A prognostic model of excessive lung function decline among Québec apprentices: a cohort exposed to occupational sensitizing agents

  • Alfi Afadiyanti Parfi Research Center, Hôpital du Sacré-Coeur de Montréal, Montréal, Canada https://orcid.org/0000-0002-1593-9526
  • Mahsa Taghiakbari Research Institute of the McGill University Health Center, Montréal, Canada https://orcid.org/0000-0001-6011-3400
  • Meshack Achore Research Center, Hôpital du Sacré-Coeur de Montréal, Montréal, Canada https://orcid.org/0000-0002-8321-7293
  • Denyse Gautrin Research Center, Hôpital du Sacré-Coeur de Montréal, Montréal, Canada
  • Gleb Bezgin McGill Centre for Studies in Aging, Montréal, Canada
  • Eva Suarthana Research Center, Hôpital du Sacré-Coeur de Montréal, Montréal, Canada; Research Institute of the McGill University Health Center, Montréal, Canada
Keywords: excessive decline, lung function, model, prognosis
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Abstract

BACKGROUND Forced expiratory volume in 1 second (FEV1) decline as a predictor of lung-related health problems is widely observed, but not fully investigated. This study aimed to develop models to predict FEV1 decline among apprentices exposed to sensitizing agents.

METHODS Of 692 apprentices recruited and followed in 3.6–17.3 years, 292 were exposed to low-molecular weight agents. The analysis was restricted to 357 apprentices with complete lung function assessment at the end of their training with a minimum of 5-year follow-up. According to the American Thoracic Society guideline, a mean FEV₁ decline >60 ml/year was defined as “accelerated.” Descriptive statistics and Cox regression analysis were utilized to determine its predictors. To develop the prognostic models, we used a logistic regression analysis adjusted for the follow-up duration. The accuracy of the models was quantified using calibration and discrimination measures.

RESULTS Of 357 subjects, 62 (17.4%) had an excessive FEV1 decline post-apprenticeship. The questionnaire model (model 1), which included male sex, wheezing, and exposure to isocyanate or animal allergens during the apprenticeship, showed a reasonable discriminative ability (area under the receiver operating characteristics curve [AUC] of 0.67, 95% CI = 0.59–0.75). Adding the percent-predicted FEV₁ value at the end of apprenticeship significantly increased the discriminative ability of the model (model 4) (AUC = 0.762, 95% CI = 0.694–0.829) with a good calibration and reasonable internal validity.

CONCLUSIONS We developed a model for accelerated lung function decline with a good accuracy and internal validity. However, external validation of the model is necessary.

References

  1. Redlich CA, Tarlo SM, Hankinson JL, Townsend MC, Eschenbacher WL, Von Essen SG, et al. Official American Thoracic Society technical standards: Spirometry in the occupational setting. Am J Respir Crit Care Med. 2014;189(8):983-93. https://doi.org/10.1164/rccm.201402-0337ST

  2. Redlich CA, Tarlo SM. Longitudinal assessment of lung function decline in the occupational setting. Curr Opin Allergy Clin Immunol. 2015;15(2):145-9. https://doi.org/10.1097/ACI.0000000000000153

  3. Wang ML, Avashia BH, Wood J, Petsonk EL. Excessive longitudinal FEV1 decline and risks to future health: a case-control study. Am J Ind Med. 2009;52(12):909-15. https://doi.org/10.1002/ajim.20764

  4. Peters CE, Demers PA, Sehmer J, Karlen B, Kennedy SM. Early changes in respiratory health in trades' apprentices and physician visits for respiratory illnesses later in life. Occup Environ Med. 2010;67:237-43. https://doi.org/10.1136/oem.2008.042663

  5. Lee PN, Fry JS. Systematic review of the evidence relating FEV1 decline to giving up smoking. BMC Med. 2010;8:84. https://doi.org/10.1186/1741-7015-8-84

