Obstructive Sleep Apnoea Working Group Meeting

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Transcript of Obstructive Sleep Apnoea Working Group Meeting

OBSTRUCTIVE SLEEP APNOEA INAUGURAL WORKING GROUP MEETING

Dr Mihaela Stefan

DATE: Saturday September 3rd

TIME: 5.00–6.15pm

VENUE: Royal College of General Practitioners; 30 Euston Square, London, UK

Agenda

17.00-17.15 Welcome / Introduction

– OSA new area for REG research...?

17.15-17.45 A first research idea

– Clinical and Cost Implications of PAP in patients with OSA

and Obstructive Lung Disease

17.45-18.10 Other potential projects for the group

18.10-18.15 Next Steps & Meeting Close

The Respiratory Effectiveness Group (REG)

•  Founded in October 2012 by David Price, Professor of Primary Care Respiratory Medicine at the University of Aberdeen.

•  Recognised the growing importance of real-life research and the need for respiratory experts around the world to come together to: o  De-fragment practice o  Set best practice quality standards o  Set a unified agenda for future ethical and meaningful real-life research.

Evolving landscape: timeline

•  Brussels Declaration on Asthma: stated a need to include evidence from real world studies in treatment guidelines

•  Michael Rawlins (NICE Chairman): RCTs should be complemented by a diversity of approaches that involve analysing the totality of the evidence base

2008

ATS/ERS

Large, prospective studies in ʻreal-worldʼ settings (e.g., trials designed pragmatically to reflect everyday clinical practice) to ensure they provide content validity as well as reflect clinically meaningful outcomes

2009

ARIA / GA2LEN

Proposed the use of composite measures when evaluating asthma control and called for the measurement properties to be validated in clinical trials

2010

NHLBI expert workshop Highlighted areas that need strengthening in order to optimize the potential of real-life/comparative effectiveness (CER) research in pulmonary diseases, sleep, and critical care.

2011

REG was founded!

2012

•  Studies have shown that efficacy RCTs exclude about 95% of asthma and 90% of COPD routine care populations due to strict inclusion criteria.1

1. Herland K, et al. Respir Med 2005;99:11–19.

Limitations: RCTs inclusions/exclusions

COPD

Asthma

Patient RCT eligibility drop-off with sequential application of standard inclusion criteria

Evidence

Theoretical

Theoretical model provide

rationale

Classical double-blind double-dummy RCTs

Gold standard, large range of

outcomes. But not “real-life” patients,

compliance and represent <10%

of patients

Pragmatic trials

More real-life Broader inclusion

criteria Allow normal factors to

occur usually randomised.

Simple outcomes, but still consent &

rigorous

Observational Data

Real-life patients Not randomised

Routine data Normal decisions Difficult to ensure

group comparability Matching of case

controls, adjustment

Real-life studies

Need for integrated approach to evidence evaluation

Working groups: specialty focus

•  Not-for profit, international research and advocacy group

•  Investigator-led; 5 executive members providing leadership

•  >300 collaborators spanning 40 countries

•  14 Working groups to identify research needs in areas where real-world research methodologies have particular utility

RESEARCH IDEA IMPACT OF POSITIVE AIRWAY PRESSURE ON

HEALTHCARE RESOURCE UTILIZATION IN PATIENTS WITH OBSTRUCTIVE LUNG DISEASE AND SLEEP-RELATED

BREATHING DISORDERS 17.15–17.45

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; 2

Background: OLDOSA WHY…?

•  Obesity is a growing problem worldwide1

•  Obesity predisposes OSA.2

•  Possible link between obesity and OLD:

o  Positive correlation between baseline BMI and the subsequent development of

asthma3

o  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 comorbid OSA may be increasing with increasing asthma severity9

•  No population-based studies using polysomnography to identify the prevalence

and severity of OSA in routine care asthma patients

•  Patients with COPD and OSA have higher mortality than those with COPD and

Tx with CPAP reduces COPD exacerbations11

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; 10. Alkhalil M, et al. Clin Sleep Med. 2009; 5: 71–78 11.Marin JM et al. AmJ Respir. Crit, Care. Med. 2010;182:325-31

