network analysis of unstructured ehr data for clinical research

Network(analysis(of(unstructured(EHR(data(for(clinical(research(

Anna$Bauer)Mehren$Shah$Lab,$Stanford$Center$for$Biomedical$Informa:cs$

Networks(

•  Networks$have$successfully$been$used$in$biology$and$partly$in$medicine$•  Ataxia$protein)protein$interac:on$network$(Lim$et$al,$Cell,$2006)$

•  Pa:ent$stra:fica:on$using$ICD9$data$(Roque$et$al,$PLoS(Comp(Biol,$2011)$

•  We$can$use$networks$from$unstructured$EHR$data$for:$•  Cohort$construc:on$•  Clinical$outcome$analysis$

4/2/13 2

4/2/13 3

NCBO(STRIDE(

•  More$than$300$biomedical$ontologies$

•  Tools$and$web$services$

•  1.8$million$pa:ents$•  18$years$•  35$million$coded$ICD9$

diagnoses$•  11$million$clinical$free$text$

notes$

Clinically(relevant(hypotheses(

Data(

Term$–$1$:$:$:$Term$–$n$

Term$recogni:on$tool$NCBO$Annotator$ NegEx$

Pa[erns$

Nega:on$detec:on$Family$History$detec:on$

Diseases$

Procedures$

Drugs$

BioPortal$–$knowledge$graph$

Crea:ng$clean$lexicons$

Annota:on$Workflow$

Text$clinical$note$

Terms$Recognized$

Nega:on$detec:on$

From(clinical(notes(to(paBent(feature(matrix$

Ontologies$provide$features$&$dependencies$

Simple$text$processing,$Feature$extrac:on$

Devices$

Diseases$ Procedures$Drugs$ Devices$

5

C1 … … Cn

P1 1 0 1 1

: 0 1 1 0

: 0 0 0 1

Pn 0 1 0 1

C1 … … Cn

C1 1 0.6 0.5 0.6

: 1 0.2 0.3

: 1 0.1

Cn 1

P1 … … Pn

P1 1 0.1 0.7 0.8

: 1 0.5 0.8

: 1 0.4

Pn 1

zolpidem

pravastatin

nifedipine

congestive heart failure

insulin glargine

cilostazol

transplantation

trimethoprim

bypass

doppler studies

surgical revision

atherectomy

bypass graftvascular surgical

procedures

ultrasound imaging

testosterone

fentanyl

amoxicillin

heart failure

coronary angiography

pantoprazole

cephalexin

hydralazine

amiodarone

obesity

wheelchair

diazepam

pneumonia

tacrolimus

sulfamethoxazole

temazepam

decompressive incision

fluoroscopic angiography heart

transplantation

revascularization

diagnostic imaging

vascular diseases

ramipril

angioplasty

doppler ultrasonography

cane

carotid endarterectomy

What is special about these

patients?

Who is getting these drugs,

conditions, etc?

Drug$Safety$ Compara:ve$Effec:veness$

Prac:ce)based$evidence$ Predic:ons$

Prac:ce)based$evidence$

PracBceEbased(evidence(

Peripheral(artery(disease((PAD):(obstruc:on$of$infra)renal$abdominal$aorta$and$lower$extremity$arteries$$

!$Cilostazol$

4/2/13 6

Cilostazol(•  Reversible$selec:ve$inhibitor$of$phosphodiesterase$(PDE)$type$III$

•  Long)term$oral$milrinone$therapy$associated$with$life)threatening$cardiovascular$events$in$conges:ve$heart$failure$(CHF)$pa:ents$

$$

$$$$$$$$

$$$$$$$$$$$$Hypothesis:$

4/2/13 7

Cilostazol is not associated with increased risk of major adverse cardiovascular events (MACE)

1.  PAD ! Cilostazol? ! MACE 2.  PAD/CHF ! Cilostazol? ! MACE

Packer et al. “Effect of oral milrinone on mortality in severe chronic heart failure. The PROMISE Study Research Group.” N Engl J Med. (1991)

50k

Pat

ient

s (1

.8 m

illio

n)

Dimension(reducBon(–(paBent(space(

4/2/13 8

t

Patient timeline

Follow up time

PAD

tPAD

Last note

tlast

Follow up time in peripheral artery disease patients

follow up time in 30 day intervals

Freq

uenc

y

0 1000 2000 3000 4000 5000 6000

050

010

0015

0020

0025

0030

00

5757 PAD patients

Concept

Peripheral artery disease

Peripheral vascular disease

Peripheral arterial occlusive disease

Intermittent claudication

Claudication (finding)

PAD

PAD

11547 PAD patients

?