  6. Pfidze TD. The rate of decline in lung function (FEV1) in workers exposed to aluminium production dust at a smelter in Australia. Intern Med J. 2017;47(S3):5-5. https://doi.org/10.1111/imj.3_13456

  7. Gautrin D, Ghezzo H, Infante-Rivard C, Magnan M, L'archevêque J, Suarthana E, et al. Long-term outcomes in a prospective cohort of apprentices exposed to high-molecular-weight agents. Am J Respir Crit Care Med. 2008;177(8):871-9. https://doi.org/10.1164/rccm.200707-991OC

  8. Gautrin D, Ghezzo H, Infante-Rivard C, Malo JL. Incidence and determinants of IgE-mediated sensitization in apprentices. A prospective study. Am J Respir Crit Care Med. 2000;162(4 Pt 1):1222-8. https://doi.org/10.1164/ajrccm.162.4.2001023

  9. Saab L, Gautrin D, Lavoué J, Suarthana E. Postapprenticeship isocyanate exposure and risk of work-related respiratory symptoms using an asthma-specific job exposure matrix, self-reported and expert-rated exposure estimates. J Occup Environ Med. 2014;56(2):125-7. https://doi.org/10.1097/JOM.0000000000000075

  10. El-Zein M, Infante-Rivard C, Malo JL, Gautrin D. Is metal fume fever a determinant of welding related respiratory symptoms and/or increased bronchial responsiveness? A longitudinal study. Occup Environ Med. 2005;62(1):688-94. https://doi.org/10.1136/oem.2004.018796

  11. Taghiakbari M, Castano R, Parfi AA, Achore M, El-Zein M, Rhazi MS, et al. A cross-sectional assessment of rhinitis symptoms and nasal patency in relation to welding exposure. Am J Respir Crit Care Med. 2018;198(7):958-61. https://doi.org/10.1164/rccm.201802-0385LE

  12. Achore M, Taghiakbari M, Parfi AA, Lemiere C, El-Zein M, Rhazi M, et al. Evaluation of long-term respiratory effects of exposure to welding fumes. Maj Kedokt UKI. 2019;35(1):2-8. https://doi.org/10.33541/mkvol34iss2pp60

  13. Austin PC, Steyerberg EW. Events per variable (EPV) and the relative performance of different strategies for estimating the out-of-sample validity of logistic regression models. Stat Methods Med Res. 2017;26(2):796-808. https://doi.org/10.1177/0962280214558972

  14. Gautrin D, Infante-Rivard C, Dao TV, Magnan-Larose M, Desjardins D, Malo JL. Specific IgE-dependent sensitization, atopy, and bronchial hyperresponsiveness in apprentices starting exposure to protein-derived agents. Am J Respir Crit Care Med. 1997;155(6):1841-7. https://doi.org/10.1164/ajrccm.155.6.9196084

  15. Burney PG, Laitinen LA, Perdrizet S, Huckauf H, Tattersfield AE, Chinn S, et al. Validity and repeatability of the IUATLD (1984) Bronchial Symptoms Questionnaire: an international comparison. Eur Respir J. 1989;2(10):940-5. 16. Pepys J. Types of allergic reaction. Clin Exp Allergy. 1973;3(s1):491-506. https://doi.org/10.1111/j.1365-2222.1973.tb03057.x

  16. Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, et al. Standardization of spirometry, 1994 Update. American Thoracic Society. Am J Respir Crit Care Med. 1995;152(3):1107-36. https://doi.org/10.1164/ajrccm.152.3.7663792

  17. Cockcroft DW, Killian DN, Mellon JJ, Hargreave FE. Bronchial reactivity to inhaled histamine: a method and clinical survey. Clin Allergy. 1977;7(3):235-43. https://doi.org/10.1111/j.1365-2222.1977.tb01448.x

  18. Townsend MC; Occupational and Environmental Lung Disorders Committee. Spirometry in the occupational health setting--2011 update. J Occup Environ Med. 2011;53(5):569-84. https://doi.org/10.1097/JOM.0b013e31821aa964

  19. Hnizdo E, Glindmeyer HW, Petsonk EL. Workplace spirometry monitoring for respiratory disease prevention: a methods review. Int J Tuberc Lung Dis. 2010;14(7):796-805.

