Abstract

Background. The lung clearance index (LCI) is a sensitive lung function index that is used to detect early lung disease changes in children with cystic fibrosis (CF). This study aimed to define the predictive role of baseline LCI, along with other potential factors on the change in forced expiratory volume in one second (FEV1) during one-year follow-up in CF patients who had a percent predicted (pp) FEV1≥80.

Methods. LCI was concurrently performed on 57 CF patients who had ppFEV1 ≥80 at month zero. The ppFEV1 decline was evaluated prospectively during the one year follow up. The primary outcome of ppFEV1 decline in the study group in one year was dichotomized according to the median value for the decline in ppFEV1, which was 3.7. The LCI value predicting ppFEV1 decline at the end of one year was calculated with receiver operating characteristic curve analysis. Regression analysis was performed. Furthermore, a decision tree was constructed using classification and regression tree methods to better define the potential effect of confounders on the ppFEV1 decline.

Results. The LCI value for predicting ppFEV1 decline >3.7% at the end of one year was 8.2 (area under the curve: 0.80) Multivariable regression analysis showed that the absence of the F508del mutation in at least one allele, LCI >8.2 and initial FEV1 z-score were predictors of a ppFEV1 decline >3.7 (p<0.001). Factors altering ppFEV1 decline>3.7% at the end of one-year evaluated by decision trees were as follows: initial FEV1 z-score, type of CFTR mutation, LCI value and initial weight-for-age z-score.

Conclusions. LCI is sensitive for predicting ppFEV1 decline in patients with ppFEV1 ≥80 along with the initial FEV1-z-score and type of CFTR mutation.

Keywords: cystic fibrosis, multiple breath wash-out, lung clearance index, spirometry, FEV1 decline

How to cite

1.
Özsezen B, Yalçın E, Emiralioğlu N, et al. The predictive role of lung clearance index on FEV1 decline in cystic fibrosis. Turk J Pediatr 2024; 66: 297-308. https://doi.org/10.24953/turkjpediatr.2024.4516

