Patterns of Response to Methylphenidate Administration in Children with ADHD
A Personalized Medicine Approach through Clustering Analysis
Bibliographic Data
| ID | 15714959 |
|---|---|
| Authors | Silvia Grazioli (0000-0002-7789-2815, IRCCS Eugenio Medea), Eleonora Rosi (0000-0002-7080-8916, IRCCS Eugenio Medea, corresponding author), Maddalena Mauri (0000-0002-7507-4675, University of Milano-Bicocca), Alessandro Crippa (0000-0002-3407-0352, IRCCS Eugenio Medea), Federica Tizzoni (0000-0002-6637-1133, IRCCS Eugenio Medea), Arianna Tarabelloni (0000-0003-3335-6866, IRCCS Eugenio Medea), Filippo Maria Villa (0000-0001-8670-7899, IRCCS Eugenio Medea), Federica Chiapasco (Humanitas University), Maria Reimers (Humanitas University), Erika Gatti (0000-0001-5899-9863, IRCCS Eugenio Medea), Silvana Bertella (0000-0002-7560-9836, IRCCS Eugenio Medea), Massimo Molteni (0000-0001-6268-5883, IRCCS Eugenio Medea), Maria Nobile (0000-0002-9917-4275, IRCCS Eugenio Medea) |
| Year | 2021 |
| Volume | 8 |
| Issue | 11 |
| Pages | 1008-1008 |
| Publication date | 2021-11-04 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Children (JOURNAL) |
| Journal identifiers | ISSN: 2227-9067 • E-ISSN: 2227-9067 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/children8111008 |
| PMID | 34828721 |
| OpenAlex | W3210687214 |
| Language | EN |
| References cited | 7 |
Individual responses to methylphenidate (MPH) can significantly differ in children with attention-deficit/hyperactivity disorder (ADHD) in terms of the extent of clinical amelioration, optimal dosage needed, possible side effects, and short- and long-term duration of the benefits. In the present repeated-measures observational study, we undertook a proof-of-concept study to determine whether clustering analysis could be useful to characterize different clusters of responses to MPH in children with ADHD. We recruited 33 children with ADHD who underwent a comprehensive clinical, cognitive, and neurophysiological assessment before and after one month of MPH treatment. Symptomatology changes were assessed by parents and clinicians. The neuropsychological measures used comprised pen-and-paper and computerized tasks. Functional near-infrared spectroscopy was used to measure cortical hemodynamic activation during an attentional task. We developed an unsupervised machine learning algorithm to characterize the possible clusters of responses to MPH in our multimodal data. A symptomatology improvement was observed for both clinical and neuropsychological measures. Our model identified distinct clusters of amelioration that were related to symptom severity and visual-attentional performances. The present findings provide preliminary evidence that clustering analysis can potentially be useful in identifying different responses to MPH in children with ADHD, highlighting the importance of a personalized medicine approach within the clinical framework
Bioinformatics · Cluster analysis · Cognition · Continuous performance task · Machine learning · Methylphenidate · Neuropsychology · Observational study · Personalized medicine · Psychiatry · Attention Deficit Hyperactivity Disorder · Clinical Psychology · Computer Science · Functional Brain Connectivity Studies · Medicine · Neural and Behavioral Psychology Studies · Psychology · Internal Medicine
| Highly cited | No |
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