Repeated recurrence of bilateral gigantomastia after subcutaneous mastectomy caused by tumoral pseudoangiomatous stromal hyperplasia: a case report and review of literature.

Pseudoangiomatous stromal hyperplasia (PASH) is an uncommon benign proliferative mesenchymal lesion of the breast with a hormonal-sensitive nature. Various manifestations of PASH, ranging from an incidental microscopic finding in a tissue biopsy to a large palpable mass or bilateral gigantomastia, have been described. For tumoral PASH, surgical excision is indicated for a growing and symptomatic mass with a small chance of recurrence. A recurrence of bilateral gigantomastia after surgical excision or reduction mammoplasty is not common but has been occasionally reported, leading to further mastectomy. Repeated recurrence of bilateral gigantomastia is extremely rare. Herein, we report a case of a 13-year-old girl who presented with the third recurrence of bilateral gigantomastia caused by tumoral PASH, after undergoing bilateral reduction mammoplasty, and later subcutaneous mastectomy. Precocious puberty occurred early in this child at the age of 9 years, which may have been a factor unmasking PASH at this young age. The incomplete removal of the PASH could also have been a recurrence risk in our case as extended masses underneath the pectoralis muscle were later identified on the MRI study. This highlights the advantage of preoperative imaging in cases with a very large tumoral PASH in order to maximize the chance of complete tumor removal.

A Clinical Prediction Model for Breast Cancer in Women Having Their First Mammogram.

BACKGROUND: Digital mammography is the most efficient screening and diagnostic modality for breast cancer (BC). However, the technology is not widely available in rural areas. This study aimed to construct a prediction model for BC in women scheduled for their first mammography at a breast center to prioritize patients on waiting lists. METHODS: This retrospective cohort study analyzed breast clinic data from January 2013 to December 2017. Clinical parameters that were significantly associated with a BC diagnosis were used to construct predictive models using stepwise multiple logistic regression. The models' discriminative capabilities were compared using receiver operating characteristic curves (AUCs). RESULTS: Data from 822 women were selected for analysis using an inverse probability weighting method. Significant risk factors were age, body mass index (BMI), family history of BC, and indicated symptoms (mass and/or nipple discharge). When these factors were used to construct a model, the model performance according to the Akaike criterion was 1387.9, and the AUC was 0.82 (95% confidence interval: 0.76-0.87). CONCLUSION: In a resource-limited setting, the priority for a first mammogram should be patients with mass and/or nipple discharge, asymptomatic patients who are older or have high BMI, and women with a family history of BC.