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1.
  • Berner, Logan T., et al. (author)
  • The Arctic plant aboveground biomass synthesis dataset
  • 2024
  • In: Scientific Data. - : Springer Nature. - 2052-4463. ; 11:1
  • Journal article (peer-reviewed)abstract
    • Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m−2) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.
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2.
  • Linde, L., et al. (author)
  • Predictors of DAPSA28 remission in patients with psoriatic arthritis initiating a first TNF inhibitor: results from 13 European registries
  • 2024
  • In: Rheumatology. - 1462-0324. ; 63:3, s. 751-764
  • Journal article (peer-reviewed)abstract
    • Objectives In bio-naive patients with PsA initiating a TNF inhibitor (TNFi), we aimed to identify baseline predictors of Disease Activity index for PsA in 28 joints (DAPSA28) remission (primary objective) and DAPSA28 moderate response at 6 months, as well as drug retention at 12 months across 13 European registries. Methods Baseline demographic and clinical characteristics were retrieved and the three outcomes investigated per registry and in pooled data, using logistic regression analyses on multiply imputed data. In the pooled cohort, selected predictors that were either consistently positive or negative across all three outcomes were defined as common predictors. Results In the pooled cohort (n = 13 369), 6-month proportions of remission, moderate response and 12-month drug retention were 25%, 34% and 63% in patients with available data (n = 6954, n = 5275 and n = 13 369, respectively). Five common baseline predictors of remission, moderate response and 12-month drug retention were identified across all three outcomes. The odds ratios (95% CIs) for DAPSA28 remission were: age, per year: 0.97 (0.96-0.98); disease duration, years (<2 years as reference): 2-3 years: 1.20 (0.89-1.60), 4-9 years: 1.42 (1.09-1.84), & GE;10 years: 1.66 (1.26-2.20); men vs women: 1.85 (1.54-2.23); CRP of >10 vs & LE;10 mg/l: 1.52 (1.22-1.89) and 1 mm increase in patient fatigue score: 0.99 (0.98-0.99). Conclusion Baseline predictors of remission, response and adherence to TNFi therapy were identified, of which five were common for all three outcomes, indicating that the predictors emerging from our pooled cohort may be considered generalizable from country level to disease level.
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3.
  • Maes, S.L., et al. (author)
  • Environmental drivers of increased ecosystem respiration in a warming tundra
  • 2024
  • In: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 629:8010, s. 105-113
  • Journal article (peer-reviewed)abstract
    • Arctic and alpine tundra ecosystems are large reservoirs of organic carbon. Climate warming may stimulate ecosystem respiration and release carbon into the atmosphere. The magnitude and persistency of this stimulation and the environmental mechanisms that drive its variation remain uncertain. This hampers the accuracy of global land carbon–climate feedback projections. Here we synthesize 136 datasets from 56 open-top chamber in situ warming experiments located at 28 arctic and alpine tundra sites which have been running for less than 1 year up to 25 years. We show that a mean rise of 1.4 °C [confidence interval (CI) 0.9–2.0 °C] in air and 0.4 °C [CI 0.2–0.7 °C] in soil temperature results in an increase in growing season ecosystem respiration by 30% [CI 22–38%] (n = 136). Our findings indicate that the stimulation of ecosystem respiration was due to increases in both plant-related and microbial respiration (n = 9) and continued for at least 25 years (n = 136). The magnitude of the warming effects on respiration was driven by variation in warming-induced changes in local soil conditions, that is, changes in total nitrogen concentration and pH and by context-dependent spatial variation in these conditions, in particular total nitrogen concentration and the carbon:nitrogen ratio. Tundra sites with stronger nitrogen limitations and sites in which warming had stimulated plant and microbial nutrient turnover seemed particularly sensitive in their respiration response to warming. The results highlight the importance of local soil conditions and warming-induced changes therein for future climatic impacts on respiration.
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4.
  • Sarneel, Judith M., et al. (author)
  • Reading tea leaves worldwide : decoupled drivers of initial litter decomposition mass-loss rate and stabilization
  • 2024
  • In: Ecology Letters. - : John Wiley & Sons. - 1461-023X .- 1461-0248. ; 27:5
  • Journal article (peer-reviewed)abstract
    • The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to-degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models.
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5.
