In the Pursuit of Methotrexate Treatment Response Biomarker in Juvenile Idiopathic Arthritis—Are We Getting Closer to Personalised Medicine?

2017 ◽  
Vol 19 (4) ◽  
Author(s):  
Justyna Roszkiewicz ◽  
Elzbieta Smolewska
Author(s):  
Adrian Goralczyk ◽  
Jerzy Konstantynowicz ◽  
Pawel Abramowicz ◽  
Elzbieta Dobrenko ◽  
Edyta Babinska-Malec

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 936.2-937
Author(s):  
F. Milatz ◽  
J. Klotsche ◽  
M. Niewerth ◽  
J. Hörstermann ◽  
D. Windschall ◽  
...  

Background:In patients with JIA, growth impairment and variance in body composition are well-known long-term complications that may be associated with prolonged drug therapy (e.g. glucocorticoids) as well as impaired physical and psychosocial well-being. An increased accumulation of body fat represents a significant risk factor for metabolic abnormalities and a modifiable variable for a number of comorbidities. Recently, evidence has emerged in favour of the potential negative influence of overweight on the course of the disease and treatment response [1].Objectives:The study aimed a) to estimate the prevalence of underweight, overweight and obesity in children and adolescents with JIA compared to the general population, and b) to investigate correlates of patients’ weight status.Methods:A cross-sectional analysis of physicians’ recorded body weights and heights of patients with JIA enrolled in the NPRD in the year 2019 was performed. Underweight (BMI <10th), overweight (BMI >90th) and obesity (BMI >97th) were defined according to age- and sex-specific percentiles used in the German reference system. For comparison with data from the general population [2], sex- and age-matched pairs of 3-17-year-old patients and controls were generated. A multinomial logistic regression analysis was performed to examine the association between weight status and patients’ clinical and self-reported outcomes.Results:In total, data from 6.515 children and adolescents with JIA (age 11.2 ± 4.1 years, disease duration 4.9 ± 3.8 years, 67% girls, 40% persistent oligoarthritis) were included. Of these, 3.334 (age 5.9 ± 2.1 years, 52.5% girls) could be considered for matched-pair analysis. Compared with the general population, patients underweight, overweight and obesity rates were 10.6% (vs. 8.1%), 8.8% (vs. 8.5%) and 6.1% (vs. 5.7%), respectively. No significant sex differences were found in either group. Largest difference in prevalence was registered for underweight, specifically in the age group 3-6 years (12.9% patients vs. 5.9% controls). Similar to the general population, higher rates of overweight were observed in adolescent patients than in affected children (19.1% age group 11-13 vs. 8.4% age group 3-6). While the highest underweight prevalence was registered in patients with RF+ polyarthritis (16%), patients with Enthesitis-related arthritis (22%), psoriatic arthritis (21%) and systemic JIA (20%) showed the highest overweight rates (including obesity). Younger age (OR = 0.51, 95% CI = 0.31-0.83), more frequent physical activity (OR = 0.92, 95% CI = 0.85-0.99) and high parental vocational education (OR = 0.39, 95% CI = 0.18-0.80) were independently associated with a lower likelihood of being overweight/obese.Conclusion:The overall prevalence of underweight, overweight and obesity in children and adolescents with JIA is comparable to that found in the general population. Behavioural health promotion, including regular physical activity, as part of the treatment strategy in JIA should preventively already begin at preschool age and necessarily be made accessible to patients of all educational levels.References:[1]Giani T et al. The influence of overweight and obesity on treatment response in juvenile idiopathic arthritis. Front Pharmacol 2019;10:637.[2]Schienkiewitz A et al. BMI among children and adolescents: prevalences and distribution considering underweight and extreme obesity. Bundesgesundheitsbl 2019;62:1225–1234.Acknowledgements:The National Paediatric Rheumatological Database has been funded by AbbVie, Chugai, Novartis and GSK.Disclosure of Interests:Florian Milatz: None declared, Jens Klotsche: None declared, Martina Niewerth: None declared, Jana Hörstermann: None declared, Daniel Windschall: None declared, Frank Weller-Heinemann Speakers bureau: Pfizer, AbbVie, SOBI, Roche and Novartis., Frank Dressler: None declared, Rainer Berendes: None declared, Johannes-Peter Haas: None declared, Gerd Horneff: None declared, Kirsten Minden Speakers bureau: Pfizer, AbbVie, Consultant of: Novartis


2018 ◽  
Vol 45 (4) ◽  
pp. 547-554 ◽  
Author(s):  
Faekah Gohar ◽  
Janneke Anink ◽  
Halima Moncrieffe ◽  
Lisette W.A. Van Suijlekom-Smit ◽  
Femke H.M. Prince ◽  
...  

