The Premarket Assessment of the

Cost-effectiveness of a

Predictive Technology StraticyteTM

for the Early Detection of Oral Cancer

Khoudigian S1, Blackhouse G1,2, Tsoi B1, Levine M1,2,3,

Thabane L1,3, O’Reilly D1, 2,3 1 Department of Clinical Epidemiology and Biostatistics, Faculty of Health Sciences,

McMaster University, Hamilton, ON, Canada; 2 PATH Research Institute and St Joseph’s Healthcare, Hamilton, ON, Canada;

3 Research Institute of St. Joseph’s, Hamilton, ON, Canada

CADTH Symposium 2016

Ottawa

April 12th, 2016

Outline

1. Background/ Research Objective

2. Methods

3. Results

4. Strengths/ Limitations

5. Conclusions

Disclosure

I have no actual or potential conflict of

interest in relation to this topic or

presentation.

Oral Cancer: Epidemiology & Diagnosis

Oral cancer (i.e., lip, oral cavity or oropharynx) accounts for 3% of all

cancers worldwide and was responsible for 1,100 deaths in 2013 in

Canada

Currently, the SOC for diagnosing oral cancer is the histopathologic

assessment of a tissue biopsy of the suspicious lesion.

The presence and the degree of epithelial dysplasia (i.e., mild,

moderate, severe) assesses the malignant risk of oral pre-malignant

lesions

Prognostic Tool for Oral Cancer:

StraticyteTM

Novel technology determines the risk of

an oral lesion becoming cancerous

Classified as Laboratory Developed Test

(LDT)

Objectively and more accurately ID

patients at high risk for developing oral

cancer

Potential to save lives, reduce morbidity

with less traumatic surgeries, increase

the duration of productive work lives, and

save healthcare costs

The “Histopathology” Vs. “StarticyteTM +

Histopathology” Diagnostic Algorithms

“Histopathology”

Algorithm

“StraticyteTM +

Histopathology”

Algorithm

Pre-cancerous

Lesion

MILD

dysplasia

MODERAT

E dysplasia

SEVERE

dysplasia

HIGH

risk

MEDIUM

risk

LOW

risk

HIGH

risk

MEDIUM

risk

LOW

risk

HIGH

risk

MEDIUM

risk

LOW

risk

Research Objective

To determine the cost-effectiveness of

StraticyteTM + Histopathology compared to

Histopathology alone (i.e. SOC) for the diagnosis

of oral lesions in Canada in adult patients with

suspected oral cancer, who had already

undergone biopsy.

Cost-Effectiveness Analysis (CEA) METHODS

Perspectives: Patients’ and private payers

Patient population: Individuals (≥35 years) with suspected oral cancer, who had already undergone biopsy

Outcome: Cancer cases

Time horizon: 5 years

Discounting: 5% (based on CADTH guidelines)

Sensitivity analysis: Deterministic (one-way) and Probabilistic (1000 Monte Carlo simulation)

1

2

3

4

5

6

Severe

Moderate

Mild

SOC

Cancer

No Cancer

Cancer

No Cancer

Cancer

No Cancer

M

M

M

M

M

M

Patients

with

Dysplasia

“Histopathology”

Algorithm

Decide which

diagnostic

test to use

“Histopathology + StraticyteTM”

Algorithm

Patients

with

Dysplasia

0

0

0

SOC +

StraticyteTM

High Risk

Medium Risk

Low Risk

High Risk

Medium Risk

Low Risk

High Risk

Medium Risk

Low Risk

Cancer

No Cancer

Cancer

No Cancer

Cancer

No Cancer

Cancer

No Cancer

Cancer

No Cancer

Cancer

No Cancer

Cancer

No Cancer

Cancer

No Cancer

Cancer

No Cancer

M

M

M

M

M

M

M

M

M

M

M

M

M

M

M

M

M

M

Decide which

diagnostic

test to use

Additional Scenarios

Scenario #1

(Assesses only 2

categories)

Moderate

Mild

Scenario #2

(Assesses only 1

category)

Mild

Base Case Analysis

(Assesses all 3 categories)

