ArticleCancer2018
Development and validation of algorithms to differentiate ductal carcinoma in situ from invasive breast cancer within administrative claims data.
Article in Cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. It is linked to trial NCT04331535 (Pragmatic Randomized Trial of Polygenic Risk Scoring for Common Diseases in Primary Care), which is not on this map. Cited by 2 papers.
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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.
Pragmatic Randomized Trial of Polygenic Risk Scoring for Common Diseases in Primary Care
Who cites it
2 citing papers in PubMed.
- Development and Validation of an Algorithm to Achieve Complete Registration of Danish Patients with Carcinoma In Situ of the Breast, 2008-2023.Clinical epidemiology · 2026Article
- Article
Corrections and comments
- Retraction · 2019-01-16Error in Analyses · Error in Cell Lines/Tissues · Error in Data · Error in Results and/or Conclusions ·
- Retracted
Authors and funding
6 authors.
Funding
Abstract
backgroundOvertreatment is a common concern for patients with ductal carcinoma in situ (DCIS), but this entity is difficult to distinguish from invasive breast cancers in administrative claims data sets because DCIS often is coded as invasive breast cancer. Therefore, the authors developed and validated algorithms to select DCIS cases from administrative claims data to enable outcomes research in this type of data.
methodsThis retrospective cohort using invasive breast cancer and DCIS cases included women aged 66 to 70 years in the 2004 through 2011 Texas Cancer Registry (TCR) data linked to Medicare administrative claims data. TCR records were used as "gold" standards to evaluate the sensitivity, specificity, and positive predictive value (PPV) of 2 algorithms. Women with a biopsy enrolled in Medicare parts A and B at 12 months before and 6 months after their first biopsy without a second incident diagnosis of DCIS or invasive breast cancer within 12 months in the TCR were included. Women in 2010 Medicare data were selected to test the algorithms in a general sample.
resultsIn the TCR data set, a total of 6907 cases met inclusion criteria, with 1244 DCIS cases. The first algorithm had a sensitivity of 79%, a specificity of 89%, and a PPV of 62%. The second algorithm had a sensitivity of 50%, a specificity of 97%. and a PPV of 77%. Among women in the general sample, the specificity was high and the sensitivity was similar for both algorithms. However, the PPV was approximately 6% to 7% lower.
conclusionsDCIS frequently is miscoded as invasive breast cancer, and thus the proposed algorithms are useful to examine DCIS outcomes using data sets not linked to cancer registries. Cancer 2018;124:2815-2823. © 2018 American Cancer Society.
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