Primary Breast Diffuse Large B-Cell Lymphoma in a 42-Year-Old Female: A Case Report and Review of Literature
Why this work is in the frame
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Bibliographic record
Abstract
Primary breast diffuse large B-cell lymphoma (PB-DLBCL) is a rare localized extranodal lymphoma. It is mainly diagnosed by pathological examination due to the lack of specific clinical and imaging manifestations. Whole-body positron emission tomography-computed tomography (PET-CT) is widely used in determining clinical staging and guiding clinical treatment. As part of comprehensive treatment, targeted therapy with rituximab, intrathecal methotrexate injection and consolidation radiotherapy remain controversial in treating PB-DLBCL, but the comprehensive treatment based on full-course of chemotherapy is still widely used as the first-line treatment. Comprehensive treatment often leads to a sharp decline in the immunity of elderly patients with malignancy. In this situation, surgery may be a good chance to improve their life quality without serious complications. We present a rare case of PB-DLBCL during the coronavirus disease 2019 (COVID-19) pandemic. The patient underwent chest CT scan to screen COVID-19 and a mass of left breast was accidentally found. Because of the city lockdown policy in Wuhan, she did not seek medical help until noticing that the mass was gradually enlarged. Both ultrasonography and mammography indicated that the lesion was breast cancer. However, ultrasound-guided core needle biopsy revealed diffuse large B-cell lymphoma of breast and PET-CT scan showed that the lesion was a primary hypermetabolic tumor of left breast. The patient subsequently received comprehensive treatment based on six cycles of rituximab-cyclophosphamide, hydroxydaunomycin, oncovin, prednisone (R-CHOP) chemotherapy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it