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ADHD Medication and Predictors of Treatment Outcome

Naturalistic Study of ADHD Medication and Predictors of Treatment Outcome

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT02136147
Acronym
ADAPT
Enrollment
632
Registered
2014-05-12
Start date
2015-06-30
Completion date
2022-06-30
Last updated
2023-10-17

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Attention Deficit Disorder With Hyperactivity (ADHD)

Keywords

Attention Deficit Disorder with Hyperactivity, Neuropsychiatry, Drug therapy, Pharmacogenetics, Child Psychiatry

Brief summary

ADHD medication of children and adolescents is becoming increasingly common. Clinical experience and scientific studies have proven that approximately 30% of children/adolescents with ADHD do not benefit from this treatment. However, there is insufficient knowledge about who these children are. All children and adolescents, who start treatment with ADHD medication at public Child and Adolescent Psychiatry units in Stockholm, on Gotland, an in Västerbotten, will be asked to participate in the study. The investigators intend to monitor the patients´clinical symptoms and possible side-effects after treatment start. The investigators will collect background information and saliva samples from the patient and his/her parents to be able to study if there are any genetic (hereditary) or other markers that can predict positive or negative outcomes of the ADHD medication. With this information, the investigators aim at, to a greater extent, be able to individualize treatment choices for children and adolescents with ADHD without unnecessary, costly and possibly unfavorable treatment attempts.

Detailed description

The specific aims for the ADAPT study are: 1. Investigate if certain gene polymorphisms are associated with poor effect of ADHD drugs (non-responders). 2. Investigate if other biologically, phenotypic or psychosocial factors are associated with poor effect of ADHD drugs (non-responders). 3. Investigate if the frequency of side-effects of ADHD drugs differs between children with different genotypes. 4. Investigate if the frequency of side-effects of ADHD drugs differs between children with different phenotypic and/or psychosocial factors Method: This study has a naturalistic design. The aim is to map all new treatments with ADHD drugs at all 13 public BUP units in Stockholm County, one BUP unit on Gotland, and three BUP units in Västerbotten Region. The participation means that medication is initiated as planned in normal clinical practice by the child´s ordinary physician, and beyond this only means a somewhat denser and more structured follow-up. In addition, the investigators will ask for saliva samples from the patient and his/her parents. The investigators aim at including at least 1000 individuals in total in the study. Part of the data will be collected via the national Quality Register for ADHD Treatment Follow-up (BUSA), which has approved security procedures approved by the Swedish Data Inspection Board. Case report forms are computerized and separate from the database registry for collected study data. The database and detailed variable lists are constructed in collaboration with professional database managers. Standard Operation Procedures are designed in collaboration by project coordinator, study nurse and principal investigator, and may be revised after pilot phase. Collected samples will be stored at KI biobank. Data analysis: 1. To judge if the patient is a responder to ADHD drugs the SNAP-IV rating of ADHD symptoms (before and after medication start) is used. The patients who at 3 months have an at least 40% reduction in SNAP-IV score are reckoned responders and those who at the same time point have a less than 20% change in SNAP-IV score are reckoned non-responders. Differences between the groups will be analyzed with logistic regression, with responder status as depending variable, and genotype and the other risk markers (biological, phenotypic, and psychosocial markers) as independent variables after correction for symptoms at baseline. Even a 50% drop-out rate will (i.e. 1000 out of estimated 2000 eligible individuals) give a 98% power to identify a 49% increase in non-responder proportion for a specific genotype. 2. Concomitantly, the outcome in side-effects, heart rate, blood pressure, weight (z-score) and length (z-score) will be analyzed with linear regression with the same independent variables. 3. The analyses are performed separately for each ADHD drug. 4. There are significantly more boys than girls (about 4:1) with ADHD. Given the sex difference in prevalence it is obvious to also include sex as a covariate in our analyses of treatment outcome. 5. Missing data will be treated according to the principles of complete case and multiple imputation.

Interventions

DRUGmethylphenidate medication
DRUGatomoxetine medication
DRUGlisdexamphetamine medication
DRUGguanfacine medication

Sponsors

Karolinska Institutet
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
6 Years to 18 Years
Healthy volunteers
No

Inclusion criteria

* Clinical diagnosis of ADHD * Starting medication against ADHD symptoms with atomoxetine, methylphenidate, lisdexamphetamine, or guanfacine

Exclusion criteria

Any medication against ADHD the last 3 months

Design outcomes

Primary

MeasureTime frameDescription
change in SNAP-IV Teacher and Parent rating scale (Swanson, Nolan and Pelham ADHD Rating Scale)at 3 months follow-upADHD symptoms
change in P-SEC (Pediatric Side Effects Checklist)at 3 months follow-upSide-effect measure

Secondary

MeasureTime frameDescription
change in heart rateat 1 month follow-up
change in C-GAS (Children´s global assessment scale)at 12 months follow-upglobal functioning measure
change in CGI-S (Clinical Global Impression- of Severity)at 12 months follow-updisease severity
change in SNAP-IV Teacher and Parent rating scaleat 1 month follow-upADHD symptoms
change in systolic blood pressureat 1 month follow-up
change in diastolic blood pressureat 1 month follow-up
change in weight z-scoreat 1 month follow-up
change in height z-scoreat 6 months follow-up
change in Autism Spectrum Screening Questionnaire (ASSQ) scoreat 3 months follow-upsymptoms of autism
change in P-SEC (Pediatric Side Effects Checklist)at 1 month follow-upside effect measure
change in Spence Children's Anxiety Scale (SCAS)at 1 month follow-upsymptoms of anxiety

Other

MeasureTime frameDescription
change in self-harm frequencyat 12 months follow-upchange in self-harm frequency behavior as noted in the quality register BUSA
change in suicide attempt frequencyat 12 months follow-upchange in suicide attempt frequency as reported in quality register BUSA

Countries

Sweden

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 12, 2026