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Asthma-COPD
Overlap (ACO)
Working Group
Meeting
CHAIR: Marc Miravitlles
DATE: Saturday 9th September 2017
TIME: 12.30–13.1...
Agenda
1) Update on current project ‘ACOS proof of concept study- Comparability
of different population-definitions of ACO...
1) Update on current projects
ACOS proof of concept study
Background / rationale
• 2014, GINA and GOLD published their first joint statement on
Asthma-COPD Overlap Syndrome (ACOS)1...
Proof of Concept Study
Aim:
Explore the influence of the definition on the prevalence and clinical
presentation of ACO in ...
Population Definition Summary
Clinical diagnosis of
COPD
N=1,017
Aged ≥40 years
N=1,015
Evidence of smoking
N=940
Airflow ...
Population Definition Summary
Clinical diagnosis
of Asthma
N=857
Aged ≥40 years
N=755
Evidence of smoking
N=429
Airflow Ob...
ACO prevalence in the clinical populations
Population A
Clinical diagnosis
of COPD only
Population B
Clinical diagnosis of...
Summary: ACO prevalence using EMR
o Approach has strengths and weaknesses
o ACO prevalence varies depending on source popu...
2) Current ideas for future projects
(Prioritisation and work plan)
Phase 1 Repetition of the analyses in other national
d...
Phase I
Repetition of the analyses in
other national databases to
evaluate the ACO definitions.
Database eligibility criteria
Inclusion:
• Must be “population-based”, requiring them to be largely representative of the ...
Which databases should be
included in the protocol?
DATABASE Time for completion of Stage 1 Cost for completion of Stage 1...
Phase II
Implications of a mixed asthma-COPD
phenotype vs COPD alone on patient
outcomes
Implications of a mixed asthma-
COPD phenotype vs COPD alone
on patient outcomes
Aims:
• To identify the prevalence and in...
Clinical Outcomes
• Presence of atopy, defined as ≥1 of the following:
o Physician diagnosis of eczema
o Physician diagnos...
Clinical Outcomes
• COPD severity: in terms of GOLD status (where evaluable)
• Comorbidities:
o Cardiovascular disease
o O...
REG projects with an ACO component
Clinical and Cost implications of OLDOSA
The term “OLDOSA syndrome” has been
proposed1,...
3) Any new ideas for projects
• Are these projects still:
o Relevant?
o Feasible?
o Valid?
o A priority?
• How do we set priorities in ACO research?
• H...
• Develop a work plan-
Will it be possible to share the data? So one person can do all the analysis
Or will different peop...
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ACO Working Group 2017

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ACO Working Group 2017

  1. 1. Asthma-COPD Overlap (ACO) Working Group Meeting CHAIR: Marc Miravitlles DATE: Saturday 9th September 2017 TIME: 12.30–13.10 VENUE: Melia Milano Hotel, Via Masaccio 19, Milan, Italy
  2. 2. Agenda 1) Update on current project ‘ACOS proof of concept study- Comparability of different population-definitions of ACOS within a UK database’. 2) Ideas for future projects. 3) Any new project ideas? 4) Prioritisation of projects and work plan to move projects forward.
