Patterns of Response to Methylphenidate Administration in Children with ADHD: A Personalized Medicine Approach through Clustering Analysis

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 rep...

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Autores principales:	Silvia Grazioli, Eleonora Rosi, Maddalena Mauri, Alessandro Crippa, Federica Tizzoni, Arianna Tarabelloni, Filippo Maria Villa, Federica Chiapasco, Maria Reimers, Erika Gatti, Silvana Bertella, Massimo Molteni, Maria Nobile
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	attention-deficit/hyperactivity disorder methylphenidate near-infrared spectroscopy machine learning clustering personalized medicine Pediatrics RJ1-570
Acceso en línea:	https://doaj.org/article/594df80057bf4273b0cda4b23ccc0464
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spelling	oai:doaj.org-article:594df80057bf4273b0cda4b23ccc04642021-11-25T17:14:29ZPatterns of Response to Methylphenidate Administration in Children with ADHD: A Personalized Medicine Approach through Clustering Analysis10.3390/children81110082227-9067https://doaj.org/article/594df80057bf4273b0cda4b23ccc04642021-11-01T00:00:00Zhttps://www.mdpi.com/2227-9067/8/11/1008https://doaj.org/toc/2227-9067Individual 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.Silvia GrazioliEleonora RosiMaddalena MauriAlessandro CrippaFederica TizzoniArianna TarabelloniFilippo Maria VillaFederica ChiapascoMaria ReimersErika GattiSilvana BertellaMassimo MolteniMaria NobileMDPI AGarticleattention-deficit/hyperactivity disordermethylphenidatenear-infrared spectroscopymachine learningclusteringpersonalized medicinePediatricsRJ1-570ENChildren, Vol 8, Iss 1008, p 1008 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	attention-deficit/hyperactivity disorder methylphenidate near-infrared spectroscopy machine learning clustering personalized medicine Pediatrics RJ1-570
spellingShingle	attention-deficit/hyperactivity disorder methylphenidate near-infrared spectroscopy machine learning clustering personalized medicine Pediatrics RJ1-570 Silvia Grazioli Eleonora Rosi Maddalena Mauri Alessandro Crippa Federica Tizzoni Arianna Tarabelloni Filippo Maria Villa Federica Chiapasco Maria Reimers Erika Gatti Silvana Bertella Massimo Molteni Maria Nobile Patterns of Response to Methylphenidate Administration in Children with ADHD: A Personalized Medicine Approach through Clustering Analysis
description	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.
format	article
author	Silvia Grazioli Eleonora Rosi Maddalena Mauri Alessandro Crippa Federica Tizzoni Arianna Tarabelloni Filippo Maria Villa Federica Chiapasco Maria Reimers Erika Gatti Silvana Bertella Massimo Molteni Maria Nobile
author_facet	Silvia Grazioli Eleonora Rosi Maddalena Mauri Alessandro Crippa Federica Tizzoni Arianna Tarabelloni Filippo Maria Villa Federica Chiapasco Maria Reimers Erika Gatti Silvana Bertella Massimo Molteni Maria Nobile
author_sort	Silvia Grazioli
title	Patterns of Response to Methylphenidate Administration in Children with ADHD: A Personalized Medicine Approach through Clustering Analysis
title_short	Patterns of Response to Methylphenidate Administration in Children with ADHD: A Personalized Medicine Approach through Clustering Analysis
title_full	Patterns of Response to Methylphenidate Administration in Children with ADHD: A Personalized Medicine Approach through Clustering Analysis
title_fullStr	Patterns of Response to Methylphenidate Administration in Children with ADHD: A Personalized Medicine Approach through Clustering Analysis
title_full_unstemmed	Patterns of Response to Methylphenidate Administration in Children with ADHD: A Personalized Medicine Approach through Clustering Analysis
title_sort	patterns of response to methylphenidate administration in children with adhd: a personalized medicine approach through clustering analysis
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/594df80057bf4273b0cda4b23ccc0464
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Patterns of Response to Methylphenidate Administration in Children with ADHD: A Personalized Medicine Approach through Clustering Analysis

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