demonstrated not only that data from a matched NCC study can be used to unbiasedly estimate absolute risk but also that matched studies give better statistical efficiency and classify subjects into more appropriate risk categories. Our result has implications for studies that aim to develop or validate risk prediction models. In addition to the traditional full cohort study and case-cohort study, researchers designing these studies now have the option of performing a NCC study with huge potential savings in cost and resources. Detailed explanations on how to obtain the absolute risk estimates under the proposed approach are given. Copyright © 2016 John Wiley & Sons, Ltd.

Background Tumour necrosis factor inhibitors (TNFi) effectively reduce inflammation in Psoriatic arthritis (PsA). However, a possible association between treatment with TNFi and an increased cancer risk has previously been suggested. Objectives To investigate the risk of cancer in TNFi treated PsA patients compared with standardized rates from the general population in Denmark, Finland, Iceland and Sweden. Methods TNFi-treated PsA patients were followed from first registration with TNFi-treatment in ARTIS (Sweden), DANBIO (Denmark), ICEBIO (Iceland) or ROB-FIN (Finland) and linked to the national Cancer Registry in each country. Patients with a cancer history prior to start of follow-up were excluded. We investigated the risk of primary cancer among TNFi-treated PsA patients compared with general population cancer rates standardized to age, sex and calendar period within each country. Standardized incidence ratios (SIRs) were estimated for each country and pooled SIRs were subsequently calculated for both any cancer and site-specific cancers of interest. Results A total of 5218, 2039, 270 and 526 patients were registered as ever TNFi-treated in ARTIS, DANBIO, ICEBIO and ROB-FIN, respectively, contributing a total of 44 041 patient years of follow-up across all 4 countries. For all cancers, the SIRs of TNFi-treated patients from ARTIS, DANBIO, ICEBIO and ROB-FIN were 0.94 (0.80 to 1.10), 0.99 (0.77 to 1.26), 1.71 (0.88 to 2.99) and 1.28 (0.82 to 1.90), respectively. The number of observed and expected cancers and the SIRs of any and selected site-specific cancers are listed in table 1. Conclusion Our results suggest that the overall cancer risk for TNFi-treated PsA patients is not increased compared to the general population. Further analysis of the risk of malignant lymphomas will inform on whether the increased risk we observed is attributed to the PsA disease or treatment with TNFi. Acknowledgement This study is funded by FOREUM and NordForsk. Disclosure of Interests Christine Ballegaard Speakers bureau: Janssen Pharmaceuticals., Karin Hellgren: None declared, Rene Cordtz: None declared, Benedicte Delcoigne: None declared, Bjorn Gudbjornsson: None declared, Thorvardur Jon Love Consultant for: Received reimbursment from Celgene for speaking about guidelines for the treatment of psoriatic arthritis, Kalle Aaltonen: None declared, Dan Nordstrom Grant/research support from: MSD, Pfizer, Consultant for: AbbVie, BMS, MSD, Novartis, Roche, Pfizer, UCB, Speakers bureau: Novartis, UCB, Sella Aarrestad Provan Consultant for: Novartis, Speakers bureau: Lilly, Johan Askling Grant/research support from: Karolinska Institutet (JA) has or has had research agreements with the following pharmaceutical companies, mainly in the context of the ATRIS national safety monitoring programme for rheumatology biologicals: Abbvie, BMS, MSD, Eli Lilly, Pfizer, Roche, Samsung Bioepis, and UCB., Consultant for: Karolinska Institutet has received remuneration for JA participating in ad boards arranged by Lilly, Novartis, and Pfizer., Kristian Zobbe: None declared, Lars Erik Kristensen Grant/research support from: UCB, Biogen, Janssen Pharmaceuticals, and Novartis, Consultant for: Consultant for AbbVie, Amgen, Biogen, BMS, Celgene, Eli Lilly, Janssen Pharmaceuticals, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB Pharma., Speakers bureau: Pfizer, AbbVie, Amgen, UCB, BMS, Biogen, MSD, Novartis, Eli Lilly and Company, and Janssen Pharmaceuticals, Lene Dreyer Consultant for: MSD, UCB and Janssen Pharmaceuticals, Speakers bureau: MSD, UCB and Janssen Pharmaceuticals, Speakers bureau: UCB, MSD, Eli Lilly and Janssen Pharmaceuticals.

