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24th May 2024
While methotrexate is currently the first-line drug given for juvenile idiopathic arthritis, its effectiveness and tolerability are in fact limited in some patients. With the development of stratified medicine their top priority, Dr Stephanie Shoop-Worrall PhD, Professor Lucy Wedderburn and the CLUSTER consortium set out to discover whether machine learning could transform treatment pathways for children with this debilitating condition.
Children with a diagnosis of juvenile idiopathic arthritis (JIA) often face a long journey to get the right medications, leading to unnecessary pain, uncontrolled symptoms and risking joint damage. Currently, methotrexate is the first-line drug given for JIA, but it is only effective or tolerated in just under half of the children who are treated with it.
In a complex and varied disease like JIA, what does ‘effective’ mean? With signs and symptoms ranging from swollen joints to skin rashes, debilitating pain to symptomless, sight-risking eye inflammation, what does ‘response to treatment’ look like? And how can it mean the same thing for every child?
Researchers have started to look beyond a response versus non-response paradigm and are seeking to understand whether different elements of disease change in different ways following a new treatment, and so require different approaches to disease management. These kinds of investigations are only made possible using new methods of machine learning.
By studying large data sets from thousands of children with JIA, it is hoped that machine learning can facilitate stratified treatment, ultimately reducing pain and suffering in children, aiding clinicians with treatment pathway decisions, and saving money for the NHS and other health systems around the world.
Professor Wedderburn is a professor of paediatric rheumatology based at Great Ormond Street Hospital and University College London (UCL). Mixing clinical and research work, she leads the large UK consortium CLUSTER – a multidisciplinary group of researchers working in JIA who have come together to find ways to improve treatment.
She describes the approach in paediatric rheumatology as ‘holistic’, bringing expertise from psychology, nursing, physiotherapy, occupational therapy and many more specialities.
‘Paediatric rheumatology is an incredibly collaborative field. We do a lot of work with the patients and families. We’re relatively small compared to the adult RA [rheumatoid arthritis] research community, but we’re very linked up, and I think that is a huge benefit,’ Professor Wedderburn says.
However, Professor Wedderburn remains ‘frustrated’ by drug treatments available for children with JIA. Despite the increase in the number of medications available, the drugs are licensed without guidance on when and how to use them in children. What’s more, with a rare and complex disease such as JIA, a child’s predicted response to drugs such as methotrexate varies significantly across different disease features.
As such, the researchers want to move away from a one-size-fits-all system and provide a scientific and biological basis for medication pathways based on the predicted outcomes shown in their data.
Professor Wedderburn says: ‘That’s really what CLUSTER is all about. How can we move to a point where you have true precision medicine or stratified medicine? Many of my patients are in these studies, if they’re willing, and most people want to be involved because we explain it’s the way to get real-world data. This consortium brought together childhood data from huge cohorts – absolutely fabulous for such a rare disease.’
Professor Wedderburn’s colleague and the lead author of their recent publication, Dr Stephanie Shoop-Worrall PhD, is a research fellow at the University of Manchester. She specialises in epidemiology and data science and analyses the CLUSTER data using machine learning.
CLUSTER represents about 5,000 families, which make up approximately half the number of cases of JIA in the UK. Looking at four cohorts of these children who began their treatment before January 2018, Dr Shoop-Worrall and the team were able to find patterns in treatment outcomes which determined how effective methotrexate was on different elements of JIA for groups of children.
‘We’ve got this window of opportunity; we need to treat early on to get better outcomes,’ Dr Shoop-Worrall says. ‘This trial-and-error approach [to medicines] is just wasting people’s time and could lead to much worse outcomes, prolonging chronic pain in children, the potential for disability in the longer term, and massively impacting their lives. So, we really do need to get the right drug first.’
When a child is diagnosed with JIA, they will be diagnosed with one of seven types of the disease. Some diagnoses mirror those seen in adults, while others are unique to children. Describing the current approach as ‘a bit contentious’, Dr Shoop-Worrall has shown through machine learning that the traditional diagnosis groups do not necessarily predict how effective methotrexate will be.
The research team analysed data from when the children started taking methotrexate and followed them over the next year, looking at four outcomes: active joint count, both clinician and patient progress scores, and blood biomarker data. The aim was to capture a spectrum of objective clinical and patient-reported measurements to give an overview of the disease and determine which parts of JIA might be affected by methotrexate.