Severe

Moderate

Mild

Model Details and Assumptions

Decision tree POPULATED

based on the retrospective

study

Relative Risk of MTR given

treatment mortality was

OBTAINED from SR

Decision tree

DEVELOPED

ASSUMPTION

MTR reflects the

natural disease

progression

Experts interview CONDUCTED to

determine change in clinical

practice given StarticyteTM

APPLICATION

RR where

appropriate given

the interview

outcome

Decision tree RE-POPULATED

based on the SR and Experts

interview

Analysis/

Results

Step #1

Step #4

Step #3

Step #5

Step #2

Results – Base Case Analysis

Histopathology Histopathology+

StraticyteTM

Total Cost $ 3,962.76 $ 3,723.02

Total cancer cases 0.30 0.24

Incremental cost $ -239.74

DOMINATES Cancer cases

avoided

0.06

Results – Scenario Analyses

Scenario #1 (Moderate and Mild Cases)

Histopathology Histopathology+ StraticyteTM

Total Cost $2,885.79 $2,578.30

Total cancer cases 0.23 0.16

Incremental cost $-307.49 DOMINATES

Cancer cases avoided 0.06

Scenario #2 (Mild cases)

Histopathology Histopathology+ StraticyteTM

Total Cost $577.71 $1,078.32

Total cancer cases 0.14 0.08

Incremental cost $500.61

IS DOMINATED by

HISTOPATHOLOGY

Cancer cases avoided 0.06

ICER $7,854.09/ cancer case

avoided

ICUR Plane – Base Case Analysis

-7000

-5000

-3000

-1000

1000

3000

5000

7000

-0.04 -0.02 0 0.02 0.04 0.06 0.08

Δ C

os

t

Cancer cases avoided

Base case

NE NW

SW SE

New treatment

DOMINATES

New treatment

Is

DOMINATED

Scenario #1

Scenario #2

Probabilistic Sensitivity Analysis

-1000.00

-800.00

-600.00

-400.00

-200.00

0.00

200.00

400.00

600.00

-0.15 -0.10 -0.05 0.00 0.05 0.10 0.15 0.20 0.25

Δ C

os

t

Cancer cases avoided

69%

Of the time

Dominates

23%

Of the time

Expensive &

More Effective

6%

Of the time

Cheaper & Less

Effective

3%

Of the time

Expensive & Less

Effective

Strengths and Limitations of this Study Strengths:

First to assess the cost-effectiveness of StraticyteTM

Helps prepare for its licensing and the adoption

Supports internal investment decisions in order to prioritize

potential products to take forward

Helps avoid investing in technologies that are unlikely to be

cost-effective

It allows the investigation of its potential downstream impact

Limitations: First to market- No clinical and economic evidence in literature

Classified as Laboratory Developed Test (LDT)

• Pre-market review and other applicable FDA

requirements are not required for LDT

Easy to introduce into the market but hard to seek reimbursement

CONCLUSIONS

The “StraticyteTM and Histopathology” diagnostic

algorithm would be less expensive and results in less

cancer cases than “Histopathology” alone

Scenario #1: “StraticyteTM and Histopathology” dominant

strategy

Scenario #2: “StraticyteTM and Histopathology” dominated by

“Histopathology” alone

Probabilistic sensitivity analysis demonstrates:

• The “StraticyteTM and Histopathology” diagnostic algorithm would

be cost-effective over a wide range of WTP values

THANK YOU!

Shoghag Khoudigian, H.BSc PhD. Candidate

Department of Clinical Epidemiology and Biostatistics,

McMaster University

Programs for Assessment of Technology in Health (PATH) Research Institute, St Joseph’s Healthcare

Hamilton

Telephone: (905) 523-7284 ext. 5275

Fax: (905) 522-0568

Email: khoudisv@mcmaster.ca

25 Main Street West

20th floor, Suite 2000

Hamilton, ON L8P 1H1

BACK UP

ICUR plane:

New

treatment more

effective

New

treatment less

effective

New

treatment

more costly

New

treatment

less costly

Existing

treatment

dominates

New treatment more

effective but more

costly

New treatment less

costly but less

effective

New

treatment

dominates

Maximum

Acceptable ICUR

North

East North

West

South

West South

East

Model Parameters

Transition Probabilities

Retrospective study

1 study (n=107) from Mt Sinai Hospital

5 year follow-up

No treatment information

RR of Malignant Transformation

Comprehensive SR 5 retrospective studies reported

the development of cancer given treatment modality (i.e. excision vs. no-excision)

None used the StraticyteTM

Biomarker

Clinical Practice by O&M Surgeons

Brief Eliciting method

Experts interview (n=4) on treatment given a dysplasia grading and how the introduction of StraticyteTM might change their practice

Common prescribed medications to patients after excision

Average number of days off work after excision

Costs and Resources

Direct & In-Direct costs

ODA suggested fee for services

Mount Sinai Hospital & Laboratory Medicine

StraticyteTM cost based on Proteocyte Diagnostics Inc.

