Nationwide cohort study indicates montelukast treatment for asthma not a risk factor for ADHD

Today, most treatment guidelines recommend starting ADHD treatment with stimulant medications. These medicines often work quickly and can be very effective, but they do not help every child, and they can have bothersome side effects, such as appetite loss, sleep problems, or mood changes. Families also worry about long-term effects, the possibility of misuse or abuse, as well as the recent nationwide stimulant shortages. Non-stimulant medications are available, but they are usually used only after stimulants have not been effective.

This stimulant-first approach means that many patients who would respond well to a non-stimulant will end up on a stimulant medication anyway. This study addresses this issue by testing two different ways of starting medication treatment for school-age children with attention-deficit/hyperactivity disorder (ADHD). We want to know whether beginning with a non-stimulant medicine can work as well as the  “stimulant-first” approach, which is currently used by most prescribers.

From this study, we hope to learn:

• Is starting with a non-stimulant medication “good enough” compared with starting with a stimulant?
  In other words, when we look at overall improvement in a child’s daily life, not just ADHD symptoms, does a non-stimulant-first approach perform similarly to a stimulant-first approach?
• Which children do better with which approach?
  Children with ADHD are very different from one another. Some have anxiety, depression, learning problems, or autism spectrum conditions. We want to know whether certain groups of children benefit more from starting with stimulants, and others from starting with non-stimulants.
• How do the two strategies compare for side effects, treatment satisfaction, and staying on medication?
  We will compare how often children stop or switch medications because of side effects or lack of benefit, and how satisfied children, parents, and clinicians are with care under each strategy.
• What are the longer-term outcomes over a year?
  We are interested not only in short-term symptom relief, but also in how children are doing months later in school, at home, with friends, and emotionally.

Our goal is to give families and clinicians clear, practical evidence to support a truly shared decision: “Given this specific child, should we start with a stimulant or a non-stimulant?”

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Who will be in the study?

We will enroll about 1,000 children and adolescents, ages 6 to 16, who:

• Have ADHD and are starting or restarting medication treatment, and
• Are being treated in everyday pediatric and mental health clinics at large children’s hospitals and health systems across the United States.

We will include children with common co-occurring conditions (such as anxiety, depression, learning or developmental disorders) so that the results reflect the “real-world” children seen in clinics, not just highly selected research volunteers.

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How will the treatments be assigned?

This is a randomized comparative effectiveness trial, which means:

• Each child will be randomly assigned (like flipping a coin) to one of two strategies:
  
  
  
  1. Stimulant-first strategy – the clinician starts treatment with a stimulant medication.
  2. Non-stimulant-first strategy – the clinician starts treatment with a non-stimulant medication.
• Within the assigned class, the clinician and family still choose the specific medicine and dose, and can adjust treatment as they normally would. This keeps the study as close as possible to real-world practice.
• The randomization is 1:1, so about half the participants will start with stimulants and half with non-stimulants.

Parents and clinicians will know which type of medicine the child is taking, as in usual care. However, the experts who rate how much each child has improved using our main outcome measure will not be told which treatment strategy the child received. This helps keep their ratings unbiased.

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What will participants be asked to do?

Each family will be followed for 12 months. We will collect information at:

• Baseline (before or just as medication is started)
• Early follow-up (about weeks 3 and 6)
• Later follow-up (about 3 months, 6 months, and 12 months)

At these times:

• Parents will complete questionnaires about ADHD symptoms, behavior, emotions, and daily functioning at home and in the community.
• Teachers will complete brief forms about the child’s behavior and performance at school.
• Children and teens (when old enough) will complete age-appropriate questionnaires about their own mood, behavior, and quality of life.
• A specially trained clinical rater, using all available information but blinded to treatment strategy, will give a global rating of how much the child has improved overall, not just in ADHD symptoms.

We will also track:

• Medication changes (stopping, switching, or adding medicines)
• Reasons for any changes (side effects, lack of benefit, or other reasons)
• Any serious side effects or safety concerns

Data will be entered into a secure, HIPAA-compliant research database. Study staff at each site will work closely with families to make participation as convenient as possible, including offering flexible visit schedules and electronic options for completing forms when feasible.

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How will we analyze the results?

