Treatment considerations and prescribing issues for obese children with asthma
Bibliographic record
Abstract
Overweight and obesity are important risk factors for poor control and exacerbation in pediatric asthma. While overweight and obese patients with asthma appear to be characterized by a different pathological process giving rise to a distinct phenotype, national and international guidelines recommend a one-size-fits-all therapeutic approach regardless of weight. This is because it is unclear whether the observed higher morbidity associated with the obese-asthma phenotype in children are due to poor response to conventional inhaled corticosteroid (ICS) therapies, treatment nonadherence, or other confounding factors. The overall aim of my thesis work was to investigate the impact of weight status on treatment-associated factors that may influence the risk of management failure and/or exacerbation in children with asthma, using causal inference methods. Specifically, I assessed whether elevated weight status: i) modified the response to different asthma maintenance therapies, based on treatment Step-2 (first manuscript) and Step-3 (second manuscript) recommended across pediatric asthma guidelines; and (ii) was associated with asthma medication nonadherence (third manuscript). From a methodological standpoint, a bias-reduction correction method was also developed to address analytical issues when estimating total effects on the hazard ratio scale (fourth manuscript). In this thesis, I analyzed a historical cohort of children with physician-diagnosed asthma consulting at the Asthma Center of the Montreal Children's Hospital between Jan 2000 and Dec 2007, linking clinical data to administrative health and prescription claims databases. In the first manuscript, there was an increased hazard of management failure in low-dose ICS and leukotriene receptor antagonists (LTRA) maintenance monotherapy (Step-2) users with elevated body mass index (BMI) percentiles. Findings also suggested a differential response to Step-2 maintenance therapies by weight status on the multiplicative (HR) scale, with LTRA achieving maximal effectiveness at higher BMI percentiles. In the second manuscript, obesity (BMI>97th percentile) was found to be an important determinant of shorter exacerbation-free time among those initiating Step-3 therapies, i.e. higher-dose ICS or low-/medium-dose ICS in combination with LTRA or long-acting beta-2 agonists (LABA). While the assessment of treatment effect modification by obesity status on the additive and multiplicative scales were not found to be statistically significant, the marginal survival curves demonstrated a potential favorable response to combination therapy relative to higher-dose ICS monotherapy in obese compared to non-obese children. In the third manuscript, weight status (BMI percentile) and excess weight (BMI>85th percentile) were associated with primary nonadherence in those newly prescribed low-dose ICS and secondary nonadherence in those with more complex regimens. Collectively, this work sheds light on potential mechanisms that may contribute to the higher morbidity associated with obese-asthma in children. The observation that LTRA monotherapy achieved maximal response in children with higher BMIs may reflect the contribution of other pathways to the asthma phenotype of obese children with mild severity. Combination therapy appeared to provide an additional benefit in terms of prolonging exacerbation-free time than higher-dose ICS alone in obese compared to non-obese children with asthma. This could suggest that obese children with severe asthma may have a tendency to exhibit resistance to higher doses of ICS. Lastly, higher weight status was associated with medication nonadherence, which may be a result of perceived treatment ineffectiveness, socioeconomic factors, misconceptions about side effects, or weight-related psychosocial comorbidities. Further research is necessary to provide an in depth understanding of the biological drivers causing the obese-asthma 'difficult-to-treat' phenotype.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".