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

N. G. P. Den Teuling*, Edwin R. van den Heuvel, Mark S. Aloia, Steffen Pauws

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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.
Original languageEnglish
Article number269
Number of pages15
JournalBMC Medical Research Methodology
Volume21
Issue number269
DOIs
Publication statusPublished - 1 Dec 2021

Keywords

  • Obstructive sleep apnea, CPAP therapy, Treatment adherence, Latent-class trajectory modeling, Multilevel mixture modeling, Hurdle modeling, Heteroskedastic modeling, Intensive longitudinal data

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