Use of POHEM to Estimate Direct Medical Costs of Current Practice and New Treatments Associated with Lung Cancer in Canada

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Context: Lung cancer has been the leading cause of cancer deaths in Canadian males for many years, and since 1994, this has been the case for Canadian females as well. It is therefore important to evaluate the resources required for its diagnosis and treatment. This article presents an estimate of the direct medical costs associated with the diagnosis and treatment of lung cancer calculated through the use of a micro-simulation model. For disease incidence, 1992 was chosen as the reference year, whereas costs are evaluated according to the rates that prevailed in 1993. Methods: A model for lung cancer has been incorporated into the Population Health Model (POHEM). The parameters of the model were drawn in part from Statistics Canada=EDs Canadian Cancer Registry (CCR), which provides information on the incidence and histological classification of lung cancer cases in Canada. The distribution of cancer stage at diagnosis was estimated by using information from two provincial cancer registries. A team of oncologists derived =ECtypical=EE treatment approaches reflective of current practice, and the associated direct costs were calculated for these approaches. Once this information and the appropriate survival curves were incorporated into the POHEM model, overall costs of treatment were estimated by means of a Monte Carlo simulation. Results: It is estimated that overall, the direct medical costs of lung cancer diagnosis and treatment were just over $528 million. The cost per year of life gained as a result of treatment of the disease was approximately $19,450. For the first time in Canada, it was possible to estimate the five-year costs following diagnosis, by stage of the disease at the time of diagnosis. It was possible to estimate the cost per year of additional life gained for three alternative treatments of non small-cell lung cancer (NSCLC). Sensitivity analyses showed that these costs varied between $1,870 and $6,860 per year of additional life gained, which compares favourably with the costs that the treatment of other diseases may involve. Conclusions: Contrary to widespread perceptions, it appears that the treatment of lung cancer is effective from an economic standpoint. In addition, the use of a micro-simulation model such as POHEM not only makes it possible to incorporate information from various sources in a coherent manner but also offers the possibility of estimating the effect of alternative medical procedures from the standpoint of financial pressures on the health care system.