Title: Hepatitis B Virus Screening before Adjuvant Chemotherapy in Patients with Early Stage

Breast Cancer: A Cost-Effectiveness Analysis: Appendix

Authors: William W. L. Wong1,2 PhD, Lisa K. Hicks3, MD, MSc, Hong-Anh Tu4, PhD, Kathleen

I. Pritchard, MD, MSc5, Murray D. Krahn1,2,4, MD, MSc, Jordan Feld6, MD, and Kelvin K.

Chan5, MD, MSc

Author Affiliations:

1Toronto Health Economics and Technology Assessment Collaborative (THETA), University of

Toronto, Toronto, ON, Canada

2University of Toronto, Leslie Dan Faculty of Pharmacy, Toronto, ON, Canada

3St Michael’s Hospital, Toronto, ON, Canada

4University of Toronto, Institute of Health Policy, Management and Evaluation, Toronto, ON,

Canada

5Sunnybrook Odette Cancer Center, Toronto, ON, Canada

6University Health Network, Toronto Centre for Liver Disease, Toronto, ON, Canada

Grant Support: This study was supported by Canadian Breast Cancer Foundation (CBCF)

Ontario.

Abbreviations:

CHB – chronic hepatitis B HBV – hepatitis B virusHBsAg – hepatitis B surface antigenHBeAg – hepatitis B “e” antigenHCC – hepatocellular carcinomaALT – alanine transaminaseQALYs – quality-adjusted life-yearsICER – incremental cost-effectiveness ratioETV – entecavirTDF – tenofovirLAM – lamivudine

Appendix 1: Detailed Methodology Section

We developed a state-transition micro-simulation model to assess the cost-effectiveness

of alternative screening strategies for patients with early stage breast cancer before adjuvant

chemotherapy.

Cohort

The study cohort included individuals diagnosed with breast cancer in Canada. The

baseline analysis focused on HBV screening in 55 year-old individuals while a broader age range

(45–65 years) was explored in sensitivity analyses.

Strategies

Three different screening strategies were evaluated for cost-effectiveness.

(1) “No screening” (Status Quo): We assumed that the majority of HBV-infected patients were

unaware of their infection prior to chemotherapy and did not receive antiviral prophylaxis to

prevent HBV reactivation. If reactivation did not occur during chemotherapy, we assumed that

0.5% of the infected but unaware individuals [1, 2] would discover that they are infected with

CHB each year and will receive anti-viral therapy according to the guideline [3]. If HBV

infection remained undetected and reactivation did not occur, we assumed that liver disease was

discovered only if they developed cirrhosis with liver failure and/or HCC. Patients who

experienced HBV reactivation during or following chemotherapy were treated with antiviral

therapy for the duration and for 6 months after the completion of chemotherapy. For those with

severe HBV reactivation, antiviral therapy was continued indefinitely after chemotherapy

completion.

(2) “Screen and Treat to prevent reactivation”: In this strategy, all individuals were screened for

HBsAg prior to starting chemotherapy. All patients who were HBsAg positive were referred to a

specialist in HBV management and offered antiviral therapy. For patients with a baseline HBV

DNA level >2,000 IU/mL, entecavir (ETV) 0.5 mg daily was used, and for patients with lower

viral loads, lamivudine (LAM) 100 mg daily was used as prophylaxis. Treatment was continued

for the duration of chemotherapy and for those with a low viral load (<2,000 IU/mL) was

stopped 6 months after completing all chemotherapy. For those with high viral load (>2,000

IU/mL), CHB treatment was continued after chemotherapy for 1 year after HBeAg loss in

HBeAg-positive patients and until HBsAg clearance in HBeAg-negative patients. HBeAg and

HBsAg clearance rates are shown in Table 1.

(3) “Screen and Treat high-risk only”: For this strategy, only foreign-born individuals were

screened for HBsAg prior to chemotherapy and received antiviral prophylaxis if the test was

found to be positive. For the base case, 20% of Canadians are assumed to be foreign-born [4].

All other individuals were not screened for HBV and were managed similarly to those in the “no

screening” strategy.

Decision Model

In our analysis, a cohort-based, state transition microsimulation model was implemented

using TreeAge Pro 2013 software [5]. Our model includes health states related to the natural

histories of breast cancer and CHB. Breast cancer health states included adjuvant chemotherapy,

disease-free stage, local relapse, treated relapse and distant relapse (Figure 1a). Hepatitis B

health states incorporated serology (HBsAg and HBeAg status), alanine transaminase (ALT)

levels, viral load and clinical states (cirrhosis, HCC, liver transplant, etc.) (Figure 1b).

