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Adherence wg summit 2018 final

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WG REG Summit 2018

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Adherence wg summit 2018 final

  1. 1. Adherence Working Group Meeting CHAIR: Alexandra Dima DATE: Thursday 22nd March 2018 TIME: 15.30–16.30 VENUE: Park Plaza Hotel, Amsterdam Airport
  2. 2. Agenda 1) Update on the current project ‘Improve understanding of the bi- directional causality relationship between asthma outcomes and adherence’. 2) Discussion of potential project ideas and decision on which project(s) to pursue first. 3) Any new project ideas?
  3. 3. 1) Update on current project Improve understanding of the bi-directional causality relationship between asthma outcomes and adherence
  4. 4. To what extent adherence may be predicted by asthma outcomes, or/and a predictor of asthma outcomes. - What is the impact of asthma outcomes on adherence? - What is the impact of adherence on asthma outcomes? Consider simultaneous relationships and lagged effects Research question
  5. 5. Inclusion / Exclusion criteria • Inclusion Criteria: • 3 years of continuous records (1 prior & 2 after IPD) • Physician-diagnosed asthma ≥ 1 year prior to IPD • Aged ≥6 years at IPD (i.e. ≥5 years at time of diagnosis) • First ICS prescription at IPD via MDI or DPI • On active asthma therapy (≥ 2 prescriptions for ICS and/or SABA at different points during each outcome year) • Exclusion Criteria: • Any prescriptions for LABA, combination ICS/LABA therapy, and/or LTRA during the baseline year • Received maintenance oral steroids during baseline year
  6. 6. Measures • ICS adherence • Asthma outcomes: • Moderate-to-severe exacerbations • Risk domain asthma control • Overall asthma control • Treatment stability • Prescription-derived mean daily SABA dosage • Prescription-derived controller to total asthma meds ratio • Covariates: • At IPD: age, gender, BMI, smoking status, device type, ICS dosage, ICS drug, asthma duration, comorbidities, etc. • Prior to baseline: any ICS prescription
  7. 7. Phase I study has been published in JACI Souverein et al. (2017) J Allergy Clin Immunol Pract. 5(2): 448-456
  8. 8. Asthma control • Moderate-to-severe exacerbations o Asthma-related hospitalizations / ED attendance – Asthma A&E or hospits – COPD/respiratory-related/generic hospits + Lower_respiratory_consultation (excl: lung function test)  Lower Respiratory read codes (incl. asthma, COPD, LRTI)  Asthma/COPD review codes (excl: monitoring letter codes)  Lung function, asthma monitoring o OCS prescriptions ! If within 1 week – 1 event
  9. 9. Asthma control • Risk domain asthma control o No moderate-to-severe exacerbations o No AB + evidence of respiratory review (± 7days) – Lower_respiratory_consultation – Any additional respiratory examinations, referrals, chest x-rays or events o Asthma-related outpatient attendance • Overall asthma control o + SABA dose ≤200mcg salbutamol / ≤500mcg terbutaline • Treatment stability o + no add-on therapy / 50% dose increase
  10. 10. Phase 2. adherence - outcomes Rx1 Rx2 Gap: 60 days 50 days Interval: 110 days Adherence: 45.5% 50 days Gap: 100 days Rx3 50 days Interval: 50 days Adherence: 100% Interval: 100 days Adherence: 0% New approach – per-prescription-interval Note: possible carry-over not illustrated in this figure
  11. 11. Select homogeneous intervals to be most accurate in estimating bidirectional relation adherence – asthma control  Focus on variation in implementation: - exclude gap intervals (0% adherence) (15%) - exclude intervals with 100% adherence (60%) (+ sensitivity analyses performed with binary 0/rest & 100/rest)  Include only intervals with range of adherence (4-99.6%) 94,498 intervals (10,472 patients)  24,102 intervals (7,501 patients) - control: - 11,509 (92.7%) of intervals with RDAC=1; - 5,882 (56.2%) patients with RDAC=1 during follow-up - adherence: 65.2% (SD=19.7) Phase 2. adherence - outcomes
  12. 12. Interval level SABA overuse within interval (ref=no) 0.98 (0.75-1.27) SABA overuse lagged (ref=no) 0.96 (0.75-1.22) Adherence within interval 1.01 (1.00-1.01)** Adherence lagged 1.00 (1.00-1.00) Patient level Age 1.00 (0.99-1.00) Gender (ref=female) 1.58 (1.34-1.87)*** BMI (ref=underweight (<18.5)) normal (18.5-25) 1.08 (0.57-2.07) overweight (25-30) 1.08 (0.56-2.09) obese (≥30) 0.90 (0.46-1.77) Smoking history (ref=current) none 1.47 (1.15-1.89)** former 1.61 (1.18-2.19)** Deprivation (ref=Q1 most affluent) Q2 1.21 (0.83-1.77) Q3 1.26 (0.84-1.88) Q4 1.27 (0.85-1.90) Q5 (most deprived) 1.08 (0.70-1.66) Diagnosed with (ref=no) rhinitis 0.74 (0.45-1.21) allergic rhinitis 1.02 (0.74-1.39) hay fever 0.99 (0.69-1.44) gastroesophageal reflux 0.68 (0.41-1.12) COPD 0.52 (0.35-0.78)** other respiratory diseases 0.33 (0.10-1.05) Asthma duration 1.00 (1.00-1.01) CCI (ref=low (≤4)) 0.65 (0.50-0.85)** Type of ICS device (ref=DPI) MDI 0.87 (0.61-1.24) BAI 1.48 (0.57-3.90) Doses in the device 1.00 (0.99-1.00)* Daily dose 1.07 (1.00-1.15)* Phase 2: adherence - outcomes