Objective.Around one-third of patients with juvenile idiopathic arthritis (JIA) fail to respond to first-line methotrexate (MTX) or anti-tumor necrosis factor (TNF) therapy, with even fewer achieving ≥ American College of Rheumatology Pediatric 70% criteria for response (ACRpedi70), though individual responses cannot yet be accurately predicted. Because change in serum S100-protein myeloid-related protein complex 8/14 (MRP8/14) is associated with therapeutic response, we tested granulocyte-specific S100-protein S100A12 as a potential biomarker for treatment response.Methods.S100A12 serum concentration was determined by ELISA in patients treated with MTX (n = 75) and anti-TNF (n = 88) at baseline and followup. Treatment response (≥ ACRpedi50 score), achievement of inactive disease, and improvement in Juvenile Arthritis Disease Activity Score (JADAS)-10 score were recorded.Results.Baseline S100A12 concentration was measured in patients treated with anti-TNF [etanercept n = 81, adalimumab n = 7; median 200, interquartile range (IQR) 133–440 ng/ml] and MTX (median 220, IQR 100–440 ng/ml). Of the patients in the anti-TNF therapy group, 74 (84%) were also receiving MTX. Responders to MTX (n = 57/75) and anti-TNF (n = 66/88) therapy had higher baseline S100A12 concentration compared to nonresponders: median 240 (IQR 125–615) ng/ml versus 150 (IQR 87–233) ng/ml, p = 0.021 for MTX, and median 308 (IQR 150–624) ng/ml versus 151 (IQR 83–201) ng/ml, p = 0.002, for anti-TNF therapy. Followup S100A12 could be measured in 44/75 MTX-treated patients (34/44 responders) and 39/88 anti-TNF-treated patients (26/39 responders). Responders had significantly reduced S100A12 concentration (MTX: p = 0.031, anti-TNF: p < 0.001) at followup versus baseline. Baseline serum S100A12 in both univariate and multivariate regression models for anti-TNF therapy and univariate analysis alone for MTX therapy was significantly associated with change in JADAS-10.Conclusion.Responders to MTX or anti-TNF treatment can be identified by higher pretreatment S100A12 serum concentration levels.


Gut ◽  
2020 ◽  
Vol 69 (11) ◽  
pp. 2025-2034 ◽  
Author(s):  
Johann von Felden ◽  
Teresa Garcia-Lezana ◽  
Kornelius Schulze ◽  
Bojan Losic ◽  
Augusto Villanueva

With increasing knowledge on molecular tumour information, precision oncology has revolutionised the medical field over the past years. Liquid biopsy entails the analysis of circulating tumour components, such as circulating tumour DNA, tumour cells or tumour-derived extracellular vesicles, and has thus come as a handy tool for personalised medicine in many cancer entities. Clinical applications under investigation include early cancer detection, prediction of treatment response and molecular monitoring of the disease, for example, to comprehend resistance patterns and clonal tumour evolution. In fact, several tests for blood-based mutation profiling are already commercially available and have entered the clinical field.In the context of hepatocellular carcinoma, where access to tissue specimens remains mostly limited to patients with early stage tumours, liquid biopsy approaches might be particularly helpful. A variety of translational liquid biopsy studies have been carried out to address clinical needs, such as early hepatocellular carcinoma detection and prediction of treatment response. To this regard, methylation profiling of circulating tumour DNA has evolved as a promising surveillance tool for early hepatocellular carcinoma detection in populations at risk, which might soon transform the way surveillance programmes are implemented. This review summarises recent developments in the liquid biopsy oncological space and, in more detail, the potential implications in the clinical management of hepatocellular carcinoma. It further outlines technical peculiarities across liquid biopsy technologies, which might be helpful for interpretation by non-experts.


2016 ◽  
Author(s):  
Raquel Perez-Lopez ◽  
Matthew D. Blackledge ◽  
Helen Mossop ◽  
Joaquin Mateo ◽  
David Collins ◽  
...  

2020 ◽  
Vol 6 (12) ◽  
pp. 133
Author(s):  
Francesco Rundo ◽  
Giuseppe Luigi Banna ◽  
Luca Prezzavento ◽  
Francesca Trenta ◽  
Sabrina Conoci ◽  
...  

Immunotherapy is regarded as one of the most significant breakthroughs in cancer treatment. Unfortunately, only a small percentage of patients respond properly to the treatment. Moreover, to date, there are no efficient bio-markers able to early discriminate the patients eligible for this treatment. In order to help overcome these limitations, an innovative non-invasive deep pipeline, integrating Computed Tomography (CT) imaging, is investigated for the prediction of a response to immunotherapy treatment. We report preliminary results collected as part of a case study in which we validated the implemented method on a clinical dataset of patients affected by Metastatic Urothelial Carcinoma. The proposed pipeline aims to discriminate patients with high chances of response from those with disease progression. Specifically, the authors propose ad-hoc 3D Deep Networks integrating Self-Attention mechanisms in order to estimate the immunotherapy treatment response from CT-scan images and such hemato-chemical data of the patients. The performance evaluation (average accuracy close to 92%) confirms the effectiveness of the proposed approach as an immunotherapy treatment response biomarker.


2011 ◽  
Vol 151 (2) ◽  
pp. 217-222 ◽  
Author(s):  
Viera Kalinina Ayuso ◽  
Evelyne Leonce van de Winkel ◽  
Aniki Rothova ◽  
Joke Helena de Boer

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