  • Glintborg, B., et al. (author)
  • Is the risk of infection higher during treatment with secukinumab than with TNF inhibitors? An observational study from the Nordic countries
  • 2023
  • In: Rheumatology. - : Oxford University Press (OUP). - 1462-0324 .- 1462-0332. ; 62:2, s. 647-658
  • Journal article (peer-reviewed)abstract
    • Objectives The positioning of secukinumab in the treatment of axial SpA (axSpA) and PsA is debated, partly due to a limited understanding of the comparative safety of the available treatments. We aimed to assess the risk of the key safety outcome infections during treatment with secukinumab and TNF inhibitors (TNFi). Methods Patients with SpA and PsA starting secukinumab or TNFi year 2015 through 2018 were identified in four Nordic rheumatology registers. The first hospitalized infection during the first year of treatment was identified through linkage to national registers. Incidence rates (IRs) with 95% CIs per 100 patient-years were calculated. Adjusted hazard ratios were estimated through Cox regression, with secukinumab as the reference. Several sensitivity analyses were performed to investigate confounding by indication. Results Among 7708 patients with SpA and 5760 patients with PsA, we identified 16 229 treatment courses of TNFi (53% bionaive) and 1948 with secukinumab (11% bionaive). For secukinumab, the first-year risk of hospitalized infection was 3.5% (IR 5.0; 3.9-6.3), compared with 1.7% (IR 2.3; 1.7-3.0) during 3201 courses with adalimumab, with the IRs for other TNFi lying in between these values. The adjusted HR for adalimumab, compared with secukinumab, was 0.58 (0.39-0.85). In sensitivity analyses, the difference from secukinumab was somewhat attenuated and in some analyses no longer statistically significant. Conclusion When used according to clinical practice in the Nordic countries, the observed first-year absolute risk of hospitalized infection was doubled for secukinumab compared with adalimumab. This excess risk seemed largely explained by confounding by indication.
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6.
  • Glintborg, B., et al. (author)
  • Uptake and effectiveness of newer biologic and targeted synthetic disease-modifying antirheumatic drugs in psoriatic arthritis: results from five Nordic biologics registries
  • 2023
  • In: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 82:6, s. 820-828
  • Journal article (peer-reviewed)abstract
    • BackgroundWe aimed to describe the uptake of newer biologic or targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) in psoriatic arthritis (PsA) in the Nordic countries and to compare their retention and effectiveness. MethodsPatients with PsA starting a b/tsDMARD in 2012-2020 in five Nordic rheumatology registers were included. Uptake and patient characteristics were described, with comorbidities identified from linkages to national patient registries. One-year retention and 6-month effectiveness (proportions achieving low disease activity (LDA) on the Disease Activity Index for PSoriatic Arthritis based on 28-joint evaluation) for the newer b/tsDMARDs (abatacept/apremilast/ixekizumab/secukinumab/tofacitinib/ustekinumab) were compared with adalimumab through adjusted regression models stratified by treatment course (first, second/third, and fourth or more). ResultsIn total, 5659 treatment courses with adalimumab (56% biologic-naive) and 4767 courses with a newer b/tsDMARD (21% biologic-naive) were included. The uptake of newer b/tsDMARDs increased from 2014 and plateaued in 2018. Patient characteristics appeared similar across treatments at treatment start. Adalimumab was more often used as the first course and newer b/tsDMARDs more often in biologic-experienced patients. Used as a second/third b/tsDMARD, the retention rate and the proportion achieving LDA were significantly better for adalimumab (rate 65%, proportion 59%) compared with abatacept (45%, 37%), apremilast (43%, 35%), ixekizumab (LDA only, 40%) and ustekinumab (LDA only, 40%), but not significantly different from other b/tsDMARDs. ConclusionUptake of newer b/tsDMARDs occurred mainly in biologic-experienced patients. Regardless of mode of action, only a minority of patients starting a second or later b/tsDMARD course remained on drug and achieved LDA. Superior outcomes for adalimumab indicate that the positioning of newer b/tsDMARDs in the PsA treatment algorithm remains to be established.
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8.
