NCDB National Cancer Database Participant User Files - onetomapanalytics/Meta_Data GitHub Wiki
NCDB - National Cancer Database Participant User Files (PUF)
General description
- Database primary purpose - Review and advance the quality of care delivered to cancer patients through analyses of cases reported to the NCDB
- Overall data type - Health outcomes
- Dataset type - Longitudinal
- Data source - Registry
- Data level - Patient level
- Geographic location of the data collection sites - United States
- Sponsor, manager, or home institution - Commission on Cancer of the American College of Surgeons and the American Cancer Society
- Date range - 2004 - 2014
- Geolocation data - Facility location based on the U.S. Census division
- Dates - Year of diagnosis
- Hospital identifiers - Facility de-identified ID
- Longitudinal tracking - Track patients and facility through the de-identified case and facility PUF ID
- Clinical areas of interest - Cancer
- Number of records - Data is collected in more than 1,500 Commission on Cancer-accredited facilities (1), including 31 million records for patients diagnosed between 1985-2015 (2)
- Variables that are uniquely present in this dataset - Data regarding cases submitted to the Commission on Cancer’s (CoC) NCDB
Applicable methods
- Association methods, such as Cox proportional hazards regression models (3, 4, 5), logistic regression (6, 7, 8), multivariate analysis (9)
- Inferential tests (10)
- Time to event (11, 12)
- Difference-in-difference (13, 14)
- Propensity scores (15, 16)
High-impact designs
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Describe the use of the NCDB to study cancer care (17)
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Compare the number of incident cancer cases in the NCDB with other datasets, such as the United States Cancer Statistics data (2), SEER-Medicare (11, 18), and the Duke University registry (19)
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Propose a revised pathologic staging classification and examine its prognostic value (10)
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Compare results from observational cancer registry data with those of randomized clinical trials (3)
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Evaluate overall survival outcomes following a surgical treatment (20, 21)
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Compare differences in surgery pre- and post-Medicaid expansion (13)
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Describe patterns of metastasis and treatment (22)
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Determine the effect of hospital affiliation and volume on mortality (23, 24)
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Identify the incidence, risk factors, and impact on survival associated with refusal of treatment (25)
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Evaluate disparities on surgical treatment based on sociodemographic factor (26, 27, 28), geographic region (29), between Veteran and non-Veteran patients (30), race (31)
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Compare distinct approaches in relation to outcomes and survival rates (32, 33)
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Determine temporal trends in chemotherapy use (34)
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Examine the impact of radiation, chemotherapy, and immunotherapy on outcomes and survival (19, 35, 36)
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Quantify internally inconsistent and anomalous radiation therapy data and determine their association with overall survival 5
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Determine whether circulating tumor cells status is predictive of radiotherapeutic benefit in early-stage cancer (37)
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Assess the role of facility type on survival (38)
Data dictionary
To access the NCDB PUF data dictionary, click here
Variable categories
- Facility (e.g., type and location)
- Patient demographics (e.g., age, sex, race, primary payor, income, education, Charlson score)
- Cancer identification (e.g., primary site, laterality, histology, behavior, grade, size)
- Stage of disease (e.g., diagnostic and staging procedure, pathologic stage group, site-specific factor)
- Treatment (e.g., surgical procedure, approach, radiation, chemotherapy, palliative care)
- Outcomes (e.g., discharge, readmission, mortality, vital status)