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Emphysema Detection in Smokers: Diffusing Capacity for Nitric Oxide Beats Diffusing Capacity of Carbon Monoxide-Based

Gerald S Zavorsky1, Roberto W Del-Negro2, Ivo van der Lee3

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Summary
This summary is machine-generated.

Pulmonary diffusing capacity for nitric oxide (DLNO) better detects emphysema in smokers than traditional measures. A model using DLNO, lung capacity, and FEV1 shows superior performance for emphysema detection.

Keywords:
emphysemalogistic modelingpredictive accuracypulmonary diffusing capacityz-scores

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Area of Science:

  • Pulmonary medicine
  • Respiratory diagnostics
  • Emphysema research

Background:

  • Pulmonary diffusing capacity for nitric oxide (DLNO) is underutilized despite potential advantages over pulmonary diffusing capacity for carbon monoxide (DLCO).
  • Emphysema detection in smokers often relies on spirometry and lung volumes, but these may not be sensitive enough.
  • Computed tomography (CT) defines emphysema, but non-invasive biomarkers are needed for early detection.

Purpose of the Study:

  • To evaluate if DLNO is a better biomarker for detecting emphysema in smokers compared to DLCO, spirometry, or lung volumes.
  • To develop and validate a predictive model for emphysema in smokers using diffusion capacity measures and lung function parameters.
  • To assess the incremental value of DLNO over DLCO in emphysema detection.

Main Methods:

  • Individual participant data meta-analysis of adult smokers with and without CT-defined emphysema.
  • Standardized 10 ± 2-second breath-hold time double diffusion protocol for DLNO and DLCO measurements.
  • Model selection using Bayesian Information Criterion (BIC) and discrimination assessment via Area Under the Receiver Operating Characteristic (AUROC) curve and Matthews Correlation Coefficient (MCC).

Main Results:

  • A 3-predictor model including total lung capacity (TLC), forced expiratory volume in 1 second (FEV1), and DLNO z-scores demonstrated the best fit (lowest BIC) and high discrimination (AUROC 0.97).
  • FEV1 z-scores (R²=0.35) and DLNO z-scores (R²=0.21) were significant unique contributors to emphysema prediction, surpassing TLC z-scores (R²=0.11).
  • Adding DLCO to the model provided minimal additional information and shared significant variance with DLNO.

Conclusions:

  • A parsimonious z-score model incorporating TLC, FEV1, and DLNO offers excellent and stable performance for predicting emphysema likelihood in smokers.
  • DLNO demonstrates superior utility over DLCO in detecting emphysema when combined with standard lung function parameters.
  • DLNO represents a promising, underutilized biomarker for enhancing emphysema detection in at-risk populations.