Severe Asthma/Biomarkers Working Group ERS 2017

1. SEVERE ASTHMA
/BIOMARKERS JOINT
WORKING GROUP MEETING
DATE: Saturday 9th September 2017
TIME: 15.50
VENUE: Meliá Milano, Via Masaccio 19, Milan
Co-chairs: Leif Bjermer & David Price
Administration: Optimum Patient Care (OPC)

2. MEETING ATTENDEES
Arata Azuma Sajid Hansraj
Alvaro Cruz Victoria Carter
K F Chung Marcela Gavornikova
Fulvio Braido Sheri Rogers
Akio Niimi Dragos Bumbacea
Ulla Seppala Akio Niimi
Renaud Louis Kjell Alving
Danny McBryan David Price
Alberto Papi Richard Costello
Glenn Crater Leif Bjermer
Heather Hoch Therese Lapperre
Mohsen Sadatsafavi Heather Hoch
Pascal Pfis Lakmini Bulathsinhala

3. Agenda
• 15.50 -15.55 Welcome / Introduction Leif Bjermer & David Price
• 15.55 – 16.10: REG Projects 2017
o Use of electronic medical records and biomarkers (published ECRJ 2017) David Price/Author present
o NICE/GINA FENO letter to the Editor: Kjell Alving
o OPC & OPRI Biomarker & Severe Asthma Projects David Price
• 16.10 –16.20 ISAR Initiative & Data Sources Update
o International Severe Asthma Registry (ISAR) Lakmini Bulathantisia
o Optimum Patient Care Research Database (OPCRD) Victoria Carter
• 16.20–16.40 New Projects & Initiatives
o New Projects Discussion All

4. REG SEVERE ASTHMA /BIOMARKERS
Projects : ERS 2017 Update

5. Use of electronic medical records and biomarkers to manage
risk and resource efficiencies
• Biomarkers used in isolation or combination are
powerful composite metrics for predicting future risk.
• Promise of greater clinical insight through combining
FeNO and blood eosinophil values to generate a
‘composite inflammatory biomarker
• An integrated EHR remains the ultimate goal, a ‘big
data’ scenario - containing
o standard clinical information,
o new biomarker results, and
o behavioural/contextual data from connected devices

6. Use of electronic medical records and biomarkers to manage
risk and resource efficiencies

7. GINA / NICE FeNO Editorial Update
• Update from Kjell Alving – paper has been written but rejected from Lancet RM
• Update on the formal NICE publication
• Decision of next steps in regard to the paper
o Kjell to rework for re-submission of this paper to ERJ

8. Predictive value of FeNO in patients with non-specific
respiratory symptoms: a randomised controlled trial
For every 10ppb increase in baseline FeNO, the improvement of ACQ was 0.071 greater in the
extrafine ICS arm compared to the placebo arm

9. Health care resource use and costs of severe, uncontrolled
eosinophilic asthma in the UK general population
Less than 1% of patients in a UK general asthma population sample have SUEA

10. Assessing the Use of FeNO and blood eosinophils as
biomarkers in predicting asthma exacerbations
The presence of FeNO ≥35ppb and BEC ≥300/µL adds to the accuracy in identifying patients
who are at risk of exacerbation, compared to the presence of FeNO or BEC alone.
Rate Ratio of exacerbations Lower CI (95%) Higher CI (95%)
High FeNO and low BEC (n=98) 1.35 0.99 1.84
High BEC and low FeNO (n=186) 1.41 0.91 2.19
High BEC AND high FeNO (n=53)
1.72 1.00 20.93

11. Lakmini Bulathsinhala
9 September 2017
International Severe Asthma Registry

12. Live EDC System: CISIV
Core variables: User Acceptability Testing (UAT) phase (complete Sept.11 2017)

13. Severe Asthma: Available Data Sources?
First year of ISAR (2017): over 1000 patients records
o Expected start of data collection: Oct 2017
o Data from the latest three years as of Dec 2017
OPCRD: a 3.4 million patient repository of routinely
collected primary care data in UK.
 ISAR severe asthma patients’ primary care data linked to secondary
care data
 benchmark analyses

14. ISAR SC : 2017 Research Prioritisation
Research Topic Rank Feasibility
Demographic, clinical characteristics, comorbidities, medical management of Severe Asthma patients worldwide 1 Yes
Predictors of biologic response failure 2 Yes, Limited*
Biologics progressing patient proportion 3 No
Late versus early onset of Severe Asthma 4 Yes
Adherence (Quality use of therapy) 5 Yes
Quality of Life in Severe Asthma 6 Yes, Limited*
Overlap in collected Biomarkers 7 Yes
Economic Burden of Severe Asthma 8 Yes, Limited*
Asthma in young adults 9 No
Asthma in elderly 10 Yes
Characteristics of Asthma & COPD Overlap Syndrome in patients with severe asthma 11 Yes
Incidence of hidden severe asthma patients in primary care 12 Yes
* Variables not in core list or low sample size expected in 2017

15. Global Research Project: Timeline
2017 2018

16. ISAR Website and Publicity
• ISAR website: portal to raise awareness and passive recruitment
• Has been launched live in lieu of the ISC Meeting

17. Victoria Carter
9 September 2017
Optimum Patient Care Research Database

18. Category All Patients Number of records Asthma Patients COPD Patients
Total 3,924,855
1,082,143,922 (Clinical) +
662,073,163(therapy)
798,546 152,788
Asthma Dx. (QoF) 798,546 3,527,324 798,546 46,750
COPD Dx. (QoF) 152,788 1,061,308 46,750 152,788
Rhinitis Dx 560,888 1,266,952 215,376 18,788
C reactive protein 655,264 1,929,812 152,335 47,550
Eosinophil Reading 2,131,253 13,060,575 474,294 126,916
FeNO
994(routine)+
1156(clinical data)
1289(routine) +
1454(clinical data)
789(routine) +
1156(clinical data)
56
FeNO and Eosinophil reading 766 5,803 603 55
Neutrophil 1,586,976 8,538,834 322,151 86,197
Vitamin D level 54,291 139,283 12,805 3,526
OPCRD Biomarkers Data

19. New Project Ideas / Group
Discussion

20. Previous Study Ideas from the Working Group…
• Evaluate the utility of blood eosinophils as a predictor of outcomes
• Utility of blood eosinophils as a predictor of response to therapy – dual bronchodilation vs
ICS/LABA
• Link between smoking and FENO level
• Consider pulmonary vs systemic drivers of high blood eosinophils
• Link between eosinophenia and increase risk of pneumonia
• Consider opportunities to use biomarkers in the upper airway
• Incidence of hidden severe asthma patients in primary care