Background: PAP

•  Positive airway pressure (PAP) is the most effective treatment for patients with moderate-to-severe obstructive OSA.1

•  Real-life evidence (claims data) suggests PAP is an effective and cost-effective OSA treatment. Compared with baseline:2 o  PAP associated with 41% lower healthcare and disability costs and

fewer missed

o  Healthcare costs in controls (diagnosed with OSA but untreated) decreased by 8%

o  Healthcare costs increased by 34% in those without OSA over the same period

•  Small observational studies suggests that PAP Tx may attenuated the risk of severe asthma in patients with comorbid OSA, particularly in older patient groups.3

1. Hoffman B, et al. J Occup Environ Med.2010;52:473-7; 2. Teodorescu M, et al. Sleep Disord. 2013; 2013: 251567;

3. Albarrak M et al. Sleep. 2005;28:1306-11.

Possible Beneficial Effects of PAP in Patients with Asthma and OSA

•  Need to understand the inter-relationship between OSA-Asthma-COPD and the real-life implications of undiagnosed or inadequately treated OSA on OLD, and vice versa.

Aim

•  To evaluate the impact of a diagnosis of sleep-related breathing disorder (SBD, including OSA) on clinical outcomes and healthcare resource utilization in a representative population of patients with OLD and comorbid SBD in the United Kingdom.

•  Hypothesis: It is assumed that a diagnosis of OSA

(surrogate marker for treatment) will be associated with a decrease in the use of health care resources.

Design & Data source

Design •  Historical matched cohort study using electronic medical records

and linked questionnaire data from the Optimum Patient Care Research Database (OPCRD)

Data source •  The Optimum Patient Care Research

Database (OPCRD) is a UK primary care database available to REG: o  Quality-controlled, longitudinal, primary-care database o  Contains anonymous data from ≥550 UK general practices

& ~2.5 million patients

o  Captured via the OPC asthma and COPD clinical review service –  Respiratory “enriched” database

o  Ethical approval for medical research

Study Population Inclusion criteria Active Population Control Population

Aged: ≥18 years at index date ✔ ✔

A physician diagnosis of SDB (defined as ≥1 SBD diagnostic codes)

X

≥3 years of continuous data: • ≥1 year prior to “index date” • ≥2 years immediately after index date

✔ ✔

OLD Diagnosis, any of: Asthma subpopulation: asthma diagnosis ever prior to index date, ≥2 asthma prescriptions in the baseline year; no COPD Read code in the 3-year study period COPD subpopulation: COPD diagnosis ever prior to index date, ≥2 COPD prescriptions in each of the baseline years; no asthma Read code in the 3-year study period Asthma & COPD subpopulation: Asthma & COPD diagnoses within 2 years of each other ever prior to the index date and ≥2 OLD prescriptions in each of the baseline years; no asthma or COPD resolved codes within the study period

Exclusion criteria Active Population Control Population

To optimise the external validity of the study findings no exclusion criteria will be applied

Study Period

•  The study will consider a three-year continuous observation period for eligible patients

•  1 baseline year immediately before the index date (months -12–0)

•  Index date (date/month 0) will be: o  Active cohort: the data of first SDB diagnosis o  Control cohort: date of a random primary care consultation in

matched controls

•  2 outcome years immediately following the index date o  Primary analysis: 24-month outcome period, months 0-24 (for

evaluation of all primary and secondary endpoints) o  Secondary analysis: 21-month outcome period, months 0-24 (for

primary endpoint evaluation only)

Study Design

Index Date:

Active: Date of first OSA diagnosis Control Group: healthcare consultation date in patients matched on age,

BMI, sex and OLD diagnosis, OLD severity

Baseline: 1 year Outcome: 2 years

(primary: months 0-24)

Active Arm

Control Arm

Outcomes:

Primary: Acute respiratory event rate Secondary: • Acute care hospital days (total days/period) • Pharmaceutical dispensations (days supply/period) • Overall healthcare costs

Outcome: 21 month (secondary: months 3-24)

Month 0

Month 3

Primary endpoint

Acute respiratory event rate •  Defined as the occurrence of any of the following events

coded for a lower respiratory complaint: o  Hospital admission o  Emergency Room / Accident & Emergency attendance

o  Acute course of oral steroid prescription

o  Antibiotics prescriptions.