In our simulations, cohort members moved between predefined health states in 3-month

cycles until all members died. In this model, CHB-infected individuals were initially assumed

to have no cirrhosis but progressed over time to different clinical states of CHB according to

their serology, ALT values, HBV DNA levels, and/or the presence or development of cirrhosis.

Those that developed cirrhosis could develop decompensated liver disease and/or HCC and

could die from complications of liver disease or require a liver transplant. Only patients in

remission from breast cancer for five or more years were eligible for liver transplantation.

Model Probabilities

Probabilities representing the likelihood of breast cancer-related events and HBV-related

events were identified from literature reviews and expert sources [1, 6-45] (Table 1).

HBV reactivation

In the model, HBV reactivation was defined as a rise in ALT (>1.5×ULN) with

concurrent 1-log rise in HBV DNA. Severe HBV reactivation was defined as grade 4 hepatitis

with either ALT or total bilirubin (>10×ULN). Patients could recover from severe HBV

reactivation or die as a result of fulminant hepatic failure. Patients experiencing a severe

reactivation would undergo a chemotherapy dose reduction. Among patients who experienced

chemotherapy dose reduction, the efficacy of the chemotherapy was modified by a hazard ratio

of 0.78 [33]. In all strategies, patients who recovered from severe reactivation would be

continuously treated with antiviral therapy according to the Canadian guidelines for CHB

treatment [3]. Probabilities related to reactivation were identified from literature reviews [33,

45]. In our baseline analysis, probability of reactivation without prophylaxis was estimated at

22% (2% with prophylaxis) [46]; probability of developing severe reactivation without

prophylaxis was 51% of those who had reactivation (20% with prophylaxis) [45]; and the

probability of death from severe reactivation was 27% [45].

Treatment for CHB

In the “Screen and Treat” strategies, our model assumed 17% of HBsAg positive patients

had high baseline HBV DNA (>2,000 IU/mL) and thus required entecavir as antiviral

prophylaxis [45]. HBeAg-positive patients were treated until 12 months after HBeAg

seroconversion. For HBeAg-negative patients, those with an HBV DNA level above 2,000

IU/mL were treated until HBsAg clearance, while those with lower baseline HBV DNA levels

were treated during and for 6 months after completion of chemotherapy. Patients with

compensated cirrhosis and detectable HBV DNA levels were treated indefinitely.

We also performed an additional analysis on lamivudine (LAM). Since the cost of LAM

is relatively low, it is still frequently prescribed in Canada [16, 17] for CHB treatment despite the

high rate of drug resistance. In the LAM analysis, patients on LAM therapy, who developed

resistance, were switched to tenofovir (TDF).

We obtained estimates of treatment effectiveness from a systematic review, Bayesian

meta-analysis[39] and from the published literature [40, 41, 44] (Table 1).

Epidemiologic Variables

The overall prevalence of HBV used in the model is 0.4% [4] (0.3% - 0.9% in sensitivity

analysis). In the model we used an HBV prevalence among immigrants of 1.6% [4].

Screening Compliance

For our model, we assumed 100% compliance with screening. In our baseline analysis, we

assumed that for a 55-year-old patient infected with CHB, this individual has a 0% chance of

being immune tolerant, a 10% chance of having HBeAg-positive CHB, a 50% chance of having

inactive CHB, and a 30% chance of having HBeAg-negative CHB. In the sensitivity analyses,

we changed this distribution to reflect to changes in the age at screening. Further details of the

distributions of CHB evaluated are listed in Appendix 2.

Direct Medical Costs and Utilities

The healthcare costs included in the analysis consist of the direct costs of screening, cost

of chemotherapy and the cost of treatment for the different breast cancer and CHB health states,

which are collected from the literature [26, 27, 45, 47-54] (Table 2).

We obtained CHB utility data from a published study [55] of over 400 patients with CHB

across different CHB health states (Table 2). Breast cancer-related utility data were collected

from the literature [56-62]. The combined health state utilities used in the analysis were

estimated by the multiplicative approach [63].

Economic Assumptions

The analysis was conducted from the payer’s perspective and was structured as a cost-

utility analysis, with outcomes expressed in quality-adjusted life-years (QALYs) and costs.

Future costs and health benefits were discounted at 5% annually [64]. Non-Canadian cost data

were converted to Canadian dollars at the purchasing power parity conversion rate [65]. All cost

data were inflated to 2014 dollars using the Statistics Canada Consumer Price Index for health

care and personal items[66].

