Cost of illness studies in rare diseases: cystic fibrosis as an example

Prof. Milan Macek, M.D, D.Sc.

Department of Biology and Medical Genetics

Charles University Prague – 2nd Faculty of Medicine

Barcelona, Val d´ Hebron VHIR– November 18, 2014

25 years of CF

research

How to apply this success in

clinical practice

in the time of austerity ?

Technology

development

&

„Interpretive

Gap“

FORGE

Canada

2014

Phenotype

PMID: 24906018 PMID: 24387988

The challenge

• Over 4700 Mendelian phenotypes with known causative gene (OMIM.org, NGS panels)

• Allelic heterogeneity is the rule

– Many genes have >100 mutations

• Disease implications

– Known (usually) for common mutations

– Variably known for low frequency mutations (<5%)

– Unknown (usually) for rare mutations (<1%)

• Clinical diagnostic DNA sequencing identifies all 3 types of mutation

Need for accurate assessment of disease-liability of mutations

• Diagnosis of clinical cases

• Newborn screening

• Carrier screening

–Pregnancy decisions

• Mutation-specific therapy

(CFTR modulating therapies)

• Molecular genetics – Mutation Specific Therapies – CFTR modulating therapies

CFTR mutations

• Over 2000 mutations identified

– One mutation is common (p.Phe508del; 70% of CF alleles)

– Twenty mutations are low frequency (15% of CF alleles)

– Remainder (>1800) are rare (15% of CF alleles)

• Disease implications of most rare mutations is unknown

Clinical variant annotation the next challenge in medical genomics:

Mutation versus Variant

PMID: 24387988

Databases

S549R

CFTR modulating therapy: mutation classes

Gating defect mutations: S549R (T>G) and G551D

„Potentiators versus Correctors“

J Cyst Fibros. 2012 May;11(3):237-45

Clinic

Laboratory

Repository

Collection of mutation data

Clinic

Laboratory

Collection of mutation data

39,689 patients> 2000 mutations

Contributors to CFTR2

Summary of data collected

Clinical data analysis35,319 patients

Lung function(FEV1% predicted)24,946 patientsb

Sweat chloride(mmol/L)

24,913 patientsa

Pancreatic status(PS or PI)

30,236 patientsc

CFTR2 database39,689 patients; 25 clinics/registries

159 mutationswith allele

frequency ≥0.01%

4,377 patients (5 registries/clinics) excluded*

Genotype70,777

chromosomes

Clinically consistent mutationAverage sweat [Cl-] ≥ 60 mEq/L

Genetically consistent mutationMutation not seen in non-transmitted

‘healthy’ CFTR gene in father of CF patient

CF-causing mutationNon-disease causing

How did we determine which mutations cause CF and which ones don’t?

A 3-pronged approach for assigning disease liability

Functionally consistent mutation

< 10% of WT CFTR function

Genetically inconsistent mutationMutation found on non-transmitted ‘healthy’

CFTR gene in father of CF patient

Improved clinical care: CFTR2.org

99

54%

87%90%

97

18 18

53%

Sweat Chloride

Pancreatic insufficiency

Average Age

Lung function

Improved education via publically available apps: CFGeneE

D11

52

H

F1

05

2V

WT

R117C R117H*

D579G

S549R*R1070W*

R347PS945L

P67L

I336K L206W

A455ED614G

R1066H

P205S

G85E0

20

40

60

80

100

1 10 100

CFT

R f

old

ing

(as

% o

f W

T)

Log CFTR chloride current (as % of WT)

T338I

L927P

G1244E

S341P

G551D

R3

34

W*

S549N

G970R

R3

52

Q

G178R

R3

47

H*

S1

25

1N

*

S997F

*

D11

0H

Channel defect

Folding and

channel defect

#

Folding defect

Mutations in red are

potentiated by

Ivacaftor/Kalydeco

Mutations cluster by ‘theratype’

Mutation in blue

responds to corrector

(VX-809)

VX-770, Ivacaftor – in vitro studies

VX-770, Ivacaftor – sweat chloride

VX-770, Ivacaftor – FEV1

KalydecoTm – mutation specific therapy in CF„CFTR modulating therapy“

Ultra-Orphan drug

for ~ 4% of CF patients

http://www.medpagetoday.com/Pulmonology/CysticFibrosis/42018

2012 2013

http://www.forbes.com/sites/matthewherper/2012/12/27/the-most-important-new-drug-of-2012/

Courtesy Dr. Wills Hughes-Wilson

Increase costs in oncology using „biological therapy“

„End of Life“ versus „Life Saving Therapies“

http://www.commonwealthfund.org/~/media/Files/Publications/Issue%20Brief/2012/Jan/1576_Chalkidou_

end_of_life_drugs_Intl_brief.pdf

Health care

Versus

Social care

Savings?