  • Selvakumar, J., et al. (author)
  • Prevalence and Characteristics Associated With Post-COVID-19 Condition Among Nonhospitalized Adolescents and Young Adults
  • 2023
  • In: JAMA Network Open. - : American Medical Association (AMA). - 2574-3805. ; 6:3
  • Journal article (peer-reviewed)abstract
    • IMPORTANCE The prevalence and baseline risk factors of post-COVID-19 condition (PCC) remain unresolved among the large number of young people who experienced mild COVID-19. OBJECTIVES To determine the point prevalence of PCC 6 months after the acute infection, to determine the risk of development of PCC adjusted for possible confounders, and to explore a broad range of potential risk factors. DESIGN, SETTING, AND PARTICIPANTS This cohort study included nonhospitalized individuals from 2 counties in Norway between ages 12 and 25 years who underwent reverse transcriptionpolymerase chain reaction (RT-PCR) testing. At the early convalescent stage and at 6-month follow-up, participants underwent a clinical examination; pulmonary, cardiac, and cognitive functional testing; immunological and organ injury biomarker analyses; and completion of a questionnaire. Participants were classified according to theWorld Health Organization case definition of PCC at follow-up. Association analyses of 78 potential risk factors were performed. EXPOSURES SARS-CoV-2 infection. MAIN OUTCOMES AND MEASURES The point prevalence of PCC 6 months after RT-PCR testing in the SARS-CoV-2-positive and SARS-CoV-2-negative groups, and the risk difference with corresponding 95% CIs. RESULTS A total of 404 individuals testing positive for SARS-CoV-2 and 105 individuals testing negative were enrolled (194 male [38.1%]; 102 non-European [20.0%] ethnicity). A total of 22 of the SARS-CoV-2-positive and 4 of the SARS-CoV-2-negative individuals were lost to follow-up, and 16 SARS-CoV-2-negative individuals were excluded due to SARS-CoV-2 infection in the observational period. Hence, 382 SARS-CoV-2-positive participants (mean [SD] age, 18.0 [3.7] years; 152 male [39.8%]) and 85 SARS-CoV-2-negative participants (mean [SD] age, 17.7 [3.2] years; 31 male [36.5%]) could be evaluated. The point prevalence of PCC at 6 months was 48.5% in the SARS-CoV-2positive group and 47.1% in the control group (risk difference, 1.5%; 95% CI, -10.2% to 13.1%). SARSCoV-2 positivity was not associated with the development of PCC (relative risk [RR], 1.06; 95% CI, 0.83 to 1.37; final multivariable model utilizing modified Poisson regression). The main risk factor for PCC was symptom severity at baseline (RR, 1.41; 95% CI, 1.27-1.56). Low physical activity (RR, 0.96; 95% CI, 0.92-1.00) and loneliness (RR, 1.01; 95% CI, 1.00-1.02) were also associated, while biological markers were not. Symptom severity correlated with personality traits. CONCLUSIONS AND RELEVANCE The persistent symptoms and disability that characterize PCC are associated with factors other than SARS-CoV-2 infection, including psychosocial factors. This finding raises questions about the utility of theWorld Health Organization case definition and has implications for the planning of health care services as well as for further research on PCC.
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9.
  • Georgiadis, S, et al. (author)
  • CAN SINGLE IMPUTATION TECHNIQUES FOR BASDAI COMPONENTS RELIABLY CALCULATE THE COMPOSITE SCORE IN AXIAL SPONDYLOARTHRITIS PATIENTS?
