Outcome of Triple Negative Breast Cancer(TNBC) as compared to other breast cancers in Bir Hospital, National Academy of Medical Sciences
Bibliographic record
Abstract
Introduction: In Nepal, breast cancer is the second most common cancer accounting for a large number of deaths.The subtype Triple-negative breast cancer (TNBC) is linked to poor prognosis and is characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2). This study describes the outcome of women with TNBC as compared to other breast cancers in Bir Hospital in Nepal. Methods: This was a cross-sectional study conducted in Bir Hospital, National Academy of Medical Sciences. The breast cancer data in Department of Surgery and Department of Oncology were collected from July 2021 to June 2024. The study data on demographic details, clinical findings, radiological and pathological investigations, operative procedures, neoadjuvant/adjuvant therapy, surgical and oncological outcomeswere collected. The study approval was taken from Institutional Review Board of National Academy of Medical Sciences. Results: There were 72 breast cancer patientsout of which 10 (13.8 %) were TNBC. Majority of the cases (70%) underwent modified radical mastectomy and 60% of them had received neoadjuvant therapy in TNBC cases. One out of 10 had positive margin post mastectomy. The proportion of TNBC patients with postoperative wound infection, seroma and flap necrosis were 10% each. The mean lymph node positivity was less in TNBC group as compared to other breast cancers.There was one recurrence, one metastasis and no mortality till one year follow up. Conclusion: The surgical outcome was satisfactory and with neo-adjuvant, surgery and adjuvant therapy, there is less tumor recurrence and satisfactory disease free survival and overall survival.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".