Recent advances in lung function standard value prediction equations: Comparison with the Global Lung Initiative prediction equation based on GAMLSS.
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| Title: | Recent advances in lung function standard value prediction equations: Comparison with the Global Lung Initiative prediction equation based on GAMLSS. |
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| Authors: | Shomura T; First Department of Internal Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto 390-8621, Japan., Wada Y; First Department of Internal Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto 390-8621, Japan. Electronic address: yosuke@shinshu-u.ac.jp., Hanaoka M; First Department of Internal Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto 390-8621, Japan. |
| Source: | Respiratory investigation [Respir Investig] 2025 Nov; Vol. 63 (6), pp. 1139-1145. Date of Electronic Publication: 2025 Sep 20. |
| Publication Type: | Journal Article; Review |
| Language: | English |
| Journal Info: | Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101581124 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2212-5353 (Electronic) Linking ISSN: 22125345 NLM ISO Abbreviation: Respir Investig Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Amsterdam : Elsevier |
| MeSH Terms: | Lung*/physiology , Models, Statistical* , Respiratory Function Tests*/standards , Respiratory Function Tests*/methods, Humans ; Algorithms ; Reference Values ; Spirometry |
| Abstract: | Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest. To accurately interpret lung function test (LFTs) results, it is necessary to appropriately select the lung function reference value prediction equation implemented in the measuring equipment of each medical institution. The American Thoracic Society (ATS) and European Respiratory Society (ERS) task force, known as the Global Lung Function Initiative (GLI), recommends the use of a lung function standard value prediction equation that can calculate continuous standard values across a wide age range. Generalized additive models for location, scale, and shape (GAMLSS) are statistical techniques used to create accurate percentiles for a wide age range. This prediction equation was created using the lambda, mu, and sigma (LMS) method, a subtype of a statistical method known as generalized additive models for location, scale, and shape (GAMLSS). Lung function equations created using the LMS method can be used to calculate the z-score, which can contribute to a more accurate interpretation of the results. As for the contents of this review, an overview of the development of equations for predicting lung function using GAMLSS, such as spirometry, diffusion capacity, and static lung volume, is provided in the first portion of this review. The second section of this review compiles the statistical knowledge required to develop lung function reference-value prediction algorithms based on GAMLSS. This section briefly explains how to calculate the z-score and provides advice on addressing ethnic diversity in the lung function standard value prediction equations. (Copyright © 2025 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.) |
| Contributed Indexing: | Keywords: Lung function; Spirometry; Static lung volume; The carbon monoxide transfer factor |
| Entry Date(s): | Date Created: 20250921 Date Completed: 20251119 Latest Revision: 20251121 |
| Update Code: | 20251122 |
| DOI: | 10.1016/j.resinv.2025.09.010 |
| PMID: | 40975970 |
| Database: | MEDLINE |
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Nájsť tento článok vo Web of Science | Abstract: | Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest.<br />To accurately interpret lung function test (LFTs) results, it is necessary to appropriately select the lung function reference value prediction equation implemented in the measuring equipment of each medical institution. The American Thoracic Society (ATS) and European Respiratory Society (ERS) task force, known as the Global Lung Function Initiative (GLI), recommends the use of a lung function standard value prediction equation that can calculate continuous standard values across a wide age range. Generalized additive models for location, scale, and shape (GAMLSS) are statistical techniques used to create accurate percentiles for a wide age range. This prediction equation was created using the lambda, mu, and sigma (LMS) method, a subtype of a statistical method known as generalized additive models for location, scale, and shape (GAMLSS). Lung function equations created using the LMS method can be used to calculate the z-score, which can contribute to a more accurate interpretation of the results. As for the contents of this review, an overview of the development of equations for predicting lung function using GAMLSS, such as spirometry, diffusion capacity, and static lung volume, is provided in the first portion of this review. The second section of this review compiles the statistical knowledge required to develop lung function reference-value prediction algorithms based on GAMLSS. This section briefly explains how to calculate the z-score and provides advice on addressing ethnic diversity in the lung function standard value prediction equations.<br /> (Copyright © 2025 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.) |
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| ISSN: | 2212-5353 |
| DOI: | 10.1016/j.resinv.2025.09.010 |