  • 2022
  • In: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 81, s. 212-213
  • Conference paper (other academic/artistic)abstract
    • In axial spondyloarthritis (axSpA), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) is a key patient-reported outcome. However, one or more of its components may be missing when recorded in clinical practice.ObjectivesTo determine whether an individual patient’s BASDAI at a given timepoint can be reliably calculated with different single imputation techniques and to explore the impact of the number of missing components and/or differences between missingness of individual components.MethodsReal-life data from axSpA patients receiving tumour necrosis factor inhibitors (TNFi) from 13 countries in the European Spondyloarthritis (EuroSpA) Research Collaboration Network were utilized [1]. We studied missingness in BASDAI components based on simulations in a complete dataset, where we applied and expanded the approach of Ramiro et al. [2]. After introducing one or more missing components completely at random, BASDAI was calculated from the available components and with three different single imputation techniques: possible middle value (i.e. 50) of the component and mean and median of the available components. Differences between the observed (original) and calculated scores were assessed and correct classification of patients as having BASDAI<40 mm was additionally evaluated. For the setting with one missing component, differences arising between missing one of components 1-4 versus 5-6 were explored. Finally, the performance of imputations in relation to the values of the original score was investigated.ResultsA total of 19,894 axSpA patients with at least one complete BASDAI registration at any timepoint were included. 59,126 complete BASDAI registrations were utilized for the analyses with a mean BASDAI of 38.5 (standard deviation 25.9). Calculating BASDAI from the available components and imputing with mean or median showed similar levels of agreement (Table 1). When allowing one missing component, >90% had a difference of ≤6.9 mm between the original and calculated scores and >95% were correctly classified as BASDAI<40 (Table 1). However, separate analyses of components 1-4 and 5-6 as a function of the BASDAI score suggested that imputing any one of the first four BASDAI components resulted in a level of agreement <90% for specific BASDAI values while imputing one of the stiffness components 5-6 always reached a level of agreement >90% (Figure 1, upper panels). As expected, it was observed that regardless of the BASDAI component set to missing and the imputation technique used, correct classification of patients as BASDAI<40 was less than 95% for values around the cutoff (Figure 1, lower panels).Table 1.Level of agreement between the original and calculated BASDAI and correct classification for BASDAI<40 mmLevel of agreement with Dif≤6.9 mm* (%)Correct classification for BASDAI<40 mm** (%)1 missing componentAvailable93.996.9Value 5073.996.3Mean94.296.8Median93.196.82 missing componentsAvailable83.794.8Value 5040.792.8Mean83.594.8Median82.894.73 missing componentsAvailable71.992.6Value 5028.187.3Mean72.292.6Median69.792.2* The levels of agreement with a difference (Dif) of ≤6.9 mm between the original and calculated scores were based on the half of the smallest detectable change. Agreement of >90% was considered as acceptable. ** Correct classification of >95% was considered as acceptable.Figure 1.Level of agreement between the original and calculated BASDAI and correct classification for BASDAI<40 mm as a function of the original scoreConclusionBASDAI calculation with available components gave similar results to single imputation of missing components with mean or median. Only when missing one of BASDAI components 5 or 6, single imputation techniques can reliably calculate individual BASDAI scores. However, missing any single component value results in misclassification of patients with original BASDAI scores close to 40.References[1]Ørnbjerg et al. (2019). Ann Rheum Dis, 78(11), 1536-1544.[2]Ramiro et al. (2014). Rheumatology, 53(2), 374-376.AcknowledgementsNovartis Pharma AG and IQVIA for supporting the EuroSpA collaboration.Disclosure of InterestsStylianos Georgiadis Grant/research support from: Novartis, Myriam Riek Grant/research support from: Novartis, Christos Polysopoulos Grant/research support from: Novartis, Almut Scherer Grant/research support from: Novartis, Daniela Di Giuseppe: None declared, Gareth T. Jones Speakers bureau: Janssen, Grant/research support from: AbbVie, Pfizer, UCB, Amgen, GSK, Merete Lund Hetland Grant/research support from: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Medac, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis, Mikkel Østergaard Speakers bureau: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Consultant of: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Grant/research support from: Abbvie, BMS, Merck, Celgene, Novartis, Simon Horskjær Rasmussen Grant/research support from: Novartis, Johan K Wallman Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Novartis, Bente Glintborg Grant/research support from: Pfizer, Abbvie, BMS, Anne Gitte Loft Speakers bureau: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Karel Pavelka Speakers bureau: Pfizer, MSD, BMS, UCB, Amgen, Egis, Roche, AbbVie, Consultant