ArticleAmerican journal of epidemiology2017
Protecting Confidentiality in Cancer Registry Data With Geographic Identifiers.
Article in American journal of epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Census tract-level socioeconomic variables and breast cancer characteristics and outcomes in California and New York State.Cancer causes & control : CCC · 2026Article
- Medicaid expansion in California and breast cancer incidence across neighborhoods with varying social vulnerabilities.Cancer causes & control : CCC · 2024Article
- Advancing Social and Environmental Research in Cancer Registries Using Geomasking for Address-Level Data.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023Article
- Feasibility of visualizing cancer incidence data at sub-county level: Findings from 21 National Program of Cancer Registries.Spatial and spatio-temporal epidemiology · 2023Article
- Multilevel mediation analysis on time-to-event outcomes: Exploring racial/ethnic disparities in breast cancer survival in California.Research methods in medicine & health sciences · 2021Article
- Causes of Socioeconomic Disparities in Colorectal Cancer and Intervention Framework and Strategies.Gastroenterology · 2020Review
- Protecting the Privacy of Cancer Patients Using Fuzzy Association Rule HidingAsian Pacific journal of cancer prevention : APJCP · 2019Article
- Using mobile location data in biomedical research while preserving privacy.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- A Multilevel Approach to Investigate Relationships Between Healthcare Resources and Lung Cancer.Nursing researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The National Cancer Institute's Surveillance, Epidemiology, and End Results Program releases research files of cancer registry data. These files include geographic information at the county level, but no finer. Access to finer geography, such as census tract identifiers, would enable richer analyses-for example, examination of health disparities across neighborhoods. To date, tract identifiers have been left off the research files because they could compromise the confidentiality of patients' identities. We present an approach to inclusion of tract identifiers based on multiply imputed, synthetic data. The idea is to build a predictive model of tract locations, given patient and tumor characteristics, and randomly simulate the tract of each patient by sampling from this model. For the predictive model, we use multivariate regression trees fitted to the latitude and longitude of the population centroid of each tract. We implement the approach in the registry data from California. The method results in synthetic data that reproduce a wide range (but not all) of analyses of census tract socioeconomic cancer disparities and have relatively low disclosure risks, which we assess by comparing individual patients' actual and synthetic tract locations. We conclude with a discussion of how synthetic data sets can be used by researchers with cancer registry data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.