Recent advances in lung function standard value prediction equations: Comparison with the Global Lung Initiative...

Area of Science:

• Pulmonary Medicine
• Biostatistics
• Medical Informatics

Background:

• Accurate interpretation of lung function tests (LFTs) relies on selecting appropriate reference prediction equations.
• The Global Lung Function Initiative (GLI) by the American Thoracic Society (ATS) and European Respiratory Society (ERS) recommends continuous standard value prediction equations for wide age ranges.
• Generalized additive models for location, scale, and shape (GAMLSS) offer a robust statistical framework for developing such equations.

Purpose of the Study:

• To provide an overview of developing lung function prediction equations using GAMLSS for spirometry, diffusion capacity, and static lung volume.
• To compile statistical knowledge essential for creating GAMLSS-based lung function reference-value prediction algorithms.
• To guide the calculation of z-scores and address ethnic diversity in prediction equations.

Main Methods:

• Utilizing Generalized Additive Models for Location, Scale, and Shape (GAMLSS) to create accurate percentile curves.
• Employing the Lambda, Mu, and Sigma (LMS) method, a subtype of GAMLSS, for prediction equation development.
• Reviewing statistical techniques for building lung function reference-value prediction algorithms.

Main Results:

• GAMLSS and the LMS method facilitate the creation of continuous lung function prediction equations applicable across broad age spans.
• These prediction equations enable the calculation of z-scores for more precise LFTs interpretation.
• The review details the statistical underpinnings and considerations for ethnic diversity in equation development.

Conclusions:

• GAMLSS provides a powerful statistical approach for developing accurate and continuous lung function prediction equations.
• The LMS method, within GAMLSS, is crucial for generating reliable reference values and z-scores.
• Standardized, statistically robust equations are vital for consistent and accurate global interpretation of lung function tests.