. 2024 Dec;29(12):3865-3873.

doi: 10.1038/s41380-024-02606-5. Epub 2024 May 23.

Individualized prediction models in ADHD: a systematic review and meta-regression

Gonzalo Salazar de Pablo^{1

2

3}, Raquel Iniesta^{4

5}, Alessio Bellato^{6

7

8}, Arthur Caye^{9

10

11}, Maja Dobrosavljevic¹², Valeria Parlatini^{1

7

8

13}, Miguel Garcia-Argibay^{7

12

14}, Lin Li^{12

14}, Anna Cabras¹⁵, Mian Haider Ali⁴, Lucinda Archer^{16

17}, Alan J Meehan^{18

19}, Halima Suleiman²⁰, Marco Solmi^{7

21

22

23

24

25}, Paolo Fusar-Poli^{26

27

28

29}, Zheng Chang¹⁴, Stephen V Faraone²⁰, Henrik Larsson^{8

12

14}, Samuele Cortese^{30

31

32

33

34}

Affiliations

¹ Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
² Child and Adolescent Mental Health Services, South London and Maudsley NHS Foundation Trust, London, UK.
³ Institute of Psychiatry and Mental Health. Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), CIBERSAM, Madrid, Spain.
⁴ Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK.
⁵ King's Institute for Artificial Intelligence, King's College London, London, UK.
⁶ School of Psychology, University of Nottingham, Nottingham, Malaysia.
⁷ Centre for Innovation in Mental Health-Developmental Lab, School of Psychology, University of Southampton, Southampton, UK.
⁸ School of Psychology, University of Southampton, Southampton, UK.
⁹ Post-Graduate Program of Psychiatry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
¹⁰ National Center for Research and Innovation (CISM), University of São Paulo, São Paulo, Brazil.
¹¹ ADHD Outpatient Program, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.
¹² School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
¹³ Solent NHS Trust, Southampton, UK.
¹⁴ Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
¹⁵ Department of Neurology and Psychiatry, University of Rome La Sapienza, Rome, Italy.
¹⁶ Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
¹⁷ National Institute for Health and Care Research (NIHR), Birmingham Biomedical Research Centre, Birmingham, UK.
¹⁸ Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
¹⁹ Yale Child Study Center, Yale School of Medicine, New Haven, CT, USA.
²⁰ Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, Syracuse, NY, USA.
²¹ Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada.
²² Department of Mental Health, The Ottawa Hospital, Ottawa, ON, Canada.
²³ Hospital Research Institute (OHRI) Clinical Epidemiology Program University of Ottawa, Ontario, ON, Canada.
²⁴ School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
²⁵ Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany.
²⁶ Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
²⁷ Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
²⁸ Outreach and Support in South-London (OASIS) service, South London and Maudsley NHS Foundation Trust, London, UK.
²⁹ Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian-University (LMU), Munich, Germany.
³⁰ Centre for Innovation in Mental Health-Developmental Lab, School of Psychology, University of Southampton, Southampton, UK. samuele.cortese@soton.ac.uk.
³¹ Solent NHS Trust, Southampton, UK. samuele.cortese@soton.ac.uk.
³² Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK. samuele.cortese@soton.ac.uk.
³³ Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York City, NY, USA. samuele.cortese@soton.ac.uk.
³⁴ DiMePRe-J-Department of Precision and Rigenerative Medicine-Jonic Area, University of Bari "Aldo Moro", Bari, Italy. samuele.cortese@soton.ac.uk.

PMID: 38783054
PMCID: PMC11609101
DOI: 10.1038/s41380-024-02606-5

Individualized prediction models in ADHD: a systematic review and meta-regression

Gonzalo Salazar de Pablo et al. Mol Psychiatry. 2024 Dec.

. 2024 Dec;29(12):3865-3873.

doi: 10.1038/s41380-024-02606-5. Epub 2024 May 23.

Authors

Affiliations

¹ Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
² Child and Adolescent Mental Health Services, South London and Maudsley NHS Foundation Trust, London, UK.
³ Institute of Psychiatry and Mental Health. Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), CIBERSAM, Madrid, Spain.
⁴ Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK.
⁵ King's Institute for Artificial Intelligence, King's College London, London, UK.
⁶ School of Psychology, University of Nottingham, Nottingham, Malaysia.
⁷ Centre for Innovation in Mental Health-Developmental Lab, School of Psychology, University of Southampton, Southampton, UK.
⁸ School of Psychology, University of Southampton, Southampton, UK.
⁹ Post-Graduate Program of Psychiatry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
¹⁰ National Center for Research and Innovation (CISM), University of São Paulo, São Paulo, Brazil.
¹¹ ADHD Outpatient Program, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.
¹² School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
¹³ Solent NHS Trust, Southampton, UK.
¹⁴ Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
¹⁵ Department of Neurology and Psychiatry, University of Rome La Sapienza, Rome, Italy.
¹⁶ Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
¹⁷ National Institute for Health and Care Research (NIHR), Birmingham Biomedical Research Centre, Birmingham, UK.
¹⁸ Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
¹⁹ Yale Child Study Center, Yale School of Medicine, New Haven, CT, USA.
²⁰ Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, Syracuse, NY, USA.
²¹ Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada.
²² Department of Mental Health, The Ottawa Hospital, Ottawa, ON, Canada.
²³ Hospital Research Institute (OHRI) Clinical Epidemiology Program University of Ottawa, Ontario, ON, Canada.
²⁴ School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
²⁵ Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany.
²⁶ Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
²⁷ Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
²⁸ Outreach and Support in South-London (OASIS) service, South London and Maudsley NHS Foundation Trust, London, UK.
²⁹ Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian-University (LMU), Munich, Germany.
³⁰ Centre for Innovation in Mental Health-Developmental Lab, School of Psychology, University of Southampton, Southampton, UK. samuele.cortese@soton.ac.uk.
³¹ Solent NHS Trust, Southampton, UK. samuele.cortese@soton.ac.uk.
³² Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK. samuele.cortese@soton.ac.uk.
³³ Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York City, NY, USA. samuele.cortese@soton.ac.uk.
³⁴ DiMePRe-J-Department of Precision and Rigenerative Medicine-Jonic Area, University of Bari "Aldo Moro", Bari, Italy. samuele.cortese@soton.ac.uk.