Background Tumor necrosis factor alpha inhibitors (TNFi) have successfully been used for the treatment of immune-mediated inflammatory disorders including rheumatoid arthritis (RA), psoriatic arthritis (PsA) and ankylosing spondylitis (AS) since 1998. However, several case reports and series have indicated that different neurological disorders including multiple sclerosis (MS), inflammatory neuropathies, demyelinating diseases and optic neuritis may be a serious, although rare, adverse event following TNFi treatment. The relationship is complex, as some studies show that RA is protective of MS and vice versa. Objectives To investigate the association between new-onset neurological events following TNFi treatment in arthritis patients compared to non-TNFi-treated arthritis patients from Denmark and Sweden. Methods 40,927/62,702 patients registered with a diagnosis of either RA, AS or PsA in DANBIO/ARTIS between January 1, 2000 and January 20, 2017 were included. Complete follow-up on mortality, emigration and incident neurological diseases suspected to be associated with use of TNFi until May 10, 2017 were obtained by linkage to the Danish and Swedish National Patient Registry and the Civil Registration Systems. Cox proportional hazard models were used to examine the association between use of TNFi and risk of a neurological event. Results The DANBIO/ARTIS arthritis cohorts contributed 612,347 person-years of observation and 221 patients were diagnosed with demyelinating disease or inflammatory neuropathy during follow-up with 117 cases among TNFi-treated patients and 104 cases among non-TNFi-treated patients. TNFi treatment among RA patients was not associated with an increased risk of a neurological event (DANBIO: HR=1.09, 95% Confidence Interval (CI) 0.60-1.99)/(ARTIS:HR=0.83, 95%CI 0.52-1.35) adjusted for age, gender and year of inclusion. However, TNFi-treated PsA and AS patients had an increased risk of neurological events (DANBIO:HR=2.57, 95%CI 1.17-5.65)/(ARTIS:HR=2.17, 95%CI 0.88-5.35). In TNFi-treated PsA/AS patients, 7 cases of inflammatory polyneuropathies were observed in DANBIO/ARTIS respectively versus 1 and 0 cases among non-TNFi treated. In on-drug models, the HR for neurologic events was 1.17 (ARTIS 95% CI: 0.41-3.35) and 1.66 (DANBIO 95% CI: 0.70-3.92) in PsA/AS. Conclusion The use of TNFi for the treatment of arthritis may be associated with increased risk of demyelinating disease or inflammatory neuropathies among patients with PsA and AS. Since these events are rare, larger multicentre studies are warranted to further characterize the risk. Acknowledgement The study is funded by FOREUM, NordForsk and Independent Research Fund Denmark Disclosure of Interests Tine Iskov Kopp : None declared, Elizabeth Arkema: None declared, Rene Cordtz: None declared, Benedicte Delcoigne: None declared, Johan Askling Grant/research support from: Karolinska Institutet (JA) has or has had research agreements with the following pharmaceutical companies, mainly in the context of the ATRIS national safety monitoring programme for rheumatology biologicals: Abbvie, BMS, MSD, Eli Lilly, Pfizer, Roche, Samsung Bioepis, and UCB., Consultant for: Karolinska Institutet has received remuneration for JA participating in ad boards arranged by Lilly, Novartis, and Pfizer., Lene Dreyer Consultant for: MSD, UCB and Janssen Pharmaceuticals, Speakers bureau: MSD, UCB and Janssen Pharmaceuticals, Speakers bureau: UCB, MSD, Eli Lilly and Janssen Pharmaceuticals.

Background: Several indexes have been constructed for the measurement of disease activity in rheumatoid arthritis (RA) patients, including the Disease Activity Score 28-joint count, which either in ...