Dr Shoop-Worrall identified six different groups of children, each describing a different response to methotrexate. The first group, known as the ‘fast responders’, comprised about one in 10 children, all of whose disease responded well to the medication. By six months, this group had no swollen joints, normal bloodwork, and both looked better clinically and felt completely better. The next group, termed ‘slow improvers’, was made up of children who took about a year to achieve the same outcome.
Two more groups showed only partial improvement of JIA with methotrexate. In approximately 8% of children, their joints got better, and the children felt better, but the clinicians reported evidence of JIA, and the children remained on methotrexate. Another 13% of children showed partial improvement and looked better clinically in terms of having no swollen joints and normal blood work, but their symptoms, including pain, persisted.
A small group of about 7% of children, known as the ‘improve-relapse’ group, showed improved symptoms after six months, followed by a relapse. And in the final group of about 44% of children, methotrexate did not impact most of their disease. Small improvements in swollen joints were observed in some cases as the drug is designed to tackle inflammation, but the overall clinical picture did not improve.
Dr Shoop-Worrall says: ‘Once we’d found the clusters, we looked to see if existing subtypes of JIA match up with the patterns. And the answer is no.’
Professor Wedderburn adds: ‘It’s a rather depressing message for families to discover that the name of the condition doesn’t help us know whether they’re going to get better on methotrexate or what the next drug should be. It really isn’t a stratifier. It’s just a label based on what we see in the first few months in the clinic – a nice descriptor.’
Their findings also challenge the traditional binary classification of patients into ‘responders’ and ‘non-responders’ seen in standard clinical trials. For Professor Wedderburn, the groups described by machine learning resonate strongly with what she sees in clinic. She adds: ‘[It’s] really important to get that message across to our community that just dichotomising response doesn’t bring the real lived experience out the way this dissecting of the response can start to do.’
Machine learning has opened the door to the possibility of predicting which aspects of a child’s disease would be helped by methotrexate and which children should start other therapies either alongside, or instead of, methotrexate as first line.
‘We want to get kids into remission quickly; that’s the overall aim of stratified medicine in this disease,’ Dr Shoop-Worrall says. ‘This paper is the first step towards that. If we can figure out who should be on this drug and what kind of response they’ll get, that really pushes forward the aim of stratified treatment.’
The next steps will see the researchers bringing more biological data, such as gene expression and protein data, into their analyses and integrating their findings across different disciplines. They will also investigate the impact of the sociological and psychological elements of the illness, in both cases, working with global cohorts of JIA patients.
Dr Shoop-Worrall concludes: ‘Being able to get a panel of biomarkers or a prediction model that we can integrate into practice to say, right, okay, now we know the different types of response, and this is exactly the group you fit into. That would be a huge step forward for drug selection right from diagnosis.’
The researchers believe machine learning will play an essential role in improving understanding of treatment outcomes, minimising children’s exposure to unnecessary treatments, optimising treatment selection and ultimately improving the quality of care for children with JIA.
22nd July 2021
Systemic juvenile idiopathic arthritis (SJIA) is a rare and serious auto-inflammatory disease characterised by joint pain or stiffness, tiredness and blurry vision and which affects 10 – 20% of children with juvenile arthritis. The cause of the condition remains largely unknown and the treatment of SJIA has historically involved the use of large doses of systemic corticosteroids, delivered as mini-pulses and which serves to achieve disease control. Nevertheless, while effective, long-term use of corticosteroids can cause serious side-effects in children including osteoporosis, slowed growth and a greater risk of infections. Studies have shown that in children with SJIA there are elevated levels of interleukins, in particular, interleukin-1 and interleukin-6. Furthermore, in 2012, two studies emerged supporting the use of the biologics canakinumab, which is an anti-interleukin-1 agent and tocilizumab, an anti-interleukin-6, in the management of SJIA. Management guidelines from the American College of Rheumatology in 2013, advocated the use of biologics as a first-line treatment for SJIA and it has been shown that biologic monotherapy is effective, avoiding the need for corticosteroids. However, what is less clear is whether the early introduction of a biologic will reduce the need for corticosteroids among children hospitalised with systemic juvenile idiopathic arthritis. Using a retrospective analysis, a team from the Children’s Hospital of Philadelphia, Division of Rheumatology, Philadelphia, US, sought to determine whether the early use of a biologic would reduce the need for corticosteroids children with SJIA. The team used electronic patient records to extract demographic and treatment data and set the primary outcome as the initiation of corticosteroids during the initial hospital stay for children with SJIA. Participants were then divided into two groups as either biologic initiators or non-initiators.
