The Cost of Managing Lung Cancer in Canada

The Cost of Managing Lung Cancer in Canada

ABSTRACT: The POpulation HEalth Model (POHEM) lung cancer microsimulation model has provided a useful framework for calculating the cost of managing individual cases of lung cancer in Canada by stage, cell type, and treatment modality, as well as the total economic burden of managing all cases of lung cancer diagnosed in Canada. These data allow an estimation of the overall cost effectiveness of lung cancer therapy. The model also provides a framework for evaluating the cost effectiveness of new therapeutic strategies, such as combined modality therapy for stage III disease or new chemotherapy drugs for stage IV disease. By expressing the cost of lung cancer treatment as cost of life-years gained, such analyses allows useful comparisons of the cost effectiveness of these treatments with those of other costly but accepted medical therapies. [ONCOLOGY 9(Suppl):147-153, 1995]


Lung cancer is a disease of epidemic proportions in North America
and the leading cause of cancer mortality for both men and women
in Canada and the United States [1,2]. There is a widely held
view that the cost of treating patients with lung cancer places
a large economic burden on the increasingly constrained health
care resources of both countries. In reality, there have been
few data available to show whether this belief is fact or fiction.
To understand the extent of the economic burden of lung cancer
in Canada, and to be better able to predict future costs, requires
a careful analysis of the complex interaction among population
demographics, smoking patterns, distribution of lung cancer cell
types and stages, treatment options, and the actual cost of care.

The Social and Economics Study Division of Statistics Canada (the
Canadian government statistical agency) is in the process of developing
a comprehensive microsimulation model of Canadian health, incorporating
population demographics, risk factors, the distribution of disease
states, and treatment options for a number of common diseases
affecting Canadians, including lung cancer [3]. Ultimately, this
POpulation HEalth Model (POHEM) will also include breast cancer,
cardiovascular disease, dementia, and arthritis. Using POHEM,
it has been possible to estimate the cost of managing an individual
case of lung cancer, according to its stage and cell type, and
to determine the total economic burden of managing all cases of
lung cancer diagnosed in Canada. From this information and data
on the survival of patients with lung cancer, it is then possible
to estimate the overall cost effectiveness of lung cancer therapy.
In addition, the model allows for simulation of new treatment
approaches, such as the use of combined modality therapy for stage
III disease or of new chemotherapy drugs for stage IV disease,
and estimation of their cost per case and cost effectiveness.

This manuscript will briefly describe the POHEM model and some
of the key observations that have been made relating to the economic
burden of lung cancer on the Canadian health care system. Some
of this information has been presented previously [4,5].


The POpulation HEalth Model (POHEM) is a software framework that
integrates data on risk factors, disease onset and outcomes, health
care utilization, and direct medical care costs. The computer
program generates a synthetic cohort of people with demographic
and labor force characteristics, risk factors exposures, and health
histories typical of Canadians [3].

The Lung Cancer Submodel

When an individual is assigned a diagnosis of lung cancer in the
microsimulation model, the lung cancer submodel then assigns a
particular histologic cell type and stage based on the distribution
of these characteristics in the Canadian population. It further
assigns treatment and subsequent progression of the disease using
lung cancer survival rates from the medical literature. Finally,
it assigns costs for the various components of care appropriate
for the management of that cell type and stage of disease.

To construct the POHEM lung cancer submodel, we first obtained
information on the distribution of lung cancer cases according
to demographic characteristics and tumor cell types. These data
were obtained from the National Cancer Incidence Reporting System
(NCIRS), which is maintained by the Health Statistics Division
of Statistics Canada. This information is collected annually from
Canada's 10 provincial and two territorial cancer registries.
Information in NCIRS is available on patient age, gender, and
tumor cell type.

When this project began, only 1984 data were available from NCIRS.
Subsequently, 1988 incident cases became available, and they are
the database on which the model is currently structured. For that
reason also, costing was done in 1988 Canadian dollars. In that
year, 15,817 cases of lung cancer were reported, of which 15,624
were either non-small-cell lung cancer (NSCLC) or small-cell lung
cancer (SCLC). Unfortunately, staging information was not available
from the NCIRS database, and it was therefore necessary to retrospectively
stage a cohort of lung cancer cases. This was done using the new
international TNM staging system for NSCLC [6] and the Veterans
Administration Lung Group Staging System for SCLC [7].