Publisher's version (útgefin grein), Objective: To investigate if autoimmune thyroid disease (AITD) impacts rheumatoid arthritis (RA) disease activity or response to methotrexate. Methods A nationwide register-based cohort study of 9 004 patients with new-onset RA from the Swedish Rheumatology Quality Register year 2006-2016, with linkage to other nationwide registers to identify comorbidity with AITD defined as thyroxine prescription before RA diagnosis, excluding non-autoimmune causes. We compared RA disease activity using 28-joint Disease Activity Score (DAS28) and its components, and EULAR response, between patients with and without AITD, using logistic regression. Results At diagnosis, patient reported outcome measures (PROMs; patient global, Health Assessment Questionnaire Disability Index and pain) but not objective disease activity measures (erythrocyte sedimentation rate and swollen joint count) were significantly higher (p, This work was supported by research grants from the Swedish Research Council, the Swedish Cancer Society, the Swedish HeartLung Foundation, Nordforsk, Vinnova and FOREUM. Financial support information: Dr Askling has acted or acts as PI in agreements between Karolinska Institutet and the following entities, mainly related to the safety monitoring of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, Pfizer, Roche, Samsung Bioepis, Sanofi.

Background:Previous studies have suggested similar effectiveness, but longer treatment retention, for tumor necrosis factor inhibitors (TNFi), when used in combination with a conventional synthetic disease modifying anti-rheumatic drug (csDMARD) in psoriatic arthritis (PsA).Objectives:To describe patients with PsA initiating a first TNFi as monotherapy compared to combination therapy, and to explore 1-year treatment retention of TNFi in the two groups.Methods:Patients with PsA starting a first TNFi (2006-2017) were identified in biologics registers of 13 European countries, and data were pooled for analysis. Co-medication with csDMARD was determined at TNFi start.Because of large inter-country variation in TNFi retention, countries were split into two strata, depending on each country’s 1-year retention rate for TNFi being above (stratum A) or below (stratum B) the average 1-year retention rate.TNFi treatment retention was compared through Kaplan-Meier curves; the proportion remaining on the TNFi at one year; and hazard ratios (HR) during the first year: (i) crude; adjusted for (ii) country-strata, and (iii) country-strata, sex, age, calendar year, DAS28 and disease duration. In model (iii) only registers contributing >1000 patients or Results:A total of 14778 patients with PsA starting a first TNFi were included. Baseline disease activity was similar within stratum B, but higher for the combination treatment group in stratum A (table 1).Table 1.Baseline characteristicsCountry strataStratum AStratum BTNFimonotherapyN=2120TNFi/csDMARDcombinationN=2128TNFimonotherapyN=3369TNFi/csDMARDcombinationN=7161Females52%51%53%51%Age, years49.7 (12.2)48.7 (11.8)48.8 (13.0)48.9 (12.2)Disease duration, yrs6.4 (7.0)6.8 (6.8)5.9 (7.5)5.9 (7.1)Tender joints 285.5 (6.3)8.0 (6.3)5.6 (6.0)5.6 (5.7)Swollen joints 282.8 (4.3)5.6 (5.0)3.0 (3.8)3.3 (3.8)VAS pain54 (29)62 (24)59 (23)56 (24)DAPSA-2824.6 (18.6)36.2 (17.6)27.3 (15.6)27.2 (15.2)DAS28 (CRP)3.5 (1.4)4.7 (1.3)4.0 (1.2)4.0 (1.1)Concomitant csDMARDMethotrexate-76%-79%Sulfasalazine-15%-15%Other csDMARD-49%-25%Numbers are means (sd) unless otherwise stated.The Kaplan-Meier curves for the treatment groups were similar within each stratum (fig 1), as were the proportions remaining on TNFi after one year, stratum A: monotherapy 86% (95%CI: 85-88) vs. combination 86% (84-87), stratum B: 71% (69-72) vs. 73% (72-74). The HRs for TNFi discontinuation (ref=TNFi monotherapy) were: (i) 1.06 (0.98-1.13), (ii) 0.94 (0.87-1.01), (iii) 0.89 (0.83-0.96), including 13078 patients (9 countries) for model (iii).Conclusion:In this exploratory study no benefit in TNFi retention was observed for csDMARD combination therapy in crude analyses, while in adjusted analyses an 11% lower risk of TNFi discontinuation was found. These