Assessing the Data Quality Dimensions of Partial and Complete Mastectomy Cohorts in the <i>All of Us</i> Research Program: Cross-Sectional Study
Our data quality framework was implemented successfully on a mastectomy phenotype. Our systematic approach identified data missingness. Moreover, the framework allowed us to differentiate breast-conserving therapy and complete mastectomy subgroups in the All of Us data.
Authors
- John Giannini (ORCID: https://orcid.org/0000-0001-7626-6540)
- Tamara R. Litwin (ORCID: https://orcid.org/0000-0003-2130-6263)
- Henry M. Spotnitz (ORCID: https://orcid.org/0000-0003-2869-0237)
- Yechiam Ostchega (ORCID: https://orcid.org/0000-0002-3598-0999)
- Lewis E. Berman (ORCID: https://orcid.org/0000-0003-3025-6990)
- Emily Clark (ORCID: https://orcid.org/0000-0002-0039-0470)
- Stephanie L. Goff (ORCID: https://orcid.org/0000-0003-3317-9804)
- Lakshmi Priya Anandan (ORCID: https://orcid.org/0009-0006-5541-0287)
Institutions
- Leidos (United States) (US)
- National Institutes of Health (US)
- National Cancer Institute (US)
- Center for Cancer Research (US)
Publication Details
- Journal
- JMIR Cancer
- Published
- 2024-12-30
- DOI
- https://doi.org/10.2196/59298
- Citations
- 3
- Primary Topic
- Breast Cancer Treatment Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.86