Using standard statistical methods, we will:

• Compare the overall improvement of children in the stimulant-first group versus the non-stimulant-first group after 12 months.
• Look at differences in side effects, discontinuation rates, and treatment satisfaction between the two strategies.
• Examine which child characteristics (such as age, sex, co-occurring conditions, and baseline severity) are linked to better results with one strategy versus the other.
• Analyze long-term outcomes, including functioning at home, school, and with peers, and emotional well-being.

All analyses will follow the “intention-to-treat” principle, meaning we compare children based on the strategy they were originally assigned to, even if their medication is later changed. This mirrors real-world decision-making: once you choose a starting strategy, what tends to happen over time?

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Why is this study necessary now?

This study addresses a critical, timely gap in ADHD care:

• Guidelines are ahead of the evidence.
  Existing guidelines almost always recommend stimulants as the first-line medication, yet careful reviews of the evidence show that direct comparisons of stimulant-first versus non-stimulant-first strategies are limited. We do not have strong data to say that starting with stimulants is clearly superior for all children.
• Real-world children are more complex than those in past trials.
  Most prior medication trials have excluded children with multiple conditions, serious family stressors, or other complexities that are very common in everyday practice. Our pragmatic, multi-site design will include these children and thus produce findings that are directly relevant to front-line clinicians and families.
• Families and clinicians are asking for alternatives.
  Parents often express worries about stimulant side effects, long-term use, and stigma. Clinicians would like clearer guidance about when a non-stimulant is a reasonable first choice. At the same time, stimulant shortages and concerns about misuse and diversion have exposed the risks of relying almost entirely on one class of medications.
• The timing is right to influence practice and policy.
  Our team includes parents, youth advocates, frontline clinicians, and national networks that link major children’s hospitals. These partners have helped shape the study from the beginning and will help interpret and share the results. This means that if starting with non-stimulants is found to be similarly effective and safer or more acceptable for some children, practice patterns and guidelines can change rapidly.

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In short, this study is needed now to move ADHD medication decisions beyond “one-size-fits-all.” By rigorously comparing stimulant-first and non-stimulant-first strategies in real-world settings, and by focusing on what matters most to children and families overall functioning, side effects, and long-term well-being, we aim to give patients, parents, and clinicians the information they need to choose the best starting treatment for each child.

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This project was conceived by Professor Stephen V. Faraone, PhD (SUNY Upstate Medical University, Department of Psychiatry, Syracuse, NY) and Professor Jeffrey H. Newcorn, MD (Icahn School of Medicine at Mount Sinai, Department of Psychiatry, New York, NY).   It will be conducted at nine sites across the USA.

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EBI-ADHD: 

If you live with ADHD, treat ADHD, or write about ADHD, you’ve probably run into the same problem: there’s a ton of research on treatments, but it’s scattered across hundreds of papers that don’t talk to each other.  The EBI-ADHD website fixes that. 

EBI-ADHD (Evidence-Based Interventions for ADHD) is a free, interactive platform that pulls together the best available research on how ADHD treatments work and how safe they are. It’s built for clinicians, people with ADHD and their families, and guideline developers who need clear, comparable information rather than a pile of PDFs. EBI-ADHD Database  The site is powered by 200+ meta-analyses covering 50,000+ participants and more than 30 different interventions.  These include medications, psychological therapies, brain-stimulation approaches, and lifestyle or “complementary” options. 

The heart of the site is an interactive dashboard.  You can: 

1. Choose an age group: children (6–17), adolescents (13–17), or adults (18+). 

2. Choose a time frame: results at 12, 26, or 52 weeks. 

3. Choose whether to explore by intervention (e.g., methylphenidate, CBT, mindfulness, diet, neurofeedback) or by outcome (e.g., ADHD symptoms, functioning, adverse events), depending on what’s available. EBI-ADHD Database 

The dashboard then shows an evidence matrix: a table where each cell is a specific treatment–outcome–time-point combination. Each cell tells you two things at a glance: 

1. How big the effect is, compared to placebo or another control (large benefit, small benefit, no effect, small negative impact, large negative impact). 

2. How confident we can be in that result (high, moderate, low, or very low certainty).  

Clicking a cell opens more detail: effect sizes, the underlying meta-analysis, and how the certainty rating was decided. 