  3. 3. 1) Update on current projects ACOS proof of concept study
  4. 4. Background / rationale • 2014, GINA and GOLD published their first joint statement on Asthma-COPD Overlap Syndrome (ACOS)1 • Current thinking now recommends reference to ACO rather than ACOS based on the clinical implications of the term “syndrome”2 • Various criteria for diagnosis of ACO have been proposed2-4 • The lack of a gold standard definition is a barrier to ACO research and to understanding the biology of the condition and optimum management approaches5 1. GINA-GOLD Diagnosis of disease of chronic airflow limitation: Asthma, COPD and asthma-COPD overlap syndrome (ACOS), 2014; 2. Barnes PJ. Asthma-COPD Overlap. Chest. 2016;149:7-8; 3. Miravitlles M, et al. Arch Bronconeumol 2014; 4.Koblizek V, et al. Pap Med Fac Univ Palacky Olomouc Czech Repub 2013; 5. Kankaanranta H, et al. Basic Clin Pharmacol Toxicol. 2015;6. Postma DS, Rabe KF. NEJM 2015
  5. 5. Proof of Concept Study Aim: Explore the influence of the definition on the prevalence and clinical presentation of ACO in databases used for observational research, in order to inform (a) standard definition(s) for future studies and clinical trials. Study design: • Historical cohort study using the UK’s Optimum Patient Care Research Database which contains >2.9 million patients from >576 primary care practices across the UK • Patients with 2 years of continuous records within the observation period 1 January 2014-31 December 2015
  6. 6. Population Definition Summary Clinical diagnosis of COPD N=1,017 Aged ≥40 years N=1,015 Evidence of smoking N=940 Airflow Obstruction (Post BD FEV1 per cent predicted or FEV1/FVC <0.7) N=750 Airflow Reversibility (≥12% and ≥200mL increase in post- bronchodilator FEV1) N=208 Subgroup A3 n= 2 (Patient is <40 years) n= 75 (No evidence of smoking – current or ex) n=190 (No airflow obstruction) n= 542 (No airflow reversibility) Subgroup A2 Subgroup A1 Subgroup A POPULATION A Clinical diagnosis of Asthma & COPD N=398 Aged ≥40 years N=395 Evidence of smoking N=330 Airflow Obstruction (Post BD FEV1 per cent predicted or FEV1/FVC <0.7) N=244 Airflow Reversibility (≥12% and ≥200mL increase in post- bronchodilator FEV1) N=127 Subgroup B3 Subgroup B2 Subgroup B1 Subgroup B POPULATION B n= 3 (Patient is <40 years) n= 65 (No evidence of smoking – current or ex) n= 86 (No airflow obstruction) n= 117 (No airflow reversibility)
  7. 7. Population Definition Summary Clinical diagnosis of Asthma N=857 Aged ≥40 years N=755 Evidence of smoking N=429 Airflow Obstruction (Post BD FEV1 per cent predicted or FEV1/FVC <0.7) N=157 Airflow Reversibility (≥12% and ≥200mL increase in post- bronchodilator FEV1) N=109 Subgroup C3 Subgroup C2 Subgroup C1 Subgroup C POPULATION C n= 102 (Patient is <40 years) n= 326 (No evidence of smoking – current or ex) n= 272 (No airflow obstruction) n= 48 (No airflow reversibility)
  8. 8. ACO prevalence in the clinical populations Population A Clinical diagnosis of COPD only Population B Clinical diagnosis of Asthma & COPD Population C Clinical diagnosis of Asthma only ACO prevalence 20.5% (208/1,015) 32.1% (127/395) 14.4% (109/755) p-value compared to asthma and COPD* p<0.001 Reference p<0.001 *Chi-squared test
  9. 9. Summary: ACO prevalence using EMR o Approach has strengths and weaknesses o ACO prevalence varies depending on source population – 20%* if clinical dx COPD only – 32%* if clinical dx asthma + COPD – 20%* if clinical dx asthma + COPD AND Asthma diagnosed when patients ≤40 years of age – 14%* if clinical dx asthma only – 8%* if neither dx *ACO definition requires airflow reversibility o Future studies – Add cross-sectional analyses to examine how patterns of comorbid conditions vary depending on the source clinical population – Compare results with similar cross-sectional analyses in different population- based databases – Cohort studies to evaluate outcomes using different ACO definitions
  10. 10. 2) Current ideas for future projects (Prioritisation and work plan) Phase 1 Repetition of the analyses in other national databases to evaluate the ACO definitions. Phase 2 Implications of a mixed asthma-COPD phenotype vs COPD alone on patient outcomes.
  11. 11. Phase I Repetition of the analyses in other national databases to evaluate the ACO definitions.
