Pulmonary Gas Exchange Improves over the First Year in Preterm Infants with and without Bronchopulmonary Dysplasia

Atrial septal defect closure is associated with improved clinical status in patients ≤ 10 kg with bronchopulmonary dysplasia

Patients with bronchopulmonary dysplasia (BPD) have shown clinical improvement after secundum atrial septal defect (ASD) closure. We sought to determine if this post-ASD closure improvement is secondary to the expected course in BPD patients or related to the closure itself. A novel BPD-ASD score was created to assess patients' clinical status (higher score = worse disease) and applied to 10 BPD-ASD inpatients weighing ≤ 10 kg who underwent ASD closure. The score and its subcomponents were retrospectively calculated serially ranging from 8 weeks pre- to 8 weeks post-intervention, and pre- and post-intervention score slopes were created. These slopes were compared using mixed regression modeling with an interaction term. There was a significant difference in pre- versus post-intervention slope with the most score drop the first week post-intervention (-2.1 + /- 0.8, p = 0.014). The mean score also dropped through weeks 2 (slope -0.8 + /- 0.8, p = 0.013) and 4 (slope -1.0 + /- 0.5, p = 0.001) post-intervention. There was a significant difference in pre- and post-intervention slopes for diuretics (p = 0.018) and the combined score of respiratory support, FiO2 need, and respiratory symptoms (p = 0.018). This study demonstrated significant improvement in BPD-ASD score, diuretic need, and respiratory status after ASD closure in BPD-ASD patients ≤ 10 kg that was outside of the natural course of BPD. Our study was limited by its small, single-center, retrospective nature. Future studies should be performed in a larger multicenter population to both validate the scoring system and compare to non-intervention infants.

Elevated leukotriene B4 and 8-isoprostane in exhaled breath condensate from preterm-born infants

BACKGROUND

Inflammation and oxidative stress play a key role in the development of bronchopulmonary dysplasia (BPD), possibly contributing to persistent respiratory morbidity after preterm birth. We aimed to assess if inflammatory markers were elevated in exhaled breath condensate (EBC) of infants born very prematurely (< 32 weeks gestation) at 12-16 corrected months of age, and if increased levels were associated with BPD diagnosis and respiratory morbidity.

METHODS

EBC samples and respiratory questionnaires were collected from 15 term-born infants and 33 preterm-born infants, 12 with a neonatal BPD diagnosis. EBC samples were analysed for leukotriene B4 (inflammation) and 8-isoprostane (oxidative stress) concentrations using enzyme-linked immune-assays. Differences between groups were analysed by Kruskal-Wallis Test with post-hoc comparisons, independent samples t-test or Mann-Whitney U test depending on normality of the data.

RESULTS

Leukotriene B4 and 8-isoprostane levels were elevated in exhaled breath condensate of preterm-born infants compared to those born at term (mean difference [95% CI]; 1.52 [0.45, 2.59], p = 0.02; 0.77 [0.52, 1.02], p < 0.001, respectively). Leukotriene B4 and 8-isoprostane levels were independent of BPD diagnosis and respiratory morbidity over the first year of life.

CONCLUSIONS

Infants born very prematurely exhibit elevated markers of airway neutrophilic inflammation and oxidative stress beyond the first year of life, regardless of a neonatal diagnosis of chronic lung disease or respiratory morbidity during infancy. These findings may have implications for future lung health.

TRIAL REGISTRATION

N/A.

Role of Disease Progression Models in Drug Development

The use of Disease progression models (DPMs) in Drug Development has been widely adopted across therapeutic areas as a method for integrating previously obtained disease knowledge to elucidate the impact of novel therapeutics or vaccines on disease course, thus quantifying the potential clinical benefit at different stages of drug development programs. This paper provides a brief overview of DPMs and the evolution in data types, analytic methods, and applications that have occurred in their use by Quantitive Clinical Pharmacologists. It also provides examples of how these models have informed decisions and clinical trial design across several therapeutic areas and at various stages of development. It briefly describes potential new applications of DPMs utilizing emerging data sources, and utilizing new analytic techniques, and discuss new challenges faced such as requiring description of multiple endpoints, rapid model development, application of machine learning-based analytics, and use of high dimensional and real-world data. Considerations for the continued evolution future of DPMs to serve as community-maintained expert systems are also provided.