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Sleep breathing disorders wg summit 2018 ms (1)

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WG meeting from REG Summit 2018

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Sleep breathing disorders wg summit 2018 ms (1)

  1. 1. Sleep Breathing Disorders Working Group Meeting CHAIR: Mihaela Stefan DATE: Thursday 22nd March 2018 TIME: 11:00–12:00 VENUE: Park Plaza Hotel, Amsterdam Airport
  2. 2. Agenda 1) Update on current project ‘Impact of obstructive sleep apnoea diagnosis on healthcare resource utilisation in patients with obstructive lung disease’ 2) Any new project ideas?
  3. 3. 1) Update on current project Impact of obstructive sleep apnoea diagnosis on healthcare resource utilisation in patients with obstructive lung disease
  4. 4. Background: OLDOSA • “OLD-OSA overlap syndrome” refers to the coexistence of OLD (obstructive lung disease: COPD and asthma) and OSA • A broader umbrella term of “OLDOSA syndrome” is proposed1 1. Ioachimescu OC, et al. Respirology. 2013;18:421-31
  5. 5. Background: OLDOSA • Obesity is a growing problem worldwide1 and predisposes to OSA.2 • Positive correlation between baseline BMI - later development of asthma3 • Rhinitis4,5 and GERD6–8 are common risk factors to both asthma and OSA • OSA is an independent risk factor for asthma exacerbations8 • Prevalence of OSA in asthma 23-50% ~ on asthma severity9 1.WHO: http://www.who.int/mediacentre/factsheets/fs311/en/ . 2.Romero-Corral A, et al. Chest. 2010;137:711–719; 3. Delgado J, et al. J Inv Aller Clin Immunol. 2008;18:420-5; 4. Staevska MT, et al. Curr Allergy Asthma Rep,2004;4:193; 5. Ing AJ, et al. Am J Med. 2000;1 08(Suppl 4a):120S–5S; 6. Avidan B, et al. Gut. 2001;49:767–72; 7. Cibella F, et al. Am J Med. 2001;111(Suppl 8A):31S–6S; 8. Ten Brinke A, et al. Eur Respir J. 2005;26:812–8; 9. Julien JY, et al. JACI. 2009;124:371-6;
  6. 6. Background: OLDOSA • COPD – OSA = Overlap Syndrome • Increasing BMI and smoking history positively correlate with the likelihood of OSA in COPD patients1 • Patients with COPD and OSA have higher mortality than those with COPD and treatment with CPAP reduces COPD exacerbations2 1. Steveling EH, et al. Predictors of the overlap syndrome and its association with comorbidities in patients with chronic obstructive pulmonary disease.Respiration 2014; 88:451-457 2. Marin JM et al. AmJ Respir. Crit, Care. Med. 2010;182:325-31
  7. 7. Main Research Question Does OSA diagnosis (CPAP therapy) reduces utilization of healthcare services in patients with OLDOSA? Context: - Within OPCRD, a UK primary care ‘enriched’ database; data from ≥550 UK general practices & ~2.5 million patients - Focus on acute care and pharmaceuticals Hypothesis: change in the trajectory of utilization after OSA diagnosis
  8. 8. Prior Research Study Population Design Results Comments Banno K et al. Sleep 2009;32 Women: 223 obese with apnea, matched obese and non-obese controls Retrospective over 10 yrs pre- diagnosis; utilization and costs Greater utilization and costs in OSA Pre-diagnosis only Cai Q et al. Am J Manag Care 2012;18(6) 13,983 with PAP, 1,441 not on PAP Retrospective over 2 yrs post PAP; costs, hospitalization Lower hospitalization rate in PAP group after PAP start; adjusted costs lower in PAP group Post-PAP only, required 2 years of continuous membership Albarak M et al. Sleep 2015 342 males, ~1360 controls matched by age, gender, geography; Retrospective, group analysis by -5, -1, +2 and +5 years Decrease in fees in CPAP group, increase in controls (hundreds of dollars) Pre and post CPAP
  9. 9. Initially, we will focus on Aims 1 & 2 1) Evaluate the prevalence of sleep-related breathing disorder (SBD) and continuous positive airway pressure (CPAP) therapy prescribing in a primary care population in the UK. 2) Assess SBD patient characteristics (clinical and demographic) in those in whom CPAP treatment is recorded vs not recorded. 3) To evaluate the impact of SBD diagnosis (with and without CPAP treatment) on clinical outcomes and healthcare resource utilization in SBD patients with comorbid obstructive lung disease (OLD), in the UK Hypothesis: It is assumed that a diagnosis of SBD/OSA (surrogate marker for treatment) will be associated with a decrease in the use of health care resources. Aims
  10. 10. Methodology for aims 1&2 Data source: OPCRD Inclusion criteria: • Read code for SBD testing/diagnosis ever • ≥18 years of age Outcomes: • Frequency of testing for SBD • Prevalence of SBD diagnosis • Prevalence of CPAP (or other treatment PAP/NIV) prescribing Including the prevalence in those with a diagnosis of asthma, COPD or both asthma and COPD. • Characterisation of patients (demographics and clinical characteristics) with SDB including a comparison of those with and without CPAP treatment.
  11. 11. Methodology for aim 3 Data source: OPCRD Inclusion criteria: • Read code for SBD testing/diagnosis ever • ≥18 years of age • Three years of continuous data: ≥1 year prior to the first recorded SDB code (“index date”) and ≥2 years immediately after index date. • An active OLD diagnosis Asthma subpopulation: Read code for asthma ever prior to index date and ≥2 asthma prescriptions in baseline year; no COPD Read code in the 3-year study period COPD subpopulation: Read code for COPD prior to index date and ≥2 COPD prescriptions in the baseline year; no asthma Read code in the 3-year study period Asthma & COPD subpopulation: Read codes for Asthma and COPD within 2 years of each other ever prior to the index date and ≥2 OLD prescriptions in the baseline year; no asthma or COPD resolved codes within the study period
  12. 12. Outcomes for aim 3 The number of any of the following events coded for a lower respiratory complaint in the 1st and 2nd year of the outcome period, compared to the 1 yr baseline period: • Hospital admission • Emergency Room / Accident & Emergency attendance • Acute course of oral steroid prescription • Antibiotics prescriptions. • Primary care consultation resulting in an oral steroid prescription • Primary care consultation resulting in an antibiotic prescription Analysis: Within-Population pre and post diagnosis of SDB Outcome comparison between pre- and post index date periods, for: • All patients • All OLD sub-populations (asthma, COPD, asthma & COPD)
  13. 13. Covariates Demographics • Age • BMI • Sex • Smoking Status Clinical Characteristics • OLD diagnosis (Asthma and/or COPD) • Spirometry • COPD patients: GOLD severity and risk. • Asthma patients: GINA treatment step • Blood eosinophils: Count closest to index date • Charlston Comorbidity Index OLD treatment • ICS • LABA • LAMA • SABA • Oral steroid (acute & maintenance courses) • Antibiotics associated with a lower respiratory complaint Co-morbidities • Rhinitis • Eczema • Nasal Polyps • GERD • Osteoporosis • Bronchiectasis • Myocardial infarction • Hypertension • Cardiovascular disease • Cerebrovascular disease • Ischaemic heart disease • Diabetes mellitus
  14. 14. Next step Dataset to be requested and subsequent analysis to begin shortly
  15. 15. 2) Any new project ideas?

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