preliminary results offer limited support for use of combination therapy in PsA. Further analyses will explore to what extent the results are affected by inter-country heterogeneity and differences between TNFi.Acknowledgments:UL and DDG contributed equally.Novartis Pharma AG and IQVIA support the EuroSpA collaboration.Disclosure of Interests:Ulf Lindström: None declared, Daniela Di Giuseppe: None declared, Bénédicte Delcoigne: None declared, Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Burkhard Moeller: None declared, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Carlos Sánchez-Piedra: None declared, Kari Eklund Consultant of: Celgene, Lilly, Speakers bureau: Pfizer, Roche, Heikki Relas Grant/research support from: Abbvie., Consultant of: Abbvie, Celgene, and Pfizer., Speakers bureau: Abbvie, Celgene, and Pfizer., Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Thorvardur Love: None declared, Gareth T. Jones Grant/research support from: Pfizer, AbbVie, UCB, Celgene and GSK., Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer., Catalin Codreanu Consultant of: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Speakers bureau: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Ruxandra Ionescu Consultant of: Consulting fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Speakers bureau: Consulting and speaker fees from Abbvie, Eli-Lilly, Novartis, Pfizer, Roche, Sandoz, Lucie Nekvindova: None declared, Jakub Zavada Speakers bureau: Abbvie, UCB, Sanofi, Elli-Lilly, Novartis, Zentiva, Accord, Nuh Atas: None declared, Servet Yolbaş: None declared, Karen Fagerli: None declared, Brigitte Michelsen Grant/research support from: Research support from Novartis, Consultant of: Consulting fees Novartis, Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Matija Tomsic: None declared, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Maria Jose Santos Speakers bureau: Novartis and Pfizer, Pedro Ávila-Ribeiro Grant/research support from: Novartis, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Lennart T.H. Jacobsson Consultant of: AbbVie, Eli Lilly, Janssen, Novartis and Pfizer, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer

Background:Disease activity in rheumatoid arthritis (RA) patients is measured through composite scores which are considered treatment targets and thus facilitate clinical decision making. Scores often combine a mix of objective and subjective measures, and, although the latter (e.g. pain, patient’s global, 28 tender joint count (TJC)) may be impacted by contextual and cultural factors, these clinical metrics are often assumed to be comparable across different settings and reflecting the RA disease.Objectives:To explore whether there are systematic differences in patient-reported measures of RA disease activity (i.e. TJC and a measure of pain on a Visual Analog Scale (VAS)) across countries, at similar time-points in the course of the RA disease, taking objective measures of concomitant disease activity and other factors into account.Methods:RA patients starting a first ever tumor necrosis factor inhibitor (TNFi) 2008 through 2017 were identified in rheumatologic registers in five Nordic countries. Data were pooled for analysis. Clinical metrics were retrieved at three time-points: at TNFi start, and after three and twelve months, irrespective of treatment.Baseline clinical variables distributions were compared between countries. The correlation between pain and patient’s global VAS was calculated with the Pearson correlation coefficient (r). At each time-point the subjective measures (TJC and pain) were compared between countries and analyzed with linear models: (i) crude; (ii) adjusted for age, sex, birth decade, disease duration (DD), year of TNFi treatment start (year), C-reactive protein (CRP) and 28 swollen joint count (SJC)) from the time-point in question.Results:A total of 23 796 RA patients were included (Table 1). At baseline, the significant differences between Nordic countries for TJC and pain (crude model) were slightly modified after adjustment but remained statistically significant (Table 2). Compared to baseline, the inter-countries