Statistics Canada contracted with the Alberta Cancer Board and
the Ontario Cancer Registry to review the charts of all cases
diagnosed in the Province of Alberta in 1984 and of 1,000 cases
diagnosed in 1984 and 1985 in the Province of Ontario. Of the
856 cases from Alberta in 1984, 57% contained sufficient information
for staging, as did 62% of the Ontario sample. The combined Alberta
and Ontario staging data were then used to estimate the probability
of the 1988 incident cases being at a particular stage given a
particular cell type, gender, and age. We assumed that between
1984 and 1988 no new diagnostic approaches were introduced that
might have caused stage migration.

Clinical Algorithms

Simplified clinical algorithms of lung cancer management were
constructed. Those knowledgeable of lung cancer will appreciate
from the example shown in the Figure of stages I and II NSCLC
that the model does not address all potential diagnostic and therapeutic
interventions. Nonetheless, it was constructed taking into account
the practice recommendations within the US National Cancer Institute's
Patient Data Query (PDQ) database, with modifications for Canadian
practice according to a lung cancer expert panel made up of physicians
working at the Ottawa Regional Cancer Centre. In addition, Canadian
thoracic surgeons and radiation oncologists completed a national
questionnaire survey of practice patterns, and this was used in
estimating the proportion of patients that Canadian physicians
would refer for treatment and, in the case of radiation therapy,
the dose and number of fractions that would be administered.

In determining the makeup of the diagnostic submodel, only essential
diagnostic tests were included, with the understanding that this
would tend to underestimate the costs of diagnosis. In practice,
some tests are repeated as a patient is referred from one physician
to another, and lung cancer does not always present in a straightforward
fashion. In addition, investigations for paraneoplastic syndromes
can add considerably to the cost of the diagnostic workup, but
these factors were ignored in the diagnostic test module. Similarly,
tests were only repeated in the model when they were considered
essential to monitor therapy. It was assumed that diagnostic procedures
and surgical/radiotherapy treatment interventions were uncomplicated.
These decisions were necessary because of the lack of available
data on resource utilization for lung cancer management through
provincial data information systems. However, valuable information
was obtained from the Ontario Cancer Registry about the average
duration of hospitalization during diagnostic workup and initial
therapy. The extent of outpatient clinic utilization and hospitalization
for chemotherapy delivery or best supportive care was obtained
from previously reported lung cancer studies done by the National
Cancer Institute of Canada (NCIC) (BR.4 and BR.5) [8,9].

Patient survival was based on data in the medical literature and
was assigned, as appropriate, for cell type and stage. The data
sources used included Lung Cancer Study Group data on the survival
of surgically resected NSCLC patients [10,11]; Radiation Therapy
Oncology Group (RTOG) data on the survival of stage III NSCLC
patients [12]; NCIC clinical trial data on best supportive care
versus chemotherapy (BR.5) in stage IV NSCLC patients [9]; and
NCIC clinical trials (BR.3 and BR.4) of therapy for patients with
limited and extensive SCLC [8,13]. When incorporating survival
information into the model, it was assumed that if a patient survived
5 years from the diagnosis of lung cancer, he or she was cured,
and no additional costs for lung cancer management were incurred.

Cost Determination

The perspective of this economic analysis was that of the Canadian
government as payer in a universal health care system. As such,
the analysis specifically excludes indirect costs, such as out-of-pocket
costs to patients for oral medications, travel to a treatment
center, parking, and lost wages. All costs were determined in
1988 Canadian dollars. Although each province and territory has
a different schedule of benefits for medical assessments, procedures,
and laboratory tests, we assumed that these benefits would be
similar to those paid in Ontario under its Health Insurance Plan

The cost of hospitalization for the surgical management of NSCLC
patients was based on a per diem rate of $545.19, which was obtained
from Statistics Canada's Annual Return of Hospitals-Hospital Indicators:
1988 to 1989 [14]. This per diem rate was the average cost per
day of care in a tertiary health care facility where, presumably,
most thoracic surgery is performed. The cost of hospitalization
for the inpatient care of patients with SCLC and for the provision
of supportive care was extracted from the economic analyses done
previously by the NCIC during its BR.4 and BR.5 studies [15,16].
This average per diem was $361.00. The cost of a radiotherapy
treatment fraction was based on a study by Wodinsky and Jenkin
in which they determined the cost of operating a radiotherapy
treatment facility in Ontario [17].


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