Findings
A total of 468 children with SJIA were included, of whom 71 were initiated on a biologic, with a mean age of 7 years (57.7% male). The most common agent was an interleukin-1 inhibitor although one received an anti-interleukin-6 agent (tocilizumab). A lower proportion of those given a biologic subsequently received a corticosteroid (36.8% vs 56.9%, biologic initiators vs non-initiators, p = 0.09). There was a non-significant trend towards a reduced odds of receiving a corticosteroid in the biological initiator arm (odds ratio, OR = 0.39, 95% CI 0.13–1.15).
Commenting on these findings, the authors felt that early use of a biologic appeared to reduce the need for concomitant corticosteroid therapy in children with new onset systemic juvenile idiopathic arthritis. They concluded by calling for future studies to provide an evidence base for the use of corticosteroids in children with this condition, given the problems associated with the long-term use of these drugs.
Citation
Peterson RG et al. Effect of first-line biologic initiation on glucocorticoid exposure in children hospitalized with new-onset systemic juvenile idiopathic arthritis: emulation of a pragmatic trial using observational data. Pediatr Rheumatol Online J 2021
12th November 2019
Research presented at the 2019 ACR/ARP Annual Meeting shows that there is a profound ongoing need for additional medications to control the signs and symptoms of juvenile idiopathic arthritis (JIA), despite the availability of disease-modifying biologic drugs.
There are several biologics used for JIA treatment in the US including etanercept, adalimumab, abatacept, tocilizumab and canakinumab. Nevertheless, many children with JIA continue to have active arthritis despite the available medications and are treated with other medications off-label. Medications that have been proven to be safe and effective in adults with chronic inflammatory arthritis are not being universally studied in children with JIA. This study’s goal was to document the continuing medical need for additional, newly approved medications to treat children with JIA.
“The approved treatment options for JIA have expanded tremendously, but there are still significant proportions of children who do not respond to available therapies or who are receiving medications that have not been approved for JIA. We must demand that newly developed medications are studied for safety and effectiveness in children,” says Timothy Beukelman, MD, MSCE, associate professor, Division of Pediatric Rheumatology, at the University of Alabama at Birmingham, and the study’s co-author.
For the study, the researchers reviewed electronic medical record data for 1599 JIA patients treated at Cincinnati Children’s Hospital Medical Center (CCHMC) since 2008 for medication use and disease activity over time. In addition, they assessed 7379 JIA patients enrolled in the Childhood Arthritis and Rheumatology Research Alliance (CARRA) registry for medication use and disease activity at their most recent registry visit.
The researchers defined ongoing medication need as active JIA despite sequential use of two or more biologics. They defined active JIA as either physician global assessment of JIA activity (on a scale of zero to 10 with zero as inactive disease) of three or higher, or three or more active joints, or a patient global assessment score (on a scale of zero to 10 with zero meaning very well) of three or higher. They only assessed medication failure for patients with complete data.
Use of biologics was common in both data sources (53% in CCHMC; 65% in CARRA registry), and ongoing medication need was assessed in 487 CCHMC patients and 1159 CARRA patients. Approximately 52% of CCHMC patients and 45% of CARRA patients had ongoing active JIA despite treatment with two or more biologics. Among all patients who received any biologic treatments, there was frequent use of medications that are not approved for JIA (37% CCHMC patients and 24% CARRA patients).
The study’s lead author Dr Hermine I. Brunner, chief of rheumatology and director Lupus Center at Cincinnati Children’s Hospital Medical Center, and scientific director of the Pediatric Rheumatology Collaborative Study Group (PRCSG), said: “There is clearly a need to increase the number and types of therapies available for the treatment of children with JIA. Only if FDA demands studies from the pharmaceutical companies as part of their drug development program, will paediatric rheumatologists have valid information about the proper dosing, efficacy and preliminary safety of new medications. Further, FDA approval greatly increases access of JIA patients to new medications.”
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