differences were reduced at 3 and 12 months, but also were statistically significant (Figure 1).Table 1.RA patients starting a first TNFi baseline characteristics, median [Interquartile range].SwedenDenmarkFinlandNorwayIcelandN (% female)†13621 (75)6701 (75)1946 (73)1113 (71)415 (73)CRP (mg/L)‡6 [3-17]9 [3-20]8 [3-20]6 [3-14]8 [3-19]Physician’s global VAS‡30 [14-50]31 [19-47]35 [20-50]32 [23-45]60 [43-70]Patient’s global VAS#‡50 [28-70]67 [46-82]50 [28-70]48 [26-69]71 [53-86]Pain VAS‡50 [26-70]60 [37-76]52 [30-71]42 [23-65]67 [49-79]SJC‡4 [1-8]4 [1-7]4 [1-9]4 [1-7]6 [3-11]TJC‡4 [1-9]6 [3-11]4 [1-10]4 [1-9]7 [4-12]DAS28‡5 [3-5]5 [4-5]4 [3-5]4 [3-5]5 [4-6]#Patient’s global and pain correlation: r=0.85†χ2test; p-value=0.04‡One-way ANOVA; all p-values < 0.001Table 2.Mean crude and adjusted differences in baseline TJC and pain between countries, using the largest (Sweden) as reference.SEDKFINOISCrude modelTJCref1.80.80.5*3.7Painref7.21.4†-4.011.1Adjusted model#TJCref2.30.70.6**2.4Painref7.90.7NS-3.37.2**All p-values NS> 0.10;†< 0.10; * < 0.05; ** < 0.01#adjusted for age, sex, birth decade, year, DD, CRP, SJCConclusion:In this observational study of 23 796 RA patients from 5 Nordic countries starting 1stTNFi, patient-reported variables related to RA disease activity (pain VAS, TJC) varied across countries. These differences were not explained by differences in demographic (age, sex, birth decade, year) or objective RA measures (DD, CRP, SJC). This implies a limit to the direct comparability of results obtained from subjective measures from different countries.Acknowledgments:Partly funded by grants from Nordforsk and ForeumDisclosure of Interests:Bénédicte Delcoigne: None declared, Sella Aarrestad Provan: None declared, Hilde Berner Hammer Consultant of: Has received fees as consultant from Roche, AbbVie and Novartis., Speakers bureau: Has received fees for speaking from AbbVie, BMS, Pfizer, UCB, Roche, MSD and Novartis, Daniela Di Giuseppe: None declared, Thomas Frisell: None declared, Bente Glintborg Grant/research support from: Grants from Pfizer, Biogen and Abbvie, Gerdur Gröndal: None declared, Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, Brigitte Michelsen: None declared, Dan Nordström Consultant of: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Speakers bureau: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Heikki Relas Grant/research support from: Abbvie., Consultant of: Abbvie, Celgene, and Pfizer., Speakers bureau: Abbvie, Celgene, and Pfizer., Niels Steen Krogh: None declared, Johan Askling Grant/research support from: JA acts or has acted as PI for agreements between Karolinska Institutet and the following entities, mainly in the context of the ARTIS national safety monitoring programme of immunomodulators in rheumatology: Abbvie, BMS, Eli Lilly, Merck, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB Pharma

Background The risk of malignancies, in particular malignant lymphomas, in Juvenile Idiopathic Arthritis (JIA) patients is low but has been reported to be elevated compared to the general population. Objectives To assess the risk of cancer in patients with JIA in comparison to non-JIA individuals. Methods Register-based cohort study of patients with a first JIA diagnosis recorded from 1987 to 2015, based on data retrieved from the Swedish Patient Register (with information on hospitalizations (1987 and onwards) and outpatients visits (2001 and onwards)), and the Swedish Cancer Register (compiling data on all invasive cancers in Sweden (since 1958)). JIA patients were matched (on sex and age) to five non-JIA individuals sampled from the Swedish child population. All participants were followed up from six months after date of 2nd visit with a JIA diagnosis (for JIA patients) or the corresponding date (for non-JIA individuals) until the first date of the following events: cancer diagnosis, migration, death, 18 years of age, or 31 December 2015. The occurrence of malignancies was compared through standardised incidence rates (SIR). The same analysis was rerun allowing participants to be followed up through adult ages (age at 31 December 2015). Results 7461 JIA patients