of: Pfizer, MSD, BMS, UCB, Amgen, Egis, Roche, AbbVie, Jakub Zavada Speakers bureau: Abbvie, Elli-Lilly, Sandoz, Novartis, Egis, UCB, Consultant of: Abbvie, Elli-Lilly, Sandoz, Novartis, Egis, UCB, Merih Birlik: None declared, Ayten Yazici Grant/research support from: Roche, Brigitte Michelsen Grant/research support from: Novartis, Eirik kristianslund: None declared, Adrian Ciurea Speakers bureau: AbbVie, Eli Lilly, Merck Sharp & Dohme, Novartis, Pfizer, Consultant of: AbbVie, Eli Lilly, Merck Sharp & Dohme, Novartis, Pfizer, Michael J. Nissen Speakers bureau: AbbVie, Eli Lilly, Janssens, Novartis, Pfizer, Consultant of: AbbVie, Eli Lilly, Janssens, Novartis, Pfizer, Ana Maria Rodrigues Speakers bureau: Abbvie, Amgen, Consultant of: Abbvie, Amgen, Grant/research support from: Novartis, Pfizer, Amgen, Maria Jose Santos Speakers bureau: Abbvie, AstraZeneca, Lilly, Novartis, Pfizer, Gary Macfarlane Grant/research support from: GSK, Anna-Mari Hokkanen Grant/research support from: MSD, Heikki Relas Speakers bureau: Abbvie, Celgene, Pfizer, UCB, Viatris, Consultant of: Abbvie, Celgene, Pfizer, UCB, Viatris, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis, Pfizer, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis, Pfizer, Corina Mogosan: None declared, Ziga Rotar Speakers bureau: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek, Janssen, Consultant of: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek, Janssen, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi, Sandoz-Lek, Consultant of: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi, Sandoz-Lek, Björn Gudbjornsson Speakers bureau: Amgen, Novartis, Consultant of: Amgen, Novartis, Arni Jon Geirsson: None declared, Pasoon Hellamand Grant/research support from: Novartis, Marleen G.H. van de Sande Speakers bureau: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Consultant of: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Grant/research support from: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Isabel Castrejon: None declared, Manuel Pombo-Suarez Consultant of: Abbvie, MSD, Roche, Bruno Frediani: None declared, Florenzo Iannone Speakers bureau: Abbvie, Amgen, AstraZeneca, BMS, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Consultant of: Abbvie, Amgen, AstraZeneca, BMS, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis
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10.
  • Glintborg, B., et al. (author)
  • One-Year Treatment Outcomes of Secukinumab Versus Tumor Necrosis Factor Inhibitors in Spondyloarthritis: Results From Five Nordic Biologic Registries Including More Than 10,000 Treatment Courses
  • 2022
  • In: Arthritis Care & Research. - : Wiley. - 2151-464X .- 2151-4658. ; 74:5, s. 748-758
  • Journal article (peer-reviewed)abstract
    • Objective To describe baseline characteristics and to compare treatment effectiveness of secukinumab versus tumor necrosis factor inhibitors (TNFi) in patients with spondyloarthritis (SpA) using adalimumab as the main comparator. Methods This was an observational, prospective cohort study. Patients with SpA (clinical ankylosing spondylitis, nonradiographic axial SpA, or undifferentiated SpA) starting secukinumab or a TNFi during 2015-2018 were identified from 5 Nordic clinical rheumatology registries. Data on comorbidities and extraarticular manifestations (psoriasis, uveitis, and inflammatory bowel disease) were captured from national registries (data available in 94% of patients) and included in multivariable analyses. We assessed 1-year treatment retention (crude survival curves, adjusted hazard ratios [HRadj] for treatment discontinuation) and 6-month response rates (Ankylosing Spondylitis Disease Activity Score [ASDAS] score <2.1, Bath Ankylosing Spondylitis Disease Activity Index [BASDAI] <40 mm, crude/LUNDEX-adjusted, adjusted logistic regression analyses with odds ratios [ORs]) stratified by line of biologic treatment (first, second, and third plus). Results In total, 10,853 treatment courses (842 secukinumab and 10,011 TNFi, of which 1,977 were adalimumab) were included. The proportions of patients treated with secukinumab during the first, second, and third-plus lines of treatment were 1%, 6%, and 22%, respectively). Extraarticular manifestations varied across treatments, while other baseline characteristics were largely similar. Secukinumab had a 1-year retention comparable to adalimumab as a first or second line of treatment but poorer as a third-plus line of therapy (secukinumab 56% [95% confidence interval (95% CI) 51-61%] versus adalimumab 70% [95% CI 64-75%]; HRadj 1.43 [95% CI 1.12-1.81]). Across treatment lines, secukinumab had poorer estimates for 6-month response rates than adalimumab, statistically significantly only for the third-plus line (adjusted analyses: ASDAS score <2.1 OR 0.56 [95% CI 0.35-0.90]; BASDAI <40 mm OR 0.62 [95% CI 0.41-0.95]). Treatment outcomes varied across the 5 TNFi. Conclusion Secukinumab was mainly used in biologics-experienced patients with SpA. Secukinumab and adalimumab performed similarly in patients who had failed a first biologic, although with increasing prior biologic exposure, adalimumab was superior.
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Michelsen, B (15)
Gudbjornsson, B (14)
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Glintborg, B (10)
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