Predictors of positive airway pressure therapy termination in the first year: analysis of big data from a German homecare provider

• Main Authors: Holger Woehrle, Michael Arzt, Andrea Graml, Ingo Fietze, Peter Young, Helmut Teschler, Joachim H. Ficker
• Format: Article
• Language: English
• Published: BMC 2018-12-01
• Series: BMC Pulmonary Medicine
• Subjects: Positive airway pressure; Compliance; Patient phenotype; Therapy termination
• Online Access: http://link.springer.com/article/10.1186/s12890-018-0748-8

Abstract Background There is a lack of robust data about factors predicting continuation (or termination) of positive airway pressure therapy (PAP) for sleep apnea. This analysis of big data from a German homecare provider describes patients treated with PAP, analyzes the therapy termination rate over the first year, and investigates predictive factors for therapy termination. Methods Data from a German homecare service provider were analyzed retrospectively. Patients who had started their first PAP therapy between September 2009 and April 2014 were eligible. Patient demographics, therapy start date, and the date of and reason for therapy termination were obtained. At 1 year, patients were classified as having compliance-related therapy termination or remaining on therapy. These groups were compared, and significant predictors of therapy termination determined. Results Of 98,329 patients included in the analysis, 11,702 (12%) terminated PAP therapy within the first year (after mean 171 ± 91 days). There was a U-shaped relationship between therapy termination and age; therapy termination was higher in the youngest (< 30 years, 15.5%) and oldest (≥ 80 years, 19.8%) patients, and lower in those aged 50–59 years (9.9%). Therapy termination was significantly more likely in females versus males (hazard ratio 1.48, 95% confidence interval 1.42–1.54), in those with public versus private insurance (1.75, 1.64–1.86) and in patients whose first device was automatically adjusting or fixed-level continuous positive airway pressure versus bilevel or adaptive servo-ventilation (1.28, 1.2–1.38). Conclusions This analysis of the largest dataset investigating PAP therapy termination identified a number of predictive factors. These can help health care providers chose the most appropriate PAP modality, identify specific patient phenotypes at higher risk of stopping PAP and target interventions to support ongoing therapy to these groups, as well as allow them to develop a risk stratification tool.