Endpoints: secondary

Healthcare resource utilization •  Primary care consultations:

o  All o  For SDB o  For a lower respiratory complaint o  For a lower respiratory code resulting in a course of antibiotics o  For a lower respiratory code resulting in a course of oral steroids

•  Secondary Care: o  Hospitalizations with a lower respiratory code o  Hospitalizations with a SDB code o  Out patient department attendances with a lower respiratory code o  All out patient department attendances with a SDB code

Endpoints: secondary

Pharmaceutical dispensations (days supply/period) •  OLD treatment– Days supplied

o  ICS daily dose

o  LABA daily dose

o  LAMA daily dose

o  SABA daily dose

•  Total Prescriptions

o  Oral steroid courses for lower respiratory complaints

o  Antibiotics courses for lower respiratory complaints

o  Theophylline prescriptions

Overall healthcare cost o  Drug-related

–  OLD –  SDB –  OLD + SDB

o  Encounter-related –  OLD –  SDB –  OLD + SDB

o  Total: Encounter + Drug related –  OLD –  SDB –  OLD + SDB

Within-population analysis •  Primary endpoint outcome comparison for baseline -12–0 months vs versus outcome periods (0–

24 months; primary and 3–21 months; secondary), for: o  All Active Patients, All Active OLD sub-populations

o  All Control Patients, All Control OLD sub-populations

•  Predictors / key independent variables of HRU Index Date:

Baseline: 1 year

Active Arm

Primary Analysis 1 – Active Cohort:

OSA + OLD pre vs post OSA diagnosis

Subanalyses:

OSA + Asthma pre vs post OSA diagnosis OSA + COPD pre vs post OSA diagnosis

OSA + Asthma + COPD pre vs post OSA diagnosis

Outcomes:

Primary: Acute respiratory events Secondary:

• Acute care hospital days (total days/period) • Pharmaceutical dispensations (days supply/period)

• Overall healthcare costs

Control Arm

Primary Analysis 1 – Control Cohort:

OLD pre vs post OSA diagnosis

Subanalyses:

Asthma pre vs post OSA diagnosis COPD pre vs post OSA diagnosis

Asthma + COPD pre vs post OSA diagnosis

Secondary Outcome: 21 month (months 3-24)

Primary Outcome: 2 years (months 0-24)

Matched outcome analysis •  Comparative analysis of active patients and matched controls over 1 year (primary) and 21

months (secondary), stratified by comorbid OLD diagnosis •  Controls matched to active patients based on:

o  Key demographic (age, sex, BMI) and clinical (OLD diagnosis, index year,) characteristics; OR, Propensity score matching (probability of being diagnosed with OSA)

Index Date:

Active: Date of first OSA diagnosis Control Group: healthcare consultation date in patients matched on age, BMI, sex and OLD

diagnosis and baseline OLD severity

Baseline: 1 year

Active Arm Primary Analysis = All patients Sub analysis by OLD diagnosis

Control Arm Primary Analysis = All patients Sub analysis by OLD diagnosis

Subanalysis: Asthma + OSA vs Asthma

Subanalysis: COPD + OSA vs COPD

Subanalysis: Asthma + COPD + OSA vs Asthma + COPD

Outcomes:

Primary: Acute respiratory events Secondary: • Acute care hospital days (total days/period) • Pharmaceutical dispensations (days supply/period) • Overall healthcare costs

Secondary Outcome: 21 month (months 3-24)

Primary Outcome: 2 years (months 0-24)

Questions for the group

•  SDB or OSA?

•  Time period before and after the index date

•  We assume that OSA diagnosis is a surrogate for PAP treatment. If the dataset has information about the CPAP delivered we can also do a secondary analysis in the group that we know that they got the machine.

OTHER RESEARCH IDEAS GROUP DISCUSSION / BRAINSTORM

17.45–18.10

NEXT STEPS FUTURE MEETINGS

18.10–18.15

Systematic Review of the Comparative Effectiveness Literature on ICS Particle Size

•  TBC