Every year, doctors in UK child mental health services prescribe ADHD medication to thousands of children by trial and error, cycling through drugs until they find one that works without causing intolerable side effects. This matters because ADHD affects 5–7% of school-aged children, and untreated cases carry a lifelong societal cost exceeding £1 billion for each annual cohort in the UK. Currently, no evidence-based method exists to match a specific medication to a child’s individual clinical characteristics or personal preferences. The trial-and-error approach wastes time in overstretched clinics, exposes children to unnecessary side effects, and reduces treatment adherence, increasing the risk of poor long-term outcomes. If successful, this project will produce the first interactive decision-aid tool that uses data from over 25,000 patient records and large-scale primary care databases to predict which ADHD medication is most likely to work for a given child. A pilot trial in 100 children aged 6–17 will test whether using the tool improves outcomes compared to standard care. The framework could later be adapted to personalise treatment for other child and adolescent mental health conditions, potentially shifting prescribing from guesswork to evidence-based choice.
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Research questions: Can the pharmacological treatment of Attention-Deficit/Hyperactivity Disorder (ADHD) in children and adolescents be personalised according to specific patient's characteristics and preferences? Background: ADHD affects around 5-7% of school-aged children. If untreated, ADHD entails a substantial societal burden, with a lifelong cost estimated at an excess of £1 billion for each one-year cohort of children in the UK. The National Institute for Health and Care Excellence recommends pharmacotherapy as the mainstay intervention for ADHD core symptoms. ADHD medications are the most commonly prescribed drugs in child and adolescent mental health services (CAMHS). Given the lack of evidence on how to choose the most effective and tolerated medication for ADHD at the patient-individual level, currently prescribers use a trial-and-error approach to find the best medication for each patient. This is time consuming and burdensome for already overstretched CAMHS, unnecessarily exposes the patient to possible side effects, and reduces adherence to treatment, thereby increasing the likelihood of negative ADHD-related outcomes. Aims and objectives: To develop and test an evidence-based interactive decision-aid tool to tailor the pharmacological treatment of ADHD according to patients' clinical characteristics and personal preferences. Methods: The project will include five phases: Gathering individual participant data (IPD) from published and unpublished randomised controlled trials (RCTs) of licensed medications for ADHD in children and adolescents Combining IPD from RCTs with data from electronic health records (over 25,000 children and adolescents with ADHD) to generate stratified predictions of treatment outcomes according to specific clinical characteristics of the patients in real-world clinical settings Modelling costs and benefits of the prediction model using discrete event simulation in large-scale primary care databases (over 270,000 children and adolescents with ADHD) Based on the prediction model developed in 2), building an interactive internet-based decision tool to tailor the pharmacological treatment of ADHD based on the patients' clinical characteristics. The tool will also incorporate patients' preference. I will run focus groups with patients, carers and prescribers to optimise the tool Finally, to inform a definitive RCT, conducting a pilot RCT (21 months including recruitment and follow-up) in 100 children with ADHD (aged 6-17) seeking pharmacological treatment. Fifty children will be pharmacologically treated as usual, and for 50 children the type of medication will be selected using the interactive tool. Timelines for delivery: The tool will be ready by year 3 of the Professorship. The cost benefit modelling and the pilot RCT will be completed by year 5. Anticipated impact and dissemination: I will develop the first evidence-based interactive tool to tailor pharmacotherapy in child and adolescent mental health, based on patients' clinical characteristics and personal preferences. I will disseminate study results in high-impact scientific journals, national and international conferences, and webinars for people with lived experience, clinicians, NHS commissioners/managers, and the wider public. The framework developed in the present project will inform stratified/personalised models for the treatment (pharmacological and non-pharmacological) of other child/adolescent mental health conditions. The decision-aid tool will have the potential to be systematically adopted in CAMHS and other clinical settings nationally and internationally.
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