References

  1. Paranjape SM, Mogayzel PJ. Cystic fibrosis in the era of precision medicine. Paediatr Respir Rev 2018; 25: 64-72. https://doi.org/10.1016/j.prrv.2017.03.001
  2. Fowler WS, Cornish ER, Kety SS. Lung function studies. VIII. Analysis of alveolar ventilation by pulmonary N2 clearance curves. J Clin Invest 1952; 31: 40-50. https://doi.org/10.1172/JCI102575
  3. Fretzayas A, Douros K, Moustaki M, Loukou I. Applications of lung clearance index in monitoring children with cystic fibrosis. World J Clin Pediatr 2019; 8: 15-22. https://doi.org/10.5409/wjcp.v8.i2.15
  4. Harun SN, Wainwright C, Klein K, Hennig S. A systematic review of studies examining the rate of lung function decline in patients with cystic fibrosis. Paediatr Respir Rev 2016; 20: 55-66. https://doi.org/10.1016/j.prrv.2016.03.002
  5. Rosenstein BJ, Cutting GR. The diagnosis of cystic fibrosis: a consensus statement. Cystic Fibrosis Foundation Consensus Panel. J Pediatr 1998; 132: 589-595. https://doi.org/10.1016/s0022-3476(98)70344-0
  6. Malhotra RK, Indrayan A. A simple nomogram for sample size for estimating sensitivity and specificity of medical tests. Indian J Ophthalmol 2010; 58: 519-522. https://doi.org/10.4103/0301-4738.71699
  7. Ulusal Kistik Fibrozis Kayıt Sistemi: 2019 Yılı Verileri. Available at: https://www.kistikfibrozisturkiye.org/wp-content/uploads/2021/05/KF-Rapor-05.03.2021-1.pdf
  8. Fuchs HJ, Borowitz DS, Christiansen DH, et al. Effect of aerosolized recombinant human DNase on exacerbations of respiratory symptoms and on pulmonary function in patients with cystic fibrosis. The Pulmozyme Study Group. N Engl J Med 1994; 331: 637-642. https://doi.org/10.1056/NEJM199409083311003
  9. Lee TW, Brownlee KG, Conway SP, Denton M, Littlewood JM. Evaluation of a new definition for chronic Pseudomonas aeruginosa infection in cystic fibrosis patients. J Cyst Fibros 2003; 2: 29-34. https://doi.org/10.1016/S1569-1993(02)00141-8
  10. Robinson PD, Latzin P, Verbanck S, et al. Consensus statement for inert gas washout measurement using multiple- and single- breath tests. Eur Respir J 2013; 41: 507-522. https://doi.org/10.1183/09031936.00069712
  11. Jensen R, Stanojevic S, Klingel M, et al. A systematic approach to multiple breath nitrogen washout test quality. PLoS One 2016; 11: e0157523. https://doi.org/10.1371/journal.pone.0157523
  12. Robinson PD, Latzin P, Ramsey KA, et al. Preschool multiple-breath washout testing. An official American Thoracic Society technical statement. Am J Respir Crit Care Med 2018; 197: e1-e19. https://doi.org/10.1164/rccm.201801-0074ST
  13. Rosenfeld M, Allen J, Arets BHGM, et al. An official American Thoracic Society workshop report: optimal lung function tests for monitoring cystic fibrosis, bronchopulmonary dysplasia, and recurrent wheezing in children less than 6 years of age. Ann Am Thorac Soc 2013; 10: S1-S11. https://doi.org/10.1513/AnnalsATS.201301-017ST
  14. Miller MR, Hankinson J, Brusasco V, et al. Standardisation of spirometry. Eur Respir J 2005; 26: 319-338. https://doi.org/10.1183/09031936.05.00034805
  15. Quanjer PH, Stanojevic S, Cole TJ, et al. Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations. Eur Respir J 2012; 40: 1324-1343. https://doi.org/10.1183/09031936.00080312
  16. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2020. Available at: http://www.r-project.org
  17. Therneau T, Atkinson B, Ripley B. Rpart: Recursive partitioning and regression trees. R package version 4.1.19. 2022. Available at: https://cran.r-project.org/web/packages/rpart/index.html
  18. Torgo L. performanceEstimation: An infra-structure for performance estimation of predictive models. R package version 1.1.0. 2016. Available at: https://cran.r-project.org/web/packages/performanceEstimation/index.html
  19. Konstan MW, Morgan WJ, Butler SM, et al. Risk factors for rate of decline in forced expiratory volume in one second in children and adolescents with cystic fibrosis. J Pediatr 2007; 151: 134-139, 139.e1. https://doi.org/10.1016/j.jpeds.2007.03.006
  20. Cogen J, Emerson J, Sanders DB, et al. Risk factors for lung function decline in a large cohort of young cystic fibrosis patients. Pediatr Pulmonol 2015; 50: 763-770. https://doi.org/10.1002/ppul.23217
  21. Vandenbranden SL, McMullen A, Schechter MS, et al. Lung function decline from adolescence to young adulthood in cystic fibrosis. Pediatr Pulmonol 2012; 47: 135-143. https://doi.org/10.1002/ppul.21526
  22. Hollander FM, de Roos NM, Heijerman HGM. The optimal approach to nutrition and cystic fibrosis: latest evidence and recommendations. Curr Opin Pulm Med 2017; 23: 556-561. https://doi.org/10.1097/MCP.0000000000000430
  23. Horsley A. Lung clearance index in the assessment of airways disease. Respir Med 2009; 103: 793-799. https://doi.org/10.1016/j.rmed.2009.01.025
  24. Fuchs SI, Sturz J, Junge S, Ballmann M, Gappa M. A novel sidestream ultrasonic flow sensor for multiple breath washout in children. Pediatr Pulmonol 2008; 43: 731-738. https://doi.org/10.1002/ppul.20825
  25. Anagnostopoulou P, Latzin P, Jensen R, et al. Normative data for multiple breath washout outcomes in school-aged Caucasian children. Eur Respir J 2020; 55: 1901302. https://doi.org/10.1183/13993003.01302-2019
  26. Ellemunter H, Fuchs SI, Unsinn KM, et al. Sensitivity of lung clearance index and chest computed tomography in early CF lung disease. Respir Med 2010; 104: 1834-1842. https://doi.org/10.1016/j.rmed.2010.06.010
  27. Kraemer R, Blum A, Schibler A, Ammann RA, Gallati S. Ventilation inhomogeneities in relation to standard lung function in patients with cystic fibrosis. Am J Respir Crit Care Med 2005; 171: 371-378. https://doi.org/10.1164/rccm.200407-948OC
  28. Aurora P, Stanojevic S, Wade A, et al. Lung clearance index at 4 years predicts subsequent lung function in children with cystic fibrosis. Am J Respir Crit Care Med 2011; 183: 752-758. https://doi.org/10.1164/rccm.200911-1646OC
  29. Sonneveld N, Stanojevic S, Amin R, et al. Lung clearance index in cystic fibrosis subjects treated for pulmonary exacerbations. Eur Respir J 2015; 46: 1055-1064. https://doi.org/10.1183/09031936.00211914
  30. Vermeulen F, Proesmans M, Boon M, Havermans T, De Boeck K. Lung clearance index predicts pulmonary exacerbations in young patients with cystic fibrosis. Thorax 2014; 69: 39-45. https://doi.org/10.1136/thoraxjnl-2013-203807
  31. Amin R, Subbarao P, Jabar A, et al. Hypertonic saline improves the LCI in paediatric patients with CF with normal lung function. Thorax 2010; 65: 379-383. https://doi.org/10.1136/thx.2009.125831
  32. Lombardi E, Gambazza S, Pradal U, Braggion C. Lung clearance index in subjects with cystic fibrosis in Italy. Ital J Pediatr 2019; 45: 56. https://doi.org/10.1186/s13052-019-0647-5
  33. Kurz JM, Ramsey KA, Rodriguez R, et al. Association of lung clearance index with survival in individuals with cystic fibrosis. Eur Respir J 2022; 59: 2100432. https://doi.org/10.1183/13993003.00432-2021
  34. Perrem L, Rayment JH, Ratjen F. The lung clearance index as a monitoring tool in cystic fibrosis: ready for the clinic? Curr Opin Pulm Med 2018; 24: 579-585. https://doi.org/10.1097/MCP.0000000000000515
  35. Oude Engberink E, Ratjen F, Davis SD, Retsch-Bogart G, Amin R, Stanojevic S. Inter-test reproducibility of the lung clearance index measured by multiple breath washout. Eur Respir J 2017; 50: 1700433. https://doi.org/10.1183/13993003.00433-2017