ArticleBreast cancer research and treatment2025
Patient perceptions around the use of clinico-pathologic and genomic tools in the management of early breast cancer.
Article in Breast cancer research and treatment, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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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.
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Who cites it
1 citing paper in PubMed.
- Transfer Learning and Machine Learning for Training Five-Year Survival Prognostic Models in Early Breast Cancer: Development and Validation Study.Journal of medical Internet research · 2026Article
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeClinico-pathologic (including nomograms) and genomic tools are widely used to determine prognosis and predict benefit from treatment in early breast cancer (EBC). However, little is reported on patient perceptions of these tools and whether they enhance understanding of their individual risk of recurrence or benefits from therapy.
methodsPatients with EBC were surveyed to evaluate the use of prognostic/predictive tools in clinical practice and their self-reported recurrence risk. Their actual risk of local, contralateral and distant recurrence was estimated using the INFLUENCE 2.0 tool. Information was also collected on key aspects that patients wanted these tools to address, as well as the anticipated benefits that would make receiving chemotherapy worthwhile from their perspective.
resultsCompleted surveys were received from 210 patients. Despite the use of NHS PREDICT 2.1 in 50% (105/210) and Oncotype DX in 10.9% (23/210) of patients, only 26% (45/210) stated they knew such a test had been performed. There was a mild association between patient self-assessment of distant recurrence risk and their actual risk as per INFLUENCE 2.0. When asked to rank what they wanted from prediction tools, patients identified chance of metastases (36.1%, 56/155) and chance of being disease free (31.3%, 46/147) as most important. Patients would consider chemotherapy if the survival benefit was ≥ 1% (31, 17.7%), 2-5% (23, 13.3%), 5-10% (24, 13.7%), ≥ 10% (36, 20.6%). These thresholds for benefit were significantly lower for patients who had received chemotherapy compared with those who had not.
conclusionDespite the widespread use of prognostic and predictive tools, patients often appeared unaware that one had been used. This may in part explain the lack of relationship between self-perceived and actual risk of disease recurrence.
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