and 36 747 non-JIA individuals were identified and followed up, with a median follow up time of 4.7 years. Twelve malignancies (among which 6 lymphomas) were recorded among the JIA patients and 40 (7 lymphomas) among the non-JIA individuals, giving a rate for all cancers of 30/100000 person-years and 20/100000 person-years respectively, and a rate ratio of 1.48 (95% Confidence Interval (CI): 0.78 to 2.82). When defining the outcome as a malignant lymphoma, the rates for JIA and non-JIA were 15 and 3.5/100000 person-years, respectively, and the rate ratio was 4.2 (95% CI: 1.4 to 12.5). Allowing the follow-up to cover ages above 18 did not substantially alter these two rate ratios. When restricting the study period to new-onset JIA diagnosed from July 2005 to December 2015, the rate for all cancers were 19.8/100000 person-years (JIA) and 21.1/100000 person-years (non-JIA), providing a rate ratio of 0.94 (95% CI: 0.27 to 3.22) when the age at the end of follow-up was 18 years. The rate ratio was 1.60 (95% CI: 0.68 to 3.74) when the follow-up covered all ages until end of 2015 (maximum 29 years of age). There were too few outcome cases to further restrict to malignant lymphomas. Conclusions JIA patients are at increased risk to develop malignant lymphoma. The low numbers of cancer cases in JIA patients underscores that the absolute risk is low, but hampered modelling inferences on the association between cancer and DMARDs in this cohort of JIA patients followed from disease onset. Disclosure of Interest B. Delcoigne: None declared, A. Horne: None declared, J. Askling Grant/research support from: Johan Askling has or has had research agreements with Abbvie, BMS, MSD, Pfizer, Roche, Astra-Zeneca, Eli Lilly, Samsung Bioepis, and UCB, mainly in the context of safety monitoring of biologics via ARTIS. Karolinska Institutet has received remuneration for JA participating in advisory boards arranged by Pfizer and Eli Lilly.

The methods developed for secondary analysis of nested case-control data have been illustrated only in simplified settings in a common cohort and have not found their way into biostatistical practice. This paper demonstrates the feasibility of reusing prior nested case-control data in a realistic setting where a new outcome is available in an overlapping cohort where no new controls were gathered and where all data have been anonymised. Using basic information about the background cohort and sampling criteria, the new cases and prior data are “aligned” to identify the common underlying study base. With this study base, a Kaplan–Meier table of the prior outcome extracts the risk sets required to calculate the weights to assign to the controls to remove the sampling bias. A weighted Cox regression, implemented in standard statistical software, provides unbiased hazard ratios. Using the method to compare cases of contralateral breast cancer to available controls from a prior study of metastases, we identified a multifocal tumor as a risk factor that has not been reported previously. We examine the sensitivity of the method to an imperfect weighting scheme and discuss its merits and pitfalls to provide guidance for its use in medical research studies.

Using both simulated and real datasets, we compared two approaches for estimating absolute risk from nested case-control (NCC) data and demonstrated the feasibility of using the NCC design for estimating absolute risk. In contrast to previously published results, we successfully demonstrated not only that data from a matched NCC study can be used to unbiasedly estimate absolute risk but also that matched studies give better statistical efficiency and classify subjects into more appropriate risk categories. Our result has implications for studies that aim to develop or validate risk prediction models. In addition to the traditional full cohort study and case-cohort study, researchers designing these studies now have the option of performing a NCC study with huge potential savings in cost and resources. Detailed explanations on how to obtain the absolute risk estimates under the proposed approach are given. Copyright © 2016 John WileySons, Ltd.