Das erste Biologikum bei rheumatoider Arthritis: Einflussfaktoren auf die Therapieentscheidung

Pattloch, Dagmar; Richter, Adrian; Manger, Bernhard; Dockhorn, R.; Meier, Lisa; Hp, Tony; Zink, Angela; Strangfeld, Anja

doi:10.1007/s00393-016-0174-3

Cited by 9 publications

(3 citation statements)

References 22 publications

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“…In the rheumatological registers and observational studies, patients are recruited via the treating rheumatologists [2,3,15,20]. A particular strength of the PROCLAIR project was therefore the availability of data on people who are not in rheumatological care, but who are treated exclusively by general practitioners or another specialist.…”

Section: Discussionmentioning

confidence: 99%

Reality of care for musculoskeletal diseases at the population level

et al. 2019

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Section: Discussionmentioning

confidence: 99%

Reality of care for musculoskeletal diseases at the population level

et al. 2019

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“…The patients in the RA cohort of GO-NICE were very similar to patients in the contemporary RABBIT RA registry in Germany (2009–2015) in terms of age (54.9 vs 56.8 years), sex (women 72.8% vs 74.8%), disease duration (10.4 vs 9.1 years) and mean DAS28 score (5.0 in both studies). 19 …”

Section: Discussionmentioning

confidence: 99%

Effectiveness and safety of golimumab in patients with rheumatoid arthritis, psoriatic arthritis and ankylosing spondylitis under real-life clinical conditions: non-interventional GO-NICE study in Germany

et al. 2018

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ObjectiveThe Non Interventional Evaluation with Golumimab (GO-NICE) study aimed to document patient and treatment characteristics as well as clinical effectiveness and safety in adult patients newly treated with the tumour necrosis factor inhibitor golimumab (GLM).DesignProspective non-interventional study with 24-month observation per patient.Setting158 office-based and clinical-based physicians in Germany.InterventionGLM administered in the 50 mg dose subcutaneously in monthly intervals under real-life conditions.ResultsOf the 1613 included patients, 1458 patients were eligible for final analysis: 474 patients with rheumatoid arthritis (RA, 54.9±13.4 years, 72.8% women, 64.7% biologic-naïve), 501 with psoriatic arthritis (PsA, 50.5±12.1 years, 54.1% women, 56.5% biologic-naïve) and 483 with ankylosing spondylitis (AS, 43.6±12.3 years, 66.5% men, 61.0% biologic-naïve). 664 patients completed follow-up (2-year retention rate 45.5%). Disease Activity Score 28-joint count erythrocyte sedimentation rate (DAS28-ESR) decreased from 5.0 to 2.9 after 24 months (p<0.0001) in patients with RA, and Bath Ankylosing Spondylitis Disease Index score decreased from 5.1 to 2.4 (p<0.0001) in patients with AS. Response rate calculated in patients with PsA by modified Psoriatic Arthritis Response Criteria was 67.9% after 24 months. Most adverse events were of mild or moderate nature, and no new safety signals were detected. According to the physicians’ clinical assessments, treatment with GLM was successful (no adverse drug reaction and a clear or moderate therapeutic effect in an individual patient) in 55.0%–56.6% of patients with RA, PsA and AS, respectively, at month 3, increasing from 74.5% to 76.1% at month 24.ConclusionsGLM subcutaneously once monthly led to substantial improvements in clinical effectiveness in patients with various inflammatory rheumatic diseases who could be followed up in a real-life setting in Germany. The treatment was well tolerated, and the safety profile of GLM was consistent with that observed in the previous randomised controlled trials.Trial registration numberNCT01313858.

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“…Most application focus on prediction modelling or variable selection. We want to briefly mention a selection of the most recent ones from the last two years: The different research questions comprise the development of birth weight prediction formulas [91] for particularly small babies, the prediction of smoking cessation and its relapse in HIV-infected patients [92], Escherichia coli Fed-Batch Fermentation Modeling [93], the prediction of cardiovascular death on older patients in the emergency department [94] and the identification of factors influencing therapeutic decisions regarding rheumatoid arthritis [95].…”

Section: New Frontiers and Applicationsmentioning

confidence: 99%

An Update on Statistical Boosting in Biomedicine

Mayr

Hofner

Waldmann

et al. 2017

Computational and Mathematical Methods in Medicine

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Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting). In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.

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Das erste Biologikum bei rheumatoider Arthritis: Einflussfaktoren auf die Therapieentscheidung

Cited by 9 publications

References 22 publications

Reality of care for musculoskeletal diseases at the population level

Reality of care for musculoskeletal diseases at the population level

Effectiveness and safety of golimumab in patients with rheumatoid arthritis, psoriatic arthritis and ankylosing spondylitis under real-life clinical conditions: non-interventional GO-NICE study in Germany

An Update on Statistical Boosting in Biomedicine

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