Peripheral Artery Disease 5757 patients

!!!!!

Variable Before Matching Patient-patient similarity network

Propensity score matching

Treatment

(n= 232) Control (n= 5525)

p-value Control (n= 232)

p-value Control (n= 5525)

p-value

Demographics Age (at indication onset), mean (sd) 71.22

(11.02) 70.43

(12.46) 0.30 72.05

(10.62) 0.41 70.87

(11.51) 0.75

Gender (female), n (%) 37.22 45.94 <0.01 36.65 0.84 35.87 0.77 Race , (%)

Asian 8.52 7.41 0.56 6.33 0.37 10.31 0.51 Black 2.69 3.71 0.36 3.61 0.59 0.90 0.16 Unknown 22.87 26.17 0.25 22.17 0.82 20.63 0.57 White 65.47 62.22 0.32 67.87 0.55 67.27 0.69

Comorbidities Coronary artery disease, n (%) 5.38 6.47 0.48 4.98 0.83 6.28 0.70 Congestive heart failure, n (%) 25.56 22.84 0.36 20.36 0.21 30.49 0.36 Hypertension, n (%) 10.76 11.31 0.80 9.50 0.75 10.31 0.88 Co-prescriptions Beta blocking agents, n (%) 75.34 60.77 <0.001 69.68 0.20 74.89 0.91 ACE inhibitors, plain, n (%) 78.03 69.57 <0.01 67.87 0.01 78.92 0.81 Platelet aggregation inhibitors excl.

heparin, n (%) 91.93 79.00 <0.001 89.59 0.41 95.51 0.07

Vasodilators, n (%) 32.29 26.36 0.06 31.67 0.84 37.22 0.29 History of Cardiac arrhythmia, n (%) 32.29 32.17 0.97 23.08 0.03 33.18 0.84 Stroke, n (%) 17.94 18.31 0.89 15.84 0.61 21.52 0.34 Myocardial infarction, n (%) 17.94 15.87 0.43 13.58 0.24 19.73 0.64 Vascular surgical procedures, n (%) 74.44 47.71 <0.001 65.61 0.05 74.44 1 Bypass surgery, n (%)

41.70 26.56 <0.001 36.20 0.24 40.36 0.75

Cilostazol patients are sicker than other PAD patients !  Might affect outcome analysis

!  Ideally, we want to compare to “medical twin”

C1 … … Cn

P1 1 0 1 1

: 0 1 1 0

: 0 0 0 1

Pn 0 1 0 1

Cohort(construcBon(

4/2/13 10

1.  Choose$variables$for$matching$

2.  Compute$PS$based$on$variables$(logis:c$regression)$

3.  Nearest$neighbor$matching$(1:1)$

1 0 1

0 0 1

1 1 0

1 0 1

0 0 1

0 0 1

0 0 1

1 1 0

0 0 1

0 0 1

1 1 1

0 0 1

1 1 1

0 1 0

0 0 1

0 1 0

0 0 0

0 1 1

0 0 1

0 1 1

1 1 1

0 0 1

1 0 1

1 1 1

Drug$classes$ Diseases$ Devices$ Procedures$ Demographics$

J(A,B) =A∩BA∪B

0 0.6 0.8 0.6 0.5 0.8

0 0.8 0.9 0.8 0.3

0 0.7 0.9 0.9

0 0.7 0.8

0 0.8

0

Pa:e

nts$

Pa:ents$

5757(

5757(Nearest(neighbor(Matching((1:1)(

1 0 1

0 0 1

1 1 0

1 0 1

0 0 1

0 0 1

0 0 1

1 1 0

0 0 1

0 0 1

1 1 1

0 0 1 464(

1159(

Cilostazol(

Control(

Concepts$

0 0 1

0 1 1

1 1 1

0 0 1

1 0 1

1 1 1

PaBentEpaBent(similarity(network((PSim)( PropensityEscore(matching((PSM)(

5757(

1159(

Pa:e

nts$

Pa:e

nts$

1 0 1

0 0 1

1 1 0

1 0 1

0 0 1

0 0 1

0 0 1

1 1 0

0 0 1

0 0 1

1 1 1

0 0 1

464(

17(Concepts$

Pa:e

nts$

cilostazolcontrolcilostazol

!!!!!

