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- Spierings, Julia, et al.
(författare)
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A randomised, open-label trial to assess the optimal treatment strategy in early diffuse cutaneous systemic sclerosis : The UPSIDE study protocol
- 2021
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Ingår i: BMJ Open. - : BMJ. - 2044-6055. ; 11:3
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Systemic sclerosis (SSc) is a chronic, autoimmune connective tissue disease associated with high morbidity and mortality, especially in diffuse cutaneous SSc (dcSSc). Currently, there are several treatments available in early dcSSc that aim to change the disease course, including immunosuppressive agents and autologous haematopoietic stem cell transplantation (HSCT). HSCT has been adopted in international guidelines and is offered in current clinical care. However, optimal timing and patient selection for HSCT are still unclear. In particular, it is unclear whether HSCT should be positioned as upfront therapy or rescue treatment for patients refractory to immunosuppressive therapy. We hypothesise that upfront HSCT is superior and results in lower toxicity and lower long-term medical costs. Therefore, we propose this randomised trial aiming to determine the optimal treatment strategy for early dcSSc by comparing two strategies used in standard care: (1) upfront autologous HSCT versus (2) immunosuppressive therapy (intravenous cyclophosphamide pulse therapy followed by mycophenolate mofetil) with rescue HSCT in case of treatment failure. Methods and analysis The UPSIDE (UPfront autologous hematopoietic Stem cell transplantation vs Immunosuppressive medication in early DiffusE cutaneous systemic sclerosis) study is a multicentre, randomised, open-label, controlled trial. In total, 120 patients with early dcSSc will be randomised. The primary outcome is event-free survival at 2 years after randomisation. Secondary outcomes include serious adverse events, functional status and health-related quality of life. We will also evaluate changes in nailfold capillaroscopy pattern, pulmonary function, cardiac MR and high-resolution CT of the chest. Follow-up visits will be scheduled 3-monthly for 2 years and annually in the following 3 years. Ethics and dissemination The study was approved by the Dutch Central Committee on Research Concerning Human Subjects (NL72607.041.20). The results will be disseminated through patient associations and conventional scientific channels. Trial registration numbers NCT04464434; NL 8720.
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- Jansen, N. W. D., et al.
(författare)
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Digital scoring of haemophilic arthropathy using radiographs is feasible
- 2008
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Ingår i: Haemophilia. - : Wiley. - 1351-8216 .- 1365-2516. ; 14:5, s. 999-1006
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Tidskriftsartikel (refereegranskat)abstract
- Radiographs are important tools to evaluate structural changes in many Joint diseases. In the case of haemophilic arthropathy (HA), the Pettersson score is widely used. The rising of digital radiography enables evaluation of these changes in a more quantitative and detailed manner, potentially improving diagnosis and follow-up. The aim of this study was to evaluate whether digital image analysis ill the case of HA is feasible, using a presently available method for radiographic changes in knee osteoarthritis (OA), knee image digital analysis (KIDA). Sixty-two knee radiographs were scored according to Pettersson and with KIDA, each by two independent observers. Inter-observer variation and correlations between the two scoring methods were determined. The inter-observer variation was smaller for KIDA than for Pettersson and for KIDA not significantly different from evaluation of OA joints. Good correlations were found for the two methods where comparison of parameters was appropriate. Importantly, for each of the parameters within one point in the ordinal Pettersson score, a large window still existed in the continuous KIDA grading. Digital analysis of radiographs to quantify joint damage in HA is feasible. The use of continuous variables, as used in a digital method Such as KIDA has the advantage that it enables objective and much more sensitive detection of small changes than by use of an ordinal analogue method Such as the Pettersson score. Based oil the present results, it would be worthwhile to adapt the KIDA method for the specific characteristics of HA and to extend the method to elbow and ankle radiographs.
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- Angelini, Federico, et al.
(författare)
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Osteoarthritis endotype discovery via clustering of biochemical marker data
- 2022
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Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 81:5, s. 666-675
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Tidskriftsartikel (refereegranskat)abstract
- Objectives Osteoarthritis (OA) patient stratification is an important challenge to design tailored treatments and drive drug development. Biochemical markers reflecting joint tissue turnover were measured in the IMI-APPROACH cohort at baseline and analysed using a machine learning approach in order to study OA-dominant phenotypes driven by the endotype-related clusters and discover the driving features and their disease-context meaning. Method Data quality assessment was performed to design appropriate data preprocessing techniques. The k-means clustering algorithm was used to find dominant subgroups of patients based on the biochemical markers data. Classification models were trained to predict cluster membership, and Explainable AI techniques were used to interpret these to reveal the driving factors behind each cluster and identify phenotypes. Statistical analysis was performed to compare differences between clusters with respect to other markers in the IMI-APPROACH cohort and the longitudinal disease progression. Results Three dominant endotypes were found, associated with three phenotypes: C1) low tissue turnover (low repair and articular cartilage/subchondral bone turnover), C2) structural damage (high bone formation/resorption, cartilage degradation) and C3) systemic inflammation (joint tissue degradation, inflammation, cartilage degradation). The method achieved consistent results in the FNIH/OAI cohort. C1 had the highest proportion of non-progressors. C2 was mostly linked to longitudinal structural progression, and C3 was linked to sustained or progressive pain. Conclusions This work supports the existence of differential phenotypes in OA. The biomarker approach could potentially drive stratification for OA clinical trials and contribute to precision medicine strategies for OA progression in the future. Trial registration number NCT03883568.
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