  20. Malo JL, Pineau L, Cartier A, Martin RR. Reference values of the provocative concentrations of methacholine that cause 6% and 20% changes in forced expiratory volume in one second in a normal population. Am Rev Respir Dis. 1983;128(1):8-11. https://doi.org/10.1164/arrd.1983.128.1.8

  21. Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15(4):361-87. https://doi.org/10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4

  22. Steyerberg EW, Vickers AJ, Cook NR, Gerds T, Gonen M, Obuchowski N, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology. 2010;21(1):128-38. https://doi.org/10.1097/EDE.0b013e3181c30fb2

  23. Brier GW. Verification of forecasts expressed in terms of probability. Mon Weather Rev. 1950;78(1):1-3. https://doi.org/10.1175/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2

  24. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982;143(1):29-36. https://doi.org/10.1148/radiology.143.1.7063747

  25. Donders AR, van der Heijden GJ, Stijnen T, Moons KG. Review: a gentle introduction to imputation of missing values. J Clin Epidemiol. 2006;59(10):1087-91. https://doi.org/10.1016/j.jclinepi.2006.01.014

  26. van der Heijden GJ, Donders AR, Stijnen T, Moons KG. Imputation of missing values is superior to complete case analysis and the missing-indicator method in multivariable diagnostic research: a clinical example. J Clin Epidemiol. 2006;59(10):1102-9. https://doi.org/10.1016/j.jclinepi.2006.01.015

  27. van Buuren S, Groothuis-Oudshoorn K. mice: Multivariate imputation by chained equations in R. J Stat Softw. 2011;45(3):1-67. https://doi.org/10.18637/jss.v045.i03

  28. IBM Corp. Released 2017. IBM SPSS Statistics for Windows, version 25.0. Armonk: IBM Corp.; 2017.

  29. R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing [Internet]. Vienna; 2014 [cited 2021 Jan 21]. Available from: http//www.r-project.org/.

  30. Alzola C, Harrell F. An introduction to S and the Hmisc and design libraries [Internet]. 2006 [cited 2021 Jan 21]. Available from: https://cran.r-project.org/doc/contrib/Alzola+Harrell-Hmisc-Design-Intro.pdf.

  31. Dahlqvist M, Tornling G, Plato N, Ulfvarson U. Effects within the week on forced vital capacity are correlated with long term changes in pulmonary function: reanalysis of studies on car painters exposed to isocyanate. Occup Environ Med. 1995;52(3):192-5. https://doi.org/10.1136/oem.52.3.192

  32. De S. Annual change in spirometric parameters among patients affected in Bhopal gas disaster: a retrospective observational study. Lung India. 2013;30(2):103-107. https://doi.org/10.4103/0970-2113.110414

  33. Pralong J, Miedinger D, Suarthana E, Keidel D, Beckmeyer-Borowko A, Schindler C, et al. Prognostic model for accelerated decline in lung function due to occupational sensitizers: SAPALDIA study. Eur Respir J. 2017;50(Suppl 61):PA1247. https://doi.org/10.1183/1393003.congress-2017.PA1247

Published
2021-03-25
How to Cite
1.
Parfi AA, Taghiakbari M, Achore M, Gautrin D, Bezgin G, Suarthana E. A prognostic model of excessive lung function decline among Québec apprentices: a cohort exposed to occupational sensitizing agents. Med J Indones [Internet]. 2021Mar.25 [cited 2021Jun.21];30(1):45-3. Available from: https://mji.ui.ac.id/journal/index.php/mji/article/view/4530
Section
Clinical Research