Variable Before Matching Patient-patient similarity network

Propensity score matching

Treatment

(n= 232) Control (n= 5525)

p-value Control (n= 232)

p-value Control (n= 5525)

p-value

Demographics Age (at indication onset), mean (sd) 71.22

(11.02) 70.43

(12.46) 0.30 72.05

(10.62) 0.41 70.87

(11.51) 0.75

Gender (female), n (%) 37.22 45.94 <0.01 36.65 0.84 35.87 0.77 Race , (%)

Asian 8.52 7.41 0.56 6.33 0.37 10.31 0.51 Black 2.69 3.71 0.36 3.61 0.59 0.90 0.16 Unknown 22.87 26.17 0.25 22.17 0.82 20.63 0.57 White 65.47 62.22 0.32 67.87 0.55 67.27 0.69

Comorbidities Coronary artery disease, n (%) 5.38 6.47 0.48 4.98 0.83 6.28 0.70 Congestive heart failure, n (%) 25.56 22.84 0.36 20.36 0.21 30.49 0.36 Hypertension, n (%) 10.76 11.31 0.80 9.50 0.75 10.31 0.88 Co-prescriptions Beta blocking agents, n (%) 75.34 60.77 <0.001 69.68 0.20 74.89 0.91 ACE inhibitors, plain, n (%) 78.03 69.57 <0.01 67.87 0.01 78.92 0.81 Platelet aggregation inhibitors excl.

heparin, n (%) 91.93 79.00 <0.001 89.59 0.41 95.51 0.07

Vasodilators, n (%) 32.29 26.36 0.06 31.67 0.84 37.22 0.29 History of Cardiac arrhythmia, n (%) 32.29 32.17 0.97 23.08 0.03 33.18 0.84 Stroke, n (%) 17.94 18.31 0.89 15.84 0.61 21.52 0.34 Myocardial infarction, n (%) 17.94 15.87 0.43 13.58 0.24 19.73 0.64 Vascular surgical procedures, n (%) 74.44 47.71 <0.001 65.61 0.05 74.44 1 Bypass surgery, n (%)

