The Cost of Managing Lung Cancer in Canada
The Cost of Managing Lung Cancer in Canada
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.
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 . 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 .
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  and the Veterans Administration Lung Group Staging System for SCLC .
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.
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 ; NCIC clinical trial data on best supportive care versus chemotherapy (BR.5) in stage IV NSCLC patients ; 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.
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 (OHIP).
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 . 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 .