Analytic Strategy

In our analysis, we first conducted the base-case analysis (the state transition model) to

estimate the expected value based on 100,000 micro-simulation calculations. We then ran a full

one-way sensitivity analysis on all parameters in the model over the plausible ranges using the

reported 95% confidence interval (CI) ranges or increases/decreases of 25% from base-case

estimates (Table 1 and 2). Finally we ran probabilistic sensitivity analyses (PSA) using the

Monte Carlo simulation for 5,000 iterations for all three screening strategies.

Model Validation

For validation purposes, we ran our model using the baseline parameter values. In

Appendix 3, we compared the predicted outcomes of our model against external studies [67-73].

These outcomes included: probability of breast cancer relapse, probability of breast cancer death,

probability of progression to cirrhosis and probability of liver-related death. Our model results

are closely matched with the results of external studies [67-73].

Appendix 2: Distribution of CHB patients used in our model

Disease States \ Age range

31-40 41-50 51-65 >65

Chronic HBeAg+ Hepatitis B(HBsAg: positive; HBeAg: positive; viral load: high; ALT level: high)

29% 20% 9.95% 5%

Inactive Hepatitis B(HBsAg: positive; HBeAg: negative; viral load: low; ALT level: normal)

50% 50% 50% 50%

Chronic HBeAg- Hepatitis B(HBsAg: positive; HBeAg: negative; viral load: high; ALT level: high)

20% 29% 30% 45%

Appendix 3: Validation Results: Probability of breast cancer relapse, breast cancer death, cirrhosis and liver-death

CHB disease progression phase Range of Natural History % from external studies [ 67-72 ]

Our Model %

Chronic HBeAg+ Hepatitis B to cirrhosis

8 – 17% (5 yrs) 16.3%

Chronic HBeAg- Hepatitis B to cirrhosis

13 – 38 % (5 yrs) 15.2%

Inactive Hepatitis B to HCC

0.5% – 1% (5 yrs) 1.3%

Chronic HBeAg- Hepatitis B to HCC

1 – 3% (5 yrs) 3.4%

Cirrhosis to HCC

9 – 17% (5 yrs) 12%

Probability of breast cancer relapseBC disease progression phase Range of Natural History %

from external studies [ 73 ] Our Model %

BC relapse (5 years) 26.1% 24.6%BC relapse (10 years) 37.3% 39.4%BC death (5 years) 15.9% 10.0%BC death (10 years) 29.3% 23.0%

Abbreviations: Chronic HBeAg+ Hepatitis B - (HBsAg: positive; HBeAg: positive; viral load: high; ALT level: high)

Chronic HBeAg- Hepatitis B - (HBsAg: positive; HBeAg: negative; viral load: high; ALT level: high)

Inactive Hepatitis B - (HBsAg: positive; HBeAg: negative; viral load: low; ALT level: normal) Cirrhosis: Hepatitis B Cirrhosis; HCC: hepatocellular carcinoma; BC: breast cancer

Appendix 4: Cost-effectiveness acceptability curve for “Screen and Treat to prevent reactivation” vs “no screen”.

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

2000000

0.1

0.2

0.3

0.4

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0.6

0.7

0.8

0.9

1

Acceptability Curve (No screening VS. Screen and Treat to prevent reactivation with LAM/TDF)

No ScreenScreen and Treat to prevent reac-tivation

Weight on Effect. (WTP)

% C

ost-

Eff

ecti

ve

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

2000000

0.1

0.2

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0.8

0.9

1

Acceptability Curve (No screening VS. Screen and Treat to prevent reactivation with ETV)

No ScreenScreen and Treat to prevent reac-tivation

Weight on Effect. (WTP)

% C

ost-

Eff

ecti

ve

Appendix 5: Cost-Effectiveness Results based on US prevalence data+

Strategy Cost QALYs Versus no screening Sequential ICER

∆Cost ∆QALYs ICER

No screening $53,970 10.4375 - - - -

Screen and Treat high-risk only (Screen-HR)

$54,036-

$54,073

10.4375-

10.4376

$65-

$102

0.0001-

0.0001

$473,782-

$1,413,119 Extendedly dominated

Screen and Treat to prevent reactivation (Screen-all)

$54,083-

$54,148

10.4396-

10.4398

$113-

$177

0.0022-

0.0023

$52,135-

$77,095

$52,135-

$77,095

+Population CHB prevalence = 0.27% [74]; Foreign born CHB prevalence = 0.89% [74]; non-foreign born CHB prevalence = 0.16% [74]; Proportion of foreign born population = 13% [75]

QALY = quality-adjusted life-year; ICER = incremental cost-effectiveness ratio; aExtendedly dominated = the combination of two other alternatives dominated the treatment.

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