ArticleFrontiers in oncology2023
Patient characteristics and clinical factors affecting lumpectomy cavity volume: implications for partial breast irradiation.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Bracketed Lumpectomy: A Comparison of Radiofrequency Identification Tag Localization to Wire Localization.Annals of surgical oncology · 2026Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Partial breast irradiation (PBI) has increased in utilization, with the postoperative lumpectomy cavity and clips used to guide target volumes. The ideal timing to perform computed tomography (CT)-based treatment planning for this technique is unclear. Prior studies have examined change in volume over time from surgery but not the effect of patient characteristics on lumpectomy cavity volume. We sought to investigate patient and clinical factors that may contribute to larger postsurgical lumpectomy cavities and therefore predict for larger PBI volumes. Methods: A total of 351 consecutive women with invasive or Results: Median age was 61.0 years (range, 30-91), 23.9% of patients were Black people, 52.1% had hypertension, the median body mass index (BMI) was 30.4 kg/m², 11.4% received neoadjuvant chemotherapy, 32.5% were treated prone, mean interval from surgery to CT simulation was 54.1 days ± 45.9, and mean lumpectomy cavity volume was 42.2 cm Discussion: These data may be used to select patients for which longer time to simulation may result in smaller lumpectomy cavity volumes and therefore smaller PBI target volumes. Racial disparity in cavity size is not explained by known confounders and may reflect unmeasured systemic determinants of health. Larger datasets and prospective evaluation would be ideal to confirm these hypotheses.
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