Women with a family history of breast cancer who develop the disease face no worse of a prognosis than others who develop breast cancer, according to a new study published in BJS.
Dr. Ramsey Cutress, PhD, from the University of Southampton and University Hospital Southampton NHS Foundation Trust, and colleagues conducted an analysis of the Prospective Study of Outcomes in Sporadic Versus Hereditary Breast Cancer (POSH).
POSH was led by Dr. Diana Eccles and included 2,850 women younger than 41 who were diagnosed with breast cancer and treated in the U.K. The study tracked patients' personal characteristics, tumor characteristics, treatment, and family history of breast or ovarian cancer over a 15-year period.
There were no significant differences in cancer recurrence rates after treatment for women with a history of breast cancer versus those without, Cutress and colleagues found (BJS, May 20, 2015).
"Successful treatment for breast cancer is just as likely in young patients with a family history of breast cancer, as in those without a family history," Cutress said in a statement released by the University of Southampton. "Patients with a family history of breast cancer can therefore be reassured that their family history alone does not mean that their outcome will be worse."
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=100&q=70&w=100)
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
