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Published on: May 17, 2019
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Secondary databases in gynecologic cancer research
Katherine Hicks-Courant1, Emily Meichun Ko2, Koji Matsuo3
1Ann B. Barshinger Cancer Institute, Lancaster General Health, Lancaster, Pennsylvania, USA; Division of Gynecologic Oncology, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA.
Summary
This review clarifies the strengths and weaknesses of large cancer databases like NCDB and SEER for gynecologic oncology research. Understanding these datasets improves the interpretation and application of study findings.
Area of Science:
- Gynecologic Oncology
- Health Services Research
- Biostatistics
Background:
- Large observational and cohort studies are crucial in gynecologic oncology.
- Understanding the characteristics of commonly used research databases is essential for accurate interpretation of findings.
- Researchers need to be aware of both the advantages and limitations of these data sources.
Purpose of the Study:
- To provide a comprehensive overview of major databases used in gynecologic oncology research.
- To detail the data, access, management, and limitations of key databases.
- To enhance the effective use and evaluation of research utilizing these datasets.
Main Methods:
- Review of prominent databases including NCDB, SEER, SEER-Medicare, MarketScan, HCUP, NSQIP, and Premier.
- Description of data content, accessibility, and management protocols for each database.
- Analysis of the highlights and limitations inherent to each data source.
Main Results:
- Detailed descriptions of seven major databases used in gynecologic oncology research.
- Identification of specific strengths and weaknesses for each database.
- Guidance on interpreting and applying results from studies using these datasets.
Conclusions:
- A thorough understanding of database specifics aids in the critical evaluation of gynecologic oncology research.
- Improved knowledge of datasets facilitates the development of practice-changing studies.
- This review empowers researchers, reviewers, and readers to better utilize and interpret findings from large-scale studies.
Keywords:
Cost-Benefit AnalysisCost-Effectiveness AnalysisCosts and Cost AnalysisCross-Sectional StudiesRetrospective Study