  13. 13. Same Occurrence of ≥1: (ref=no) Asthma-related hospitalizations -0.20 (12.0) Respiratory-related hospitalizations -8.40 (11.2) Asthma-related hospitalizations & emergency visits -3.0 (15.3) Prescriptions of acute OCS -5.0 (9.0) Prescription of antibiotics -1.77 (0.64)** Asthma-related outpatient visits -2.32 (1.17)* Moderate to severe exacerbations 3.04 (8.99) SABA overuse (ref=no) -6.68 (0.42)*** -6.69 (0.42)*** Risk domain asthma control (ref=no) 2.18 (0.46)** Previous Occurrence of ≥1: (ref=no) Asthma-related hospitalizations 0.41 (10.4) Respiratory-related hospitalizations -2.80 (9.55) Asthma-related hospitalizations & emergency visits 1.86 (12.5) Prescriptions of acute OCS -6.32 (7.77) Prescription of antibiotics -0.97 (0.64) Asthma-related outpatient visits -1.34 (1.19) Moderate to severe exacerbations 6.21 (7.79) SABA overuse (ref=no) -1.22 (0.44)** -1.21 (0.44)** Risk domain asthma control (ref=no) -0.25 (0.46) … (continued) Phase 2: outcomes – adherence Interval level
  14. 14. …(continued) Patient Age 0.07 (0.01)*** 0.07 (0.01)*** Gender (ref=female) 0.25 (0.36) 0.27 (0.36) BMI (ref=underweight (<18.5)) normal (18.5-25) -1.15 (1.28) -1.10 (1.28) overweight (25-30) 0.59 (1.31) 0.65 (1.32) obese (≥30) 0.16(1.37) 0.20 (1.37) Smoking history (ref=current) none -0.74 (0.58) -0.73 (0.58) former -1.01 (0.71) -1.00 (0.71) Deprivation (ref=Q1 most affluent) Q2 0.94 (0.88) 0.91 (0.88) Q3 2.05 (0.91)* 2.02 (0.91)* Q4 0.51 (0.91) 0.46 (0.91) Q5 (most deprived) 0.96 (0.98) 0.93 (0.98) Diagnosed with (ref=no) rhinitis -0.72 (1.10) -0.74 (1.10) allergic rhinitis -0.11 (0.64) -0.12 (0.63) hay fever -2.63 (0.79)*** -2.62 (0.79)*** gastroesophageal reflux 0.33 (1.22) 0.33 (1.2) COPD 2.75 (1.10)* 2.59 (1.10)* other respiratory diseases 1.35 (3.32) 1.30 (3.32) Asthma duration -0.00 (0.02) -0.00 (0.02) CCI (ref=low (≤4)) 0.12 (0.65) 0.12 (0.65) Doses in the device 0.13 (0.0)*** 0.13 (0.0)*** Daily dose -3.88 (0.15)*** -3.87 (0.15)*** Phase 2: outcomes – adherence Patient level
  15. 15. Phase 2 – preliminary conclusions • Higher adherence predicts asthma control during the same interval between 2 prescriptions • No lagged effects of adherence on control • Uncontrolled asthma (esp. antibiotic use, outpatient visits), and reliever overuse predict lower adherence in the same interval • No lagged effects of control (markers) on adherence. • Reliever overuse in preceding interval is predictive of lower adherence in the next
  16. 16. Phase 2 – limitations • The control-related event could have happened at the beginning, middle or end of the interval – adherence is assumed stable across the interval  moderator variable time of event within interval? • 100% and 0% adherence intervals are artificially defined based on pre-defined permissible treatment gap and by censoring at the end of the 2-year period  gap may be too short? • No separation of variance between- and within-patient levels  person-centering may clarify effects?
  17. 17. Phase 2 – next steps • Results to share with scientific committee for interpretation • Discussion of possible publication of findings • Different methodological approaches to test in the future: o Selection of subsamples (type of ICs, >2000 only) o Solutions for considering both persistence and implementation o Testing of different permissible gap values
  18. 18. 2) Current ideas for future studies • Look at prevalence of non-adherence phenotypes - Erratic (forgetfulness) - Intelligent (conscious decision) - Unwitting (lack of knowledge) Why are people non-adherent? How can we target populations where non-adherence is causing problems? Patient empowerment. More focus on clinician’s role in non-adherence and less blame on patients. • What can we learn from regional differences, comparing adherence in respiratory diseases across multiple countries. • In populations on high dose steroids how many are fully adherent and would benefit from new treatments? • Using Pharmacy data to validate adherence measures calculated using UK Prescribing data Which project should be a priority?
  19. 19. 3) Any new project ideas? REG research needs that involve adherence- NEED 7. To improve understanding of medication adherence behaviours (including inhaler device challenges) in respiratory and allergic airways disease, their implications on clinical and health economic outcomes and optimised management options NEED 1. To characterise current routine care disease epidemiology and burden for respiratory, allergic and obstructive airways disease outcomes NEED 2. To characterise current routine care prescribing practices (diagnostic and management) and their implications for respiratory and allergic airways disease outcomes How should these be prioritised with the existing project ideas?

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