This dissertation comprises a series of studies conducted as part of the Cost of Cancer Treatment Study (CCTS). An exploration of the sample size requirements for power and significance levels in clinical trials suggests that proportional representation of subpopulations in trials will often not allow valid inferences to be drawn about differential treatment effects. Where differential treatment effects in subpopulations are suspected, targeted trials should be undertaken. Underrepresentation of older cancer patients could be accounted for by exclusion criteria based on comorbid conditions that disproportionately afflict the elderly. The author compared data from patient interviews, medical records abstraction, provider billing records, and Medicare claims as data sources for estimating health care utilization rates and costs; the data were compared in terms of completeness and accessibility. Cost estimates for utilization measures were derived from administrative data using hedonic regression models. Prescription drug costs and out-of-pocket drug expenditures were compared for patients enrolled in cancer trials and for similar cancer patients with who did not participate in trials. Trial participation was associated with higher prescription drug costs, but that did not result in any significant difference in out-of-pocket expenditures for participants. These results were robust to a variety of modeling approaches.
Table of Contents
The Effect of Clinical Trial Design on Participation Rates of Elderly Cancer Patients
Comparing Data Sources for Health Services Research
Pricing Health Service Utilization Measures Using Medicare SEER Linked Data
The Effect of Clinical Trial Participation on Prescription Drug Costs and Out of Pocket Expenses