Female breast cancer incidence predisposing risk factors identification using nationwide big data: a matched nested case-control study in Taiwan.

BACKGROUND: Breast cancer is an umbrella term referring to a group of biologically and molecularly heterogeneous diseases originating from the breast. Globally, incidences of breast cancer has been increasing dramatically over the past decades. Analyses of multiple clinical "big data" can aid us in clarifying the means of preventing the disease. In addition, predisposing risk factors will be the most important issues if we can confirm their relevance. This study aims to provide an overview of the predisposing factors that contribute to a higher possibility of developing breast cancer and emphasize the signs that we ought to pay more attention to. METHODS: This is a matched nested case-control study. The cohort focused on identifying the eligible risk factors in breast cancer development by data screening (2000-2013) from the Taiwan National Health Insurance Research Database (NHIRD) under approved protocol. A total of 486,069 females were enrolled from a nationwide sampled database, and 3281 females was elligible as breast cancer cohort, 478,574 females who had never diagnosed with breast cancer from 2000 to 2013 were eligible as non-breast cancer controls, and matched to breast cancer cases according to age using a 1:6 ratio. RESULTS: We analyzed 3281 breast cancer cases and 19,686 non-breast cancer controls after an age-matched procedure. The significant predisposing factors associated with breast cancer development including obesity, hyperlipidemia, thyroid cancer and liver cancer. As for patients under the age of 55, gastric cancer does seem to have an impact on the development of breast cancer; compared with their counterparts over the age of 55, endometrial cancer appears to exhibit an evocative effect. CONCLUSIONS: In this nationwide matched nested case-control study, we identified obesity, hyperlipidemia, previous cancers of the thyroid, stomach and liver as risk factors associated with breast cancer. However, the retrospective nature and limited case numbers of certain cancers still difficult to provide robust evidence. Further prospective studies are necessitated to corroborate this finding in order to nip the disease in the bud. TRIAL REGISTRATION: The studies involving human participants were reviewed and approved by the China Medical University Hospital [CMUH104-REC2-115(AR-4)].

A giant malignant phyllodes tumor of breast post mastectomy with metastasis to stomach manifesting as anemia: a case report and review of literature.

BACKGROUND: Phyllodes tumors (PTs) are well known for local recurrence and progression. Less than 10% of these tumors grow larger than 10 cm. Distant metastases have been reported in up to 22% of malignant PTs, with most metastases being discovered in the lungs. PTs of the breast rarely metastasize to the gastrointestinal tract, and reported cases are scarce. To date, a review of the English literature revealed only 3 cases, including our case, of PTs metastasis to stomach. CASE PRESENTATION: An 82-year-old female patient had 10-year-duration of palpable huge tumor on left breast which was in rapid growth in recent months. Total mastectomy of left breast was performed thereafter, and pathology diagnosis was malignant phyllodes tumor. Adjuvant radiotherapy was suggested while she declined out of personal reasons initially. For PTs recurred locally on left chest wall 2 months later, and excision of the recurrent PTs was performed. She, at length, completed adjuvant radiation therapy since then. Six months later, she was diagnosed of metastasis to stomach due to severe anemia with symptom of melena. Gastrostomy with tumor excision was performed for uncontrollable tumor bleeding. CONCLUSION: For PTs presenting as anemia without known etiologies, further studies are suggested to rule out possible gastrointestinal tract metastasis though such cases are extremely rare. Management of metastatic gastric tumor from PTs should be done on a case-to-case basis, surgical intervention may be needed if there is persistent active bleeding despite medical treatment. Adjuvant radiotherapy is recommended in borderline and malignant PTs with tumor-free margin < 1 cm and high-risk malignant tumors. Adjuvant chemotherapy or target therapy may be helpful for metastatic PTs. Molecular and genomic techniques may predict clinical outcomes of benign and borderline PTs more precisely.

Intra-abdominal bleeding with hemorrhagic shock: a case of adrenal myelolipoma and review of literature.

Background: Adrenal myelolipoma is an uncommon, benign, and hormonally non-functioning tumor that is composed of mature adipose tissue and normal hematopoietic tissue. Most cases to date are asymptomatic or have epigastric pain. Acute hemorrhage is the most dramatic manifestation of adrenal myelolipoma; though, it is a rare entity. Hemorrhagic shock due to adrenal myelolipoma, to our knowledge, was much less mentioned so far. Persistent bleeding and uncontrollable hypotension are considered to be absolute indications for immediate surgical operation. Case presentation: Herein we presented a 32-year-old male patient with initial symptoms of nausea, vomiting, and epigastric pain progressing to altered consciousness and hypotension during ER course. Hemorrhagic shock due to a giant adrenal myelolipoma, R't was diagnosed. Emergent exploratory laparotomy was executed, and en bloc excision of tumor was done. Conclusion: Adrenal myelolipoma might be diagnosed as a adjunction to other main causes of illness; furthermore, adrenal myelolipoma could be asymptomatic in lifetime. In our case, however, manifesting as hemorrhage shock was challenging to diagnose step by step; instead, maintaining vital organs perfusion and identifying bleeding sources were to be done. Management of myelolipoma should be done on a case-to-case basis.

Identification of Skin Lesions by Snapshot Hyperspectral Imaging.

This study pioneers the application of artificial intelligence (AI) and hyperspectral imaging (HSI) in the diagnosis of skin cancer lesions, particularly focusing on Mycosis fungoides (MF) and its differentiation from psoriasis (PsO) and atopic dermatitis (AD). By utilizing a comprehensive dataset of 1659 skin images, including cases of MF, PsO, AD, and normal skin, a novel multi-frame AI algorithm was used for computer-aided diagnosis. The automatic segmentation and classification of skin lesions were further explored using advanced techniques, such as U-Net Attention models and XGBoost algorithms, transforming images from the color space to the spectral domain. The potential of AI and HSI in dermatological diagnostics was underscored, offering a noninvasive, efficient, and accurate alternative to traditional methods. The findings are particularly crucial for early-stage invasive lesion detection in MF, showcasing the model's robust performance in segmenting and classifying lesions and its superior predictive accuracy validated through k-fold cross-validation. The model attained its optimal performance with a k-fold cross-validation value of 7, achieving a sensitivity of 90.72%, a specificity of 96.76%, an F1-score of 90.08%, and an ROC-AUC of 0.9351. This study marks a substantial advancement in dermatological diagnostics, thereby contributing significantly to the early and precise identification of skin malignancies and inflammatory conditions.