  12. 12. Database eligibility criteria Inclusion: • Must be “population-based”, requiring them to be largely representative of the broad, heterogeneous population treated within everyday routine care in their respective country of origin. The following types of population-based databases may be eligible: o Clinical databases (e.g. primary care databases) o Administrative/billing-based (e.g. insurance claims records) • Have at least two continuous years of “recent” (within the last 10 years: 2006-2015) clinical data • Have produced at least one publication in a peer reviewed journal • Include variables permitting: o Evaluation of patient age (i.e. patient age or date/year of birth) o Evidence of current or past smoking (e.g. smoking status, pack years, prescription of smoking cessation therapy/advice). Exclusion: • To maximise the external validity of the study findings and avoid biasing outcomes by working within pre-selected populations unrepresentative of the diversity of patients managed in routine clinical practice, the following will not be eligible for inclusion in the initial phase of this study: o Clinical trials databases o Case series of patients
  13. 13. Which databases should be included in the protocol? DATABASE Time for completion of Stage 1 Cost for completion of Stage 1 1. Dutch ASTHMA / COPD Service 8 weeks EUR 10,000 (~2 months post-doc salary) 2. Adelphi Respiratory Disease Specific Programme ≤ 4 weeks £0 3. Optimum Patient Care Research Database (OPCRD) 4-6 weeks £10,000 4. SIDIAP 6 weeks EUR 1,500 5. MAJORICA TBC TBC 6. PCORnet Common Data Model Data available Sept 2016; analysis estimate ? TBC 7. HealthCore 3 weeks $4,167 (if manual programming required) 8. MarketScan "1 day" ? 9. Optum Humedica "1 day" ? ? ✓ X Valuable for repeat analysis and validation when available
  14. 14. Phase II Implications of a mixed asthma-COPD phenotype vs COPD alone on patient outcomes
  15. 15. Implications of a mixed asthma- COPD phenotype vs COPD alone on patient outcomes Aims: • To identify the prevalence and incidence of patients diagnosed as having ACO • To identify the burden and cost of ACO compared with COPD and asthma populations • To assess respiratory and cardiovascular outcomes in ACO, COPD, asthma treated with ICS, ICS/LABA and LABA. • Characterising ACO patients to develop a diagnostic tool
  16. 16. Clinical Outcomes • Presence of atopy, defined as ≥1 of the following: o Physician diagnosis of eczema o Physician diagnosis of allergic rhinitis o Eosinophilia (cut off >200/μl; REG COPD blood eosinophilia study used ≥450μl) o Positive skin prick test o Positive to ≥1 allergen • Smoking history: o Pack years, where available o Duration of smoking, defined as: – For ex-smokers: years between first current smoking / active smoking code and non- smoker or smoking cessation code – For current smokers: years between first current smoking record and year of study / cross sectional analysis • Historical “onset” of disease: o Duration of asthma, defined as years between first recorded asthma diagnosis / encounter and year of study / cross-sectional analysis o Duration of COPD, defined as years between first recorded COPD diagnosis / encounter and year of study / cross-sectional analysis o Time between first recorded asthma diagnosis/encounter and first COPD diagnosis/encounter
  17. 17. Clinical Outcomes • COPD severity: in terms of GOLD status (where evaluable) • Comorbidities: o Cardiovascular disease o Other chronic respiratory conditions o Diabetes o Gastroesophageal reflux disease (GERD) o Charleson Comorbidity Index o Lung Cancer • Respiratory treatment: Current management (i.e. during the phase 1 24-month cross- sectional analysis period), records (prescriptions for / claims data) for the following, and combinations of the following, will be examined: SABA, SAMA, LABA, LAMA, ICS, theophylline, LTRA, Roflumilast, chronic azithromycin. • Exacerbations: Functional consequences of different definitions, (i) proportion of patients and (ii) annualised rate of respiratory-related exacerbations over the phase 1 24-month evaluation period, where a respiratory-related event is defined as any of the following: o Physician diagnosis of asthma exacerbation; o Physician diagnosis COPD exacerbation; o Accident & Emergency / Emergency Room attendance with a lower respiratory code o Hospital admission with a lower respiratory code o A course of prednisolone o A course of systemic antibiotics coded for a lower respiratory tract infection
  18. 18. REG projects with an ACO component Clinical and Cost implications of OLDOSA The term “OLDOSA syndrome” has been proposed1, which refers to the coexistence of OLD (obstructive lung disease: COPD and asthma) and OSA 1. Ioachimescu OC, et al. Respirology. 2013;18:421-31 AIMS: Evaluate the impact of (i) continuous positive airway pressure (CPAP) therapy (ii) a sleep breathing disorder diagnosis (as a proxy for CPAP treatment) (iii) an OSA diagnosis on clinical outcomes and healthcare resource utilisation in UK patients with comorbid OLD Obstructive sleep apnoea WG are looking for anyone interested in being involved
  19. 19. 3) Any new ideas for projects
  20. 20. • Are these projects still: o Relevant? o Feasible? o Valid? o A priority? • How do we set priorities in ACO research? • How to we ensure these priorities are pursued? • What are the two most important projects to push forwards? Prioritisation
  21. 21. • Develop a work plan- Will it be possible to share the data? So one person can do all the analysis Or will different people need to analyse the different databases? Should be possible to share analysis scripts to minimize analysis time. • Need to secure - funding - database access - analytical support Next steps for Phase I study- Evaluation of ACO definition in other national databases

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