Health Care Costs for State Transition Models in Prostate Cancer

Abstract

Objective. To obtain estimates of direct health care costs for prostate cancer (PC) from diagnosis to death to inform state transition models. Methods. A stratified random sample of PC patients residing in 3 geographically diverse regions of Ontario, Canada, and diagnosed in 1993–1994, 1997–1998, and 2001–2002, was selected from the Ontario Cancer Registry. We retrieved patients’ pathology reports to identify referring physicians and contacted surviving patients and next of kin of deceased patients for informed consent. We reviewed clinic charts to obtain data required to allocate each patient’s observation time to 11 PC-specific health states. We linked these data to health care administrative databases to calculate resource use and costs (Canadian dollars, 2008) per health state. A multivariable mixed-effects model determined predictors of costs. Results. The final sample numbered 829 patients. In the regression model, total direct costs increased with age, comorbidity, and Gleason score (all P < 0.0001). Radical prostatectomy was the most costly primary treatment health state ($4676 per 100 days). Radical prostatectomy, hormone-refractory metastatic disease ($6398 per 100 days), and final (predeath) ($13,739 per 100 days) health states were significantly more costly ( P < 0.05) than nontreated nonmetastatic PC ($3440 per 100 days), whereas the postprostatectomy ($732 per 100 days) and postradiation ($1556 per 100 days) states cost significantly less ( P < 0.0001). Conclusions. This study used an innovative but labor-intensive approach linking chart and administrative data to estimate health care costs. Researchers should weigh the potential benefits of this method against what is involved in implementation. Modifications in methodology may achieve similar gains with less outlay in individual studies. However, we believe that this is a promising approach for researchers wishing to advance the quality of costing in state transition modeling.