Merging of the National Cancer Institute-funded
cooperative oncology group data with an administrative data source to develop a more effective platform for clinical trial analysis and comparative effectiveness research: a report from the Children's Oncology Group.
Pharmacoepidemiol Drug Saf 2012;
21 Suppl 2:37-43. [PMID:
22552978 PMCID:
PMC3359580 DOI:
10.1002/pds.3241]
[Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
PURPOSE
The National Cancer Institute-funded cooperative oncology group trials have improved overall survival for children with cancer from 10% to 85% and have set standards of care for adults with malignancies. Despite these successes, cooperative oncology groups currently face substantial challenges. We are working to develop methods to improve the efficiency and effectiveness of these trials. Specifically, we merged data from the Children's Oncology Group (COG) and the Pediatric Health Information Systems (PHIS) to improve toxicity monitoring, to estimate treatment-associated resource utilization and costs, and to address important clinical epidemiology questions.
METHODS
COG and PHIS data on patients enrolled on a phase III COG trial for de novo acute myeloid leukemia at 43 PHIS hospitals were merged using a probabilistic algorithm. Resource utilization summary statistics were then tabulated for the first chemotherapy course based on PHIS data.
RESULTS
Of 416 patients enrolled on the phase III COG trial at PHIS centers, 392 (94%) were successfully matched. Of these, 378 (96%) had inpatient PHIS data available beginning at the date of study enrollment. For these, daily blood product usage and anti-infective exposures were tabulated and standardized costs were described.
CONCLUSIONS
These data demonstrate that patients enrolled in a cooperative group oncology trial can be successfully identified in an administrative data set and that supportive care resource utilization can be described. Further work is required to optimize the merging algorithm, map resource utilization metrics to the National Cancer Institute Common Toxicity Criteria for monitoring toxicity, to perform comparative effectiveness studies, and to estimate the costs associated with protocol therapy.
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