Pulmonology — Weekly Evidence Brief

Precision medicine is transforming chronic obstructive pulmonary disease (COPD) management by integrating phenotypes, endotypes, and biomarkers to guide individualized therapies 1. For instance, exhaled breath analysis is emerging as a tool to identify metabolic alterations, such as disturbances in aminosugar metabolism, during acute exacerbations of COPD (AECOPD) in patients already on triple inhaled therapy, potentially revealing new therapeutic targets and enabling rapid detection 2. Furthermore, artificial intelligence (AI) shows promise in primary care for interpreting spirometry, demonstrating high sensitivity (84%) and specificity (86.8%) in identifying COPD, which could significantly improve diagnostic accuracy 34.

Environmental exposures like long-term inhalation of fine particulate matter (PM2.5) and its components, particularly black carbon, organic matter, and sulfate, are significantly associated with an increased risk of chronic lung disease (CLD) in middle-aged and elderly populations 56. Beyond environmental factors, patient-specific risks such as malnutrition significantly impact outcomes in idiopathic pulmonary fibrosis (IPF); older IPF patients with malnutrition risk, as assessed by the Geriatric Nutritional Risk Index, experience more frequent acute exacerbations and higher mortality rates 7. Moreover, emerging data suggest that dual cannabis and tobacco smoking in younger lung cancer patients is associated with a distinct clinical pattern, including earlier onset, more emphysema, and a higher incidence of aggressive tumor types compared to tobacco-only smokers 8.

Deep learning models are proving instrumental in evaluating structural lung abnormalities and predicting treatment response in various lung diseases. In cystic fibrosis (CF), deep learning accurately quantifies CT abnormalities, revealing that muco-inflammatory lesions like bronchial wall thickening and mucus plugging are reversible with elexacaftor-tezacaftor-ivacaftor (ETI) treatment, with younger age and greater initial lesion extent predicting better lung function improvement 9. Similarly, a multi-modality prediction approach combining deep learning features from CT scans, radiomics, and clinical data can assess the risk of immunotherapy-induced pneumonitis in non-small cell lung cancer patients, aiding in personalized immunotherapy strategies 10. In lung transplant recipients, monitoring the forced expiratory volume in 1 second (FEV1) rate of decline is crucial for assessing response to standard-of-care therapy for bronchiolitis obliterans syndrome and guiding rescue therapy 11.

Antifibrotic therapies in IPF show differential effects, with positive slopes of MMP degraded C-reactive protein (CRPM) associated with worse 5-year mortality in nintedanib-treated patients, suggesting CRPM kinetics as a prognostic biomarker for this specific therapy 12. For patients with long COVID, maintaining moderate-to-high physical activity levels correlates with reduced shortness of breath, improved cardiorespiratory fitness, better sleep quality, and an enhanced quality of life 13. Furthermore, protective ventilation strategies in lung transplantation should be highly personalized, advocating for early extubation and considering specific end-stage lung disease pathophysiology to minimize lung injury 14.