Rare Breast Cancer Histotypes-A Retrospective Study and Literature Review.

Breast cancer is the most common cancer among women globally and can be classified according to various histological subtypes. Current treatment strategies are typically based on the cancer stage and molecular subtypes. This article aims to address the knowledge gap in the understanding of rare breast cancer. A retrospective study was conducted on 4393 breast cancer patients diagnosed from 1992 to 2012, focusing on five rare subtypes: mucinous, invasive lobular, papillary, mixed invasive and lobular, and pure tubular/cribriform carcinomas. Our analysis, supplemented by a literature review, compared patient characteristics, disease characteristics, and survival outcomes of rare breast cancer patients with invasive carcinoma (not otherwise specified (NOS)). Comparative analysis revealed no significant difference in overall survival rates between these rare cancers and the more common invasive carcinoma (NOS). However, mucinous, papillary, and tubular/cribriform carcinomas demonstrated better disease-specific survival. These subtypes presented with similar characteristics such as early detection, less nodal involvement, more hormonal receptor positivity, and less human epidermal growth factor receptor 2 (HER2) positivity. To conclude, our study demonstrated the diversity in the characteristics and prognosis of rare breast cancer histotypes. Future research should be carried out to investigate histotype-specific management and targeted therapies, given their distinct behavior.

ChatGPT versus human in generating medical graduate exam multiple choice questions-A multinational prospective study (Hong Kong S.A.R., Singapore, Ireland, and the United Kingdom).

INTRODUCTION: Large language models, in particular ChatGPT, have showcased remarkable language processing capabilities. Given the substantial workload of university medical staff, this study aims to assess the quality of multiple-choice questions (MCQs) produced by ChatGPT for use in graduate medical examinations, compared to questions written by university professoriate staffs based on standard medical textbooks. METHODS: 50 MCQs were generated by ChatGPT with reference to two standard undergraduate medical textbooks (Harrison's, and Bailey & Love's). Another 50 MCQs were drafted by two university professoriate staff using the same medical textbooks. All 100 MCQ were individually numbered, randomized and sent to five independent international assessors for MCQ quality assessment using a standardized assessment score on five assessment domains, namely, appropriateness of the question, clarity and specificity, relevance, discriminative power of alternatives, and suitability for medical graduate examination. RESULTS: The total time required for ChatGPT to create the 50 questions was 20 minutes 25 seconds, while it took two human examiners a total of 211 minutes 33 seconds to draft the 50 questions. When a comparison of the mean score was made between the questions constructed by A.I. with those drafted by humans, only in the relevance domain that the A.I. was inferior to humans (A.I.: 7.56 +/- 0.94 vs human: 7.88 +/- 0.52; p = 0.04). There was no significant difference in question quality between questions drafted by A.I. versus humans, in the total assessment score as well as in other domains. Questions generated by A.I. yielded a wider range of scores, while those created by humans were consistent and within a narrower range. CONCLUSION: ChatGPT has the potential to generate comparable-quality MCQs for medical graduate examinations within a significantly shorter time.

Is virtual endoscopy of the middle ear useful?

Virtual endoscopy is a relatively new imaging technology in otology, and therefore data on its efficacy in clinical situations are limited. We conducted a prospective study to evaluate the clinical relevance of radiologic diagnoses based on virtual endoscopy of the middle ear. Our patient population was made up of 30 adults who were scheduled to undergo surgery to correct conductive hearing loss of unknown etiology. Virtual endoscopy was performed on three-dimensional images that were constructed from images obtained with conventional two-dimensional computed tomography (CT). Findings on virtual endoscopy were then compared with the subsequent surgical findings. Virtual endoscopy suggested a middle ear pathology in 19 patients and a normal middle ear in 11 patients. Postoperatively, we found that the virtual diagnoses correlated moderately well with the surgical findings in the group of patients with predicted pathology; 13 of these 19 patients were found to have middle ear problems such as ossicular chain anomalies, otosclerosis, and cholesteatoma (positive predictive value: 68%). However, among the 11 patients whose middle ear structures were radiologically predicted to be normal, only 2 had negative middle ear findings on surgical exploration; of the remaining 9 patients, 8 had otosclerosis and 1 had malleus fixation (negative predictive value: 18%). Thus, the sensitivity and specificity of virtual endoscopy were 59 and 25%, respectively. Virtual endoscopy provides images from a surgeon's perspective, and so it has the potential to be useful in the preoperative evaluation of the middle ear cavity. With ongoing advancements in computer systems and imaging techniques, the cost, reliability, and efficacy of virtual endoscopy may improve. However, further clinical validation and cost-benefit analysis are required before we can determine if it has any additional advantages over conventional two-dimensional CT.