Different bugets?

Redistribution of

insurance

„Generics dividend“…. Will it shitt towards orphan medicinal products?

Background• Analysis of the economic burden in CF is important for disease management

• Assessment of baseline (direct) costs prior to the introduction of CFTRmodulating therapies for health insurance companies

• Assessment of cost effectivness and implemenation of CF treatment schemes

Klimeš et al. ERS Monogr 2014; 64: 304–319

Objectives

• To assess the direct costs of CF within the CZ medical care

• The prevalence-based cost of illness analysis was performed in relation previously identified „major cost drivers“:

– severity of CF lung disease (measured by FEV1 % predicted)

– Age / gender

– BMI (reflecting underweight = general nutritional status)

– Presence of chronic sino-bronchial infections (P. aeruginosa)

Patients and Methods

• Clinical and laboratory data from the national CF registry (www.cfregistr.cz)

• Cost data from the health insurance (www.vzp.cz, www.szpcr.cz)

• Overall, 245 CF randomly selected patients were stratified by their age, gender, BMI and BMI z-score, P. aeruginosa and FEV1% (“mild” >70; „moderate 40< and <70 and severe CF lung disease <40; % predicted)

• Healthcare costs were considered within: a) inpatient care, b) medicinal products and devices (MPD) and c) Procedures (laboratory examinations, diagnostics and outpatient care)

• All costs were in year 2010 prices

• Descriptive statistics, Multivariate regression analysis (generalized linear model – GLM)

• The average (median) patient age was 16.46 (15.0) and 34.7% were adults (older than 18 years)

• The average (median) FEV1% was 86.8% (94.0%): 76.7% patients had mild-, 14.3% moderate- and 9% severe- CF lung disease

• A total of 23.3% cases were chronically colonized with P. aeruginosa.

• The mean (median) costs of mild, moderate and severe lung disease were €3,804 (€1,069), €5,825 (€1,271), and €13,929 (€6,197)

• Patients with P. aeruginosa had substantially higher costs than those without proven infection (€3,455 vs. €10,105; Mann-Whitney p=0.0001), using ECFS registry classification.

• Costs are mostly clustered around lower monetary values, but have been increasing markedly with decreasing FEV1%

Results - 1

• In regression analysis we used only variables which are related to the direct costs:

– In the case of total costs, disease severity (measured by FEV1%) had the most significant impact on costs, while, for instance, its decrease by approximately 10 percentage points (pp) means an increase in costs by approximately 10%.

– The presence of P. aeruginosa increased the costs by 1.82 x

– Other studied variables (gender, nutritional status and age) did not significantly influence total costs.

• Chronic infection of P. aeruginosa has substantial impact on each cost category (~increased hospitalisation costs)

– inpatient costs were increased by 2.7 times

– MPD cost were increased by 5.8 times

Results - 2

DISCUSSION and Conclusions

• Health care costs and their subsections (for inpatients, MPD, procedures) are predominantly influenced by the overall CF severity reflected by FEV1, and P. aeruginosa.

• Deteriorated nutritional status significantly influences procedure costs (p=0.014).

• the costs presented in our analysis are below those reported in other European countries studies. Even if accounted for different price level (by purchasing power parity (PPP) € exchange rate, average total costs equal to PPP €6,913 (vs. €5,002)

• These data are used for negotiations with health-insurance companies

– Needs further breakdown by e.g. individual drugs utilized, adolescents x adults

– Relatively younger and generally less severe (or better treated) cohort….

Figure 1: Total mean (median) annual costs related to the overall disease

severity (cost in € 2010)

Figure 2: Mean annual costs of each cost component based on the disease

severity (cost in € 2010)

THANK YOU FOR YOUR ATTENTION!

milan.macek.jr@lfmotol.cuni.cz