1. New Insights in Personalising Medicine, from Bedside to Primary Care
Thys van der Molen
Groningen

2. Disclosures/ conflict of interest
Reimbursement for travel, research grants, consultation fees and fees for presentations from:
Almirall
AstraZeneca
Boehringer Ingelheim
GlaxoSmithKline
Mundipharma International
TEVA
UMCG
Lung foundation
EU projects

3. New Insights in Personalising Medicine, from Bedside to Primary Care

4. Asthma in the community

5. COPD in the community/mortality

6. Asthma and COPD in the world
Total prevalence of patients with obstructive lung disease around 7- 10%
Most patients have mild to moderate disease
Most patients (>80%)–depending on health care system- are not treated or treated in primary care
Despite the relative mildness of their disease most patients are uncontrolled

7. Personalising medicine from primary care perspective
What is the diagnosis?
What is the phenotype?
What kind of mindset has the patient
What kind of advice can be communicated
What kind of pharmaceutical treatment would be probably of benifit?

8. Diagnosis new approaches
It seems so easy and yet we all have trouble

9. Differences in diagnosis based on individual patient data between pulmonologists

11. Personalising medicine
What is the diagnosis?
What is the phenotype?
What kind of mindset has the patient
What kind of advice can be communicated
What kind of pharmaceutical treatment would be probably of benifit?

12. Phenotype of the common patient
Marsh thorax 2008

13. Phenotype asthma

14. Network medicine & COPD
Environmental network
Pollution
Allergens
Diet
Smoking
Temperature
Infections
Activity
Life-style
Modifiable factors
COPD
CVD
Cancer
Myopathy
Osteoporosis
Metab Syn.
Clinical network
Clinical phenotypes
Integrated care
Personalized medicine
Guidelines network
Innate inmunity
Ageing
Bioenergetics
Repair
Oxidative stress
Acquired immunity
Biological network
Genetic network
GWAS
ncRNA
miDNA
miRNA
Epigenetics
Pharmacogenomics
Intermediate pathophenotypes
Diagnostic biomarkers
Therapeutic targets
Genetic markers
Risk assessment
Agusti A, Vestbo J. Am J Respir Crit Care Med 184 (5): , 2011

15. Personalising medicine
What is the diagnosis?
What is the phenotype?
What kind of mindset has the patient
What kind of advice can be communicated
What kind of pharmaceutical treatment would be probably of benifit?

16. Countries included in the REALISE survey
The REALISE survey was conducted in:
Austria
Belgium
Finland
France
Germany
Italy
Netherlands
Norway
Spain
Sweden UK
Numbers of included respondents are shown for each country; Belgium and Norway were excluded from this analysis
REALISE, Recognise Asthma and Link to Symptoms and Experience

17. Demographic profiles – 5 EU segments
INDIFFERENT
Segment 2
WORRIER
Segment 3
WELL ADJUSTED
Segment 4
DEPENDENT
Segment 5
LOST
Base: All respondents n=7930 [ Seg1 (2782), Seg2 (2194), Seg3 (2044), Seg4 (442), Seg5 (468)]

18. Size and geographic distribution of segments - Europe
Overall, the biggest segment is Seg1, consisting of a third of the respondents.
Seg4 and Seg5 are relatively small, each taking 6% of the sample.
The segment distribution in each country roughly follows the overall pattern in EU, suggesting certain degree of conformity of the EU population on attitude towards asthma.
Base: All respondents n=7930 [ Seg1 (2782), Seg2 (2194), Seg3 (2044), Seg4 (442), Seg5 (468)] [UK (996), Germany (991), Belgium (300), France (1015), Italy (1005), Spain (1010), Netherlands (849), Norway (232), Finland (465), Austria (468), Sweden (599)]

19. Personalising medicine
What is the diagnosis?
What is the phenotype?
What kind of mindset has the patient
What kind of advice can be communicated and how?
What kind of pharmaceutical treatment would be probably of benifit?

20. What kind of advice can I communicate and how?
Smoking
Exacerbations
Dyspnea
BMI
Lung function
Physical activity
Complaints (symptoms)
Functional status
Mental health
Fatigue
Emotions

21. Selection of instruments

22. Better communication development of the ABC tool
Slok et al PCRM 2014

23. Personalising medicine
What is the diagnosis?
What is the phenotype?
What kind of mindset has the patient
What kind of advice can be communicated
What kind of pharmaceutical treatment would be probably of benifit?

24. Male, 65 years Patient history: CCQ: ACQ: Total: 2,0
CCQ1 short of breath at rest: 2
CCQ2 short of breath at exertion: 2
CCQ3 concerned: 2
CCQ4 depressed: 2
CCQ5 cough: 2
CCQ6 produce phlegm: 2
CCQ7 strenuous physical activities: 3
CCQ8 moderate physical activities: 3
CCQ9 daily activities at home: 1
CCQ10 social activities: 1
ACQ:
Total: 1,5
ACQ1 how often wake up at night: 1
ACQ2 symptoms in the morning: 2
ACQ3 limit of usual activities: 2
ACQ4 short of breath: 2
ACQ5 wheezing: 2
ACQ6 using of rescue medication: 0
MRC:
Total: 1
Patient history:
Reason for visit: integrated care
occupation: teacher
smoking pattern: former smoking
Familial: no
Clinical history: hay fever, bronchitis
Atopy: season, grasses, cigarette smoke, exertion
Exacerbations: 1 (last year)
Disease timecourse: since age of 64
Medical treatment: Oxis 12 ug 2dd1
Adherence takes Oxis occasionally

25. Spirometry

26. REALISE EU Patient clusters:
Segment 1
INDIFFERENT
Segment 2
WORRIER
Segment 3 WELL ADJUSTED
segment 4 DEPENDENT
Segment 5 LOST
Level of asthma control (Gina-defined control status)
Moderate
Lowest
Highest
Low
Level of confidence in managing asthma
High
Perceived severity of asthma
Not serious
Serious
Frequency of seeking information about asthma
Level of concern about their asthma
Socially conscious about asthma
Base: All respondents n=7930 [ Seg1 (2782), Seg2 (2194), Seg3 (2044), Seg4 (442), Seg5 (468)]

27. Patient profile
Segment 1
INDIFFERENT
Segment 2
WORRIER
Segment 3
WELL ADJUSTED
Segment 4
DEPENDENT
Segment 5
LOST
Base: All respondents n=7930 [ Seg1 (2782), Seg2 (2194), Seg3 (2044), Seg4 (442), Seg5 (468)]

28. Patient summary Severe obstruction / good reversibility on BD
Former smoker
Moderate symptoms/uncontrolled
Slightly depressed/concerned
Cluster indifferent (high confidence in self management and low perceived severity)
Atopy / hay fever bronchitis

29. What would you do? 39 % chance that you would label him as ACOS
100 % chance that you would prescribe ICS LABA combi

30. Conclusion
1: Personalising medicine in primary care encompasses many levels
2 Personalising medicine on the level of patient mindset or personality traits might be of larger importance than based on biomarkers
Personalising medicine in primary care is our core work

31. Thank you for your atttention!