Statistics Canada and Canada Revenue Agency

Model Input Parameters- Probabilities

To determine the relative risk of developing oral cancer in patients

who had local excision (surgery)

MEDLINE and EMBASE databases were used

Keywords:

• “dysplasia”, “oral or epithelial or mouth”, “progress”, “follow-up”, “treat”, “monitor”,

and “risk reduction”

No limits on year and language were applied

Inclusion criteria:

• RCTs, comparative observational studies

• Comparing outcomes of patients who had surgery vs. who were

solely monitored for at least 5 years

Model Input Parameters- RR of Malignant

Transformation

PRISMA Diagram

EMBASE (n = 1480)

2669 Total Records

1036 duplicates excluded

1633 Records

(title and abstract) screened

1573 Records excluded

60 Full-text articles assessed

for eligibility

55 Studies excluded:

Not RCT or OB

(n=21)

No comparator (n=

25)

Wrong outcome

(n=5)

Not English (n=4)

5 Studies included in synthesis

Ide

ntification

Scre

en

ing

Elig

ibili

ty

MEDLINE (n = 1189)

Inclu

de

d

1 grey literature • The following data were abstracted

from 5 included studies:

1. Authors

2. Year

3. Type and setting of the study

4. Mean age

5. Mean follow-up time

6. Number of patients in each

arm

7. Malignant transformation rate

Study Characteristics

First

author/ year

Country Methodology

/setting

Date of

enrollment

Mean

age

# of cancer

cases/ total #

of surgically

treated

patients

# of cancer

cases/ total #

of non-

surgically

treated

patients

Saito,

2001

Japan Retrospective/

Hospital 1976-1997 54 1/48 3/34

Banoczy,

1976 Hungary Retrospective/

Hospital NR NR 1/45 8/23

Arduino,

2009 Italy Retrospective/

Hospital 1991-2007 63.58 7/133 3/74

Arnaoutakis,

2013 USA Retrospective/

Hospital 1990-2011 59.2 14/75 17/38

Holmstrup,

2006 Denmark Retrospective/

Pathology

laboratory

1977-1997 60.8 8/67 2/21

The Forest Plot

Model Input Parameters- Clinical

Practice by Oral Surgeons

Treatment Follow-up

Histopathology

Severe Dysplasia Excision Every 6 months for 5 years

Moderate Dysplasia Excision Every 3 months for 5 years

Mild Dysplasia Monitor -

Histopathology + StraticyteTM

Severe + High Risk Excision Every 6 months for 5 years

Severe + Medium Risk Excision Every 6 months for 5 years

Severe + Low Risk Excision Every 6 months for 5 years

Moderate + High Risk Excision Every 6 months for 5 years

Moderate + Medium Risk Excision Every 6 months for 5 years

Moderate + Low Risk Excision Every 3 months for 5 years

Mild + High Risk Excision Every 6 months for 5 years

Mild + Medium Risk Excision Every 6 months for 5 years

Mild + Low Risk Monitor Every 6 months for 2 years

Interview Results

Deterministic Sensitivity Analysis

SOC +StraticyteTM Algorithm vs. SOC Algorithm

Conservative Values Optimistic Values

Inc.

Cost

Cancer

cases

avoided

ICER

($/cancer

case

avoided)

Inc.

Cost

Cancer

cases

avoided

ICER

($/cancer

case

avoided)

Visits every 6

months per year $-714.29 0.06 -11,206.67 $326.98 0.06 5,130.08

DOMINATES DOES NOT DOMINATE

RR of malignant

transformation given

excision

$-193.66 0.09 -2,242.55 $-193.66 0.01 -15,697.86

DOMINATES DOMINATES

Visits every 3

months per year $206.75 0.06 3,243.74 $-594.06 0.06 -9,320.33

DOES NOT DOMINATE DOMINATES