PMID: 38783054
PMCID: PMC11609101
DOI: 10.1038/s41380-024-02606-5

Abstract

There have been increasing efforts to develop prediction models supporting personalised detection, prediction, or treatment of ADHD. We overviewed the current status of prediction science in ADHD by: (1) systematically reviewing and appraising available prediction models; (2) quantitatively assessing factors impacting the performance of published models. We did a PRISMA/CHARMS/TRIPOD-compliant systematic review (PROSPERO: CRD42023387502), searching, until 20/12/2023, studies reporting internally and/or externally validated diagnostic/prognostic/treatment-response prediction models in ADHD. Using meta-regressions, we explored the impact of factors affecting the area under the curve (AUC) of the models. We assessed the study risk of bias with the Prediction Model Risk of Bias Assessment Tool (PROBAST). From 7764 identified records, 100 prediction models were included (88% diagnostic, 5% prognostic, and 7% treatment-response). Of these, 96% and 7% were internally and externally validated, respectively. None was implemented in clinical practice. Only 8% of the models were deemed at low risk of bias; 67% were considered at high risk of bias. Clinical, neuroimaging, and cognitive predictors were used in 35%, 31%, and 27% of the studies, respectively. The performance of ADHD prediction models was increased in those models including, compared to those models not including, clinical predictors (β = 6.54, p = 0.007). Type of validation, age range, type of model, number of predictors, study quality, and other type of predictors did not alter the AUC. Several prediction models have been developed to support the diagnosis of ADHD. However, efforts to predict outcomes or treatment response have been limited, and none of the available models is ready for implementation into clinical practice. The use of clinical predictors, which may be combined with other type of predictors, seems to improve the performance of the models. A new generation of research should address these gaps by conducting high quality, replicable, and externally validated models, followed by implementation research.

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Conflict of interest statement

Competing interests: Dr. Salazar de Pablo has received honoraria from Janssen Cilag, Lundbeck and Angelini. Dr Archer is supported by funding from the NIHR Birmingham Biomedical Research Centre at the University Hospitals Birmingham NHS Foundation Trust and the University of Birmingham. Dr. Solmi has received honoraria/has been a consultant for Abbvie, Angelini, Lundbeck, Otsuka. Prof. Fusar-Poli has received grant support from Lundbeck and honoraria fees from Angelini, Menarini, and Lundbeck. In the past year, Dr. Faraone received income, potential income, travel expenses continuing education support and/or research support from Aardvark, Aardwolf, AIMH, Tris, Otsuka, Ironshore, KemPharm/Corium, Akili, Supernus, Atentiv, Noven, Sky Therapeutics, Axsome and Genomind. With his institution, he has US patent US20130217707 A1 for the use of sodium-hydrogen exchange inhibitors in the treatment of ADHD. He also receives royalties from books published by Guilford Press: Straight Talk about Your Child’s Mental Health, Oxford University Press: Schizophrenia: The Facts and Elsevier: ADHD: Non-Pharmacologic Interventions. He is Program Director of www.ADHDEvidence.org and www.ADHDinAdults.com . Prof Larsson reports receiving grants from Shire Pharmaceuticals; personal fees from and serving as a speaker for Medice, Shire/Takeda Pharmaceuticals and Evolan Pharma AB; all outside the submitted work. Henrik Larsson is editor-in-chief of JCPP Advances. Prof. Cortese has declared reimbursement for travel and accommodation expenses from the Association for Child and Adolescent Central Health (ACAMH) in relation to lectures delivered for ACAMH, the Canadian AADHD Alliance Resource, the British Association of Psychopharmacology, and from Healthcare Convention for educational activity on ADHD.

Figures

**Fig. 1. PRISMA flowchart.**
Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flowchart outlining study selection process.

**Fig. 2. Reported predictors.**
Most frequently reported predictors across prediction model types.

**Fig. 3. Quality assessment.**
Risk of bias of the retrieved studies, as assessed by the PROBAST tool.

See this image and copyright information in PMC

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Individualized prediction models in ADHD: a systematic review and meta-regression

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Individualized prediction models in ADHD: a systematic review and meta-regression

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