A latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy

Abstract Background Sleep apnea patients on CPAP therapy exhibit differences in how they adhere to the therapy. Previous studies have demonstrated the benefit of describing adherence in terms of discernible longitudinal patterns. However, these analyses have been done on a limited number of patients...

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Autores principales:	Niek G. P. Den Teuling, Edwin R. van den Heuvel, Mark S. Aloia, Steffen C. Pauws
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Obstructive sleep apnea CPAP therapy Treatment adherence Latent-class trajectory modeling Multilevel mixture modeling Hurdle modeling Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/18ebcfbb87574363a8eae9bf5ab295e3
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spelling	oai:doaj.org-article:18ebcfbb87574363a8eae9bf5ab295e32021-12-05T12:24:44ZA latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy10.1186/s12874-021-01407-61471-2288https://doaj.org/article/18ebcfbb87574363a8eae9bf5ab295e32021-12-01T00:00:00Zhttps://doi.org/10.1186/s12874-021-01407-6https://doaj.org/toc/1471-2288Abstract Background Sleep apnea patients on CPAP therapy exhibit differences in how they adhere to the therapy. Previous studies have demonstrated the benefit of describing adherence in terms of discernible longitudinal patterns. However, these analyses have been done on a limited number of patients, and did not properly represent the temporal characteristics and heterogeneity of adherence. Methods We illustrate the potential of identifying patterns of adherence with a latent-class heteroskedastic hurdle trajectory approach using generalized additive modeling. The model represents the adherence trajectories on three aspects over time: the daily hurdle of using the therapy, the daily time spent on therapy, and the day-to-day variability. The combination of these three characteristics has not been studied before. Results Applying the proposed model to a dataset of 10,000 patients in their first three months of therapy resulted in nine adherence groups, among which 49% of patients exhibited a change in adherence over time. The identified group trajectories revealed a non-linear association between the change in the daily hurdle of using the therapy, and the average time on therapy. The largest difference between groups was observed in the patient motivation score. The adherence patterns were also associated with different levels of high residual AHI, and day-to-day variability in leakage. Conclusion The inclusion of the hurdle model and the heteroskedastic model into the mixture model enabled the discovery of additional adherence patterns, and a more descriptive representation of patient behavior over time. Therapy adherence was mostly affected by a lack of attempts over time, suggesting that encouraging these patients to attempt therapy on a daily basis, irrespective of the number of hours used, could drive adherence. We believe the methodology is applicable to other domains of therapy or medication adherence.Niek G. P. Den TeulingEdwin R. van den HeuvelMark S. AloiaSteffen C. PauwsBMCarticleObstructive sleep apneaCPAP therapyTreatment adherenceLatent-class trajectory modelingMultilevel mixture modelingHurdle modelingMedicine (General)R5-920ENBMC Medical Research Methodology, Vol 21, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Obstructive sleep apnea CPAP therapy Treatment adherence Latent-class trajectory modeling Multilevel mixture modeling Hurdle modeling Medicine (General) R5-920
spellingShingle	Obstructive sleep apnea CPAP therapy Treatment adherence Latent-class trajectory modeling Multilevel mixture modeling Hurdle modeling Medicine (General) R5-920 Niek G. P. Den Teuling Edwin R. van den Heuvel Mark S. Aloia Steffen C. Pauws A latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy
description	Abstract Background Sleep apnea patients on CPAP therapy exhibit differences in how they adhere to the therapy. Previous studies have demonstrated the benefit of describing adherence in terms of discernible longitudinal patterns. However, these analyses have been done on a limited number of patients, and did not properly represent the temporal characteristics and heterogeneity of adherence. Methods We illustrate the potential of identifying patterns of adherence with a latent-class heteroskedastic hurdle trajectory approach using generalized additive modeling. The model represents the adherence trajectories on three aspects over time: the daily hurdle of using the therapy, the daily time spent on therapy, and the day-to-day variability. The combination of these three characteristics has not been studied before. Results Applying the proposed model to a dataset of 10,000 patients in their first three months of therapy resulted in nine adherence groups, among which 49% of patients exhibited a change in adherence over time. The identified group trajectories revealed a non-linear association between the change in the daily hurdle of using the therapy, and the average time on therapy. The largest difference between groups was observed in the patient motivation score. The adherence patterns were also associated with different levels of high residual AHI, and day-to-day variability in leakage. Conclusion The inclusion of the hurdle model and the heteroskedastic model into the mixture model enabled the discovery of additional adherence patterns, and a more descriptive representation of patient behavior over time. Therapy adherence was mostly affected by a lack of attempts over time, suggesting that encouraging these patients to attempt therapy on a daily basis, irrespective of the number of hours used, could drive adherence. We believe the methodology is applicable to other domains of therapy or medication adherence.
format	article
author	Niek G. P. Den Teuling Edwin R. van den Heuvel Mark S. Aloia Steffen C. Pauws
author_facet	Niek G. P. Den Teuling Edwin R. van den Heuvel Mark S. Aloia Steffen C. Pauws
author_sort	Niek G. P. Den Teuling
title	A latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy
title_short	A latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy
title_full	A latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy
title_fullStr	A latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy
title_full_unstemmed	A latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy
title_sort	latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on cpap therapy
publisher	BMC
publishDate	2021
url	https://doaj.org/article/18ebcfbb87574363a8eae9bf5ab295e3
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A latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy

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