41.70 26.56 <0.001 36.20 0.24 40.36 0.75

Cohort(construcBon(

controlcilostazol

> 1000 variables

Concepts$

Pa:e

nts$

464(

17(

17 expert-selected variables

1 0 1

0 0 1

1 1 0

1 0 1

0 0 1

0 0 1

0 0 1

1 1 0

0 0 1

0 0 1

1 1 1

0 0 1

No difference in results

Outcome(in(PAD(paBents(

4/2/13 12

C1 … Cn CIL

CIL1 1 0 1 1

CIL2 0 1 1 1

: 0 0 0 1

PAD1 0 1 0 0

: 1 0 1 0

PADn 0 1 1 0

�

�

�

�

�

�

�

�

�

�

�

�

�

�

�

�

�

�

0 1 2 3 4 5 6

Revascularization procedure

Bypass procedure

Cardiac arrhythmia

Atrial fibrillation

Ventricular tachicardia

Ventricular fibrillation

Death

Stroke

Myocardial infarctionMACE

Arrhythmias

MALE

similaritypsm control

cilostazol

A B

Differences(in(cohorts(

4/2/13 13

Concepts(enriched(in(PSim(but(not(in(PSM(cohort(

•  No difference in MACE among patients taking Cilostazol

•  Uncovered a “natural experiment” that supports what clinicians suspect

�

�

�

�

�

�

�

�

�

�

�

�

�

�

�

�

�

�

0 1 2 3 4 5 6

Revascularization procedure

Bypass procedure

Cardiac arrhythmia

Atrial fibrillation

Ventricular tachicardia

Ventricular fibrillation

Death

Stroke

Myocardial infarctionMACE

Arrhythmias

MALE

similaritypsm control

cilostazol

A B

pantoprazole

zolpidem

obesity

coronaryangiography

diazepam

hydralazine

amiodarone

amoxicillin

pravastatinheart failure

pneumonia

wheelchair

congestive heart failure

cephalexin

nifedipine

insulin glargine

carotidendarterectomy

trimethoprim

ramiprildecompressive

incisiontransplantation

temazepam

sulfamethoxazole

fluoroscopicangiography

hearttransplantation tacrolimus

cane

angioplasty

ultrasonography,doppler

cilostazol

doppler studies

diagnosticimaging

vasculardiseases

vascularsurgical

procedures

bypass

revascularization

fentanyl

surgical revision

atherectomy

ultrasoundimaging

bypass graft

cilostazol

control

drugdisease

proceduredevice

Natural(experiment(

4/2/13 14

Outcome(in(CHF(paBents(Iden:fied$and$manually$confirmed$43$PAD$pa:ents$$

with$history$of$CHF$taking$Cilostazol$despite$the$black)box$warning$$

4/2/13 15

A Major adverse cardiovascular events

revascularization

bypass

angioplasty

amputation

MALE

B Major adverse limb events

palpitations

dizziness

ventricular tachycardia

ventricular fibrillation

tachycardia

conduction disease/bradyarrythmia

atrial fibrillation

ARRHYTHMIAS

C Arrhythmias and symptoms

0 0.5 1 1.5 2 2.5 3 3.5 4

sudden cardiac death

stroke

myocardial infarction

defibrillation events

death (SSDI)

cardiac arrest

MACE

0 0.5 1 1.5 2 2.5 3 3.5 4 0 0.5 1 1.5 2 2.5 3 3.5 4Odds ratio

Confirmed results in 96 PAD/CHF patients in PAMF dataset

Conclusions$

•  No$significant$differences$in$MACE$or$cardiac$arrhythmias$in$cilostazol$vs.$controls$

•  Uncovered$“natural$experiment”$CHF$pa:ents$

•  Cilostazol$has$no$differen:al$effect$on$survival$in$CHF$pa:ents$

$

•  Pa:ent)pa:ent$similarity$can$be$used$for$cohort$building$

•  Concept)concept$associa:on$networks$can$be$used$to$analyze$outcomes,$and$uncover$“natural$experiments”$

Cilostazol([is(or(is(not](associated(with(increased(risk(of(major(adverse(cardiovascular(events((MACE)(

P1( …( …( Pn(

P1( 1$ 0.6$ 0.5$ 0.6$

:( 1$ 0.2$ 0.3$

:( 1$ 0.1$

Pn( 1$

C1( …( …( Cn(

C1( 1$ 0.6$ 0.5$ 0.6$

:( 1$ 0.2$ 0.3$

:( 1$ 0.1$

Cn( 1$

controlcilostazol

zolpidem

pravastatin

nifedipine

congestive heart failure

insulin glargine

cilostazol

transplantation

trimethoprim

bypass

doppler studies

surgical revision

atherectomy

bypass graftvascular surgical

procedures

ultrasound imaging

testosterone

fentanyl

amoxicillin

heart failure

coronary angiography

pantoprazole

cephalexin

hydralazine

amiodarone

obesity

wheelchair

diazepam

pneumonia

tacrolimus

sulfamethoxazole

temazepam

decompressive incision

fluoroscopic angiography heart

transplantation

revascularization

diagnostic imaging

vascular diseases

ramipril

angioplasty

doppler ultrasonography

cane

carotid endarterectomy

Acknowledgements(

•  Shah$Lab$•  Nigam$Shah$•  Paea$LePendu$•  Rave$Harpaz$•  Srinivasan$Iyer$•  Kenneth$Jung$•  Amogh$Vasekar$•  Sandy$Huang$•  Tyler$Cole$

•  Medical$collaborator$•  Nicholas$Leeper$

4/2/13 17

•  NCBO$Team$•  Mark$Musen$•  NIH$funding$

$

•  STRIDE$Team$•  Tanya$Podchiyska$•  Todd$Ferris$

•  PAMF$Team$•  Cliff$Olson$

$

$We$are$hiring$postdocs!$

$ $ $ $ $ $ $ $$nigam@stanford.edu$