Economic evaluation of outcomes: long term primary and surrogate endpointsDr. Giampiero Favatopresented at the University Program in Health EconomicsRagusa, 26-28 June 2008

2

Measuring health and disease

Many measures are used to assess health outcomes, ranging from:– Those trying to capture the effect of an intervention on people’s general health

(e.g. quality of life, Short Form36 (SF36) or days off work). To:

– Measures of a specific dimension relevant to a particular disease (e.g. peak flow rate).

People do not have the experience or knowledge of these conditions and the interventions to make accurate judgements as to the likely benefits.

Health care policy makers also need evidence on the likely benefits from health care spending (clinical evaluation) and whether these benefits justify the costs (economic evaluation).

Primary endpoints

Surrogate endpoints

3

Continuous vs. discrete outcomes measures

When the outcomes of a study are continuous (e.g. temperature, blood pressure, or cholesterol concentrations), the researchers are usually interested in the extent to which these values change after exposure to an intervention.

Instead of measuring health outcomes on a continuous scale, studies often focus on health events, such as cases of disease, death, or hospital discharge. What these outcomes have in common is that the event either occurs or it does not; they are discrete measures.

Surrogate endpoints

Primary endpoints

4

Components of economic evaluation

Source: M. Drummond et al., Methods for the economic evaluation of health care programmes. Second edition. OUP 1997

5

Extrapolating health benefits from the short to the long term For some health care interventions, such as antibiotic

treatment for an acute infection, all the relevant benefits (and costs) occur over a relatively short period of time.

Many interventions are for diseases (that progress over time), such as Alzheimer’s disease or rheumatoid arthritis. In such cases the relevant time period for the economic evaluation could be a number of years.

If clinical studies always followed patients for a lifetime, there would be no need for extrapolation. However, long-term follow-up is costly and often infeasible, so some method of extrapolation is required in order to estimate health benefits over the relevant time period for economic evaluation.

6

Methods of extrapolation

Linking short and long-term outcomes via an epidemiological risk factor model.

Statistical extrapolations of survival curves. State transition models, the most well-known of which is the

Markov model (Briggs and Sculpher, 1998).

7

Favato G. et al. Cost-effective analysis of anti-HPV vaccination programme in Italy: a multi-cohort Markov model. Henley discussion paper series. HCVI n° 13, February 2007

Example: cost-effective analysis of anti-HPV vaccination programme in Italy. Study objective: to evaluate the cost-effectiveness of a multi-

cohort vaccination strategy. Perspective: the provider (Italian SSN) Method: multi-cohort Markov model.

8

Parameters InputsCohorts 4

Age 11, 12, 18, 25 yearsCoverage 70-80% (IC95%: 60-90)

Immunization 90% (IC95%: 80-100)Clinical efficacy 90% (IC95%: 85-100)

Doses (administered at 0, 2, 6 months)

3

Duration of protection LifetimeBooster Not necessary

Individual cost Euro 312

The model

Favato G. et al. Cost-effective analysis of anti-HPV vaccination programme in Italy: a multi-cohort Markov model. Henley discussion paper series. HCVI n° 13, February 2007

9

Vaccination strategy

11 year old cohort: reference 4 options evaluated:

– 2 cohorts (11-25 and 11-18 years)– 3 cohorts (11-18-25 years)– 4 cohorts (11-12-18-25 years)

year 1 year 2 year 3 year 4 year 5 year 6

11 17

18 25

1412 15 16 1713

2119 22 23 2420

age

age

10

0%

5%

10%

15%

20%

25%

15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 >65

Prev

alen

za H

PV

HPV

Multi-cohort strategy

11-12 years: still not exposed to HPV virus

18 years: age immediately before HPV infection peak

25 years: reduction of pre-cancerous lesions (integration with screening programme)

11

Results: 3-4 cohorts to obtain high efficiency in short-medium time

90%

35%

66%

85%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Max

theo

retic

al re

duct

ion

ofHP

V 16

/18

indu

ced

carc

inom

a (%

)

Co-horts

∆ = 5

∆ = 19

∆ = 31 Average reduction obtainablewith screening programme

12

3-4 cohorts reduce the time to event reduction

0

10

20

30

40

50

60

70

80

1 2 3 4 5 6 7 8 9

4 Coorti 3 Coorti2 Coorti 1 Coorte

Cum

ulat

ive

redu

ctio

n of

all

even

ts

(%)

5 10 3015 20 251 35 anni

Events: erroneous Pap test, colposcopies, ASCUS, LSIL, HSIL, cervical cancer and genital condilomatosis

13

Outcome

0

20

40

60

80

100

120

140

0 5 10 15 20 25 30

Costi del vaccinoRiduzione di spesa

savings

incrementalcost

years

Euro (Mill)

Break-even reached after 8 yearsOverall cost reduction > 50%

Favato G. et al. Cost-effective analysis of anti-HPV vaccination programme in Italy: a multi-cohort Markov model. Henley discussion paper series. HCVI n° 13, February 2007

14

The cost reduction for SSN progressively exceeds 50%

1.4

16.4

46.7

79.1

93.8

109.698.2

59.3

24.1

2.6

010

2030

4050

6070

8090

100110

120130

0 5 10 15 20 25

Min reduction Max reduction Average reduction

15

Dealing with uncertainty: sensitivity to cervical carcinoma in different ethnic groups

8,711,1

8,9

15,8

2,5

5,3

2,7

3,5

0

2

4

6

8

10

12

14

16

18

Bianche Colore Asiatiche Ispaniche

Casi

x 1

00.0

00

American Cancer Society. Cancer Facts & Figures 2006, Atlanta. Data Source 2005: Reis LA, Eisner PM. et al. SEER Cancer Statistics Review, 1975-2002, National Cancer Institute, Bethesda, Maryland (http//seer.cancer.gov/csr/1975_2002)Da Favato G, et al. Henley Management College, Henley (Oxford) UK, 2007

Incidenza Decessi Incidenza Decessi La stabilizzazione dei flussi

di immigrazione potrebbe determinare un ritardo nei tempi di comparsa dei benefici derivanti dalla vaccinazione, se questa fosse effettuata in una sola coorte come quella delle adolescenti di 11 anni.