IEEE EMBC session slides on global migraine survey (N= 800,000) Spain, USA, France, Canada, Japan, UK

1. #embc16
Migraine factors as reported by
smartphone users
Jose Berengueres
& Francois Cadiou
The 38th Annual International Conference
of the IEEE Engineering in Medicine and
Biology Society (EMBC’16), Walt Disney
World® Resort, Lake Buena Vista
(Orlando), Florida USA.
Oral session: Biomarkers and Global
Healthcare
Track 14: Sorcerers Apprentice 2
Wednesday, August 17, 2016, 08:00-09:30

2. Berengueres & Cadiou | 2
Outline
1. Migraine: Review of what we know
2. Why collecting data with a Smartphone?
3. Triggers
4. Symptoms
5. Pain locations
6. Outcomes
7. Discussion

3. Berengueres & Cadiou | 3
1. Migraine: Review of what we know
1. It is a Neurological disorder
• 4.7% affected
• Medical Cost $200/year
• Pathogenesis: not well understood
2. Typical clinical study sample size
• N ~ 50 (1980)
• N ~ 500 (1990)
• N ~ 65,000 (2000)
• N ~ 1,000,000 (this study, not clinical)
3. Q: What are the most common triggers of
migraine according to you?
• Chocolate, Cheese, Wine, Temperature,
Menstruation or Pollution
4. Selection Bias
• Emergency room visit only
• Geographic
• Cautionary tale (Beijing pollution in winter)
Evolution
Screenshots

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2. Why collecting data with Smartphone?

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2. Why collecting data with Smartphone?

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Advice
Data
New Questions
Drug Co. Dashboard
Migraine
user
The Virtuous Circle of iHealth:
Drivers & levers
A.I+Cloud
X

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Advice
Data
Real Time
New
Questions
Drug Co. Dashboard
Migraine
user
The Virtuous Circle of
iHealth
A.I+Cloud

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2. Why collecting data with Smartphone?
1. Clinical vs. Observational
• Clinical +Control
• Smartphone  +Convenience
• Smartphone  less transformation steps
2. App stats
• 65k active users
• 800k migraines logged
• 87% female
3. Face to face vs. screen mediated
• Honesty
• Convenience
0
0
0
0
20 40 60
Age
Age of the app users

9. Berengueres & Cadiou | 9
3. Triggers: Global
0
5
10
15
20
25
Percent

10. 0
5
10
15
20
25
30
Percent
en_CA
en_GB
en_US
es_ES
es_US
fr_FR
jp_JP
Berengueres & Cadiou | 10
3. Triggers: by country

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3. Triggers: by country stack bar
0
20
40
60
80
100
120
140
160
180
en_CA
en_GB
en_US
es_ES
es_US
fr_FR
ja_JP

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3. Triggers: outliers, by conditional probability of locale given the trigger
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
en_CA en_GB en_US es_ES es_US fr_FR ja_JP

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4. Symptoms: Global
0
5
10
15
20
Percent

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4. Symptoms: by country
%Migraines
en_CA
en_GB
en_US
es_ES
es_US
fr_FR
ja_JP

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4. Symptoms: by country
0
50
100
150
%ofmigraines
ja_JP
fr_FR
es_US
es_ES
en_US
en_GB
en_CA

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4. Symptoms: outliers by conditional probability
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
en_CA en_GB en_US es_ES es_US fr_FR ja_JP

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5. Pain locations: touch based data collection

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5. Pain locations: global
0.00 10.00 20.00 30.00
Front head
Eye
Back head
Top back head
Neck
Temple
Between eyes
Cheek
Jaw
% onset pain locations
47% 50% 53%
Front head
Eye
Back head
Top back head
Neck
Temple
Between eyes
Cheek
Jaw
% onset pain locations
L R
Right
Left

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5. Pain locations: by country
-3.0 0.0 3.0 6.0
Back head
Eye
Frontal
Neck
Temple
Top back head
Spread = % (R-L)/(R+L) migraines logged
ja_JP
fr_FR
es_US
es_ES
en_US
en_GB
en_CA

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5. Pain locations: JP vs non-JP asymmetry. Genetic, cultural, or language induced?
-12 -10 -8 -6 -4 -2 0 2 4 6
Back Head
Cheek
Eye
Head
Neck
Temple
Top Back Head
Grand Total
jp non_jp

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6. Outcomes: How drugs are priced in the US

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6. Outcomes: How drugs are priced in the US
0 20 40 60 80 100
-1.00.00.51.01.5
Price vs. outcome
Drug outcome as % times it was rated effective
Log(price)
Excedrin Migraine
Zomig
Relpax
RizatriptanSumitriptan
Maxalt
Advil
Excedrin
Ibuprofen
Tylenol
Propranolol
R2= 0.53

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7. Discussion: web survey vs. Migraine Buddy App
Other PC-based surveys… (PC-bias)

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7. Discussion: Migraine Buddy App vs. migraine.com web survey (triggers)
0
5
10
15
20
25
Percent
Sleep
Stress

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7. Discussion
1. Discrepancies by locale:
• Lost in translation  sinus
• Geographic/culture factor  skipped a meal
• Unknown factor
• (UX/UI/Lang/DNA/?)  pain asymmetry JPN
vs non JPN
2. Popular triggers vs what research actually focuses on
• We found top triggers  anxiety & stress
• Not top  menstruation, weather, food
• However, most studies focus on weather, food)
3. We show an alternative to case crossover studies
• more global, convenient and wider in scope
• All approaches suffer bias (ER bias, smartphone
bias, geographic bias…)
4. Further works:
1. Migraine waves / AI
2. Could not replicate correlation with temperature
from other studies (Boston ref. Mittelmann)
1. Review
2. Why Smartphone
3. Triggers
4. Symptoms
5. Pain locations
6. Outcomes
7. Discussion

26. Berengueres & Cadiou | 26
8. Acknowledgement