EBI-ADHD is not just a curated list of papers. It’s built on a formal umbrella review of ADHD interventions, published in The BMJ in 2025. That review re-analyzed 221 meta-analyses using a standardized statistical pipeline and rating system. 

The platform was co-created with 100+ clinicians and 100+ people with lived ADHD experience from around 30 countries and follows the broader U-REACH framework for turning complex evidence into accessible digital tools.  

Why it Matters 

ADHD is one of the most studied conditions in mental health, yet decisions in everyday practice are still often driven by habit, marketing, or selective reading of the literature. EBI-ADHD offers something different: a transparent, continuously updated map of what we actually know about ADHD treatments and how sure we are about it. 

In short, it’s a tool to move conversations about ADHD care from “I heard this works” to “Here’s what the best current evidence shows, and let’s decide together what matters most for you.” 

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The Background:

Meta-analyses have previously suggested a link between maternal thyroid dysfunction and neurodevelopmental disorders (NDDs) in children, though some studies report no significant difference. Overweight and obesity are more common in children and adolescents with NDDs. Hypothyroidism is often associated with obesity, which may result from reduced energy expenditure or disrupted hormone signaling affecting growth and appetite. These hormone-related parameters could potentially serve as biomarkers for NDDs; however, research findings on these indicators vary. 

The Study:

A Chinese research group recently released a meta-analysis examining the relationship between neurodevelopmental disorders (NDDs) and hormone levels – including thyroid, growth, and appetite hormones – in children and adolescents.  

The analysis included peer-reviewed studies that compared hormone levels – such as thyroid hormones (FT3, FT4, TT3, TT4, TSH, TPO-Ab, or TG-Ab), growth hormones (IGF-1 or IGFBP-3), and appetite-related hormones (leptin, ghrelin, or adiponectin) – in children and adolescents with NDDs like ADHD, against matched healthy controls. To be included, NDD cases had to be first-diagnosis and medication-free, or have stopped medication before testing. Hormone measurements needed to come from blood, urine, or cerebrospinal fluid samples, and all studies were required to provide both means and standard deviations for these measurements. 

Meta-analysis of nine studies encompassing over 5,700 participants reported a medium effect size increase in free triiodothyronine (FT3) in children and adolescents with ADHD relative to healthy controls. There was no indication of publication bias, but variation between individual study outcomes (heterogeneity) was very high. Further analysis showed FT3 was only significantly elevated in the predominantly inattentive form of ADHD (three studies), again with medium effect size, but not in the hyperactive/impulsive and combined forms. 

Meta-analysis of two studies combining more than 4,800 participants found a small effect size increase in thyroid peroxidase antibody (TPO-Ab) in children and adolescents with ADHD relative to healthy controls. In this case, the two studies had consistent results. Because only two studies were involved, there was no way to evaluate publication bias. 

The remaining thyroid hormone meta-analyses, involving 6 to 18 studies and over 5,000 participants in each instance, found no significant differences in levels between children and adolescents with ADHD and healthy controls. 

Meta-analyses of six studies with 317 participants and two studies with 192 participants found no significant differences in growth hormone levels between children and adolescents with ADHD and healthy controls. 

Finally, meta-analyses of nine studies with 333 participants, five studies with 311 participants, and three studies with 143 participants found no significant differences in appetite-related hormone levels between children and adolescents with ADHD and healthy controls. 

The Conclusion:

‍The team concluded that FT3 and TPO-Ab might be useful biomarkers for predicting ADHD in youth. However, since FT3 was only linked to inattentive ADHD, and TPO-Ab’s evidence came from just two studies with small effects, this conclusion may overstate the meta-analysis results. 

Our Take-Away:

‍Overall, this meta-analysis found only limited evidence that hormone differences are linked to ADHD. One thyroid hormone (FT3) was higher in children with ADHD—mainly in the inattentive presentation—but the findings varied widely across studies. Another marker, TPO-Ab, showed a small increase, but this came from only two studies, making the result less certain. For all other thyroid, growth, and appetite-related hormones, the researchers found no meaningful differences between children with ADHD and those without. While FT3 and TPO-Ab may be worth exploring in future research, the current evidence is not strong enough to consider them reliable biomarkers.

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